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openpilot v0.7.3 release

Vehicle Researcher 2020-02-17 18:12:52 -08:00
parent b3e67e28e2
commit 332cb82886
64 changed files with 2602 additions and 1351 deletions
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585
.pylintrc
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@ -1,585 +0,0 @@
[MASTER]
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# run arbitrary code
extension-pkg-whitelist=scipy
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# Enable the message, report, category or checker with the given id(s). You can
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[REPORTS]
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# note). You have access to the variables errors warning, statement which
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# number of statements analyzed. This is used by the global evaluation report
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evaluation=10.0 - ((float(5 * error + warning + refactor + convention) / statement) * 10)
# Template used to display messages. This is a python new-style format string
# used to format the message information. See doc for all details
#msg-template=
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# and msvs (visual studio).You can also give a reporter class, eg
# mypackage.mymodule.MyReporterClass.
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# Tells whether to display a full report or only the messages
reports=no
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score=yes
[REFACTORING]
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max-nested-blocks=5
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never-returning-functions=optparse.Values,sys.exit
[LOGGING]
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# function parameter format
logging-modules=logging
[SPELLING]
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max-spelling-suggestions=4
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# install python-enchant package.
spelling-dict=
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spelling-store-unknown-words=no
[MISCELLANEOUS]
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notes=FIXME,
XXX,
TODO
[SIMILARITIES]
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ignore-comments=yes
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ignore-docstrings=yes
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[TYPECHECK]
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contextmanager-decorators=contextlib.contextmanager
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generated-members=capnp.* cereal.* pygame.* zmq.* setproctitle.* smbus2.* usb1.* serial.* cv2.*
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# of finding the hint is based on edit distance.
missing-member-hint=yes
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missing-member-hint-distance=1
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# showing a hint for a missing member.
missing-member-max-choices=1
[VARIABLES]
# List of additional names supposed to be defined in builtins. Remember that
# you should avoid to define new builtins when possible.
additional-builtins=
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allow-global-unused-variables=yes
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# name must start or end with one of those strings.
callbacks=cb_,
_cb
# A regular expression matching the name of dummy variables (i.e. expectedly
# not used).
dummy-variables-rgx=_+$|(_[a-zA-Z0-9_]*[a-zA-Z0-9]+?$)|dummy|^ignored_|^unused_
# Argument names that match this expression will be ignored. Default to name
# with leading underscore
ignored-argument-names=_.*|^ignored_|^unused_
# Tells whether we should check for unused import in __init__ files.
init-import=no
# List of qualified module names which can have objects that can redefine
# builtins.
redefining-builtins-modules=six.moves,past.builtins,future.builtins
[FORMAT]
# Expected format of line ending, e.g. empty (any line ending), LF or CRLF.
expected-line-ending-format=
# Regexp for a line that is allowed to be longer than the limit.
ignore-long-lines=^\s*(# )?<?https?://\S+>?$
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indent-after-paren=4
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# tab).
indent-string=' '
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max-line-length=100
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max-module-lines=1000
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# separator` is used to allow tabulation in dicts, etc.: {1 : 1,\n222: 2}.
# `trailing-comma` allows a space between comma and closing bracket: (a, ).
# `empty-line` allows space-only lines.
no-space-check=trailing-comma,
dict-separator
# Allow the body of a class to be on the same line as the declaration if body
# contains single statement.
single-line-class-stmt=no
# Allow the body of an if to be on the same line as the test if there is no
# else.
single-line-if-stmt=no
[BASIC]
# Naming style matching correct argument names
argument-naming-style=snake_case
# Regular expression matching correct argument names. Overrides argument-
# naming-style
#argument-rgx=
# Naming style matching correct attribute names
attr-naming-style=snake_case
# Regular expression matching correct attribute names. Overrides attr-naming-
# style
#attr-rgx=
# Bad variable names which should always be refused, separated by a comma
bad-names=foo,
bar,
baz,
toto,
tutu,
tata
# Naming style matching correct class attribute names
class-attribute-naming-style=any
# Regular expression matching correct class attribute names. Overrides class-
# attribute-naming-style
#class-attribute-rgx=
# Naming style matching correct class names
class-naming-style=PascalCase
# Regular expression matching correct class names. Overrides class-naming-style
#class-rgx=
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const-naming-style=UPPER_CASE
# Regular expression matching correct constant names. Overrides const-naming-
# style
#const-rgx=
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# ones are exempt.
docstring-min-length=-1
# Naming style matching correct function names
function-naming-style=snake_case
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# naming-style
#function-rgx=
# Good variable names which should always be accepted, separated by a comma
good-names=i,
j,
k,
ex,
Run,
_
# Include a hint for the correct naming format with invalid-name
include-naming-hint=no
# Naming style matching correct inline iteration names
inlinevar-naming-style=any
# Regular expression matching correct inline iteration names. Overrides
# inlinevar-naming-style
#inlinevar-rgx=
# Naming style matching correct method names
method-naming-style=snake_case
# Regular expression matching correct method names. Overrides method-naming-
# style
#method-rgx=
# Naming style matching correct module names
module-naming-style=snake_case
# Regular expression matching correct module names. Overrides module-naming-
# style
#module-rgx=
# Colon-delimited sets of names that determine each other's naming style when
# the name regexes allow several styles.
name-group=
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# not require a docstring.
no-docstring-rgx=^_
# List of decorators that produce properties, such as abc.abstractproperty. Add
# to this list to register other decorators that produce valid properties.
property-classes=abc.abstractproperty
# Naming style matching correct variable names
variable-naming-style=snake_case
# Regular expression matching correct variable names. Overrides variable-
# naming-style
#variable-rgx=
[DESIGN]
# Maximum number of arguments for function / method
max-args=5
# Maximum number of attributes for a class (see R0902).
max-attributes=7
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max-bool-expr=5
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max-returns=6
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max-statements=50
# Minimum number of public methods for a class (see R0903).
min-public-methods=2
[CLASSES]
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defining-attr-methods=__init__,
__new__,
setUp
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# warning.
exclude-protected=_asdict,
_fields,
_replace,
_source,
_make
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valid-classmethod-first-arg=cls
# List of valid names for the first argument in a metaclass class method.
valid-metaclass-classmethod-first-arg=mcs
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# only in one or another interpreter, leading to false positives when analysed.
analyse-fallback-blocks=no
# Deprecated modules which should not be used, separated by a comma
deprecated-modules=regsub,
TERMIOS,
Bastion,
rexec
# Create a graph of external dependencies in the given file (report RP0402 must
# not be disabled)
ext-import-graph=
# Create a graph of every (i.e. internal and external) dependencies in the
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import-graph=
# Create a graph of internal dependencies in the given file (report RP0402 must
# not be disabled)
int-import-graph=
# Force import order to recognize a module as part of the standard
# compatibility libraries.
known-standard-library=
# Force import order to recognize a module as part of a third party library.
known-third-party=enchant
[EXCEPTIONS]
# Exceptions that will emit a warning when being caught. Defaults to
# "Exception"
overgeneral-exceptions=Exception

7
.travis.yml
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@ -1,7 +0,0 @@
sudo: required
services:
- docker
script:
- ./run_docker_tests.sh

2
README.md
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@ -96,6 +96,7 @@ Supported Cars
| Lexus | ES Hybrid 2019 | All | openpilot | 0mph | 0mph |
| Lexus | IS 2017-2019 | All | Stock | 22mph | 0mph |
| Lexus | IS Hybrid 2017 | All | Stock | 0mph | 0mph |
| Lexus | NX Hybrid 2018 | All | Stock<sup>4</sup>| 0mph | 0mph |
| Lexus | RX 2016-17 | All | Stock<sup>4</sup>| 0mph | 0mph |
| Lexus | RX 2020 | All | openpilot | 0mph | 0mph |
| Lexus | RX Hybrid 2016-19 | All | Stock<sup>4</sup>| 0mph | 0mph |
@ -113,6 +114,7 @@ Supported Cars
| Toyota | Corolla Hybrid 2020 | All | openpilot | 0mph | 0mph |
| Toyota | Highlander 2017-19 | All | Stock<sup>4</sup>| 0mph | 0mph |
| Toyota | Highlander Hybrid 2017-19 | All | Stock<sup>4</sup>| 0mph | 0mph |
| Toyota | Highlander 2020 | All | openpilot | 0mph | 0mph |
| Toyota | Prius 2016 | TSS-P | Stock<sup>4</sup>| 0mph | 0mph |
| Toyota | Prius 2017-19 | All | Stock<sup>4</sup>| 0mph | 0mph |
| Toyota | Prius Prime 2017-20 | All | Stock<sup>4</sup>| 0mph | 0mph |

8
RELEASES.md
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@ -1,3 +1,11 @@
Version 0.7.3 (2020-02-21)
========================
* Improved autofocus for road facing camera
* Support for 2020 Highlander thanks to che220!
* Support for 2018 Lexus NX 300h thanks to kengggg!
* Speed up ECU firmware query
* Fix bug where manager would sometimes hang after shutting down the car
Version 0.7.2 (2020-02-07)
========================
* ECU firmware version based fingerprinting for Honda & Toyota

1
SConstruct
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@ -228,5 +228,6 @@ if arch == "aarch64":
SConscript(['selfdrive/clocksd/SConscript'])
SConscript(['selfdrive/locationd/SConscript'])
SConscript(['selfdrive/locationd/kalman/SConscript'])
# TODO: finish cereal, dbcbuilder, MPC

BIN
apk/ai.comma.plus.offroad.apk
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Binary file not shown.

2
common/params.py
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@ -81,6 +81,7 @@ keys = {
"LiveParameters": [TxType.PERSISTENT],
"LongitudinalControl": [TxType.PERSISTENT],
"OpenpilotEnabledToggle": [TxType.PERSISTENT],
"LaneChangeEnabled": [TxType.PERSISTENT],
"PandaFirmware": [TxType.CLEAR_ON_MANAGER_START, TxType.CLEAR_ON_PANDA_DISCONNECT],
"PandaFirmwareHex": [TxType.CLEAR_ON_MANAGER_START, TxType.CLEAR_ON_PANDA_DISCONNECT],
"PandaDongleId": [TxType.CLEAR_ON_MANAGER_START, TxType.CLEAR_ON_PANDA_DISCONNECT],
@ -93,6 +94,7 @@ keys = {
"TermsVersion": [TxType.PERSISTENT],
"TrainingVersion": [TxType.PERSISTENT],
"UpdateAvailable": [TxType.CLEAR_ON_MANAGER_START],
"UpdateFailedCount": [TxType.CLEAR_ON_MANAGER_START],
"Version": [TxType.PERSISTENT],
"Offroad_ChargeDisabled": [TxType.CLEAR_ON_MANAGER_START, TxType.CLEAR_ON_PANDA_DISCONNECT],
"Offroad_ConnectivityNeeded": [TxType.CLEAR_ON_MANAGER_START],

57
selfdrive/camerad/cameras/camera_qcom.c
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@ -1710,6 +1710,9 @@ static void parse_autofocus(CameraState *s, uint8_t *d) {
int good_count = 0;
int16_t max_focus = -32767;
int avg_focus = 0;
// force to max if not able to determine focus for long
const int patience_cnt = 100;
static int nan_cnt = 0;
/*printf("FOCUS: ");
for (int i = 0; i < 0x10; i++) {
@ -1717,42 +1720,56 @@ static void parse_autofocus(CameraState *s, uint8_t *d) {
}*/
for (int i = 0; i < NUM_FOCUS; i++) {
int doff = i*5+5;
s->confidence[i] = d[doff];
int16_t focus_t = (d[doff+1] << 3) | (d[doff+2] >> 5);
if (focus_t >= 1024) focus_t = -(2048-focus_t);
s->focus[i] = focus_t;
//printf("%x->%d ", d[doff], focus_t);
if (s->confidence[i] > 0x20) {
int pd_idx = (i+1)*5;
s->confidence[i] = d[pd_idx];
int16_t focus_delta = d[pd_idx+1];
if (focus_delta >= 128) focus_delta = - (256 - focus_delta);
s->focus[i] = focus_delta;
if (s->confidence[i] > 64) {
good_count++;
max_focus = max(max_focus, s->focus[i]);
avg_focus += s->focus[i];
// printf("%d\n", s->focus[i]);
}
}
//printf("\n");
if (good_count < 4) {
if (good_count < 7) {
s->focus_err = nan("");
nan_cnt += 1;
if (nan_cnt > patience_cnt) {
s->focus_err = 16;
nan_cnt = 0;
}
return;
}
avg_focus /= good_count;
// outlier rejection
if (abs(avg_focus - max_focus) > 200) {
s->focus_err = nan("");
return;
if (abs(avg_focus - max_focus) > 32) {
if (nan_cnt < patience_cnt) {
s->focus_err = nan("");
nan_cnt += 1;
return;
} else {
s->focus_err = 16;
// s->focus_err = max_focus*8.0;
nan_cnt = 0;
}
} else {
s->focus_err = avg_focus;
nan_cnt = 0;
}
s->focus_err = max_focus*1.0;
// printf("fe=%f\n", s->focus_err);
}
static void do_autofocus(CameraState *s) {
// params for focus PI controller
const float focus_kp = 0.005;
// params for focus P controller
const float focus_kp = 0.1;
float err = s->focus_err;
float offset = 0;
// don't allow big change
err = clamp(err, -16, 16);
float sag = (s->last_sag_acc_z/9.8) * 128;
const int dac_up = s->device == DEVICE_LP3? 634:456;
@ -1776,6 +1793,7 @@ static void do_autofocus(CameraState *s) {
LOGD(debug);*/
actuator_move(s, target);
// printf("ltp=%f, clp=%d\n",s->lens_true_pos,s->cur_lens_pos);
}
@ -2165,6 +2183,9 @@ void cameras_run(DualCameraState *s) {
} else {
uint8_t *d = c->ss[buffer].bufs[buf_idx].addr;
if (buffer == 1) {
// FILE *df = fopen("/sdcard/focus_buf","wb");
// fwrite(d, c->ss[buffer].bufs[buf_idx].len, sizeof(uint8_t), df);
// fclose(df);
parse_autofocus(c, d);
}
c->ss[buffer].qbuf_info[buf_idx].dirty_buf = 1;

5
selfdrive/car/car_helpers.py
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@ -133,6 +133,11 @@ def fingerprint(logcan, sendcan, has_relay):
car_fingerprint = list(fw_candidates)[0]
source = car.CarParams.FingerprintSource.fw
fixed_fingerprint = os.environ.get('FINGERPRINT', "")
if len(fixed_fingerprint):
car_fingerprint = fixed_fingerprint
source = car.CarParams.FingerprintSource.fixed
cloudlog.warning("fingerprinted %s", car_fingerprint)
return car_fingerprint, finger, vin, car_fw, source

10
selfdrive/car/chrysler/carcontroller.py
View File

@ -35,14 +35,14 @@ class CarController():
# steer torque
new_steer = actuators.steer * SteerLimitParams.STEER_MAX
apply_steer = apply_toyota_steer_torque_limits(new_steer, self.apply_steer_last,
CS.steer_torque_motor, SteerLimitParams)
CS.out.steeringTorqueEps, SteerLimitParams)
self.steer_rate_limited = new_steer != apply_steer
moving_fast = CS.v_ego > CS.CP.minSteerSpeed # for status message
if CS.v_ego > (CS.CP.minSteerSpeed - 0.5): # for command high bit
moving_fast = CS.out.vEgo > CS.CP.minSteerSpeed # for status message
if CS.out.vEgo > (CS.CP.minSteerSpeed - 0.5): # for command high bit
self.gone_fast_yet = True
elif self.car_fingerprint in (CAR.PACIFICA_2019_HYBRID, CAR.PACIFICA_2020_HYBRID, CAR.JEEP_CHEROKEE_2019):
if CS.v_ego < (CS.CP.minSteerSpeed - 3.0):
if CS.out.vEgo < (CS.CP.minSteerSpeed - 3.0):
self.gone_fast_yet = False # < 14.5m/s stock turns off this bit, but fine down to 13.5
lkas_active = moving_fast and enabled
@ -65,7 +65,7 @@ class CarController():
if (self.ccframe % 25 == 0): # 0.25s period
if (CS.lkas_car_model != -1):
new_msg = create_lkas_hud(
self.packer, CS.gear_shifter, lkas_active, hud_alert,
self.packer, CS.out.gearShifter, lkas_active, hud_alert,
self.hud_count, CS.lkas_car_model)
can_sends.append(new_msg)
self.hud_count += 1

109
selfdrive/car/chrysler/carstate.py
View File

@ -1,14 +1,9 @@
from cereal import car
from opendbc.can.parser import CANParser
from opendbc.can.can_define import CANDefine
from selfdrive.config import Conversions as CV
from selfdrive.car.interfaces import CarStateBase
from selfdrive.car.chrysler.values import DBC, STEER_THRESHOLD
from common.kalman.simple_kalman import KF1D
GearShifter = car.CarState.GearShifter
def parse_gear_shifter(can_gear):
return {0x1: GearShifter.park, 0x2: GearShifter.reverse, 0x3: GearShifter.neutral,
0x4: GearShifter.drive, 0x5: GearShifter.low}.get(can_gear, GearShifter.unknown)
def get_can_parser(CP):
@ -68,83 +63,61 @@ def get_camera_parser(CP):
return CANParser(DBC[CP.carFingerprint]['pt'], signals, checks, 2)
class CarState():
class CarState(CarStateBase):
def __init__(self, CP):
self.CP = CP
self.left_blinker_on = 0
self.right_blinker_on = 0
# initialize can parser
self.car_fingerprint = CP.carFingerprint
# vEgo kalman filter
dt = 0.01
# Q = np.matrix([[10.0, 0.0], [0.0, 100.0]])
# R = 1e3
self.v_ego_kf = KF1D(x0=[[0.0], [0.0]],
A=[[1.0, dt], [0.0, 1.0]],
C=[1.0, 0.0],
K=[[0.12287673], [0.29666309]])
self.v_ego = 0.0
super().__init__(CP)
can_define = CANDefine(DBC[CP.carFingerprint]['pt'])
self.shifter_values = can_define.dv["GEAR"]['PRNDL']
def update(self, cp, cp_cam):
# update prevs, update must run once per loop
self.prev_left_blinker_on = self.left_blinker_on
self.prev_right_blinker_on = self.right_blinker_on
ret = car.CarState.new_message()
self.frame_23b = int(cp.vl["WHEEL_BUTTONS"]['COUNTER'])
self.frame = int(cp.vl["EPS_STATUS"]['COUNTER'])
self.door_all_closed = not any([cp.vl["DOORS"]['DOOR_OPEN_FL'],
cp.vl["DOORS"]['DOOR_OPEN_FR'],
cp.vl["DOORS"]['DOOR_OPEN_RL'],
cp.vl["DOORS"]['DOOR_OPEN_RR']])
self.seatbelt = (cp.vl["SEATBELT_STATUS"]['SEATBELT_DRIVER_UNLATCHED'] == 0)
ret.doorOpen = any([cp.vl["DOORS"]['DOOR_OPEN_FL'],
cp.vl["DOORS"]['DOOR_OPEN_FR'],
cp.vl["DOORS"]['DOOR_OPEN_RL'],
cp.vl["DOORS"]['DOOR_OPEN_RR']])
ret.seatbeltUnlatched = cp.vl["SEATBELT_STATUS"]['SEATBELT_DRIVER_UNLATCHED'] == 1
ret.brakePressed = cp.vl["BRAKE_2"]['BRAKE_PRESSED_2'] == 5 # human-only
ret.brake = 0
ret.brakeLights = ret.brakePressed
ret.gas = cp.vl["ACCEL_GAS_134"]['ACCEL_134']
ret.gasPressed = ret.gas > 1e-5
self.brake_pressed = cp.vl["BRAKE_2"]['BRAKE_PRESSED_2'] == 5 # human-only
self.pedal_gas = cp.vl["ACCEL_GAS_134"]['ACCEL_134']
self.car_gas = self.pedal_gas
self.esp_disabled = (cp.vl["TRACTION_BUTTON"]['TRACTION_OFF'] == 1)
self.v_wheel_fl = cp.vl['WHEEL_SPEEDS']['WHEEL_SPEED_FL']
self.v_wheel_rr = cp.vl['WHEEL_SPEEDS']['WHEEL_SPEED_RR']
self.v_wheel_rl = cp.vl['WHEEL_SPEEDS']['WHEEL_SPEED_RL']
self.v_wheel_fr = cp.vl['WHEEL_SPEEDS']['WHEEL_SPEED_FR']
v_wheel = (cp.vl['SPEED_1']['SPEED_LEFT'] + cp.vl['SPEED_1']['SPEED_RIGHT']) / 2.
ret.wheelSpeeds.fl = cp.vl['WHEEL_SPEEDS']['WHEEL_SPEED_FL']
ret.wheelSpeeds.rr = cp.vl['WHEEL_SPEEDS']['WHEEL_SPEED_RR']
ret.wheelSpeeds.rl = cp.vl['WHEEL_SPEEDS']['WHEEL_SPEED_RL']
ret.wheelSpeeds.fr = cp.vl['WHEEL_SPEEDS']['WHEEL_SPEED_FR']
ret.vEgoRaw = (cp.vl['SPEED_1']['SPEED_LEFT'] + cp.vl['SPEED_1']['SPEED_RIGHT']) / 2.
ret.vEgo, ret.aEgo = self.update_speed_kf(ret.vEgoRaw)
ret.standstill = not ret.vEgoRaw > 0.001
# Kalman filter
if abs(v_wheel - self.v_ego) > 2.0: # Prevent large accelerations when car starts at non zero speed
self.v_ego_kf.x = [[v_wheel], [0.0]]
ret.leftBlinker = cp.vl["STEERING_LEVERS"]['TURN_SIGNALS'] == 1
ret.rightBlinker = cp.vl["STEERING_LEVERS"]['TURN_SIGNALS'] == 2
ret.steeringAngle = cp.vl["STEERING"]['STEER_ANGLE']
ret.steeringRate = cp.vl["STEERING"]['STEERING_RATE']
ret.gearShifter = self.parse_gear_shifter(self.shifter_values.get(cp.vl['GEAR']['PRNDL'], None))
self.v_ego_raw = v_wheel
v_ego_x = self.v_ego_kf.update(v_wheel)
self.v_ego = float(v_ego_x[0])
self.a_ego = float(v_ego_x[1])
self.standstill = not v_wheel > 0.001
ret.cruiseState.enabled = cp.vl["ACC_2"]['ACC_STATUS_2'] == 7 # ACC is green.
ret.cruiseState.available = ret.cruiseState.enabled # FIXME: for now same as enabled
ret.cruiseState.speed = cp.vl["DASHBOARD"]['ACC_SPEED_CONFIG_KPH'] * CV.KPH_TO_MS
self.angle_steers = cp.vl["STEERING"]['STEER_ANGLE']
self.angle_steers_rate = cp.vl["STEERING"]['STEERING_RATE']
self.gear_shifter = parse_gear_shifter(cp.vl['GEAR']['PRNDL'])
self.main_on = cp.vl["ACC_2"]['ACC_STATUS_2'] == 7 # ACC is green.
self.left_blinker_on = cp.vl["STEERING_LEVERS"]['TURN_SIGNALS'] == 1
self.right_blinker_on = cp.vl["STEERING_LEVERS"]['TURN_SIGNALS'] == 2
self.steer_torque_driver = cp.vl["EPS_STATUS"]["TORQUE_DRIVER"]
self.steer_torque_motor = cp.vl["EPS_STATUS"]["TORQUE_MOTOR"]
self.steer_override = abs(self.steer_torque_driver) > STEER_THRESHOLD
ret.steeringTorque = cp.vl["EPS_STATUS"]["TORQUE_DRIVER"]
ret.steeringTorqueEps = cp.vl["EPS_STATUS"]["TORQUE_MOTOR"]
ret.steeringPressed = abs(ret.steeringTorque) > STEER_THRESHOLD
steer_state = cp.vl["EPS_STATUS"]["LKAS_STATE"]
self.steer_error = steer_state == 4 or (steer_state == 0 and self.v_ego > self.CP.minSteerSpeed)
self.steer_error = steer_state == 4 or (steer_state == 0 and ret.vEgo > self.CP.minSteerSpeed)
self.user_brake = 0
self.brake_lights = self.brake_pressed
self.v_cruise_pcm = cp.vl["DASHBOARD"]['ACC_SPEED_CONFIG_KPH']
self.pcm_acc_status = self.main_on
self.generic_toggle = bool(cp.vl["STEERING_LEVERS"]['HIGH_BEAM_FLASH'])
ret.genericToggle = bool(cp.vl["STEERING_LEVERS"]['HIGH_BEAM_FLASH'])
self.lkas_counter = cp_cam.vl["LKAS_COMMAND"]['COUNTER']
self.lkas_car_model = cp_cam.vl["LKAS_HUD"]['CAR_MODEL']
self.lkas_status_ok = cp_cam.vl["LKAS_HEARTBIT"]['LKAS_STATUS_OK']
return ret

68
selfdrive/car/chrysler/interface.py
View File

@ -20,6 +20,8 @@ class CarInterface(CarInterfaceBase):
self.brake_pressed_prev = False
self.cruise_enabled_prev = False
self.low_speed_alert = False
self.left_blinker_prev = False
self.right_blinker_prev = False
# *** init the major players ***
self.CS = CarState(CP)
@ -113,78 +115,33 @@ class CarInterface(CarInterfaceBase):
self.cp.update_strings(can_strings)
self.cp_cam.update_strings(can_strings)
self.CS.update(self.cp, self.cp_cam)
# create message
ret = car.CarState.new_message()
ret = self.CS.update(self.cp, self.cp_cam)
ret.canValid = self.cp.can_valid and self.cp_cam.can_valid
# speeds
ret.vEgo = self.CS.v_ego
ret.vEgoRaw = self.CS.v_ego_raw
ret.aEgo = self.CS.a_ego
ret.yawRate = self.VM.yaw_rate(self.CS.angle_steers * CV.DEG_TO_RAD, self.CS.v_ego)
ret.standstill = self.CS.standstill
ret.wheelSpeeds.fl = self.CS.v_wheel_fl
ret.wheelSpeeds.fr = self.CS.v_wheel_fr
ret.wheelSpeeds.rl = self.CS.v_wheel_rl
ret.wheelSpeeds.rr = self.CS.v_wheel_rr
# gear shifter
ret.gearShifter = self.CS.gear_shifter
# gas pedal
ret.gas = self.CS.car_gas
ret.gasPressed = self.CS.pedal_gas > 0
# brake pedal
ret.brake = self.CS.user_brake
ret.brakePressed = self.CS.brake_pressed
ret.brakeLights = self.CS.brake_lights
# steering wheel
ret.steeringAngle = self.CS.angle_steers
ret.steeringRate = self.CS.angle_steers_rate
ret.steeringTorque = self.CS.steer_torque_driver
ret.steeringPressed = self.CS.steer_override
ret.yawRate = self.VM.yaw_rate(ret.steeringAngle * CV.DEG_TO_RAD, ret.vEgo)
ret.steeringRateLimited = self.CC.steer_rate_limited if self.CC is not None else False
# cruise state
ret.cruiseState.enabled = self.CS.pcm_acc_status # same as main_on
ret.cruiseState.speed = self.CS.v_cruise_pcm * CV.KPH_TO_MS
ret.cruiseState.available = self.CS.main_on
ret.cruiseState.speedOffset = 0.
ret.cruiseState.standstill = False
# TODO: button presses
buttonEvents = []
if self.CS.left_blinker_on != self.CS.prev_left_blinker_on:
if ret.leftBlinker != self.left_blinker_prev:
be = car.CarState.ButtonEvent.new_message()
be.type = ButtonType.leftBlinker
be.pressed = self.CS.left_blinker_on != 0
be.pressed = ret.leftBlinker != 0
buttonEvents.append(be)
if self.CS.right_blinker_on != self.CS.prev_right_blinker_on:
if ret.rightBlinker != self.right_blinker_prev:
be = car.CarState.ButtonEvent.new_message()
be.type = ButtonType.rightBlinker
be.pressed = self.CS.right_blinker_on != 0
be.pressed = ret.rightBlinker != 0
buttonEvents.append(be)
ret.buttonEvents = buttonEvents
ret.leftBlinker = bool(self.CS.left_blinker_on)
ret.rightBlinker = bool(self.CS.right_blinker_on)
ret.doorOpen = not self.CS.door_all_closed
ret.seatbeltUnlatched = not self.CS.seatbelt
self.low_speed_alert = (ret.vEgo < self.CP.minSteerSpeed)
ret.genericToggle = self.CS.generic_toggle
#ret.lkasCounter = self.CS.lkas_counter
#ret.lkasCarModel = self.CS.lkas_car_model
# events
events = []
if not (ret.gearShifter in (GearShifter.drive, GearShifter.low)):
@ -195,7 +152,7 @@ class CarInterface(CarInterfaceBase):
events.append(create_event('seatbeltNotLatched', [ET.NO_ENTRY, ET.SOFT_DISABLE]))
if self.CS.esp_disabled:
events.append(create_event('espDisabled', [ET.NO_ENTRY, ET.SOFT_DISABLE]))
if not self.CS.main_on:
if not ret.cruiseState.available:
events.append(create_event('wrongCarMode', [ET.NO_ENTRY, ET.USER_DISABLE]))
if ret.gearShifter == GearShifter.reverse:
events.append(create_event('reverseGear', [ET.NO_ENTRY, ET.IMMEDIATE_DISABLE]))
@ -220,8 +177,13 @@ class CarInterface(CarInterfaceBase):
self.gas_pressed_prev = ret.gasPressed
self.brake_pressed_prev = ret.brakePressed
self.cruise_enabled_prev = ret.cruiseState.enabled
self.left_blinker_prev = ret.leftBlinker
self.right_blinker_prev = ret.rightBlinker
return ret.as_reader()
# copy back carState packet to CS
self.CS.out = ret.as_reader()
return self.CS.out
# pass in a car.CarControl
# to be called @ 100hz

5
selfdrive/car/chrysler/values.py
View File

@ -53,7 +53,10 @@ FINGERPRINTS = {
# Based on 3c7ce223e3571b54|2019-05-11--20-16-14
{
168: 8, 257: 5, 258: 8, 264: 8, 268: 8, 270: 8, 274: 2, 280: 8, 284: 8, 288: 7, 290: 6, 291: 8, 292: 8, 294: 8, 300: 8, 308: 8, 320: 8, 324: 8, 331: 8, 332: 8, 344: 8, 368: 8, 376: 3, 384: 8, 388: 4, 448: 6, 456: 4, 464: 8, 469: 8, 480: 8, 500: 8, 501: 8, 512: 8, 514: 8, 520: 8, 528: 8, 532: 8, 544: 8, 557: 8, 559: 8, 560: 8, 564: 8, 571: 3, 579: 8, 584: 8, 608: 8, 624: 8, 625: 8, 632: 8, 639: 8, 653: 8, 654: 8, 655: 8, 658: 6, 660: 8, 669: 3, 671: 8, 672: 8, 678: 8, 680: 8, 701: 8, 703: 8, 704: 8, 705: 8, 706: 8, 709: 8, 710: 8, 719: 8, 720: 6, 729: 5, 736: 8, 737: 8, 746: 5, 752: 2, 754: 8, 760: 8, 764: 8, 766: 8, 770: 8, 773: 8, 779: 8, 782: 8, 784: 8, 792: 8, 799: 8, 800: 8, 804: 8, 808: 8, 816: 8, 817: 8, 820: 8, 825: 2, 826: 8, 832: 8, 838: 2, 848: 8, 853: 8, 856: 4, 860: 6, 863: 8, 878: 8, 882: 8, 897: 8, 906: 8, 908: 8, 924: 8, 926: 3, 929: 8, 937: 8, 938: 8, 939: 8, 940: 8, 941: 8, 942: 8, 943: 8, 947: 8, 948: 8, 958: 8, 959: 8, 962: 8, 969: 4, 973: 8, 974: 5, 979: 8, 980: 8, 981: 8, 982: 8, 983: 8, 984: 8, 992: 8, 993: 7, 995: 8, 996: 8, 1000: 8, 1001: 8, 1002: 8, 1003: 8, 1008: 8, 1009: 8, 1010: 8, 1011: 8, 1012: 8, 1013: 8, 1014: 8, 1015: 8, 1024: 8, 1025: 8, 1026: 8, 1031: 8, 1033: 8, 1050: 8, 1059: 8, 1082: 8, 1083: 8, 1098: 8, 1100: 8, 1562: 8, 1570: 8
}
},
# Based on "d26bf42deb1910e7|2020-02-13--16-22-31"
{168: 8, 257: 5, 258: 8, 264: 8, 268: 8, 270: 8, 274: 2, 280: 8, 284: 8, 288: 7, 290: 6, 291: 8, 292: 8, 294: 8, 300: 8, 308: 8, 320: 8, 324: 8, 331: 8, 332: 8, 344: 8, 368: 8, 376: 3, 384: 8, 388: 4, 448: 6, 456: 4, 464: 8, 469: 8, 480: 8, 500: 8, 501: 8, 512: 8, 514: 8, 520: 8, 528: 8, 532: 8, 542: 8, 544: 8, 557: 8, 559: 8, 560: 8, 564: 8, 571: 3, 579: 8, 584: 8, 608: 8, 624: 8, 625: 8, 632: 8, 639: 8, 653: 8, 654: 8, 655: 8, 658: 6, 660: 8, 669: 3, 671: 8, 672: 8, 678: 8, 680: 8, 701: 8, 703: 8, 704: 8, 705: 8, 706: 8, 709: 8, 710: 8, 719: 8, 720: 6, 729: 5, 736: 8, 737: 8, 746: 5, 752: 2, 754: 8, 760: 8, 764: 8, 766: 8, 770: 8, 773: 8, 779: 8, 782: 8, 784: 8, 792: 8, 799: 8, 800: 8, 804: 8, 808: 8, 816: 8, 817: 8, 820: 8, 825: 2, 826: 8, 832: 8, 838: 2, 848: 8, 853: 8, 856: 4, 860: 6, 863: 8, 878: 8, 882: 8, 897: 8, 906: 8, 908: 8, 924: 8, 926: 3, 929: 8, 937: 8, 938: 8, 939: 8, 940: 8, 941: 8, 942: 8, 943: 8, 947: 8, 948: 8, 958: 8, 959: 8, 962: 8, 969: 4, 973: 8, 974: 5, 979: 8, 980: 8, 981: 8, 982: 8, 983: 8, 984: 8, 992: 8, 993: 7, 995: 8, 996: 8, 1000: 8, 1001: 8, 1002: 8, 1003: 8, 1008: 8, 1009: 8, 1010: 8, 1011: 8, 1012: 8, 1013: 8, 1014: 8, 1015: 8, 1024: 8, 1025: 8, 1026: 8, 1031: 8, 1033: 8, 1050: 8, 1059: 8, 1082: 8, 1083: 8, 1098: 8, 1100: 8, 1262: 8, 1284: 8, 1568: 8, 1902: 8, 2015: 8, 2016: 8, 2018: 8, 2023: 8, 2024: 8, 2026: 8, 2031: 8
},
],
CAR.PACIFICA_2020_HYBRID: [
{168: 8, 257: 5, 258: 8, 264: 8, 268: 8, 270: 8, 274: 2, 280: 8, 284: 8, 288: 7, 290: 6, 291: 8, 292: 8, 294: 8, 300: 8, 308: 8, 320: 8, 324: 8, 331: 8, 332: 8, 344: 8, 368: 8, 376: 3, 384: 8, 388: 4, 448: 6, 456: 4, 464: 8, 469: 8, 480: 8, 500: 8, 501: 8, 512: 8, 514: 8, 515: 7, 516: 7, 517: 7, 518: 7, 520: 8, 524: 8, 526: 6, 528: 8, 532: 8, 542: 8, 544: 8, 557: 8, 559: 8, 560: 8, 564: 8, 571: 3, 579: 8, 584: 8, 608: 8, 624: 8, 625: 8, 632: 8, 639: 8, 650: 8, 653: 8, 654: 8, 655: 8, 656: 4, 658: 6, 660: 8, 669: 3, 671: 8, 672: 8, 678: 8, 680: 8, 683: 8, 701: 8, 703: 8, 704: 8, 705: 8, 706: 8, 709: 8, 710: 8, 719: 8, 720: 6, 729: 5, 736: 8, 737: 8, 738: 8, 746: 5, 752: 2, 754: 8, 760: 8, 764: 8, 766: 8, 770: 8, 773: 8, 779: 8, 782: 8, 784: 8, 792: 8, 799: 8, 800: 8, 804: 8, 808: 8, 816: 8, 817: 8, 820: 8, 825: 2, 826: 8, 832: 8, 838: 2, 848: 8, 853: 8, 856: 4, 860: 6, 863: 8, 878: 8, 882: 8, 897: 8, 906: 8, 908: 8, 924: 8, 926: 3, 929: 8, 937: 8, 938: 8, 939: 8, 940: 8, 941: 8, 942: 8, 943: 8, 947: 8, 948: 8, 958: 8, 959: 8, 962: 8, 969: 4, 973: 8, 974: 5, 979: 8, 980: 8, 981: 8, 982: 8, 983: 8, 984: 8, 992: 8, 993: 7, 995: 8, 996: 8, 1000: 8, 1001: 8, 1002: 8, 1003: 8, 1008: 8, 1009: 8, 1010: 8, 1011: 8, 1012: 8, 1013: 8, 1014: 8, 1015: 8, 1024: 8, 1025: 8, 1026: 8, 1031: 8, 1033: 8, 1050: 8, 1059: 8, 1082: 8, 1083: 8, 1098: 8, 1100: 8, 2015: 8, 2016: 8, 2024: 8},

32
selfdrive/car/fingerprints.py
View File

@ -1,11 +1,12 @@
import os
from common.basedir import BASEDIR
def get_attr_from_cars(attr):
def get_attr_from_cars(attr, result=dict):
# read all the folders in selfdrive/car and return a dict where:
# - keys are all the car models
# - values are attr values from all car folders
result = {}
result = result()
for car_folder in [x[0] for x in os.walk(BASEDIR + '/selfdrive/car')]:
try:
@ -16,8 +17,11 @@ def get_attr_from_cars(attr):
else:
continue
for f, v in attr_values.items():
result[f] = v
if isinstance(attr_values, dict):
for f, v in attr_values.items():
result[f] = v
elif isinstance(attr_values, list):
result += attr_values
except (ImportError, IOError):
pass
@ -25,20 +29,9 @@ def get_attr_from_cars(attr):
return result
def get_fw_versions_list():
return get_attr_from_cars('FW_VERSIONS')
def get_fingerprint_list():
# read all the folders in selfdrive/car and return a dict where:
# - keys are all the car models for which we have a fingerprint
# - values are lists dicts of messages that constitute the unique
# CAN fingerprint of each car model and all its variants
return get_attr_from_cars('FINGERPRINTS')
FW_VERSIONS = get_fw_versions_list()
_FINGERPRINTS = get_fingerprint_list()
FW_VERSIONS = get_attr_from_cars('FW_VERSIONS')
_FINGERPRINTS = get_attr_from_cars('FINGERPRINTS')
IGNORED_FINGERPRINTS = get_attr_from_cars('IGNORED_FINGERPRINTS', list)
_DEBUG_ADDRESS = {1880: 8} # reserved for debug purposes
@ -61,6 +54,9 @@ def eliminate_incompatible_cars(msg, candidate_cars):
compatible_cars = []
for car_name in candidate_cars:
if car_name in IGNORED_FINGERPRINTS:
continue
car_fingerprints = _FINGERPRINTS[car_name]
for fingerprint in car_fingerprints:

14
selfdrive/car/ford/carcontroller.py
View File

@ -33,27 +33,27 @@ class CarController():
if (frame % 3) == 0:
curvature = self.vehicle_model.calc_curvature(actuators.steerAngle*3.1415/180., CS.v_ego)
curvature = self.vehicle_model.calc_curvature(actuators.steerAngle*3.1415/180., CS.out.vEgo)
# The use of the toggle below is handy for trying out the various LKAS modes
if TOGGLE_DEBUG:
self.lkas_action += int(CS.generic_toggle and not self.generic_toggle_last)
self.lkas_action += int(CS.out.genericToggle and not self.generic_toggle_last)
self.lkas_action &= 0xf
else:
self.lkas_action = 5 # 4 and 5 seem the best. 8 and 9 seem to aggressive and laggy
can_sends.append(create_steer_command(self.packer, apply_steer, enabled,
CS.lkas_state, CS.angle_steers, curvature, self.lkas_action))
self.generic_toggle_last = CS.generic_toggle
CS.lkas_state, CS.out.steeringAngle, curvature, self.lkas_action))
self.generic_toggle_last = CS.out.genericToggle
if (frame % 100) == 0:
can_sends.append(make_can_msg(973, b'\x00\x00\x00\x00\x00\x00\x00\x00', 0))
#can_sends.append(make_can_msg(984, b'\x00\x00\x00\x00\x80\x45\x60\x30', 0))
if (frame % 100) == 0 or (self.enabled_last != enabled) or (self.main_on_last != CS.main_on) or \
if (frame % 100) == 0 or (self.enabled_last != enabled) or (self.main_on_last != CS.out.cruiseState.available) or \
(self.steer_alert_last != steer_alert):
can_sends.append(create_lkas_ui(self.packer, CS.main_on, enabled, steer_alert))
can_sends.append(create_lkas_ui(self.packer, CS.out.cruiseState.available, enabled, steer_alert))
if (frame % 200) == 0:
can_sends.append(make_can_msg(1875, b'\x80\xb0\x55\x55\x78\x90\x00\x00', 1))
@ -81,7 +81,7 @@ class CarController():
can_sends.append(make_can_msg(addr, (cnt<<4).to_bytes(1, 'little') + b'\x00\x00\x00\x00\x00\x00\x00', 1))
self.enabled_last = enabled
self.main_on_last = CS.main_on
self.main_on_last = CS.out.cruiseState.available
self.steer_alert_last = steer_alert
return can_sends

76
selfdrive/car/ford/carstate.py
View File

@ -1,8 +1,9 @@
from cereal import car
from opendbc.can.parser import CANParser
from common.numpy_fast import mean
from selfdrive.config import Conversions as CV
from selfdrive.car.interfaces import CarStateBase
from selfdrive.car.ford.values import DBC
from common.kalman.simple_kalman import KF1D
WHEEL_RADIUS = 0.33
@ -32,57 +33,28 @@ def get_can_parser(CP):
return CANParser(DBC[CP.carFingerprint]['pt'], signals, checks, 0)
class CarState():
def __init__(self, CP):
self.CP = CP
self.left_blinker_on = 0
self.right_blinker_on = 0
# initialize can parser
self.car_fingerprint = CP.carFingerprint
# vEgo kalman filter
dt = 0.01
# Q = np.matrix([[10.0, 0.0], [0.0, 100.0]])
# R = 1e3
self.v_ego_kf = KF1D(x0=[[0.0], [0.0]],
A=[[1.0, dt], [0.0, 1.0]],
C=[1.0, 0.0],
K=[[0.12287673], [0.29666309]])
self.v_ego = 0.0
class CarState(CarStateBase):
def update(self, cp):
# update prevs, update must run once per loop
self.prev_left_blinker_on = self.left_blinker_on
self.prev_right_blinker_on = self.right_blinker_on
# calc best v_ego estimate, by averaging two opposite corners
self.v_wheel_fl = cp.vl["WheelSpeed_CG1"]['WhlRr_W_Meas'] * WHEEL_RADIUS
self.v_wheel_fr = cp.vl["WheelSpeed_CG1"]['WhlRl_W_Meas'] * WHEEL_RADIUS
self.v_wheel_rl = cp.vl["WheelSpeed_CG1"]['WhlFr_W_Meas'] * WHEEL_RADIUS
self.v_wheel_rr = cp.vl["WheelSpeed_CG1"]['WhlFl_W_Meas'] * WHEEL_RADIUS
v_wheel = mean([self.v_wheel_fl, self.v_wheel_fr, self.v_wheel_rl, self.v_wheel_rr])
# Kalman filter
if abs(v_wheel - self.v_ego) > 2.0: # Prevent large accelerations when car starts at non zero speed
self.v_ego_kf.x = [[v_wheel], [0.0]]
self.v_ego_raw = v_wheel
v_ego_x = self.v_ego_kf.update(v_wheel)
self.v_ego = float(v_ego_x[0])
self.a_ego = float(v_ego_x[1])
self.standstill = not v_wheel > 0.001
self.angle_steers = cp.vl["Steering_Wheel_Data_CG1"]['SteWhlRelInit_An_Sns']
self.v_cruise_pcm = cp.vl["Cruise_Status"]['Set_Speed'] * CV.MPH_TO_MS
self.pcm_acc_status = cp.vl["Cruise_Status"]['Cruise_State']
self.main_on = cp.vl["Cruise_Status"]['Cruise_State'] != 0
self.lkas_state = cp.vl["Lane_Keep_Assist_Status"]['LaActAvail_D_Actl']
ret = car.CarState.new_message()
ret.wheelSpeeds.rr = cp.vl["WheelSpeed_CG1"]['WhlRr_W_Meas'] * WHEEL_RADIUS
ret.wheelSpeeds.rl = cp.vl["WheelSpeed_CG1"]['WhlRl_W_Meas'] * WHEEL_RADIUS
ret.wheelSpeeds.fr = cp.vl["WheelSpeed_CG1"]['WhlFr_W_Meas'] * WHEEL_RADIUS
ret.wheelSpeeds.fl = cp.vl["WheelSpeed_CG1"]['WhlFl_W_Meas'] * WHEEL_RADIUS
ret.vEgoRaw = mean([ret.wheelSpeeds.rr, ret.wheelSpeeds.rl, ret.wheelSpeeds.fr, ret.wheelSpeeds.fl])
ret.vEgo, ret.aEgo = self.update_speed_kf(ret.vEgoRaw)
ret.standstill = not ret.vEgoRaw > 0.001
ret.steeringAngle = cp.vl["Steering_Wheel_Data_CG1"]['SteWhlRelInit_An_Sns']
ret.steeringPressed = not cp.vl["Lane_Keep_Assist_Status"]['LaHandsOff_B_Actl']
ret.cruiseState.speed = cp.vl["Cruise_Status"]['Set_Speed'] * CV.MPH_TO_MS
ret.cruiseState.enabled = not (cp.vl["Cruise_Status"]['Cruise_State'] in [0, 3])
ret.cruiseState.available = cp.vl["Cruise_Status"]['Cruise_State'] != 0
ret.gas = cp.vl["EngineData_14"]['ApedPosScal_Pc_Actl'] / 100.
ret.gasPressed = ret.gas > 1e-6
ret.brakePressed = bool(cp.vl["Cruise_Status"]["Brake_Drv_Appl"])
ret.brakeLights = bool(cp.vl["BCM_to_HS_Body"]["Brake_Lights"])
ret.genericToggle = bool(cp.vl["Steering_Buttons"]["Dist_Incr"])
# TODO: we also need raw driver torque, needed for Assisted Lane Change
self.steer_override = not cp.vl["Lane_Keep_Assist_Status"]['LaHandsOff_B_Actl']
self.lkas_state = cp.vl["Lane_Keep_Assist_Status"]['LaActAvail_D_Actl']
self.steer_error = cp.vl["Lane_Keep_Assist_Status"]['LaActDeny_B_Actl']
self.user_gas = cp.vl["EngineData_14"]['ApedPosScal_Pc_Actl']
self.brake_pressed = bool(cp.vl["Cruise_Status"]["Brake_Drv_Appl"])
self.brake_lights = bool(cp.vl["BCM_to_HS_Body"]["Brake_Lights"])
self.generic_toggle = bool(cp.vl["Steering_Buttons"]["Dist_Incr"])
return ret

34
selfdrive/car/ford/interface.py
View File

@ -106,38 +106,10 @@ class CarInterface(CarInterfaceBase):
# ******************* do can recv *******************
self.cp.update_strings(can_strings)
self.CS.update(self.cp)
# create message
ret = car.CarState.new_message()
ret = self.CS.update(self.cp)
ret.canValid = self.cp.can_valid
# speeds
ret.vEgo = self.CS.v_ego
ret.vEgoRaw = self.CS.v_ego_raw
ret.standstill = self.CS.standstill
ret.wheelSpeeds.fl = self.CS.v_wheel_fl
ret.wheelSpeeds.fr = self.CS.v_wheel_fr
ret.wheelSpeeds.rl = self.CS.v_wheel_rl
ret.wheelSpeeds.rr = self.CS.v_wheel_rr
# steering wheel
ret.steeringAngle = self.CS.angle_steers
ret.steeringPressed = self.CS.steer_override
# gas pedal
ret.gas = self.CS.user_gas / 100.
ret.gasPressed = self.CS.user_gas > 0.0001
ret.brakePressed = self.CS.brake_pressed
ret.brakeLights = self.CS.brake_lights
ret.cruiseState.enabled = not (self.CS.pcm_acc_status in [0, 3])
ret.cruiseState.speed = self.CS.v_cruise_pcm
ret.cruiseState.available = self.CS.pcm_acc_status != 0
ret.genericToggle = self.CS.generic_toggle
# events
events = []
@ -167,7 +139,9 @@ class CarInterface(CarInterfaceBase):
self.brake_pressed_prev = ret.brakePressed
self.cruise_enabled_prev = ret.cruiseState.enabled
return ret.as_reader()
self.CS.out = ret.as_reader()
return self.CS.out
# pass in a car.CarControl
# to be called @ 100hz

7
selfdrive/car/fw_versions.py
View File

@ -123,9 +123,12 @@ def get_fw_versions(logcan, sendcan, bus, extra=None, timeout=0.1, debug=False,
ecu_types[a] = ecu_type
if sub_addr is None:
parallel_addrs.append(a)
if a not in parallel_addrs:
parallel_addrs.append(a)
else:
addrs.append([a])
if [a] not in addrs:
addrs.append([a])
addrs.insert(0, parallel_addrs)
fw_versions = {}

43
selfdrive/car/gm/carstate.py
View File

@ -1,9 +1,10 @@
from cereal import car
from common.numpy_fast import mean
from common.kalman.simple_kalman import KF1D
from selfdrive.config import Conversions as CV
from opendbc.can.can_define import CANDefine
from opendbc.can.parser import CANParser
from selfdrive.car.gm.values import DBC, CAR, parse_gear_shifter, \
from selfdrive.car.interfaces import CarStateBase
from selfdrive.car.gm.values import DBC, CAR, \
CruiseButtons, is_eps_status_ok, \
STEER_THRESHOLD, SUPERCRUISE_CARS
@ -50,25 +51,11 @@ def get_powertrain_can_parser(CP, canbus):
return CANParser(DBC[CP.carFingerprint]['pt'], signals, [], canbus.powertrain)
class CarState():
def __init__(self, CP, canbus):
self.CP = CP
# initialize can parser
self.car_fingerprint = CP.carFingerprint
self.cruise_buttons = CruiseButtons.UNPRESS
self.left_blinker_on = False
self.prev_left_blinker_on = False
self.right_blinker_on = False
self.prev_right_blinker_on = False
# vEgo kalman filter
dt = 0.01
self.v_ego_kf = KF1D(x0=[[0.], [0.]],
A=[[1., dt], [0., 1.]],
C=[1., 0.],
K=[[0.12287673], [0.29666309]])
self.v_ego = 0.
class CarState(CarStateBase):
def __init__(self, CP):
super().__init__(CP)
can_define = CANDefine(DBC[CP.carFingerprint]['pt'])
self.shifter_values = can_define.dv["ECMPRDNL"]["PRNDL"]
def update(self, pt_cp):
self.prev_cruise_buttons = self.cruise_buttons
@ -78,20 +65,12 @@ class CarState():
self.v_wheel_fr = pt_cp.vl["EBCMWheelSpdFront"]['FRWheelSpd'] * CV.KPH_TO_MS
self.v_wheel_rl = pt_cp.vl["EBCMWheelSpdRear"]['RLWheelSpd'] * CV.KPH_TO_MS
self.v_wheel_rr = pt_cp.vl["EBCMWheelSpdRear"]['RRWheelSpd'] * CV.KPH_TO_MS
v_wheel = mean([self.v_wheel_fl, self.v_wheel_fr, self.v_wheel_rl, self.v_wheel_rr])
if abs(v_wheel - self.v_ego) > 2.0: # Prevent large accelerations when car starts at non zero speed
self.v_ego_kf.x = [[v_wheel], [0.0]]
self.v_ego_raw = v_wheel
v_ego_x = self.v_ego_kf.update(v_wheel)
self.v_ego = float(v_ego_x[0])
self.a_ego = float(v_ego_x[1])
self.v_ego_raw = mean([self.v_wheel_fl, self.v_wheel_fr, self.v_wheel_rl, self.v_wheel_rr])
self.v_ego, self.a_ego = self.update_speed_kf(self.v_ego_raw)
self.standstill = self.v_ego_raw < 0.01
self.angle_steers = pt_cp.vl["PSCMSteeringAngle"]['SteeringWheelAngle']
self.gear_shifter = parse_gear_shifter(pt_cp.vl["ECMPRDNL"]['PRNDL'])
self.gear_shifter = self.parse_gear_shifter(self.shifter_values.get(pt_cp.vl["ECMPRDNL"]['PRNDL'], None))
self.user_brake = pt_cp.vl["EBCMBrakePedalPosition"]['BrakePedalPosition']
self.pedal_gas = pt_cp.vl["AcceleratorPedal"]['AcceleratorPedal']

4
selfdrive/car/gm/gmcan.py
View File

@ -67,8 +67,8 @@ def create_friction_brake_command(packer, bus, apply_brake, idx, near_stop, at_f
else:
mode = 0xa
if at_full_stop:
mode = 0xd
if at_full_stop:
mode = 0xd
# TODO: this is to have GM bringing the car to complete stop,
# but currently it conflicts with OP controls, so turned off.
#elif near_stop:

18
selfdrive/car/gm/interface.py
View File

@ -29,7 +29,7 @@ class CarInterface(CarInterfaceBase):
# *** init the major players ***
canbus = CanBus()
self.CS = CarState(CP, canbus)
self.CS = CarState(CP)
self.VM = VehicleModel(CP)
self.pt_cp = get_powertrain_can_parser(CP, canbus)
self.ch_cp_dbc_name = DBC[CP.carFingerprint]['chassis']
@ -64,6 +64,13 @@ class CarInterface(CarInterfaceBase):
ret.openpilotLongitudinalControl = ret.enableCamera
tire_stiffness_factor = 0.444 # not optimized yet
# Start with a baseline lateral tuning for all GM vehicles. Override tuning as needed in each model section below.
ret.lateralTuning.pid.kiBP, ret.lateralTuning.pid.kpBP = [[0.], [0.]]
ret.lateralTuning.pid.kpV, ret.lateralTuning.pid.kiV = [[0.2], [0.00]]
ret.lateralTuning.pid.kf = 0.00004 # full torque for 20 deg at 80mph means 0.00007818594
ret.steerRateCost = 1.0
ret.steerActuatorDelay = 0.1 # Default delay, not measured yet
if candidate == CAR.VOLT:
# supports stop and go, but initial engage must be above 18mph (which include conservatism)
ret.minEnableSpeed = 18 * CV.MPH_TO_MS
@ -141,11 +148,6 @@ class CarInterface(CarInterfaceBase):
ret.tireStiffnessFront, ret.tireStiffnessRear = scale_tire_stiffness(ret.mass, ret.wheelbase, ret.centerToFront,
tire_stiffness_factor=tire_stiffness_factor)
# same tuning for Volt and CT6 for now
ret.lateralTuning.pid.kiBP, ret.lateralTuning.pid.kpBP = [[0.], [0.]]
ret.lateralTuning.pid.kpV, ret.lateralTuning.pid.kiV = [[0.2], [0.00]]
ret.lateralTuning.pid.kf = 0.00004 # full torque for 20 deg at 80mph means 0.00007818594
ret.steerMaxBP = [0.] # m/s
ret.steerMaxV = [1.]
ret.gasMaxBP = [0.]
@ -163,8 +165,6 @@ class CarInterface(CarInterfaceBase):
ret.stoppingControl = True
ret.startAccel = 0.8
ret.steerActuatorDelay = 0.1 # Default delay, not measured yet
ret.steerRateCost = 1.0
ret.steerLimitTimer = 0.4
ret.radarTimeStep = 0.0667 # GM radar runs at 15Hz instead of standard 20Hz
ret.steerControlType = car.CarParams.SteerControlType.torque
@ -237,7 +237,7 @@ class CarInterface(CarInterfaceBase):
be.pressed = self.CS.right_blinker_on
buttonEvents.append(be)
if self.CS.cruise_buttons != self.CS.prev_cruise_buttons:
if self.CS.cruise_buttons != self.CS.prev_cruise_buttons and self.CS.prev_cruise_buttons != CruiseButtons.INIT:
be = car.CarState.ButtonEvent.new_message()
be.type = ButtonType.unknown
if self.CS.cruise_buttons != CruiseButtons.UNPRESS:

13
selfdrive/car/gm/values.py
View File

@ -14,6 +14,7 @@ class CAR:
SUPERCRUISE_CARS = [CAR.CADILLAC_CT6]
class CruiseButtons:
INIT = 0
UNPRESS = 1
RES_ACCEL = 2
DECEL_SET = 3
@ -34,18 +35,6 @@ def is_eps_status_ok(eps_status, car_fingerprint):
valid_eps_status += [0, 1]
return eps_status in valid_eps_status
def parse_gear_shifter(can_gear):
if can_gear == 0:
return car.CarState.GearShifter.park
elif can_gear == 1:
return car.CarState.GearShifter.neutral
elif can_gear == 2:
return car.CarState.GearShifter.drive
elif can_gear == 3:
return car.CarState.GearShifter.reverse
else:
return car.CarState.GearShifter.unknown
FINGERPRINTS = {
# Astra BK MY17, ASCM unplugged
CAR.HOLDEN_ASTRA: [{

52
selfdrive/car/honda/carstate.py
View File

@ -1,19 +1,11 @@
from cereal import car
from collections import defaultdict
from common.numpy_fast import interp
from common.kalman.simple_kalman import KF1D
from opendbc.can.can_define import CANDefine
from opendbc.can.parser import CANParser
from selfdrive.config import Conversions as CV
from selfdrive.car.interfaces import CarStateBase
from selfdrive.car.honda.values import CAR, DBC, STEER_THRESHOLD, SPEED_FACTOR, HONDA_BOSCH
GearShifter = car.CarState.GearShifter
def parse_gear_shifter(gear):
return {'P': GearShifter.park, 'R': GearShifter.reverse, 'N': GearShifter.neutral,
'D': GearShifter.drive, 'S': GearShifter.sport, 'L': GearShifter.low}.get(gear, GearShifter.unknown)
def calc_cruise_offset(offset, speed):
# euristic formula so that speed is controlled to ~ 0.3m/s below pid_speed
# constraints to solve for _K0, _K1, _K2 are:
@ -188,38 +180,21 @@ def get_cam_can_parser(CP):
bus_cam = 1 if CP.carFingerprint in HONDA_BOSCH and not CP.isPandaBlack else 2
return CANParser(DBC[CP.carFingerprint]['pt'], signals, checks, bus_cam)
class CarState():
class CarState(CarStateBase):
def __init__(self, CP):
self.CP = CP
self.can_define = CANDefine(DBC[CP.carFingerprint]['pt'])
self.shifter_values = self.can_define.dv["GEARBOX"]["GEAR_SHIFTER"]
self.steer_status_values = defaultdict(lambda: "UNKNOWN", self.can_define.dv["STEER_STATUS"]["STEER_STATUS"])
super().__init__(CP)
can_define = CANDefine(DBC[CP.carFingerprint]['pt'])
self.shifter_values = can_define.dv["GEARBOX"]["GEAR_SHIFTER"]
self.steer_status_values = defaultdict(lambda: "UNKNOWN", can_define.dv["STEER_STATUS"]["STEER_STATUS"])
self.user_gas, self.user_gas_pressed = 0., 0
self.brake_switch_prev = 0
self.brake_switch_ts = 0
self.cruise_buttons = 0
self.cruise_setting = 0
self.v_cruise_pcm_prev = 0
self.blinker_on = 0
self.left_blinker_on = 0
self.right_blinker_on = 0
self.cruise_mode = 0
self.stopped = 0
# vEgo kalman filter
dt = 0.01
# Q = np.matrix([[10.0, 0.0], [0.0, 100.0]])
# R = 1e3
self.v_ego_kf = KF1D(x0=[[0.0], [0.0]],
A=[[1.0, dt], [0.0, 1.0]],
C=[1.0, 0.0],
K=[[0.12287673], [0.29666309]])
self.v_ego = 0.0
def update(self, cp, cp_cam):
# car params
@ -229,8 +204,6 @@ class CarState():
# update prevs, update must run once per loop
self.prev_cruise_buttons = self.cruise_buttons
self.prev_cruise_setting = self.cruise_setting
self.prev_blinker_on = self.blinker_on
self.prev_left_blinker_on = self.left_blinker_on
self.prev_right_blinker_on = self.right_blinker_on
@ -260,7 +233,6 @@ class CarState():
self.brake_error = cp.vl["STANDSTILL"]['BRAKE_ERROR_1'] or cp.vl["STANDSTILL"]['BRAKE_ERROR_2']
self.esp_disabled = cp.vl["VSA_STATUS"]['ESP_DISABLED']
# calc best v_ego estimate, by averaging two opposite corners
speed_factor = SPEED_FACTOR[self.CP.carFingerprint]
self.v_wheel_fl = cp.vl["WHEEL_SPEEDS"]['WHEEL_SPEED_FL'] * CV.KPH_TO_MS * speed_factor
self.v_wheel_fr = cp.vl["WHEEL_SPEEDS"]['WHEEL_SPEED_FR'] * CV.KPH_TO_MS * speed_factor
@ -270,16 +242,10 @@ class CarState():
# blend in transmission speed at low speed, since it has more low speed accuracy
self.v_weight = interp(v_wheel, v_weight_bp, v_weight_v)
speed = (1. - self.v_weight) * cp.vl["ENGINE_DATA"]['XMISSION_SPEED'] * CV.KPH_TO_MS * speed_factor + \
self.v_ego_raw = (1. - self.v_weight) * cp.vl["ENGINE_DATA"]['XMISSION_SPEED'] * CV.KPH_TO_MS * speed_factor + \
self.v_weight * v_wheel
if abs(speed - self.v_ego) > 2.0: # Prevent large accelerations when car starts at non zero speed
self.v_ego_kf.x = [[speed], [0.0]]
self.v_ego_raw = speed
v_ego_x = self.v_ego_kf.update(speed)
self.v_ego = float(v_ego_x[0])
self.a_ego = float(v_ego_x[1])
self.v_ego, self.a_ego = self.update_speed_kf(self.v_ego_raw)
# this is a hack for the interceptor. This is now only used in the simulation
# TODO: Replace tests by toyota so this can go away
@ -310,7 +276,7 @@ class CarState():
self.main_on = cp.vl["SCM_BUTTONS"]['MAIN_ON']
can_gear_shifter = int(cp.vl["GEARBOX"]['GEAR_SHIFTER'])
self.gear_shifter = parse_gear_shifter(self.shifter_values.get(can_gear_shifter, None))
self.gear_shifter = self.parse_gear_shifter(self.shifter_values.get(can_gear_shifter, None))
self.pedal_gas = cp.vl["POWERTRAIN_DATA"]['PEDAL_GAS']
# crv doesn't include cruise control

33
selfdrive/car/honda/values.py
View File

@ -132,11 +132,12 @@ FW_VERSIONS = {
b'37805-6A0-A640\x00\x00',
b'37805-6B2-A550\x00\x00',
b'37805-6B2-A650\x00\x00',
b'37805-6B2-A660\x00\x00',
b'37805-6B2-M520\x00\x00',
],
(Ecu.unknown, 0x18da0bf1, None): [b'54008-TVC-A910\x00\x00'],
(Ecu.unknown, 0x18da1ef1, None): [b'28102-6B8-A560\x00\x00', b'28102-6B8-M520\x00\x00'],
(Ecu.unknown, 0x18da2bf1, None): [b'46114-TVA-A060\x00\x00'],
(Ecu.unknown, 0x18da2bf1, None): [b'46114-TVA-A060\x00\x00', b'46114-TVA-A080\x00\x00'],
(Ecu.unknown, 0x18da28f1, None): [b'57114-TVA-C050\x00\x00'],
(Ecu.eps, 0x18da30f1, None): [
b'39990-TVA-A150\x00\x00',
@ -153,7 +154,11 @@ FW_VERSIONS = {
b'78109-TVC-M510\x00\x00',
],
(Ecu.unknown, 0x18da61f1, None): [b'78209-TVA-A010\x00\x00'],
(Ecu.unknown, 0x18dab0f1, None): [b'36802-TVA-A160\x00\x00', b'36802-TWA-A070\x00\x00'],
(Ecu.unknown, 0x18dab0f1, None): [
b'36802-TVA-A160\x00\x00',
b'36802-TVA-A170\x00\x00',
b'36802-TWA-A070\x00\x00',
],
(Ecu.unknown, 0x18dab5f1, None): [b'36161-TVA-A060\x00\x00', b'36161-TWA-A070\x00\x00'],
(Ecu.unknown, 0x18daeff1, None): [b'38897-TVA-A010\x00\x00'],
},
@ -224,6 +229,7 @@ FW_VERSIONS = {
b'37805-5AA-A670\x00\x00',
b'37805-5AA-A680\x00\x00',
b'37805-5AA-A810\x00\x00',
b'37805-5AA-C820\x00\x00',
b'37805-5AA-L660\x00\x00',
b'37805-5AJ-A610\x00\x00',
b'37805-5BA-A510\x00\x00',
@ -236,6 +242,7 @@ FW_VERSIONS = {
b'28101-5CG-A070\x00\x00',
b'28101-5CG-A080\x00\x00',
b'28101-5CG-A810\x00\x00',
b'28101-5CG-A820\x00\x00',
b'28101-5DJ-A040\x00\x00',
b'28101-5DJ-A060\x00\x00',
b'28101-5DJ-A510\x00\x00',
@ -262,6 +269,7 @@ FW_VERSIONS = {
b'78109-TBC-A510\x00\x00',
b'78109-TBC-A520\x00\x00',
b'78109-TBC-A530\x00\x00',
b'78109-TBC-C530\x00\x00',
b'78109-TBH-A530\x00\x00',
b'78109-TEG-A310\x00\x00',
],
@ -272,7 +280,6 @@ FW_VERSIONS = {
b'36161-TEG-A010\x00\x00',
],
(Ecu.unknown, 0x18daeff1, None): [
b'36161-TBA-A030\x00\x00',
b'38897-TBA-A010\x00\x00',
b'38897-TBA-A020\x00\x00',
],
@ -285,11 +292,15 @@ FW_VERSIONS = {
b'37805-5AN-A830\x00\x00',
b'37805-5AN-A930\x00\x00',
b'37805-5AN-L940\x00\x00',
b'37805-5AN-LH20\x00\x00',
b'37805-5AN-LJ20\x00\x00',
b'37805-5AZ-E850\x00\x00',
b'37805-5BB-L640\x00\x00',
],
(Ecu.unknown, 0x18da1ef1, None): [
b'28101-5CG-A920\x00\x00',
b'28101-5CG-C220\x00\x00',
b'28101-5CG-C320\x00\x00',
b'28101-5CK-A130\x00\x00',
b'28101-5CK-A140\x00\x00',
b'28101-5CK-A150\x00\x00',
@ -301,6 +312,7 @@ FW_VERSIONS = {
b'57114-TBG-A340\x00\x00',
b'57114-TGG-A340\x00\x00',
b'57114-TGL-G330\x00\x00',
b'57114-TGG-C320\x00\x00',
],
(Ecu.eps, 0x18da30f1, None): [
b'39990-TBA-C020\x00\x00',
@ -308,31 +320,41 @@ FW_VERSIONS = {
b'39990-TGG-A020\x00\x00',
b'39990-TGG-A120\x00\x00',
b'39990-TGL-E130\x00\x00',
b'39990-TGG-A020\x00\x00',
],
(Ecu.unknown, 0x18da53f1, None): [
b'77959-TBA-A060\x00\x00',
b'77959-TGG-A020\x00\x00',
b'77959-TGG-G010\x00\x00',
b'77959-TGG-A020\x00\x00',
],
(Ecu.unknown, 0x18da60f1, None): [
b'78109-TBA-A910\x00\x00',
b'78109-TBC-A740\x00\x00',
b'78109-TGG-A210\x00\x00',
b'78109-TGG-A310\x00\x00',
b'78109-TGG-A320\x00\x00',
b'78109-TGG-A810\x00\x00',
b'78109-TGG-A820\x00\x00',
b'78109-TGL-G120\x00\x00',
],
(Ecu.unknown, 0x18dab0f1, None): [
b'36802-TBA-A150\x00\x00',
b'36802-TGG-A050\x00\x00',
b'36802-TGL-G040\x00\x00',
b'36802-TGG-A060\x00\x00',
],
(Ecu.unknown, 0x18dab5f1, None): [
b'36161-TBA-A130\x00\x00',
b'36161-TGG-A060\x00\x00',
b'36161-TGL-G050\x00\x00',
b'36161-TGG-A080\x00\x00',
],
(Ecu.unknown, 0x18daeff1, None): [
b'38897-TBA-A110\x00\x00',
b'38897-TBA-A020\x00\x00',
b'38897-TBA-A020\x00\x00',
],
(Ecu.unknown, 0x18daeff1, None): [b'38897-TBA-A110\x00\x00', b'38897-TBA-A020\x00\x00'],
},
CAR.CRV_5G: {
(Ecu.unknown, 0x18da10f1, None): [
@ -344,6 +366,7 @@ FW_VERSIONS = {
b'37805-5PA-A680\x00\x00',
b'37805-5PA-A850\x00\x00',
b'37805-5PA-A870\x00\x00',
b'37805-5PA-A880\x00\x00',
b'37805-5PA-A890\x00\x00',
],
(Ecu.unknown, 0x18da1ef1, None): [
@ -422,6 +445,7 @@ FW_VERSIONS = {
b'28102-5MX-A610\x00\x00',
b'28102-5MX-A710\x00\x00',
b'28102-5MX-A910\x00\x00',
b'28102-5MX-C001\x00\x00',
b'28103-5NZ-A300\x00\x00',
],
(Ecu.unknown, 0x18da28f1, None): [b'57114-THR-A040\x00\x00', b'57114-THR-A110\x00\x00'],
@ -436,6 +460,7 @@ FW_VERSIONS = {
b'78109-THR-AE40\x00\x00',
b'78109-THR-AL10\x00\x00',
b'78109-THR-C330\x00\x00',
b'78109-THR-CE20\x00\x00',
],
(Ecu.unknown, 0x18da0bf1, None): [b'54008-THR-A020\x00\x00'],
},

42
selfdrive/car/hyundai/carstate.py
View File

@ -1,8 +1,8 @@
from cereal import car
from selfdrive.car.hyundai.values import DBC, STEER_THRESHOLD
from selfdrive.car.interfaces import CarStateBase
from opendbc.can.parser import CANParser
from selfdrive.config import Conversions as CV
from common.kalman.simple_kalman import KF1D
GearShifter = car.CarState.GearShifter
@ -124,27 +124,7 @@ def get_camera_parser(CP):
return CANParser(DBC[CP.carFingerprint]['pt'], signals, checks, 2)
class CarState():
def __init__(self, CP):
self.CP = CP
# initialize can parser
self.car_fingerprint = CP.carFingerprint
# vEgo kalman filter
dt = 0.01
# Q = np.matrix([[10.0, 0.0], [0.0, 100.0]])
# R = 1e3
self.v_ego_kf = KF1D(x0=[[0.0], [0.0]],
A=[[1.0, dt], [0.0, 1.0]],
C=[1.0, 0.0],
K=[[0.12287673], [0.29666309]])
self.v_ego = 0.0
self.left_blinker_on = 0
self.left_blinker_flash = 0
self.right_blinker_on = 0
self.right_blinker_flash = 0
class CarState(CarStateBase):
def update(self, cp, cp_cam):
# update prevs, update must run once per Loop
@ -162,36 +142,26 @@ class CarState():
self.acc_active = cp.vl["SCC12"]['ACCMode'] != 0
self.pcm_acc_status = int(self.acc_active)
# calc best v_ego estimate, by averaging two opposite corners
self.v_wheel_fl = cp.vl["WHL_SPD11"]['WHL_SPD_FL'] * CV.KPH_TO_MS
self.v_wheel_fr = cp.vl["WHL_SPD11"]['WHL_SPD_FR'] * CV.KPH_TO_MS
self.v_wheel_rl = cp.vl["WHL_SPD11"]['WHL_SPD_RL'] * CV.KPH_TO_MS
self.v_wheel_rr = cp.vl["WHL_SPD11"]['WHL_SPD_RR'] * CV.KPH_TO_MS
v_wheel = (self.v_wheel_fl + self.v_wheel_fr + self.v_wheel_rl + self.v_wheel_rr) / 4.
self.v_ego_raw = (self.v_wheel_fl + self.v_wheel_fr + self.v_wheel_rl + self.v_wheel_rr) / 4.
self.v_ego, self.a_ego = self.update_speed_kf(self.v_ego_raw)
self.low_speed_lockout = v_wheel < 1.0
self.low_speed_lockout = self.v_ego_raw < 1.0
# Kalman filter, even though Hyundai raw wheel speed is heaviliy filtered by default
if abs(v_wheel - self.v_ego) > 2.0: # Prevent large accelerations when car starts at non zero speed
self.v_ego_kf.x = [[v_wheel], [0.0]]
self.v_ego_raw = v_wheel
v_ego_x = self.v_ego_kf.update(v_wheel)
self.v_ego = float(v_ego_x[0])
self.a_ego = float(v_ego_x[1])
is_set_speed_in_mph = int(cp.vl["CLU11"]["CF_Clu_SPEED_UNIT"])
speed_conv = CV.MPH_TO_MS if is_set_speed_in_mph else CV.KPH_TO_MS
self.cruise_set_speed = cp.vl["SCC11"]['VSetDis'] * speed_conv
self.standstill = not v_wheel > 0.1
self.standstill = not self.v_ego_raw > 0.1
self.angle_steers = cp.vl["SAS11"]['SAS_Angle']
self.angle_steers_rate = cp.vl["SAS11"]['SAS_Speed']
self.yaw_rate = cp.vl["ESP12"]['YAW_RATE']
self.main_on = True
self.left_blinker_on = cp.vl["CGW1"]['CF_Gway_TSigLHSw']
self.left_blinker_flash = cp.vl["CGW1"]['CF_Gway_TurnSigLh']
self.right_blinker_on = cp.vl["CGW1"]['CF_Gway_TSigRHSw']
self.right_blinker_flash = cp.vl["CGW1"]['CF_Gway_TurnSigRh']
self.steer_override = abs(cp.vl["MDPS11"]['CR_Mdps_DrvTq']) > STEER_THRESHOLD
self.steer_state = cp.vl["MDPS12"]['CF_Mdps_ToiActive'] #0 NOT ACTIVE, 1 ACTIVE
self.steer_error = cp.vl["MDPS12"]['CF_Mdps_ToiUnavail']

32
selfdrive/car/interfaces.py
View File

@ -1,8 +1,12 @@
import os
import time
from cereal import car
from common.kalman.simple_kalman import KF1D
from common.realtime import DT_CTRL
from selfdrive.car import gen_empty_fingerprint
GearShifter = car.CarState.GearShifter
# generic car and radar interfaces
class CarInterfaceBase():
@ -42,3 +46,31 @@ class RadarInterfaceBase():
time.sleep(self.radar_ts) # radard runs on RI updates
return ret
class CarStateBase:
def __init__(self, CP):
self.CP = CP
self.car_fingerprint = CP.carFingerprint
self.left_blinker_on = 0
self.right_blinker_on = 0
self.cruise_buttons = 0
# Q = np.matrix([[10.0, 0.0], [0.0, 100.0]])
# R = 1e3
self.v_ego_kf = KF1D(x0=[[0.0], [0.0]],
A=[[1.0, DT_CTRL], [0.0, 1.0]],
C=[1.0, 0.0],
K=[[0.12287673], [0.29666309]])
def update_speed_kf(self, v_ego_raw):
if abs(v_ego_raw - self.v_ego_kf.x[0][0]) > 2.0: # Prevent large accelerations when car starts at non zero speed
self.v_ego_kf.x = [[v_ego_raw], [0.0]]
v_ego_x = self.v_ego_kf.update(v_ego_raw)
return float(v_ego_x[0]), float(v_ego_x[1])
@staticmethod
def parse_gear_shifter(gear):
return {'P': GearShifter.park, 'R': GearShifter.reverse, 'N': GearShifter.neutral,
'E': GearShifter.eco, 'T': GearShifter.manumatic, 'D': GearShifter.drive,
'S': GearShifter.sport, 'L': GearShifter.low, 'B': GearShifter.brake}.get(gear, GearShifter.unknown)

2
selfdrive/car/subaru/carcontroller.py
View File

@ -53,7 +53,7 @@ class CarController():
apply_steer = apply_std_steer_torque_limits(new_steer, self.apply_steer_last, CS.steer_torque_driver, P)
self.steer_rate_limited = new_steer != apply_steer
lkas_enabled = enabled and not CS.steer_not_allowed
lkas_enabled = enabled
if not lkas_enabled:
apply_steer = 0

33
selfdrive/car/subaru/carstate.py
View File

@ -1,6 +1,6 @@
import copy
from common.kalman.simple_kalman import KF1D
from selfdrive.config import Conversions as CV
from selfdrive.car.interfaces import CarStateBase
from opendbc.can.parser import CANParser
from selfdrive.car.subaru.values import DBC, STEER_THRESHOLD
@ -82,29 +82,12 @@ def get_camera_can_parser(CP):
return CANParser(DBC[CP.carFingerprint]['pt'], signals, checks, 2)
class CarState():
class CarState(CarStateBase):
def __init__(self, CP):
super().__init__(CP)
# initialize can parser
self.CP = CP
self.car_fingerprint = CP.carFingerprint
self.left_blinker_on = False
self.left_blinker_cnt = 0
self.prev_left_blinker_on = False
self.right_blinker_on = False
self.right_blinker_cnt = 0
self.prev_right_blinker_on = False
self.steer_torque_driver = 0
self.steer_not_allowed = False
self.main_on = False
# vEgo kalman filter
dt = 0.01
self.v_ego_kf = KF1D(x0=[[0.], [0.]],
A=[[1., dt], [0., 1.]],
C=[1., 0.],
K=[[0.12287673], [0.29666309]])
self.v_ego = 0.
def update(self, cp, cp_cam):
@ -124,16 +107,10 @@ class CarState():
if cp.vl["Dash_State"]['Units'] == 1:
self.v_cruise_pcm *= CV.MPH_TO_KPH
v_wheel = (self.v_wheel_fl + self.v_wheel_fr + self.v_wheel_rl + self.v_wheel_rr) / 4.
self.v_ego_raw = (self.v_wheel_fl + self.v_wheel_fr + self.v_wheel_rl + self.v_wheel_rr) / 4.
# Kalman filter, even though Subaru raw wheel speed is heaviliy filtered by default
if abs(v_wheel - self.v_ego) > 2.0: # Prevent large accelerations when car starts at non zero speed
self.v_ego_kf.x = [[v_wheel], [0.0]]
self.v_ego, self.a_ego = self.update_speed_kf(self.v_ego_raw)
self.v_ego_raw = v_wheel
v_ego_x = self.v_ego_kf.update(v_wheel)
self.v_ego = float(v_ego_x[0])
self.a_ego = float(v_ego_x[1])
self.standstill = self.v_ego_raw < 0.01
self.prev_left_blinker_on = self.left_blinker_on

6
selfdrive/car/toyota/carcontroller.py
View File

@ -23,12 +23,6 @@ ANGLE_DELTA_BP = [0., 5., 15.]
ANGLE_DELTA_V = [5., .8, .15] # windup limit
ANGLE_DELTA_VU = [5., 3.5, 0.4] # unwind limit
TARGET_IDS = [0x340, 0x341, 0x342, 0x343, 0x344, 0x345,
0x363, 0x364, 0x365, 0x370, 0x371, 0x372,
0x373, 0x374, 0x375, 0x380, 0x381, 0x382,
0x383]
def accel_hysteresis(accel, accel_steady, enabled):
# for small accel oscillations within ACCEL_HYST_GAP, don't change the accel command

50
selfdrive/car/toyota/carstate.py
View File

@ -1,17 +1,10 @@
from cereal import car
from common.numpy_fast import mean
from common.kalman.simple_kalman import KF1D
from opendbc.can.can_define import CANDefine
from selfdrive.car.interfaces import CarStateBase
from opendbc.can.parser import CANParser
from selfdrive.config import Conversions as CV
from selfdrive.car.toyota.values import CAR, DBC, STEER_THRESHOLD, TSS2_CAR, NO_DSU_CAR
GearShifter = car.CarState.GearShifter
def parse_gear_shifter(gear):
return {'P': GearShifter.park, 'R': GearShifter.reverse, 'N': GearShifter.neutral,
'D': GearShifter.drive, 'B': GearShifter.brake}.get(gear, GearShifter.unknown)
def get_can_parser(CP):
@ -89,30 +82,14 @@ def get_cam_can_parser(CP):
return CANParser(DBC[CP.carFingerprint]['pt'], signals, checks, 2)
class CarState():
class CarState(CarStateBase):
def __init__(self, CP):
self.CP = CP
self.can_define = CANDefine(DBC[CP.carFingerprint]['pt'])
self.shifter_values = self.can_define.dv["GEAR_PACKET"]['GEAR']
self.left_blinker_on = 0
self.right_blinker_on = 0
super().__init__(CP)
can_define = CANDefine(DBC[CP.carFingerprint]['pt'])
self.shifter_values = can_define.dv["GEAR_PACKET"]['GEAR']
self.angle_offset = 0.
self.init_angle_offset = False
# initialize can parser
self.car_fingerprint = CP.carFingerprint
# vEgo kalman filter
dt = 0.01
# Q = np.matrix([[10.0, 0.0], [0.0, 100.0]])
# R = 1e3
self.v_ego_kf = KF1D(x0=[[0.0], [0.0]],
A=[[1.0, dt], [0.0, 1.0]],
C=[1.0, 0.0],
K=[[0.12287673], [0.29666309]])
self.v_ego = 0.0
def update(self, cp, cp_cam):
# update prevs, update must run once per loop
self.prev_left_blinker_on = self.left_blinker_on
@ -127,25 +104,16 @@ class CarState():
self.pedal_gas = (cp.vl["GAS_SENSOR"]['INTERCEPTOR_GAS'] + cp.vl["GAS_SENSOR"]['INTERCEPTOR_GAS2']) / 2.
else:
self.pedal_gas = cp.vl["GAS_PEDAL"]['GAS_PEDAL']
self.car_gas = self.pedal_gas
self.esp_disabled = cp.vl["ESP_CONTROL"]['TC_DISABLED']
# calc best v_ego estimate, by averaging two opposite corners
self.v_wheel_fl = cp.vl["WHEEL_SPEEDS"]['WHEEL_SPEED_FL'] * CV.KPH_TO_MS
self.v_wheel_fr = cp.vl["WHEEL_SPEEDS"]['WHEEL_SPEED_FR'] * CV.KPH_TO_MS
self.v_wheel_rl = cp.vl["WHEEL_SPEEDS"]['WHEEL_SPEED_RL'] * CV.KPH_TO_MS
self.v_wheel_rr = cp.vl["WHEEL_SPEEDS"]['WHEEL_SPEED_RR'] * CV.KPH_TO_MS
v_wheel = mean([self.v_wheel_fl, self.v_wheel_fr, self.v_wheel_rl, self.v_wheel_rr])
self.v_ego_raw = mean([self.v_wheel_fl, self.v_wheel_fr, self.v_wheel_rl, self.v_wheel_rr])
self.v_ego, self.a_ego = self.update_speed_kf(self.v_ego_raw)
# Kalman filter
if abs(v_wheel - self.v_ego) > 2.0: # Prevent large accelerations when car starts at non zero speed
self.v_ego_kf.x = [[v_wheel], [0.0]]
self.v_ego_raw = v_wheel
v_ego_x = self.v_ego_kf.update(v_wheel)
self.v_ego = float(v_ego_x[0])
self.a_ego = float(v_ego_x[1])
self.standstill = not v_wheel > 0.001
self.standstill = not self.v_ego_raw > 0.001
if self.CP.carFingerprint in TSS2_CAR:
self.angle_steers = cp.vl["STEER_TORQUE_SENSOR"]['STEER_ANGLE']
@ -161,7 +129,7 @@ class CarState():
self.angle_steers = cp.vl["STEER_ANGLE_SENSOR"]['STEER_ANGLE'] + cp.vl["STEER_ANGLE_SENSOR"]['STEER_FRACTION']
self.angle_steers_rate = cp.vl["STEER_ANGLE_SENSOR"]['STEER_RATE']
can_gear = int(cp.vl["GEAR_PACKET"]['GEAR'])
self.gear_shifter = parse_gear_shifter(self.shifter_values.get(can_gear, None))
self.gear_shifter = self.parse_gear_shifter(self.shifter_values.get(can_gear, None))
if self.CP.carFingerprint == CAR.LEXUS_IS:
self.main_on = cp.vl["DSU_CRUISE"]['MAIN_ON']
else:

32
selfdrive/car/toyota/interface.py
View File

@ -163,6 +163,16 @@ class CarInterface(CarInterfaceBase):
ret.lateralTuning.pid.kpV, ret.lateralTuning.pid.kiV = [[0.6], [0.1]]
ret.lateralTuning.pid.kf = 0.00006
elif candidate == CAR.HIGHLANDER_TSS2:
stop_and_go = True
ret.safetyParam = 73
ret.wheelbase = 2.84988 # 112.2 in = 2.84988 m
ret.steerRatio = 16.0
tire_stiffness_factor = 0.8
ret.mass = 4700. * CV.LB_TO_KG + STD_CARGO_KG # 4260 + 4-5 people
ret.lateralTuning.pid.kpV, ret.lateralTuning.pid.kiV = [[0.18], [0.015]] # community tuning
ret.lateralTuning.pid.kf = 0.00012 # community tuning
elif candidate in [CAR.HIGHLANDER, CAR.HIGHLANDERH]:
stop_and_go = True
ret.safetyParam = 73
@ -192,7 +202,7 @@ class CarInterface(CarInterfaceBase):
ret.lateralTuning.pid.kpV, ret.lateralTuning.pid.kiV = [[0.6], [0.1]]
ret.mass = 3370. * CV.LB_TO_KG + STD_CARGO_KG
ret.lateralTuning.pid.kf = 0.00007818594
elif candidate == CAR.RAV4H_TSS2:
stop_and_go = True
ret.safetyParam = 73
@ -253,6 +263,16 @@ class CarInterface(CarInterfaceBase):
ret.lateralTuning.pid.kpV, ret.lateralTuning.pid.kiV = [[0.3], [0.05]]
ret.lateralTuning.pid.kf = 0.00007
elif candidate == CAR.LEXUS_NXH:
stop_and_go = True
ret.safetyParam = 73
ret.wheelbase = 2.66
ret.steerRatio = 14.7
tire_stiffness_factor = 0.444 # not optimized yet
ret.mass = 4070 * CV.LB_TO_KG + STD_CARGO_KG
ret.lateralTuning.pid.kpV, ret.lateralTuning.pid.kiV = [[0.6], [0.1]]
ret.lateralTuning.pid.kf = 0.00006
ret.steerRateCost = 1.
ret.centerToFront = ret.wheelbase * 0.44
@ -276,11 +296,14 @@ class CarInterface(CarInterfaceBase):
ret.brakeMaxV = [1.]
ret.enableCamera = is_ecu_disconnected(fingerprint[0], FINGERPRINTS, ECU_FINGERPRINT, candidate, Ecu.fwdCamera) or has_relay
# Detect smartDSU, which intercepts ACC_CMD from the DSU allowing openpilot to send it
smartDsu = 0x2FF in fingerprint[0]
# In TSS2 cars the camera does long control
ret.enableDsu = is_ecu_disconnected(fingerprint[0], FINGERPRINTS, ECU_FINGERPRINT, candidate, Ecu.dsu) and candidate not in TSS2_CAR
ret.enableApgs = False # is_ecu_disconnected(fingerprint[0], FINGERPRINTS, ECU_FINGERPRINT, candidate, Ecu.apgs)
ret.enableGasInterceptor = 0x201 in fingerprint[0]
ret.openpilotLongitudinalControl = ret.enableCamera and (ret.enableDsu or candidate in TSS2_CAR)
# if the smartDSU is detected, openpilot can send ACC_CMD (and the smartDSU will block it from the DSU) or not (the DSU is "connected")
ret.openpilotLongitudinalControl = ret.enableCamera and (smartDsu or ret.enableDsu or candidate in TSS2_CAR)
cloudlog.warning("ECU Camera Simulated: %r", ret.enableCamera)
cloudlog.warning("ECU DSU Simulated: %r", ret.enableDsu)
cloudlog.warning("ECU APGS Simulated: %r", ret.enableApgs)
@ -291,7 +314,8 @@ class CarInterface(CarInterfaceBase):
ret.minEnableSpeed = -1. if (stop_and_go or ret.enableGasInterceptor) else 19. * CV.MPH_TO_MS
# removing the DSU disables AEB and it's considered a community maintained feature
ret.communityFeature = ret.enableGasInterceptor or ret.enableDsu
# intercepting the DSU is a community feature since it requires unofficial hardware
ret.communityFeature = ret.enableGasInterceptor or ret.enableDsu or smartDsu
ret.longitudinalTuning.deadzoneBP = [0., 9.]
ret.longitudinalTuning.deadzoneV = [0., .15]
@ -341,7 +365,7 @@ class CarInterface(CarInterfaceBase):
ret.gearShifter = self.CS.gear_shifter
# gas pedal
ret.gas = self.CS.car_gas
ret.gas = self.CS.pedal_gas
if self.CP.enableGasInterceptor:
# use interceptor values to disengage on pedal press
ret.gasPressed = self.CS.pedal_gas > 15

163
selfdrive/car/toyota/values.py
View File

@ -22,6 +22,7 @@ class CAR:
CAMRY = "TOYOTA CAMRY 2018"
CAMRYH = "TOYOTA CAMRY HYBRID 2018"
HIGHLANDER = "TOYOTA HIGHLANDER 2017"
HIGHLANDER_TSS2 = "TOYOTA HIGHLANDER 2020"
HIGHLANDERH = "TOYOTA HIGHLANDER HYBRID 2018"
AVALON = "TOYOTA AVALON 2016"
RAV4_TSS2 = "TOYOTA RAV4 2019"
@ -33,28 +34,29 @@ class CAR:
LEXUS_IS = "LEXUS IS300 2018"
LEXUS_CTH = "LEXUS CT 200H 2018"
RAV4H_TSS2 = "TOYOTA RAV4 HYBRID 2019"
LEXUS_NXH = "LEXUS NX300H 2018"
# addr: (ecu, cars, bus, 1/freq*100, vl)
STATIC_MSGS = [
(0x128, Ecu.dsu, (CAR.PRIUS, CAR.RAV4H, CAR.LEXUS_RXH, CAR.RAV4, CAR.COROLLA, CAR.AVALON), 1, 3, b'\xf4\x01\x90\x83\x00\x37'),
(0x128, Ecu.dsu, (CAR.PRIUS, CAR.RAV4H, CAR.LEXUS_RXH, CAR.LEXUS_NXH, CAR.RAV4, CAR.COROLLA, CAR.AVALON), 1, 3, b'\xf4\x01\x90\x83\x00\x37'),
(0x128, Ecu.dsu, (CAR.HIGHLANDER, CAR.HIGHLANDERH, CAR.SIENNA, CAR.LEXUS_CTH), 1, 3, b'\x03\x00\x20\x00\x00\x52'),
(0x141, Ecu.dsu, (CAR.PRIUS, CAR.RAV4H, CAR.LEXUS_RXH, CAR.RAV4, CAR.COROLLA, CAR.HIGHLANDER, CAR.HIGHLANDERH, CAR.AVALON, CAR.SIENNA, CAR.LEXUS_CTH, CAR.LEXUS_RX), 1, 2, b'\x00\x00\x00\x46'),
(0x160, Ecu.dsu, (CAR.PRIUS, CAR.RAV4H, CAR.LEXUS_RXH, CAR.RAV4, CAR.COROLLA, CAR.HIGHLANDER, CAR.HIGHLANDERH, CAR.AVALON, CAR.SIENNA, CAR.LEXUS_CTH, CAR.LEXUS_RX), 1, 7, b'\x00\x00\x08\x12\x01\x31\x9c\x51'),
(0x161, Ecu.dsu, (CAR.PRIUS, CAR.RAV4H, CAR.LEXUS_RXH, CAR.RAV4, CAR.COROLLA, CAR.AVALON, CAR.LEXUS_RX), 1, 7, b'\x00\x1e\x00\x00\x00\x80\x07'),
(0x141, Ecu.dsu, (CAR.PRIUS, CAR.RAV4H, CAR.LEXUS_RXH, CAR.LEXUS_NXH, CAR.RAV4, CAR.COROLLA, CAR.HIGHLANDER, CAR.HIGHLANDERH, CAR.AVALON, CAR.SIENNA, CAR.LEXUS_CTH, CAR.LEXUS_RX), 1, 2, b'\x00\x00\x00\x46'),
(0x160, Ecu.dsu, (CAR.PRIUS, CAR.RAV4H, CAR.LEXUS_RXH, CAR.LEXUS_NXH, CAR.RAV4, CAR.COROLLA, CAR.HIGHLANDER, CAR.HIGHLANDERH, CAR.AVALON, CAR.SIENNA, CAR.LEXUS_CTH, CAR.LEXUS_RX), 1, 7, b'\x00\x00\x08\x12\x01\x31\x9c\x51'),
(0x161, Ecu.dsu, (CAR.PRIUS, CAR.RAV4H, CAR.LEXUS_RXH, CAR.LEXUS_NXH, CAR.RAV4, CAR.COROLLA, CAR.AVALON, CAR.LEXUS_RX), 1, 7, b'\x00\x1e\x00\x00\x00\x80\x07'),
(0X161, Ecu.dsu, (CAR.HIGHLANDERH, CAR.HIGHLANDER, CAR.SIENNA, CAR.LEXUS_CTH), 1, 7, b'\x00\x1e\x00\xd4\x00\x00\x5b'),
(0x283, Ecu.dsu, (CAR.PRIUS, CAR.RAV4H, CAR.LEXUS_RXH, CAR.RAV4, CAR.COROLLA, CAR.HIGHLANDER, CAR.HIGHLANDERH, CAR.AVALON, CAR.SIENNA, CAR.LEXUS_CTH, CAR.LEXUS_RX), 0, 3, b'\x00\x00\x00\x00\x00\x00\x8c'),
(0x283, Ecu.dsu, (CAR.PRIUS, CAR.RAV4H, CAR.LEXUS_RXH, CAR.LEXUS_NXH, CAR.RAV4, CAR.COROLLA, CAR.HIGHLANDER, CAR.HIGHLANDERH, CAR.AVALON, CAR.SIENNA, CAR.LEXUS_CTH, CAR.LEXUS_RX), 0, 3, b'\x00\x00\x00\x00\x00\x00\x8c'),
(0x2E6, Ecu.dsu, (CAR.PRIUS, CAR.RAV4H, CAR.LEXUS_RXH), 0, 3, b'\xff\xf8\x00\x08\x7f\xe0\x00\x4e'),
(0x2E7, Ecu.dsu, (CAR.PRIUS, CAR.RAV4H, CAR.LEXUS_RXH), 0, 3, b'\xa8\x9c\x31\x9c\x00\x00\x00\x02'),
(0x33E, Ecu.dsu, (CAR.PRIUS, CAR.RAV4H, CAR.LEXUS_RXH), 0, 20, b'\x0f\xff\x26\x40\x00\x1f\x00'),
(0x344, Ecu.dsu, (CAR.PRIUS, CAR.RAV4H, CAR.LEXUS_RXH, CAR.RAV4, CAR.COROLLA, CAR.HIGHLANDER, CAR.HIGHLANDERH, CAR.AVALON, CAR.SIENNA, CAR.LEXUS_CTH, CAR.LEXUS_RX), 0, 5, b'\x00\x00\x01\x00\x00\x00\x00\x50'),
(0x365, Ecu.dsu, (CAR.PRIUS, CAR.LEXUS_RXH, CAR.HIGHLANDERH), 0, 20, b'\x00\x00\x00\x80\x03\x00\x08'),
(0x344, Ecu.dsu, (CAR.PRIUS, CAR.RAV4H, CAR.LEXUS_RXH, CAR.LEXUS_NXH, CAR.RAV4, CAR.COROLLA, CAR.HIGHLANDER, CAR.HIGHLANDERH, CAR.AVALON, CAR.SIENNA, CAR.LEXUS_CTH, CAR.LEXUS_RX), 0, 5, b'\x00\x00\x01\x00\x00\x00\x00\x50'),
(0x365, Ecu.dsu, (CAR.PRIUS, CAR.LEXUS_RXH, CAR.LEXUS_NXH, CAR.HIGHLANDERH), 0, 20, b'\x00\x00\x00\x80\x03\x00\x08'),
(0x365, Ecu.dsu, (CAR.RAV4, CAR.RAV4H, CAR.COROLLA, CAR.HIGHLANDER, CAR.AVALON, CAR.SIENNA, CAR.LEXUS_CTH, CAR.LEXUS_RX), 0, 20, b'\x00\x00\x00\x80\xfc\x00\x08'),
(0x366, Ecu.dsu, (CAR.PRIUS, CAR.RAV4H, CAR.LEXUS_RXH, CAR.HIGHLANDERH), 0, 20, b'\x00\x00\x4d\x82\x40\x02\x00'),
(0x366, Ecu.dsu, (CAR.PRIUS, CAR.RAV4H, CAR.LEXUS_RXH, CAR.LEXUS_NXH, CAR.HIGHLANDERH), 0, 20, b'\x00\x00\x4d\x82\x40\x02\x00'),
(0x366, Ecu.dsu, (CAR.RAV4, CAR.COROLLA, CAR.HIGHLANDER, CAR.AVALON, CAR.SIENNA, CAR.LEXUS_CTH, CAR.LEXUS_RX), 0, 20, b'\x00\x72\x07\xff\x09\xfe\x00'),
(0x470, Ecu.dsu, (CAR.PRIUS, CAR.LEXUS_RXH), 1, 100, b'\x00\x00\x02\x7a'),
(0x470, Ecu.dsu, (CAR.HIGHLANDER, CAR.HIGHLANDERH, CAR.RAV4H, CAR.SIENNA, CAR.LEXUS_CTH), 1, 100, b'\x00\x00\x01\x79'),
(0x4CB, Ecu.dsu, (CAR.PRIUS, CAR.RAV4H, CAR.LEXUS_RXH, CAR.RAV4, CAR.COROLLA, CAR.HIGHLANDERH, CAR.HIGHLANDER, CAR.AVALON, CAR.SIENNA, CAR.LEXUS_CTH, CAR.LEXUS_RX), 0, 100, b'\x0c\x00\x00\x00\x00\x00\x00\x00'),
(0x4CB, Ecu.dsu, (CAR.PRIUS, CAR.RAV4H, CAR.LEXUS_RXH, CAR.LEXUS_NXH, CAR.RAV4, CAR.COROLLA, CAR.HIGHLANDERH, CAR.HIGHLANDER, CAR.AVALON, CAR.SIENNA, CAR.LEXUS_CTH, CAR.LEXUS_RX), 0, 100, b'\x0c\x00\x00\x00\x00\x00\x00\x00'),
(0x292, Ecu.apgs, (CAR.PRIUS), 0, 3, b'\x00\x00\x00\x00\x00\x00\x00\x9e'),
(0x32E, Ecu.apgs, (CAR.PRIUS), 0, 20, b'\x00\x00\x00\x00\x00\x00\x00\x00'),
@ -67,195 +69,206 @@ STATIC_MSGS = [
ECU_FINGERPRINT = {
Ecu.fwdCamera: [0x2e4], # steer torque cmd
Ecu.dsu: [0x343], # accel cmd
Ecu.dsu: [0x283], # accel cmd
Ecu.apgs: [0x835], # angle cmd
}
FINGERPRINTS = {
CAR.RAV4: [{
36: 8, 37: 8, 170: 8, 180: 8, 186: 4, 426: 6, 452: 8, 464: 8, 466: 8, 467: 8, 512: 6, 513: 6, 547: 8, 548: 8, 552: 4, 562: 4, 608: 8, 610: 5, 643: 7, 705: 8, 725: 2, 740: 5, 800: 8, 835: 8, 836: 8, 849: 4, 869: 7, 870: 7, 871: 2, 896: 8, 897: 8, 900: 6, 902: 6, 905: 8, 911: 8, 916: 3, 918: 7, 921: 8, 933: 8, 944: 8, 945: 8, 951: 8, 955: 4, 956: 8, 979: 2, 998: 5, 999: 7, 1000: 8, 1001: 8, 1005: 2, 1008: 2, 1014: 8, 1017: 8, 1041: 8, 1042: 8, 1043: 8, 1044: 8, 1056: 8, 1059: 1, 1114: 8, 1161: 8, 1162: 8, 1163: 8, 1176: 8, 1177: 8, 1178: 8, 1179: 8, 1180: 8, 1181: 8, 1190: 8, 1191: 8, 1192: 8, 1196: 8, 1227: 8, 1228: 8, 1235: 8, 1237: 8, 1263: 8, 1264: 8, 1279: 8, 1408: 8, 1409: 8, 1410: 8, 1552: 8, 1553: 8, 1554: 8, 1555: 8, 1556: 8, 1557: 8, 1561: 8, 1562: 8, 1568: 8, 1569: 8, 1570: 8, 1571: 8, 1572: 8, 1584: 8, 1589: 8, 1592: 8, 1593: 8, 1595: 8, 1596: 8, 1597: 8, 1600: 8, 1656: 8, 1664: 8, 1728: 8, 1745: 8, 1779: 8, 1904: 8, 1912: 8, 1990: 8, 1998: 8, 2015: 8, 2024: 8
36: 8, 37: 8, 170: 8, 180: 8, 186: 4, 426: 6, 452: 8, 464: 8, 466: 8, 467: 8, 512: 6, 513: 6, 547: 8, 548: 8, 552: 4, 562: 4, 608: 8, 610: 5, 643: 7, 705: 8, 725: 2, 740: 5, 767:4, 800: 8, 835: 8, 836: 8, 849: 4, 869: 7, 870: 7, 871: 2, 896: 8, 897: 8, 900: 6, 902: 6, 905: 8, 911: 8, 916: 3, 918: 7, 921: 8, 933: 8, 944: 8, 945: 8, 951: 8, 955: 4, 956: 8, 979: 2, 998: 5, 999: 7, 1000: 8, 1001: 8, 1005: 2, 1008: 2, 1014: 8, 1017: 8, 1041: 8, 1042: 8, 1043: 8, 1044: 8, 1056: 8, 1059: 1, 1114: 8, 1161: 8, 1162: 8, 1163: 8, 1176: 8, 1177: 8, 1178: 8, 1179: 8, 1180: 8, 1181: 8, 1190: 8, 1191: 8, 1192: 8, 1196: 8, 1227: 8, 1228: 8, 1235: 8, 1237: 8, 1263: 8, 1264: 8, 1279: 8, 1408: 8, 1409: 8, 1410: 8, 1552: 8, 1553: 8, 1554: 8, 1555: 8, 1556: 8, 1557: 8, 1561: 8, 1562: 8, 1568: 8, 1569: 8, 1570: 8, 1571: 8, 1572: 8, 1584: 8, 1589: 8, 1592: 8, 1593: 8, 1595: 8, 1596: 8, 1597: 8, 1600: 8, 1656: 8, 1664: 8, 1728: 8, 1745: 8, 1779: 8, 1904: 8, 1912: 8, 1990: 8, 1998: 8, 2015: 8, 2024: 8
}],
CAR.RAV4H: [{
36: 8, 37: 8, 170: 8, 180: 8, 186: 4, 296: 8, 426: 6, 452: 8, 464: 8, 466: 8, 467: 8, 547: 8, 548: 8, 550: 8, 552: 4, 560: 7, 562: 4, 581: 5, 608: 8, 610: 5, 643: 7, 705: 8, 713: 8, 725: 2, 740: 5, 800: 8, 835: 8, 836: 8, 849: 4, 869: 7, 870: 7, 871: 2, 896: 8, 897: 8, 900: 6, 902: 6, 905: 8, 911: 8, 916: 3, 918: 7, 921: 8, 933: 8, 944: 8, 945: 8, 950: 8, 951: 8, 953: 3, 955: 8, 956: 8, 979: 2, 998: 5, 999: 7, 1000: 8, 1001: 8, 1005: 2, 1008: 2, 1014: 8, 1017: 8, 1041: 8, 1042: 8, 1043: 8, 1044: 8, 1056: 8, 1059: 1, 1114: 8, 1161: 8, 1162: 8, 1163: 8, 1176: 8, 1177: 8, 1178: 8, 1179: 8, 1180: 8, 1181: 8, 1184: 8, 1185: 8, 1186: 8, 1190: 8, 1191: 8, 1192: 8, 1196: 8, 1197: 8, 1198: 8, 1199: 8, 1212: 8, 1227: 8, 1228: 8, 1232: 8, 1235: 8, 1237: 8, 1263: 8, 1264: 8, 1279: 8, 1408: 8, 1409: 8, 1410: 8, 1552: 8, 1553: 8, 1554: 8, 1555: 8, 1556: 8, 1557: 8, 1561: 8, 1562: 8, 1568: 8, 1569: 8, 1570: 8, 1571: 8, 1572: 8, 1584: 8, 1589: 8, 1592: 8, 1593: 8, 1595: 8, 1596: 8, 1597: 8, 1600: 8, 1656: 8, 1664: 8, 1728: 8, 1745: 8, 1779: 8, 1904: 8, 1912: 8, 1990: 8, 1998: 8
36: 8, 37: 8, 170: 8, 180: 8, 186: 4, 296: 8, 426: 6, 452: 8, 464: 8, 466: 8, 467: 8, 547: 8, 548: 8, 550: 8, 552: 4, 560: 7, 562: 4, 581: 5, 608: 8, 610: 5, 643: 7, 705: 8, 713: 8, 725: 2, 740: 5, 767:4, 800: 8, 835: 8, 836: 8, 849: 4, 869: 7, 870: 7, 871: 2, 896: 8, 897: 8, 900: 6, 902: 6, 905: 8, 911: 8, 916: 3, 918: 7, 921: 8, 933: 8, 944: 8, 945: 8, 950: 8, 951: 8, 953: 3, 955: 8, 956: 8, 979: 2, 998: 5, 999: 7, 1000: 8, 1001: 8, 1005: 2, 1008: 2, 1014: 8, 1017: 8, 1041: 8, 1042: 8, 1043: 8, 1044: 8, 1056: 8, 1059: 1, 1114: 8, 1161: 8, 1162: 8, 1163: 8, 1176: 8, 1177: 8, 1178: 8, 1179: 8, 1180: 8, 1181: 8, 1184: 8, 1185: 8, 1186: 8, 1190: 8, 1191: 8, 1192: 8, 1196: 8, 1197: 8, 1198: 8, 1199: 8, 1212: 8, 1227: 8, 1228: 8, 1232: 8, 1235: 8, 1237: 8, 1263: 8, 1264: 8, 1279: 8, 1408: 8, 1409: 8, 1410: 8, 1552: 8, 1553: 8, 1554: 8, 1555: 8, 1556: 8, 1557: 8, 1561: 8, 1562: 8, 1568: 8, 1569: 8, 1570: 8, 1571: 8, 1572: 8, 1584: 8, 1589: 8, 1592: 8, 1593: 8, 1595: 8, 1596: 8, 1597: 8, 1600: 8, 1656: 8, 1664: 8, 1728: 8, 1745: 8, 1779: 8, 1904: 8, 1912: 8, 1990: 8, 1998: 8
},
# Chinese RAV4
{
36: 8, 37: 8, 170: 8, 180: 8, 186: 4, 355: 5, 426: 6, 452: 8, 464: 8, 466: 8, 467: 8, 512: 6, 513: 6, 547: 8, 548: 8, 552: 4, 562: 4, 608: 8, 610: 5, 643: 7, 705: 8, 725: 2, 740: 5, 742: 8, 743: 8, 800: 8, 830: 7, 835: 8, 836: 8, 849: 4, 869: 7, 870: 7, 871: 2, 896: 8, 897: 8, 900: 6, 902: 6, 905: 8, 911: 8, 916: 3, 921: 8, 922: 8, 933: 8, 944: 8, 945: 8, 951: 8, 955: 8, 956: 8, 979: 2, 998: 5, 999: 7, 1000: 8, 1001: 8, 1008: 2, 1017: 8, 1041: 8, 1042: 8, 1043: 8, 1044: 8, 1056: 8, 1059: 1, 1114: 8, 1161: 8, 1162: 8, 1163: 8, 1176: 8, 1177: 8, 1178: 8, 1179: 8, 1180: 8, 1181: 8, 1190: 8, 1191: 8, 1192: 8, 1196: 8, 1207: 8, 1227: 8, 1235: 8, 1263: 8, 1279: 8, 1552: 8, 1553: 8, 1554: 8, 1555: 8, 1556: 8, 1557: 8, 1561: 8, 1562: 8, 1568: 8, 1569: 8, 1570: 8, 1571: 8, 1572: 8, 1584: 8, 1589: 8, 1592: 8, 1593: 8, 1595: 8, 1596: 8, 1597: 8, 1600: 8, 1664: 8, 1728: 8, 1745: 8, 1779: 8
36: 8, 37: 8, 170: 8, 180: 8, 186: 4, 355: 5, 426: 6, 452: 8, 464: 8, 466: 8, 467: 8, 512: 6, 513: 6, 547: 8, 548: 8, 552: 4, 562: 4, 608: 8, 610: 5, 643: 7, 705: 8, 725: 2, 740: 5, 742: 8, 743: 8, 767:4, 800: 8, 830: 7, 835: 8, 836: 8, 849: 4, 869: 7, 870: 7, 871: 2, 896: 8, 897: 8, 900: 6, 902: 6, 905: 8, 911: 8, 916: 3, 921: 8, 922: 8, 933: 8, 944: 8, 945: 8, 951: 8, 955: 8, 956: 8, 979: 2, 998: 5, 999: 7, 1000: 8, 1001: 8, 1008: 2, 1017: 8, 1041: 8, 1042: 8, 1043: 8, 1044: 8, 1056: 8, 1059: 1, 1114: 8, 1161: 8, 1162: 8, 1163: 8, 1176: 8, 1177: 8, 1178: 8, 1179: 8, 1180: 8, 1181: 8, 1190: 8, 1191: 8, 1192: 8, 1196: 8, 1207: 8, 1227: 8, 1235: 8, 1263: 8, 1279: 8, 1552: 8, 1553: 8, 1554: 8, 1555: 8, 1556: 8, 1557: 8, 1561: 8, 1562: 8, 1568: 8, 1569: 8, 1570: 8, 1571: 8, 1572: 8, 1584: 8, 1589: 8, 1592: 8, 1593: 8, 1595: 8, 1596: 8, 1597: 8, 1600: 8, 1664: 8, 1728: 8, 1745: 8, 1779: 8
}],
CAR.PRIUS: [{
# with ipas
36: 8, 37: 8, 166: 8, 170: 8, 180: 8, 295: 8, 296: 8, 426: 6, 452: 8, 466: 8, 467: 8, 512: 6, 513: 6, 550: 8, 552: 4, 560: 7, 562: 6, 581: 5, 608: 8, 610: 8, 614: 8, 643: 7, 658: 8, 713: 8, 740: 5, 742: 8, 743: 8, 800: 8, 810: 2, 814: 8, 824: 2, 829: 2, 830: 7, 835: 8, 836: 8, 845: 5, 863: 8, 869: 7, 870: 7, 871: 2,898: 8, 900: 6, 902: 6, 905: 8, 913: 8, 918: 8, 921: 8, 933: 8, 944: 8, 945: 8, 950: 8, 951: 8, 953: 8, 955: 8, 956: 8, 971: 7, 974: 8, 975: 5, 993: 8, 998: 5, 999: 7, 1000: 8, 1001: 8, 1005: 2, 1014: 8, 1017: 8, 1020: 8, 1041: 8, 1042: 8, 1044: 8, 1056: 8, 1057: 8, 1059: 1, 1071: 8, 1076: 8, 1077: 8, 1082: 8, 1083: 8, 1084: 8, 1085: 8, 1086: 8, 1114: 8, 1132: 8, 1161: 8, 1162: 8, 1163: 8, 1164: 8, 1165: 8, 1166: 8, 1167: 8, 1175: 8, 1227: 8, 1228: 8, 1235: 8, 1237: 8, 1264: 8, 1279: 8, 1552: 8, 1553: 8, 1556: 8, 1557: 8, 1568: 8, 1570: 8, 1571: 8, 1572: 8, 1595: 8, 1777: 8, 1779: 8, 1904: 8, 1912: 8, 1990: 8, 1998: 8
36: 8, 37: 8, 166: 8, 170: 8, 180: 8, 295: 8, 296: 8, 426: 6, 452: 8, 466: 8, 467: 8, 512: 6, 513: 6, 550: 8, 552: 4, 560: 7, 562: 6, 581: 5, 608: 8, 610: 8, 614: 8, 643: 7, 658: 8, 713: 8, 740: 5, 742: 8, 743: 8, 767:4, 800: 8, 810: 2, 814: 8, 824: 2, 829: 2, 830: 7, 835: 8, 836: 8, 845: 5, 863: 8, 869: 7, 870: 7, 871: 2,898: 8, 900: 6, 902: 6, 905: 8, 913: 8, 918: 8, 921: 8, 933: 8, 944: 8, 945: 8, 950: 8, 951: 8, 953: 8, 955: 8, 956: 8, 971: 7, 974: 8, 975: 5, 993: 8, 998: 5, 999: 7, 1000: 8, 1001: 8, 1005: 2, 1014: 8, 1017: 8, 1020: 8, 1041: 8, 1042: 8, 1044: 8, 1056: 8, 1057: 8, 1059: 1, 1071: 8, 1076: 8, 1077: 8, 1082: 8, 1083: 8, 1084: 8, 1085: 8, 1086: 8, 1114: 8, 1132: 8, 1161: 8, 1162: 8, 1163: 8, 1164: 8, 1165: 8, 1166: 8, 1167: 8, 1175: 8, 1227: 8, 1228: 8, 1235: 8, 1237: 8, 1264: 8, 1279: 8, 1552: 8, 1553: 8, 1556: 8, 1557: 8, 1568: 8, 1570: 8, 1571: 8, 1572: 8, 1595: 8, 1777: 8, 1779: 8, 1904: 8, 1912: 8, 1990: 8, 1998: 8
},
#2019 LE
{
36: 8, 37: 8, 166: 8, 170: 8, 180: 8, 295: 8, 296: 8, 426: 6, 452: 8, 466: 8, 467: 8, 550: 8, 552: 4, 560: 7, 562: 6, 581: 5, 608: 8, 610: 8, 614: 8, 643: 7, 658: 8, 713: 8, 740: 5, 742: 8, 743: 8, 800: 8, 810: 2, 814: 8, 829: 2, 830: 7, 835: 8, 836: 8, 863: 8, 865: 8, 869: 7, 870: 7, 871: 2, 896: 8, 898: 8, 900: 6, 902: 6, 905: 8, 918: 8, 921: 8, 933: 8, 944: 8, 945: 8, 950: 8, 951: 8, 953: 8, 955: 8, 956: 8, 971: 7, 975: 5, 993: 8, 998: 5, 999: 7, 1000: 8, 1001: 8, 1002: 8, 1014: 8, 1017: 8, 1020: 8, 1041: 8, 1042: 8, 1044: 8, 1056: 8, 1057: 8, 1059: 1, 1071: 8, 1076: 8, 1077: 8, 1082: 8, 1083: 8, 1084: 8, 1085: 8, 1086: 8, 1114: 8, 1132: 8, 1161: 8, 1162: 8, 1163: 8, 1175: 8, 1227: 8, 1228: 8, 1235: 8, 1237: 8, 1279: 8, 1552: 8, 1553: 8, 1556: 8, 1557: 8, 1568: 8, 1570: 8, 1571: 8, 1572: 8, 1592: 8, 1595: 8, 1777: 8, 1779: 8, 1904: 8, 1912: 8, 1990: 8, 1998: 8
36: 8, 37: 8, 166: 8, 170: 8, 180: 8, 295: 8, 296: 8, 426: 6, 452: 8, 466: 8, 467: 8, 550: 8, 552: 4, 560: 7, 562: 6, 581: 5, 608: 8, 610: 8, 614: 8, 643: 7, 658: 8, 713: 8, 740: 5, 742: 8, 743: 8, 767:4, 800: 8, 810: 2, 814: 8, 829: 2, 830: 7, 835: 8, 836: 8, 863: 8, 865: 8, 869: 7, 870: 7, 871: 2, 896: 8, 898: 8, 900: 6, 902: 6, 905: 8, 918: 8, 921: 8, 933: 8, 944: 8, 945: 8, 950: 8, 951: 8, 953: 8, 955: 8, 956: 8, 971: 7, 975: 5, 993: 8, 998: 5, 999: 7, 1000: 8, 1001: 8, 1002: 8, 1014: 8, 1017: 8, 1020: 8, 1041: 8, 1042: 8, 1044: 8, 1056: 8, 1057: 8, 1059: 1, 1071: 8, 1076: 8, 1077: 8, 1082: 8, 1083: 8, 1084: 8, 1085: 8, 1086: 8, 1114: 8, 1132: 8, 1161: 8, 1162: 8, 1163: 8, 1175: 8, 1227: 8, 1228: 8, 1235: 8, 1237: 8, 1279: 8, 1552: 8, 1553: 8, 1556: 8, 1557: 8, 1568: 8, 1570: 8, 1571: 8, 1572: 8, 1592: 8, 1595: 8, 1777: 8, 1779: 8, 1904: 8, 1912: 8, 1990: 8, 1998: 8
},
# 2020 Prius Prime LE
{
36: 8, 37: 8, 166: 8, 170: 8, 180: 8, 295: 8, 296: 8, 426: 6, 452: 8, 466: 8, 467: 8, 550: 8, 552: 4, 560: 7, 562: 6, 581: 5, 608: 8, 610: 8, 643: 7, 713: 8, 740: 5, 742: 8, 743: 8, 764: 8, 800: 8, 810: 2, 824: 8, 829: 2, 830: 7, 835: 8, 836: 8, 863: 8, 865: 8, 869: 7, 870: 7, 871: 2, 896: 8, 898: 8, 900: 6, 902: 6, 905: 8, 913: 8, 921: 8, 933: 8, 934: 8, 935: 8, 944: 8, 945: 8, 950: 8, 951: 8, 953: 8, 955: 8, 956: 8, 971: 7, 974: 8, 975: 5, 993: 8, 998: 5, 999: 7, 1000: 8, 1001: 8, 1017: 8, 1020: 8, 1041: 8, 1042: 8, 1044: 8, 1056: 8, 1057: 8, 1059: 1, 1071: 8, 1076: 8, 1077: 8, 1084: 8, 1085: 8, 1086: 8, 1114: 8, 1132: 8, 1161: 8, 1162: 8, 1163: 8, 1164: 8, 1165: 8, 1166: 8, 1167: 8, 1227: 8, 1235: 8, 1279: 8, 1541: 8, 1552: 8, 1553: 8, 1556: 8, 1557: 8, 1568: 8, 1570: 8, 1571: 8, 1572: 8, 1592: 8, 1595: 8, 1649: 8, 1777: 8, 1779: 8, 1786: 8, 1787: 8, 1788: 8, 1789: 8, 1904: 8, 1912: 8, 1990: 8, 1998: 8
36: 8, 37: 8, 166: 8, 170: 8, 180: 8, 295: 8, 296: 8, 426: 6, 452: 8, 466: 8, 467: 8, 550: 8, 552: 4, 560: 7, 562: 6, 581: 5, 608: 8, 610: 8, 643: 7, 713: 8, 740: 5, 742: 8, 743: 8, 764: 8, 767:4, 800: 8, 810: 2, 824: 8, 829: 2, 830: 7, 835: 8, 836: 8, 863: 8, 865: 8, 869: 7, 870: 7, 871: 2, 896: 8, 898: 8, 900: 6, 902: 6, 905: 8, 913: 8, 921: 8, 933: 8, 934: 8, 935: 8, 944: 8, 945: 8, 950: 8, 951: 8, 953: 8, 955: 8, 956: 8, 971: 7, 974: 8, 975: 5, 993: 8, 998: 5, 999: 7, 1000: 8, 1001: 8, 1017: 8, 1020: 8, 1041: 8, 1042: 8, 1044: 8, 1056: 8, 1057: 8, 1059: 1, 1071: 8, 1076: 8, 1077: 8, 1084: 8, 1085: 8, 1086: 8, 1114: 8, 1132: 8, 1161: 8, 1162: 8, 1163: 8, 1164: 8, 1165: 8, 1166: 8, 1167: 8, 1227: 8, 1235: 8, 1279: 8, 1541: 8, 1552: 8, 1553: 8, 1556: 8, 1557: 8, 1568: 8, 1570: 8, 1571: 8, 1572: 8, 1592: 8, 1595: 8, 1649: 8, 1777: 8, 1779: 8, 1786: 8, 1787: 8, 1788: 8, 1789: 8, 1904: 8, 1912: 8, 1990: 8, 1998: 8
},
#2020 Prius Prime Limited
{
36: 8, 37: 8, 166: 8, 170: 8, 180: 8, 295: 8, 296: 8, 426: 6, 452: 8, 466: 8, 467: 8, 550: 8, 552: 4, 560: 7, 562: 6, 581: 5, 608: 8, 610: 8, 614: 8, 643: 7, 658: 8, 713: 8, 740: 5, 742: 8, 743: 8, 800: 8, 810: 2, 814: 8, 824: 2, 829: 2, 830: 7, 835: 8, 836: 8, 863: 8, 865: 8, 869: 7, 870: 7, 871: 2, 896: 8, 898: 8, 900: 6, 902: 6, 905: 8, 913: 8, 918: 8, 921: 8, 933: 8, 944: 8, 945: 8, 950: 8, 951: 8, 953: 8, 955: 8, 956: 8, 971: 7, 974: 8, 975: 5, 993: 8, 998: 5, 999: 7, 1000: 8, 1001: 8, 1014: 8, 1017: 8, 1020: 8, 1041: 8, 1042: 8, 1044: 8, 1056: 8, 1057: 8, 1059: 1, 1071: 8, 1076: 8, 1077: 8, 1082: 8, 1083: 8, 1084: 8, 1085: 8, 1086: 8, 1114: 8, 1132: 8, 1161: 8, 1162: 8, 1163: 8, 1164: 8, 1165: 8, 1166: 8, 1167: 8, 1175: 8, 1227: 8, 1228: 8, 1235: 8, 1237: 8, 1279: 8, 1541: 8, 1552: 8, 1553: 8, 1556: 8, 1557: 8, 1568: 8, 1570: 8, 1571: 8, 1572: 8, 1592: 8, 1595: 8, 1649: 8, 1777: 8, 1779: 8, 1904: 8, 1912: 8, 1990: 8, 1998: 8, 2015: 8, 2024: 8, 2026: 8, 2027: 8, 2029: 8, 2030: 8, 2031: 8
36: 8, 37: 8, 166: 8, 170: 8, 180: 8, 295: 8, 296: 8, 426: 6, 452: 8, 466: 8, 467: 8, 550: 8, 552: 4, 560: 7, 562: 6, 581: 5, 608: 8, 610: 8, 614: 8, 643: 7, 658: 8, 713: 8, 740: 5, 742: 8, 743: 8, 767:4, 800: 8, 810: 2, 814: 8, 824: 2, 829: 2, 830: 7, 835: 8, 836: 8, 863: 8, 865: 8, 869: 7, 870: 7, 871: 2, 896: 8, 898: 8, 900: 6, 902: 6, 905: 8, 913: 8, 918: 8, 921: 8, 933: 8, 944: 8, 945: 8, 950: 8, 951: 8, 953: 8, 955: 8, 956: 8, 971: 7, 974: 8, 975: 5, 993: 8, 998: 5, 999: 7, 1000: 8, 1001: 8, 1014: 8, 1017: 8, 1020: 8, 1041: 8, 1042: 8, 1044: 8, 1056: 8, 1057: 8, 1059: 1, 1071: 8, 1076: 8, 1077: 8, 1082: 8, 1083: 8, 1084: 8, 1085: 8, 1086: 8, 1114: 8, 1132: 8, 1161: 8, 1162: 8, 1163: 8, 1164: 8, 1165: 8, 1166: 8, 1167: 8, 1175: 8, 1227: 8, 1228: 8, 1235: 8, 1237: 8, 1279: 8, 1541: 8, 1552: 8, 1553: 8, 1556: 8, 1557: 8, 1568: 8, 1570: 8, 1571: 8, 1572: 8, 1592: 8, 1595: 8, 1649: 8, 1777: 8, 1779: 8, 1904: 8, 1912: 8, 1990: 8, 1998: 8, 2015: 8, 2024: 8, 2026: 8, 2027: 8, 2029: 8, 2030: 8, 2031: 8
},
#2020 Central Europe Prime
{
36: 8, 37: 8, 166: 8, 170: 8, 180: 8, 295: 8, 296: 8, 426: 6, 452: 8, 466: 8, 467: 8, 550: 8, 552: 4, 560: 7, 562: 6, 581: 5, 608: 8, 610: 8, 643: 7, 713: 8, 740: 5, 742: 8, 743: 8, 764: 8, 800: 8, 810: 2, 818: 8, 824: 8, 829: 2, 830: 7, 835: 8, 836: 8, 845: 5, 863: 8, 865: 8, 869: 7, 870: 7, 871: 2, 889: 8, 896: 8, 898: 8, 900: 6, 902: 6, 905: 8, 913: 8, 921: 8, 933: 8, 934: 8, 935: 8, 944: 8, 945: 8, 950: 8, 951: 8, 953: 8, 955: 8, 956: 8, 971: 8, 974: 8, 975: 5, 993: 8, 998: 5, 999: 7, 1000: 8, 1001: 8, 1014: 8, 1017: 8, 1020: 8, 1041: 8, 1042: 8, 1056: 8, 1057: 8, 1059: 1, 1071: 8, 1076: 8, 1077: 8, 1084: 8, 1085: 8, 1086: 8, 1114: 8, 1132: 8, 1161: 8, 1162: 8, 1163: 8, 1164: 8, 1165: 8, 1166: 8, 1167: 8, 1227: 8, 1235: 8, 1237: 8, 1264: 8, 1279: 8, 1541: 8, 1552: 8, 1553: 8, 1556: 8, 1557: 8, 1568: 8, 1570: 8, 1571: 8, 1572: 8, 1592: 8, 1595: 8, 1777: 8, 1779: 8, 1786: 8, 1787: 8, 1788: 8, 1789: 8
36: 8, 37: 8, 166: 8, 170: 8, 180: 8, 295: 8, 296: 8, 426: 6, 452: 8, 466: 8, 467: 8, 550: 8, 552: 4, 560: 7, 562: 6, 581: 5, 608: 8, 610: 8, 643: 7, 713: 8, 740: 5, 742: 8, 743: 8, 764: 8, 767:4, 800: 8, 810: 2, 818: 8, 824: 8, 829: 2, 830: 7, 835: 8, 836: 8, 845: 5, 863: 8, 865: 8, 869: 7, 870: 7, 871: 2, 889: 8, 896: 8, 898: 8, 900: 6, 902: 6, 905: 8, 913: 8, 921: 8, 933: 8, 934: 8, 935: 8, 944: 8, 945: 8, 950: 8, 951: 8, 953: 8, 955: 8, 956: 8, 971: 8, 974: 8, 975: 5, 993: 8, 998: 5, 999: 7, 1000: 8, 1001: 8, 1014: 8, 1017: 8, 1020: 8, 1041: 8, 1042: 8, 1056: 8, 1057: 8, 1059: 1, 1071: 8, 1076: 8, 1077: 8, 1084: 8, 1085: 8, 1086: 8, 1114: 8, 1132: 8, 1161: 8, 1162: 8, 1163: 8, 1164: 8, 1165: 8, 1166: 8, 1167: 8, 1227: 8, 1235: 8, 1237: 8, 1264: 8, 1279: 8, 1541: 8, 1552: 8, 1553: 8, 1556: 8, 1557: 8, 1568: 8, 1570: 8, 1571: 8, 1572: 8, 1592: 8, 1595: 8, 1777: 8, 1779: 8, 1786: 8, 1787: 8, 1788: 8, 1789: 8
},
#2017 German Prius
{
36: 8, 37: 8, 166: 8, 170: 8, 180: 8, 295: 8, 296:8, 426: 6, 452: 8, 466: 8, 467: 8, 550: 8, 552: 4, 560: 7, 562: 6, 581: 5, 608: 8, 610: 8, 614: 8, 643: 7, 658: 8, 713: 8,740: 5, 742: 8, 743: 8, 767:4, 800: 8, 810: 2, 814: 8, 829: 2, 830: 7, 835: 8, 836: 8, 845: 5, 863: 8, 869: 7, 870: 7, 871: 2, 898: 8, 900: 6, 902: 6, 905: 8, 913: 8, 918: 8, 921: 8, 933: 8, 944: 8, 945: 8, 950: 8, 951: 8, 953: 8, 955: 8, 956: 8, 971: 7, 975: 5, 993: 8, 998: 5, 999: 7, 1000: 8, 1001: 8, 1005: 2, 1014: 8, 1017: 8, 1020: 8, 1041: 8, 1042: 8, 1044: 8, 1056: 8, 1057: 8, 1059: 1, 1071: 8, 1077: 8, 1082: 8, 1083: 8, 1084: 8, 1085: 8, 1086: 8, 1114: 8, 1132: 8, 1161: 8, 1162: 8, 1163: 8, 1175: 8, 1227: 8, 1228: 8, 1235: 8, 1237: 8, 1264: 8, 1279: 8, 1552: 8, 1553: 8, 1556: 8, 1557: 8, 1568: 8, 1570: 8, 1571: 8, 1572: 8, 1595: 8, 1777: 8, 1779: 8, 1792: 8, 1767:4, 800: 8, 1863:8, 1904: 8, 1912: 8, 1984: 8, 1988: 8, 1990: 8, 1992: 8, 1996:8, 1998: 8, 2002: 8, 2010: 8, 2015: 8, 2016: 8, 2018: 8, 2024: 8, 2026: 8, 2030: 8
}],
#Corolla w/ added Pedal Support (512L and 513L)
CAR.COROLLA: [{
36: 8, 37: 8, 170: 8, 180: 8, 186: 4, 426: 6, 452: 8, 464: 8, 466: 8, 467: 8, 512: 6, 513: 6, 547: 8, 548: 8, 552: 4, 608: 8, 610: 5, 643: 7, 705: 8, 740: 5, 800: 8, 835: 8, 836: 8, 849: 4, 869: 7, 870: 7, 871: 2, 896: 8, 897: 8, 900: 6, 902: 6, 905: 8, 911: 8, 916: 2, 921: 8, 933: 8, 944: 8, 945: 8, 951: 8, 955: 4, 956: 8, 979: 2, 992: 8, 998: 5, 999: 7, 1000: 8, 1001: 8, 1017: 8, 1041: 8, 1042: 8, 1043: 8, 1044: 8, 1056: 8, 1059: 1, 1114: 8, 1161: 8, 1162: 8, 1163: 8, 1196: 8, 1227: 8, 1235: 8, 1279: 8, 1552: 8, 1553: 8, 1556: 8, 1557: 8, 1561: 8, 1562: 8, 1568: 8, 1569: 8, 1570: 8, 1571: 8, 1572: 8, 1584: 8, 1589: 8, 1592: 8, 1596: 8, 1597: 8, 1600: 8, 1664: 8, 1728: 8, 1779: 8, 1904: 8, 1912: 8, 1990: 8, 1998: 8, 2016: 8, 2017: 8, 2018: 8, 2019: 8, 2020: 8, 2021: 8, 2022: 8, 2023: 8, 2024: 8
36: 8, 37: 8, 170: 8, 180: 8, 186: 4, 426: 6, 452: 8, 464: 8, 466: 8, 467: 8, 512: 6, 513: 6, 547: 8, 548: 8, 552: 4, 608: 8, 610: 5, 643: 7, 705: 8, 740: 5, 767:4, 800: 8, 835: 8, 836: 8, 849: 4, 869: 7, 870: 7, 871: 2, 896: 8, 897: 8, 900: 6, 902: 6, 905: 8, 911: 8, 916: 2, 921: 8, 933: 8, 944: 8, 945: 8, 951: 8, 955: 4, 956: 8, 979: 2, 992: 8, 998: 5, 999: 7, 1000: 8, 1001: 8, 1017: 8, 1041: 8, 1042: 8, 1043: 8, 1044: 8, 1056: 8, 1059: 1, 1114: 8, 1161: 8, 1162: 8, 1163: 8, 1196: 8, 1227: 8, 1235: 8, 1279: 8, 1552: 8, 1553: 8, 1556: 8, 1557: 8, 1561: 8, 1562: 8, 1568: 8, 1569: 8, 1570: 8, 1571: 8, 1572: 8, 1584: 8, 1589: 8, 1592: 8, 1596: 8, 1597: 8, 1600: 8, 1664: 8, 1728: 8, 1779: 8, 1904: 8, 1912: 8, 1990: 8, 1998: 8, 2016: 8, 2017: 8, 2018: 8, 2019: 8, 2020: 8, 2021: 8, 2022: 8, 2023: 8, 2024: 8
}],
CAR.LEXUS_RX: [{
# 2016 Lexus RX 350
36: 8, 37: 8, 114: 5, 119: 6, 120: 4, 170: 8, 180: 8, 186: 4, 426: 6, 452: 8, 464: 8, 466: 8, 467: 8, 544: 4, 550: 8, 552: 4, 562: 6, 608: 8, 610: 5, 643: 7, 705: 8, 740: 5, 742: 8, 743: 8, 800: 8, 810: 2, 812: 3, 818: 8, 819: 8, 820: 8, 821: 8, 822: 8, 830: 7, 835: 8, 836: 8, 845: 5, 869: 7, 870: 7, 871: 2, 898: 8, 900: 6, 902: 6, 905: 8, 913: 8, 918: 8, 921: 8, 933: 8, 944: 8, 945: 8, 951: 8, 955: 8, 956: 8, 998: 5, 999: 7, 1000: 8, 1001: 8, 1014: 8, 1017: 8, 1020: 8, 1041: 8, 1042: 8, 1044: 8, 1056: 8, 1059: 1, 1063: 8, 1077: 8, 1114: 8, 1161: 8, 1162: 8, 1163: 8, 1164: 8, 1165: 8, 1166: 8, 1167: 8, 1227: 8, 1228: 8, 1235: 8, 1237: 8, 1263: 8, 1264: 8, 1279: 8, 1349: 8, 1350: 8, 1351: 8, 1413: 8, 1414: 8, 1415: 8, 1416: 8, 1552: 8, 1553: 8, 1556: 8, 1557: 8, 1568: 8, 1570: 8, 1571: 8, 1572: 8, 1575: 8, 1595: 8, 1777: 8, 1779: 8, 1904: 8, 1912: 8, 1990: 8, 1998: 8, 2015: 8, 2016: 8, 2024: 8
36: 8, 37: 8, 114: 5, 119: 6, 120: 4, 170: 8, 180: 8, 186: 4, 426: 6, 452: 8, 464: 8, 466: 8, 467: 8, 544: 4, 550: 8, 552: 4, 562: 6, 608: 8, 610: 5, 643: 7, 705: 8, 740: 5, 742: 8, 743: 8, 767:4, 800: 8, 810: 2, 812: 3, 818: 8, 819: 8, 820: 8, 821: 8, 822: 8, 830: 7, 835: 8, 836: 8, 845: 5, 869: 7, 870: 7, 871: 2, 898: 8, 900: 6, 902: 6, 905: 8, 913: 8, 918: 8, 921: 8, 933: 8, 944: 8, 945: 8, 951: 8, 955: 8, 956: 8, 998: 5, 999: 7, 1000: 8, 1001: 8, 1014: 8, 1017: 8, 1020: 8, 1041: 8, 1042: 8, 1044: 8, 1056: 8, 1059: 1, 1063: 8, 1077: 8, 1114: 8, 1161: 8, 1162: 8, 1163: 8, 1164: 8, 1165: 8, 1166: 8, 1167: 8, 1227: 8, 1228: 8, 1235: 8, 1237: 8, 1263: 8, 1264: 8, 1279: 8, 1349: 8, 1350: 8, 1351: 8, 1413: 8, 1414: 8, 1415: 8, 1416: 8, 1552: 8, 1553: 8, 1556: 8, 1557: 8, 1568: 8, 1570: 8, 1571: 8, 1572: 8, 1575: 8, 1595: 8, 1777: 8, 1779: 8, 1904: 8, 1912: 8, 1990: 8, 1998: 8, 2015: 8, 2016: 8, 2024: 8
},
# 2017 Lexus RX 350
{
36: 8, 37: 8, 114: 5, 119: 6, 120: 4, 170: 8, 180: 8, 186: 4, 426: 6, 452: 8, 464: 8, 466: 8, 467: 8, 544: 4, 550: 8, 552: 4, 562: 6, 608: 8, 610: 5, 643: 7, 658: 8, 705: 8, 740: 5, 742: 8, 743: 8, 800: 8, 810: 2, 812: 3, 814: 8, 818: 8, 819: 8, 820: 8, 821: 8, 822: 8, 830: 7, 835: 8, 836: 8, 869: 7, 870: 7, 871: 2, 898: 8, 900: 6, 902: 6, 905: 8, 918: 8, 921: 8, 933: 8, 944: 8, 945: 8, 951: 8, 955: 8, 956: 8, 998: 5, 999: 7, 1000: 8, 1001: 8, 1014: 8, 1017: 8, 1020: 8, 1041: 8, 1042: 8, 1044: 8, 1056: 8, 1059: 1, 1063: 8, 1077: 8, 1082: 8, 1114: 8, 1161: 8, 1162: 8, 1163: 8, 1164: 8, 1165: 8, 1166: 8, 1167: 8, 1227: 8, 1228: 8, 1235: 8, 1237: 8, 1263: 8, 1264: 8, 1279: 8, 1349: 8, 1350: 8, 1351: 8, 1413: 8, 1414: 8, 1415: 8, 1416: 8, 1552: 8, 1553: 8, 1556: 8, 1557: 8, 1568: 8, 1570: 8, 1571: 8, 1572: 8, 1575: 8, 1595: 8, 1777: 8, 1779: 8, 1904: 8, 1912: 8, 1990: 8, 1998: 8
36: 8, 37: 8, 114: 5, 119: 6, 120: 4, 170: 8, 180: 8, 186: 4, 426: 6, 452: 8, 464: 8, 466: 8, 467: 8, 544: 4, 550: 8, 552: 4, 562: 6, 608: 8, 610: 5, 643: 7, 658: 8, 705: 8, 740: 5, 742: 8, 743: 8, 767:4, 800: 8, 810: 2, 812: 3, 814: 8, 818: 8, 819: 8, 820: 8, 821: 8, 822: 8, 830: 7, 835: 8, 836: 8, 869: 7, 870: 7, 871: 2, 898: 8, 900: 6, 902: 6, 905: 8, 918: 8, 921: 8, 933: 8, 944: 8, 945: 8, 951: 8, 955: 8, 956: 8, 998: 5, 999: 7, 1000: 8, 1001: 8, 1014: 8, 1017: 8, 1020: 8, 1041: 8, 1042: 8, 1044: 8, 1056: 8, 1059: 1, 1063: 8, 1077: 8, 1082: 8, 1114: 8, 1161: 8, 1162: 8, 1163: 8, 1164: 8, 1165: 8, 1166: 8, 1167: 8, 1227: 8, 1228: 8, 1235: 8, 1237: 8, 1263: 8, 1264: 8, 1279: 8, 1349: 8, 1350: 8, 1351: 8, 1413: 8, 1414: 8, 1415: 8, 1416: 8, 1552: 8, 1553: 8, 1556: 8, 1557: 8, 1568: 8, 1570: 8, 1571: 8, 1572: 8, 1575: 8, 1595: 8, 1777: 8, 1779: 8, 1904: 8, 1912: 8, 1990: 8, 1998: 8
}],
CAR.LEXUS_RXH: [{
36: 8, 37: 8, 166: 8, 170: 8, 180: 8, 295: 8, 296: 8, 426: 6, 452: 8, 466: 8, 467: 8, 512: 6, 513:6, 550: 8, 552: 4, 560: 7, 562: 6, 581: 5, 608: 8, 610: 5, 643: 7, 658: 8, 713: 8, 740: 5, 742: 8, 743: 8, 800: 8, 810: 2, 812: 3, 814: 8, 830: 7, 835: 8, 836: 8, 845: 5, 863: 8, 869: 7, 870: 7, 871: 2, 898: 8, 900: 6, 902: 6, 905: 8, 913: 8, 918: 8, 921: 8, 933: 8, 944: 8, 945: 8, 950: 8, 951: 8, 953: 8, 955: 8, 956: 8, 971: 7, 975: 6, 993: 8, 998: 5, 999: 7, 1000: 8, 1001: 8, 1005: 2, 1014: 8, 1017: 8, 1020: 8, 1041: 8, 1042: 8, 1044: 8, 1056: 8, 1059: 1, 1063: 8, 1071: 8, 1077: 8, 1082: 8, 1114: 8, 1161: 8, 1162: 8, 1163: 8, 1164: 8, 1165: 8, 1166: 8, 1167: 8, 1227: 8, 1228: 8, 1235: 8, 1237: 8, 1264: 8, 1279: 8, 1552: 8, 1553: 8, 1556: 8, 1557: 8, 1568: 8, 1570: 8, 1571: 8, 1572: 8, 1575: 8, 1595: 8, 1777: 8, 1779: 8, 1808: 8, 1810: 8, 1816: 8, 1818: 8, 1840: 8, 1848: 8, 1904: 8, 1912: 8, 1940: 8, 1941: 8, 1948: 8, 1949: 8, 1952: 8, 1956: 8, 1960: 8, 1964: 8, 1986: 8, 1990: 8, 1994: 8, 1998: 8, 2004: 8, 2012: 8
36: 8, 37: 8, 166: 8, 170: 8, 180: 8, 295: 8, 296: 8, 426: 6, 452: 8, 466: 8, 467: 8, 512: 6, 513:6, 550: 8, 552: 4, 560: 7, 562: 6, 581: 5, 608: 8, 610: 5, 643: 7, 658: 8, 713: 8, 740: 5, 742: 8, 743: 8, 767:4, 800: 8, 810: 2, 812: 3, 814: 8, 830: 7, 835: 8, 836: 8, 845: 5, 863: 8, 869: 7, 870: 7, 871: 2, 898: 8, 900: 6, 902: 6, 905: 8, 913: 8, 918: 8, 921: 8, 933: 8, 944: 8, 945: 8, 950: 8, 951: 8, 953: 8, 955: 8, 956: 8, 971: 7, 975: 6, 993: 8, 998: 5, 999: 7, 1000: 8, 1001: 8, 1005: 2, 1014: 8, 1017: 8, 1020: 8, 1041: 8, 1042: 8, 1044: 8, 1056: 8, 1059: 1, 1063: 8, 1071: 8, 1077: 8, 1082: 8, 1114: 8, 1161: 8, 1162: 8, 1163: 8, 1164: 8, 1165: 8, 1166: 8, 1167: 8, 1227: 8, 1228: 8, 1235: 8, 1237: 8, 1264: 8, 1279: 8, 1552: 8, 1553: 8, 1556: 8, 1557: 8, 1568: 8, 1570: 8, 1571: 8, 1572: 8, 1575: 8, 1595: 8, 1777: 8, 1779: 8, 1808: 8, 1810: 8, 1816: 8, 1818: 8, 1840: 8, 1848: 8, 1904: 8, 1912: 8, 1940: 8, 1941: 8, 1948: 8, 1949: 8, 1952: 8, 1956: 8, 1960: 8, 1964: 8, 1986: 8, 1990: 8, 1994: 8, 1998: 8, 2004: 8, 2012: 8
},
# RX450HL
# TODO: get proper fingerprint in stock mode
{
36: 8, 37: 8, 166: 8, 170: 8, 180: 8, 295: 8, 296: 8, 426: 6, 452: 8, 466: 8, 467: 8, 512: 6, 513: 6, 550: 8, 552: 4, 560: 7, 562: 6, 581: 5, 608: 8, 610: 5, 643: 7, 658: 8, 713: 8, 740: 5, 742: 8, 743: 8, 800: 8, 810: 2, 812: 3, 814: 8, 830: 7, 835: 8, 836: 8, 863: 8, 865: 8, 869: 7, 870: 7, 898: 8, 900: 6, 902: 6, 905: 8, 918: 8, 921: 8, 933: 8, 944: 8, 945: 8, 950: 8, 951: 8, 953: 8, 955: 8, 956: 8, 971: 7, 975: 6, 993: 8, 998: 5, 999: 7, 1000: 8, 1001: 8, 1005: 2, 1014: 8, 1017: 8, 1020: 8, 1041: 8, 1056: 8, 1057: 8, 1059: 1, 1063: 8, 1071: 8, 1076: 8, 1077: 8, 1082: 8, 1114: 8, 1164: 8, 1165: 8, 1166: 8, 1167: 8, 1227: 8, 1228: 8, 1237: 8, 1264: 8, 1279: 8, 1552: 8, 1553: 8, 1556: 8, 1557: 8, 1568: 8, 1570: 8, 1571: 8, 1572: 8, 1575: 8, 1592: 8, 1594: 8, 1595: 8, 1649: 8, 1777: 8, 1779: 8, 1904: 8, 1912: 8, 1990: 8, 1998: 8
36: 8, 37: 8, 166: 8, 170: 8, 180: 8, 295: 8, 296: 8, 426: 6, 452: 8, 466: 8, 467: 8, 512: 6, 513: 6, 550: 8, 552: 4, 560: 7, 562: 6, 581: 5, 608: 8, 610: 5, 643: 7, 658: 8, 713: 8, 740: 5, 742: 8, 743: 8, 767:4, 800: 8, 810: 2, 812: 3, 814: 8, 830: 7, 835: 8, 836: 8, 863: 8, 865: 8, 869: 7, 870: 7, 898: 8, 900: 6, 902: 6, 905: 8, 918: 8, 921: 8, 933: 8, 944: 8, 945: 8, 950: 8, 951: 8, 953: 8, 955: 8, 956: 8, 971: 7, 975: 6, 993: 8, 998: 5, 999: 7, 1000: 8, 1001: 8, 1005: 2, 1014: 8, 1017: 8, 1020: 8, 1041: 8, 1056: 8, 1057: 8, 1059: 1, 1063: 8, 1071: 8, 1076: 8, 1077: 8, 1082: 8, 1114: 8, 1164: 8, 1165: 8, 1166: 8, 1167: 8, 1227: 8, 1228: 8, 1237: 8, 1264: 8, 1279: 8, 1552: 8, 1553: 8, 1556: 8, 1557: 8, 1568: 8, 1570: 8, 1571: 8, 1572: 8, 1575: 8, 1592: 8, 1594: 8, 1595: 8, 1649: 8, 1777: 8, 1779: 8, 1904: 8, 1912: 8, 1990: 8, 1998: 8
},
# RX540H 2019 with color hud
{
36: 8, 37: 8, 166: 8, 170: 8, 180: 8, 295: 8, 296: 8, 426: 6, 452: 8, 466: 8, 467: 8, 512: 6, 513: 6, 550: 8, 552: 4, 560: 7, 562: 6, 581: 5, 608: 8, 610: 5, 643: 7, 658: 8, 713: 8, 740: 5, 742: 8, 743: 8, 800: 8, 810: 2, 812: 3, 814: 8, 818: 8, 819: 8, 820: 8, 821: 8, 822: 8, 830: 7, 835: 8, 836: 8, 845: 5, 863: 8, 865: 8, 869: 7, 870: 7, 871: 2, 898: 8, 900: 6, 902: 6, 905: 8, 913: 8, 918: 8, 921: 8, 933: 8, 944: 8, 945: 8, 950: 8, 951: 8, 953: 8, 955: 8, 956: 8, 971: 7, 975: 6, 993: 8, 998: 5, 999: 7, 1000: 8, 1001: 8, 1014: 8, 1017: 8, 1020: 8, 1041: 8, 1042: 8, 1044: 8, 1056: 8, 1057: 8, 1059: 1, 1063: 8, 1071: 8, 1076: 8, 1077: 8, 1082: 8, 1114: 8, 1161: 8, 1162: 8, 1163: 8, 1164: 8, 1165: 8, 1166: 8, 1167: 8, 1227: 8, 1228: 8, 1235: 8, 1237: 8, 1263: 8, 1264: 8, 1279: 8, 1349: 8, 1350: 8, 1351: 8, 1413: 8, 1414: 8, 1415: 8, 1416: 8, 1552: 8, 1553: 8, 1556: 8, 1557: 8, 1568: 8, 1570: 8, 1571: 8, 1572: 8, 1575: 8, 1592: 8, 1594: 8, 1595: 8, 1649: 8, 1777: 8, 1779: 8, 1808: 8, 1810: 8, 1816: 8, 1818: 8, 1904: 8, 1912: 8, 1952: 8, 1960: 8, 1990: 8, 1998: 8
36: 8, 37: 8, 166: 8, 170: 8, 180: 8, 295: 8, 296: 8, 426: 6, 452: 8, 466: 8, 467: 8, 512: 6, 513: 6, 550: 8, 552: 4, 560: 7, 562: 6, 581: 5, 608: 8, 610: 5, 643: 7, 658: 8, 713: 8, 740: 5, 742: 8, 743: 8, 767:4, 800: 8, 810: 2, 812: 3, 814: 8, 818: 8, 819: 8, 820: 8, 821: 8, 822: 8, 830: 7, 835: 8, 836: 8, 845: 5, 863: 8, 865: 8, 869: 7, 870: 7, 871: 2, 898: 8, 900: 6, 902: 6, 905: 8, 913: 8, 918: 8, 921: 8, 933: 8, 944: 8, 945: 8, 950: 8, 951: 8, 953: 8, 955: 8, 956: 8, 971: 7, 975: 6, 993: 8, 998: 5, 999: 7, 1000: 8, 1001: 8, 1014: 8, 1017: 8, 1020: 8, 1041: 8, 1042: 8, 1044: 8, 1056: 8, 1057: 8, 1059: 1, 1063: 8, 1071: 8, 1076: 8, 1077: 8, 1082: 8, 1114: 8, 1161: 8, 1162: 8, 1163: 8, 1164: 8, 1165: 8, 1166: 8, 1167: 8, 1227: 8, 1228: 8, 1235: 8, 1237: 8, 1263: 8, 1264: 8, 1279: 8, 1349: 8, 1350: 8, 1351: 8, 1413: 8, 1414: 8, 1415: 8, 1416: 8, 1552: 8, 1553: 8, 1556: 8, 1557: 8, 1568: 8, 1570: 8, 1571: 8, 1572: 8, 1575: 8, 1592: 8, 1594: 8, 1595: 8, 1649: 8, 1777: 8, 1779: 8, 1808: 8, 1810: 8, 1816: 8, 1818: 8, 1904: 8, 1912: 8, 1952: 8, 1960: 8, 1990: 8, 1998: 8
},
# 2017 RX 450h
{
36: 8, 37: 8, 166: 8, 170: 8, 180: 8, 295: 8, 296: 8, 426: 6, 452: 8, 466: 8, 467: 8, 550: 8, 552: 4, 560: 7, 562: 6, 581: 5, 608: 8, 610: 5, 643: 7, 658: 8, 713: 8, 740: 5, 742: 8, 743: 8, 744: 8, 800: 8, 810: 2, 812: 3, 814: 8, 818: 8, 819: 8, 820: 8, 821: 8, 822: 8, 830: 7, 835: 8, 836: 8, 845: 5, 863: 8, 869: 7, 870: 7, 871: 2, 898: 8, 900: 6, 902: 6, 905: 8, 913: 8, 918: 8, 921: 8, 933: 8, 944: 8, 945: 8, 950: 8, 951: 8, 953: 8, 955: 8, 956: 8, 971: 7, 975: 6, 993: 8, 998: 5, 999: 7, 1000: 8, 1001: 8, 1014: 8, 1017: 8, 1020: 8, 1041: 8, 1042: 8, 1044: 8, 1056: 8, 1059: 1, 1063: 8, 1071: 8, 1077: 8, 1082: 8, 1114: 8, 1161: 8, 1162: 8, 1163: 8, 1164: 8, 1165: 8, 1166: 8, 1167: 8, 1227: 8, 1228: 8, 1235: 8, 1237: 8, 1263: 8, 1264: 8, 1279: 8, 1349: 8, 1350: 8, 1351: 8, 1413: 8, 1414: 8, 1415: 8, 1416: 8, 1552: 8, 1553: 8, 1556: 8, 1557: 8, 1568: 8, 1570: 8, 1571: 8, 1572: 8, 1575: 8, 1595: 8, 1745: 8, 1777: 8, 1779: 8, 1904: 8, 1912: 8, 1990: 8, 1998: 8, 2015: 8, 2016: 8, 2024: 8
36: 8, 37: 8, 166: 8, 170: 8, 180: 8, 295: 8, 296: 8, 426: 6, 452: 8, 466: 8, 467: 8, 550: 8, 552: 4, 560: 7, 562: 6, 581: 5, 608: 8, 610: 5, 643: 7, 658: 8, 713: 8, 740: 5, 742: 8, 743: 8, 744: 8, 767:4, 800: 8, 810: 2, 812: 3, 814: 8, 818: 8, 819: 8, 820: 8, 821: 8, 822: 8, 830: 7, 835: 8, 836: 8, 845: 5, 863: 8, 869: 7, 870: 7, 871: 2, 898: 8, 900: 6, 902: 6, 905: 8, 913: 8, 918: 8, 921: 8, 933: 8, 944: 8, 945: 8, 950: 8, 951: 8, 953: 8, 955: 8, 956: 8, 971: 7, 975: 6, 993: 8, 998: 5, 999: 7, 1000: 8, 1001: 8, 1014: 8, 1017: 8, 1020: 8, 1041: 8, 1042: 8, 1044: 8, 1056: 8, 1059: 1, 1063: 8, 1071: 8, 1077: 8, 1082: 8, 1114: 8, 1161: 8, 1162: 8, 1163: 8, 1164: 8, 1165: 8, 1166: 8, 1167: 8, 1227: 8, 1228: 8, 1235: 8, 1237: 8, 1263: 8, 1264: 8, 1279: 8, 1349: 8, 1350: 8, 1351: 8, 1413: 8, 1414: 8, 1415: 8, 1416: 8, 1552: 8, 1553: 8, 1556: 8, 1557: 8, 1568: 8, 1570: 8, 1571: 8, 1572: 8, 1575: 8, 1595: 8, 1745: 8, 1777: 8, 1779: 8, 1904: 8, 1912: 8, 1990: 8, 1998: 8, 2015: 8, 2016: 8, 2024: 8
}],
CAR.LEXUS_RX_TSS2: [
# 2020 Lexus RX 350
{
36: 8, 37: 8, 114: 5, 119: 6, 120: 4, 170: 8, 180: 8, 186: 4, 401: 8, 426: 6, 452: 8, 464: 8, 466: 8, 467: 8, 544: 4, 550: 8, 552: 4, 562: 6, 608: 8, 610: 8, 643: 7, 658: 8, 705: 8, 740: 5, 742: 8, 743: 8, 764: 8, 765: 8, 800: 8, 810: 2, 812: 8, 814: 8, 818: 8, 824: 8, 830: 7, 835: 8, 836: 8, 865: 8, 869: 7, 870: 7, 871: 2, 877: 8, 881: 8, 891: 8, 896: 8, 898: 8, 900: 6, 902: 6, 905: 8, 918: 8, 921: 8, 933: 8, 934: 8, 935: 8, 944: 8, 945: 8, 951: 8, 955: 8, 956: 8, 976: 1, 987: 8, 998: 5, 999: 7, 1000: 8, 1001: 8, 1002: 8, 1014: 8, 1017: 8, 1020: 8, 1041: 8, 1042: 8, 1044: 8, 1056: 8, 1059: 1, 1063: 8, 1076: 8, 1077: 8,1082: 8, 1114: 8, 1161: 8, 1162: 8, 1163: 8, 1164: 8, 1165: 8, 1166: 8, 1167: 8, 1172: 8, 1228: 8, 1235: 8, 1237: 8, 1264: 8, 1279: 8, 1541: 8, 1552: 8, 1553: 8, 1556: 8, 1557: 8, 1568: 8, 1570: 8, 1571: 8, 1572: 8, 1575: 8, 1592: 8, 1594:8, 1595: 8, 1600: 8, 1649: 8, 1775: 8, 1777: 8, 1779: 8, 1786: 8, 1787: 8, 1788: 8, 1789: 8, 1808: 8, 1816: 8, 1904: 8, 1912: 8, 1990: 8, 1998: 8, 2015: 8, 2016: 8, 2024: 8
36: 8, 37: 8, 114: 5, 119: 6, 120: 4, 170: 8, 180: 8, 186: 4, 401: 8, 426: 6, 452: 8, 464: 8, 466: 8, 467: 8, 544: 4, 550: 8, 552: 4, 562: 6, 608: 8, 610: 8, 643: 7, 658: 8, 705: 8, 740: 5, 742: 8, 743: 8, 764: 8, 765: 8, 767:4, 800: 8, 810: 2, 812: 8, 814: 8, 818: 8, 824: 8, 830: 7, 835: 8, 836: 8, 865: 8, 869: 7, 870: 7, 871: 2, 877: 8, 881: 8, 891: 8, 896: 8, 898: 8, 900: 6, 902: 6, 905: 8, 918: 8, 921: 8, 933: 8, 934: 8, 935: 8, 944: 8, 945: 8, 951: 8, 955: 8, 956: 8, 976: 1, 987: 8, 998: 5, 999: 7, 1000: 8, 1001: 8, 1002: 8, 1014: 8, 1017: 8, 1020: 8, 1041: 8, 1042: 8, 1044: 8, 1056: 8, 1059: 1, 1063: 8, 1076: 8, 1077: 8,1082: 8, 1114: 8, 1161: 8, 1162: 8, 1163: 8, 1164: 8, 1165: 8, 1166: 8, 1167: 8, 1172: 8, 1228: 8, 1235: 8, 1237: 8, 1264: 8, 1279: 8, 1541: 8, 1552: 8, 1553: 8, 1556: 8, 1557: 8, 1568: 8, 1570: 8, 1571: 8, 1572: 8, 1575: 8, 1592: 8, 1594:8, 1595: 8, 1600: 8, 1649: 8, 1775: 8, 1777: 8, 1779: 8, 1786: 8, 1787: 8, 1788: 8, 1789: 8, 1808: 8, 1816: 8, 1904: 8, 1912: 8, 1990: 8, 1998: 8, 2015: 8, 2016: 8, 2024: 8
}],
CAR.CHR: [{
36: 8, 37: 8, 170: 8, 180: 8, 186: 4, 426: 6, 452: 8, 464: 8, 466: 8, 467: 8, 544: 4, 550: 8, 552: 4, 562: 6, 608: 8, 610: 8, 614: 8, 643: 7, 658: 8, 705: 8, 740: 5, 800: 8, 810: 2, 812: 8, 814: 8, 830: 7, 835: 8, 836: 8, 845: 5, 869: 7, 870: 7, 871: 2, 898: 8, 913: 8, 918: 8, 921: 8, 944: 8, 945: 8, 951: 8, 955: 8, 956: 8, 976: 1, 1014: 8, 1017: 8, 1020: 8, 1021: 8, 1041: 8, 1042: 8, 1044: 8, 1056: 8, 1059: 1, 1082: 8, 1083: 8, 1114: 8, 1161: 8, 1162: 8, 1163: 8, 1175: 8, 1228: 8, 1235: 8, 1237: 8, 1279: 8, 1552: 8, 1553: 8, 1556: 8, 1557: 8, 1568: 8, 1570: 8, 1571: 8, 1572: 8, 1595: 8, 1745: 8, 1779: 8
36: 8, 37: 8, 170: 8, 180: 8, 186: 4, 426: 6, 452: 8, 464: 8, 466: 8, 467: 8, 544: 4, 550: 8, 552: 4, 562: 6, 608: 8, 610: 8, 614: 8, 643: 7, 658: 8, 705: 8, 740: 5, 767:4, 800: 8, 810: 2, 812: 8, 814: 8, 830: 7, 835: 8, 836: 8, 845: 5, 869: 7, 870: 7, 871: 2, 898: 8, 913: 8, 918: 8, 921: 8, 944: 8, 945: 8, 951: 8, 955: 8, 956: 8, 976: 1, 1014: 8, 1017: 8, 1020: 8, 1021: 8, 1041: 8, 1042: 8, 1044: 8, 1056: 8, 1059: 1, 1082: 8, 1083: 8, 1114: 8, 1161: 8, 1162: 8, 1163: 8, 1175: 8, 1228: 8, 1235: 8, 1237: 8, 1279: 8, 1552: 8, 1553: 8, 1556: 8, 1557: 8, 1568: 8, 1570: 8, 1571: 8, 1572: 8, 1595: 8, 1745: 8, 1779: 8
}],
CAR.CHRH: [{
36: 8, 37: 8, 166: 8, 170: 8, 180: 8, 295: 8, 296: 8, 426: 6, 452: 8, 466: 8, 467: 8, 550: 8, 552: 4, 560: 7, 562: 6, 581: 5, 608: 8, 610: 8, 614: 8, 643: 7, 658: 8, 713: 8, 740: 5, 800: 8, 810: 2, 812: 8, 814: 8, 829: 2, 830: 7, 835: 8, 836: 8, 845: 5, 869: 7, 870: 7, 871: 2, 898: 8, 900: 6, 902: 6, 905: 8, 913: 8, 918: 8, 921: 8, 933: 8, 944: 8, 945: 8, 950: 8, 951: 8, 953: 8, 955: 8, 956: 8, 971: 7, 975: 5, 993: 8, 998: 5, 999: 7, 1000: 8, 1001: 8, 1014: 8, 1017: 8, 1020: 8, 1021: 8, 1041: 8, 1042: 8, 1044: 8, 1056: 8, 1057: 8, 1059: 1, 1071: 8, 1076: 8, 1077: 8, 1082: 8, 1083: 8, 1114: 8, 1161: 8, 1162: 8, 1163: 8, 1175: 8, 1228: 8, 1235: 8, 1237: 8, 1279: 8, 1552: 8, 1553: 8, 1556: 8, 1557: 8, 1568: 8, 1570: 8, 1571: 8, 1572: 8, 1595: 8, 1745: 8, 1779: 8, 1904: 8, 1912: 8, 1990: 8, 1998: 8
36: 8, 37: 8, 166: 8, 170: 8, 180: 8, 295: 8, 296: 8, 426: 6, 452: 8, 466: 8, 467: 8, 550: 8, 552: 4, 560: 7, 562: 6, 581: 5, 608: 8, 610: 8, 614: 8, 643: 7, 658: 8, 713: 8, 740: 5, 767:4, 800: 8, 810: 2, 812: 8, 814: 8, 829: 2, 830: 7, 835: 8, 836: 8, 845: 5, 869: 7, 870: 7, 871: 2, 898: 8, 900: 6, 902: 6, 905: 8, 913: 8, 918: 8, 921: 8, 933: 8, 944: 8, 945: 8, 950: 8, 951: 8, 953: 8, 955: 8, 956: 8, 971: 7, 975: 5, 993: 8, 998: 5, 999: 7, 1000: 8, 1001: 8, 1014: 8, 1017: 8, 1020: 8, 1021: 8, 1041: 8, 1042: 8, 1044: 8, 1056: 8, 1057: 8, 1059: 1, 1071: 8, 1076: 8, 1077: 8, 1082: 8, 1083: 8, 1114: 8, 1161: 8, 1162: 8, 1163: 8, 1175: 8, 1228: 8, 1235: 8, 1237: 8, 1279: 8, 1552: 8, 1553: 8, 1556: 8, 1557: 8, 1568: 8, 1570: 8, 1571: 8, 1572: 8, 1595: 8, 1745: 8, 1779: 8, 1904: 8, 1912: 8, 1990: 8, 1998: 8
}],
CAR.CAMRY: [
#XLE and LE
{
36: 8, 37: 8, 119: 6, 170: 8, 180: 8, 186: 4, 426: 6, 452: 8, 464: 8, 466: 8, 467: 8, 544: 4, 550: 8, 552: 4, 562: 6, 608: 8, 610: 8, 643: 7, 658: 8, 705: 8, 728: 8, 740: 5, 761: 8, 764: 8, 800: 8, 810: 2, 812: 8, 814: 8, 818: 8, 822: 8, 824: 8, 830: 7, 835: 8, 836: 8, 869: 7, 870: 7, 871: 2, 888: 8, 889: 8, 891: 8, 898: 8, 900: 6, 902: 6, 905: 8, 918: 8, 921: 8, 933: 8, 934: 8, 935: 8, 944: 8, 945: 8, 951: 8, 955: 8, 956: 8, 976: 1, 983: 8, 984: 8, 998: 5, 999: 7, 1000: 8, 1001: 8, 1002: 8, 1011: 8, 1014: 8, 1017: 8, 1020: 8, 1041: 8, 1042: 8, 1044: 8, 1056: 8, 1059: 1, 1076: 8, 1077: 8, 1082: 8, 1114: 8, 1161: 8, 1162: 8, 1163: 8, 1164: 8, 1165: 8, 1166: 8, 1167: 8, 1228: 8, 1235: 8, 1237: 8, 1263: 8, 1264: 8, 1279: 8, 1412: 8, 1541: 8, 1552: 8, 1553: 8, 1556: 8, 1557: 8, 1568: 8, 1570: 8, 1571: 8, 1572: 8, 1595: 8, 1745: 8, 1779: 8, 1786: 8, 1787: 8, 1788: 8, 1789: 8, 1808: 8, 1816: 8, 1904: 8, 1912: 8, 1990: 8, 1998: 8
36: 8, 37: 8, 119: 6, 170: 8, 180: 8, 186: 4, 426: 6, 452: 8, 464: 8, 466: 8, 467: 8, 544: 4, 550: 8, 552: 4, 562: 6, 608: 8, 610: 8, 643: 7, 658: 8, 705: 8, 728: 8, 740: 5, 761: 8, 764: 8, 767:4, 800: 8, 810: 2, 812: 8, 814: 8, 818: 8, 822: 8, 824: 8, 830: 7, 835: 8, 836: 8, 869: 7, 870: 7, 871: 2, 888: 8, 889: 8, 891: 8, 898: 8, 900: 6, 902: 6, 905: 8, 918: 8, 921: 8, 933: 8, 934: 8, 935: 8, 944: 8, 945: 8, 951: 8, 955: 8, 956: 8, 976: 1, 983: 8, 984: 8, 998: 5, 999: 7, 1000: 8, 1001: 8, 1002: 8, 1011: 8, 1014: 8, 1017: 8, 1020: 8, 1041: 8, 1042: 8, 1044: 8, 1056: 8, 1059: 1, 1076: 8, 1077: 8, 1082: 8, 1114: 8, 1161: 8, 1162: 8, 1163: 8, 1164: 8, 1165: 8, 1166: 8, 1167: 8, 1228: 8, 1235: 8, 1237: 8, 1263: 8, 1264: 8, 1279: 8, 1412: 8, 1541: 8, 1552: 8, 1553: 8, 1556: 8, 1557: 8, 1568: 8, 1570: 8, 1571: 8, 1572: 8, 1595: 8, 1745: 8, 1779: 8, 1786: 8, 1787: 8, 1788: 8, 1789: 8, 1808: 8, 1816: 8, 1904: 8, 1912: 8, 1990: 8, 1998: 8
},
#XSE and SE
# TODO: get proper fingerprint in stock mode
{
36: 8, 37: 8, 114: 5, 119: 6, 120: 4, 170: 8, 180: 8, 186: 4, 426: 6, 452: 8, 464: 8, 466: 8, 467: 8, 544: 4, 550: 8, 552: 4, 562: 6, 608: 8, 610: 8, 643: 7, 658: 8, 705: 8, 728: 8, 740: 5, 761: 8, 764: 8, 800: 8, 810: 2, 812: 8, 814: 8, 818: 8, 822: 8, 824: 8, 830: 7, 835: 8, 836: 8, 869: 7, 870: 7, 888: 8, 889: 8, 891: 8, 898: 8, 900: 6, 902: 6, 905: 8, 918: 8, 921: 8, 933: 8, 934: 8, 935: 8, 944: 8, 945: 8, 951: 8, 955: 8, 956: 8, 976: 1, 983: 8, 984: 8, 998: 5, 999: 7, 1000: 8, 1001: 8, 1002: 8, 1011: 8, 1014: 8, 1017: 8, 1020: 8, 1041: 8, 1056: 8, 1059: 1, 1076: 8, 1077: 8, 1082: 8, 1114: 8, 1164: 8, 1165: 8, 1166: 8, 1167: 8, 1228: 8, 1237: 8, 1263: 8, 1264: 8, 1279: 8, 1412: 8, 1541: 8, 1552: 8, 1553: 8, 1556: 8, 1557: 8, 1568: 8, 1570: 8, 1571: 8, 1572: 8, 1595: 8, 1745: 8, 1779: 8, 1786: 8, 1787: 8, 1788: 8, 1789: 8, 1808: 8, 1816: 8, 1904: 8, 1912: 8, 1990: 8, 1998: 8
36: 8, 37: 8, 114: 5, 119: 6, 120: 4, 170: 8, 180: 8, 186: 4, 426: 6, 452: 8, 464: 8, 466: 8, 467: 8, 544: 4, 550: 8, 552: 4, 562: 6, 608: 8, 610: 8, 643: 7, 658: 8, 705: 8, 728: 8, 740: 5, 761: 8, 764: 8, 767:4, 800: 8, 810: 2, 812: 8, 814: 8, 818: 8, 822: 8, 824: 8, 830: 7, 835: 8, 836: 8, 869: 7, 870: 7, 888: 8, 889: 8, 891: 8, 898: 8, 900: 6, 902: 6, 905: 8, 918: 8, 921: 8, 933: 8, 934: 8, 935: 8, 944: 8, 945: 8, 951: 8, 955: 8, 956: 8, 976: 1, 983: 8, 984: 8, 998: 5, 999: 7, 1000: 8, 1001: 8, 1002: 8, 1011: 8, 1014: 8, 1017: 8, 1020: 8, 1041: 8, 1056: 8, 1059: 1, 1076: 8, 1077: 8, 1082: 8, 1114: 8, 1164: 8, 1165: 8, 1166: 8, 1167: 8, 1228: 8, 1237: 8, 1263: 8, 1264: 8, 1279: 8, 1412: 8, 1541: 8, 1552: 8, 1553: 8, 1556: 8, 1557: 8, 1568: 8, 1570: 8, 1571: 8, 1572: 8, 1595: 8, 1745: 8, 1779: 8, 1786: 8, 1787: 8, 1788: 8, 1789: 8, 1808: 8, 1816: 8, 1904: 8, 1912: 8, 1990: 8, 1998: 8
},
{
# 2019 XSE
36: 8, 37: 8, 170: 8, 180: 8, 186: 4, 426: 6, 452: 8, 464: 8, 466: 8, 467: 8, 544: 4, 550: 8, 552: 4, 562: 6, 608: 8, 610: 8, 643: 7, 658: 8, 705: 8, 728: 8, 740: 5, 761: 8, 764: 8, 800: 8, 810: 2, 812: 8, 814: 8, 818: 8, 822: 8, 824: 8, 830: 7, 835: 8, 836: 8, 865: 8, 869: 7, 870: 7, 871: 2, 888: 8, 889: 8, 891: 8, 896: 8, 898: 8, 900: 6, 902: 6, 905: 8, 918: 8, 921: 8, 933: 8, 934: 8, 935: 8, 942: 8, 944: 8, 945: 8, 951: 8, 955: 8, 956: 8, 976: 1, 983: 8, 984: 8, 998: 5, 999: 7, 1000: 8, 1001: 8, 1002: 8, 1011: 8, 1014: 8, 1017: 8, 1020: 8, 1041: 8, 1042: 8, 1044: 8, 1056: 8, 1059: 1, 1076: 8, 1077: 8, 1082: 8, 1114: 8, 1161: 8, 1162: 8, 1163: 8, 1164: 8, 1165: 8, 1166: 8, 1167: 8, 1228: 8, 1235: 8, 1237: 8, 1263: 8, 1264: 8, 1279: 8, 1412: 8, 1541: 8, 1552: 8, 1553: 8, 1556: 8, 1557: 8, 1568: 8, 1570: 8, 1571: 8, 1572: 8, 1592: 8, 1594: 8, 1595: 8, 1649: 8, 1745: 8, 1779: 8, 1786: 8, 1787: 8, 1788: 8, 1789: 8, 1792: 8, 1800: 8, 1808: 8, 1816: 8, 1872: 8, 1880: 8, 1904: 8, 1912: 8, 1937: 8, 1945: 8, 1953: 8, 1961: 8, 1968: 8, 1976: 8, 1990: 8, 1998: 8, 2015: 8, 2016: 8, 2024: 8
36: 8, 37: 8, 170: 8, 180: 8, 186: 4, 426: 6, 452: 8, 464: 8, 466: 8, 467: 8, 544: 4, 550: 8, 552: 4, 562: 6, 608: 8, 610: 8, 643: 7, 658: 8, 705: 8, 728: 8, 740: 5, 761: 8, 764: 8, 767:4, 800: 8, 810: 2, 812: 8, 814: 8, 818: 8, 822: 8, 824: 8, 830: 7, 835: 8, 836: 8, 865: 8, 869: 7, 870: 7, 871: 2, 888: 8, 889: 8, 891: 8, 896: 8, 898: 8, 900: 6, 902: 6, 905: 8, 918: 8, 921: 8, 933: 8, 934: 8, 935: 8, 942: 8, 944: 8, 945: 8, 951: 8, 955: 8, 956: 8, 976: 1, 983: 8, 984: 8, 998: 5, 999: 7, 1000: 8, 1001: 8, 1002: 8, 1011: 8, 1014: 8, 1017: 8, 1020: 8, 1041: 8, 1042: 8, 1044: 8, 1056: 8, 1059: 1, 1076: 8, 1077: 8, 1082: 8, 1114: 8, 1161: 8, 1162: 8, 1163: 8, 1164: 8, 1165: 8, 1166: 8, 1167: 8, 1228: 8, 1235: 8, 1237: 8, 1263: 8, 1264: 8, 1279: 8, 1412: 8, 1541: 8, 1552: 8, 1553: 8, 1556: 8, 1557: 8, 1568: 8, 1570: 8, 1571: 8, 1572: 8, 1592: 8, 1594: 8, 1595: 8, 1649: 8, 1745: 8, 1779: 8, 1786: 8, 1787: 8, 1788: 8, 1789: 8, 1792: 8, 1767:4, 800: 8, 1808: 8, 1816: 8, 1872: 8, 1880: 8, 1904: 8, 1912: 8, 1937: 8, 1945: 8, 1953: 8, 1961: 8, 1968: 8, 1976: 8, 1990: 8, 1998: 8, 2015: 8, 2016: 8, 2024: 8
}],
CAR.CAMRYH: [
#SE, LE and LE with Blindspot Monitor
{
36: 8, 37: 8, 166: 8, 170: 8, 180: 8, 295: 8, 296: 8, 426: 6, 452: 8, 466: 8, 467: 8, 550: 8, 552: 4, 560: 7, 562: 6, 581: 5, 608: 8, 610: 8, 643: 7, 713: 8, 728: 8, 740: 5, 761: 8, 764: 8, 800: 8, 810: 2, 812: 8, 818: 8, 824: 8, 829: 2, 830: 7, 835: 8, 836: 8, 865: 8, 869: 7, 870: 7, 871: 2, 889: 8, 896: 8, 898: 8, 900: 6, 902: 6, 905: 8, 921: 8, 933: 8, 934: 8, 935: 8, 944: 8, 945: 8, 950: 8, 951: 8, 953: 8, 955: 8, 956: 8, 971: 7, 975: 5, 983: 8, 984: 8, 993: 8, 998: 5, 999: 7, 1000: 8, 1001: 8, 1002: 8, 1011: 8, 1014: 8, 1017: 8, 1020: 8, 1041: 8, 1042: 8, 1044: 8, 1056: 8, 1057: 8, 1059: 1, 1071: 8, 1076: 8, 1077: 8, 1084: 8, 1085: 8, 1086: 8, 1114: 8, 1132: 8, 1161: 8, 1162: 8, 1163: 8, 1164: 8, 1165: 8, 1166: 8, 1167: 8, 1235: 8, 1237: 8, 1264: 8, 1279: 8, 1541: 8, 1552: 8, 1553: 8, 1556: 8, 1557: 8, 1568: 8, 1570: 8, 1571: 8, 1572: 8, 1592: 8, 1594: 8, 1595: 8, 1649: 8, 1745: 8, 1779: 8, 1786: 8, 1787: 8, 1788: 8, 1789: 8, 1808: 8, 1810: 8, 1816: 8, 1818: 8, 1904: 8, 1912: 8, 1990: 8, 1998: 8
36: 8, 37: 8, 166: 8, 170: 8, 180: 8, 295: 8, 296: 8, 426: 6, 452: 8, 466: 8, 467: 8, 550: 8, 552: 4, 560: 7, 562: 6, 581: 5, 608: 8, 610: 8, 643: 7, 713: 8, 728: 8, 740: 5, 761: 8, 764: 8, 767:4, 800: 8, 810: 2, 812: 8, 818: 8, 824: 8, 829: 2, 830: 7, 835: 8, 836: 8, 865: 8, 869: 7, 870: 7, 871: 2, 889: 8, 896: 8, 898: 8, 900: 6, 902: 6, 905: 8, 921: 8, 933: 8, 934: 8, 935: 8, 944: 8, 945: 8, 950: 8, 951: 8, 953: 8, 955: 8, 956: 8, 971: 7, 975: 5, 983: 8, 984: 8, 993: 8, 998: 5, 999: 7, 1000: 8, 1001: 8, 1002: 8, 1011: 8, 1014: 8, 1017: 8, 1020: 8, 1041: 8, 1042: 8, 1044: 8, 1056: 8, 1057: 8, 1059: 1, 1071: 8, 1076: 8, 1077: 8, 1084: 8, 1085: 8, 1086: 8, 1114: 8, 1132: 8, 1161: 8, 1162: 8, 1163: 8, 1164: 8, 1165: 8, 1166: 8, 1167: 8, 1235: 8, 1237: 8, 1264: 8, 1279: 8, 1541: 8, 1552: 8, 1553: 8, 1556: 8, 1557: 8, 1568: 8, 1570: 8, 1571: 8, 1572: 8, 1592: 8, 1594: 8, 1595: 8, 1649: 8, 1745: 8, 1779: 8, 1786: 8, 1787: 8, 1788: 8, 1789: 8, 1808: 8, 1810: 8, 1816: 8, 1818: 8, 1904: 8, 1912: 8, 1990: 8, 1998: 8
},
#SL
{
36: 8, 37: 8, 166: 8, 170: 8, 180: 8, 295: 8, 296: 8, 426: 6, 452: 8, 466: 8, 467: 8, 550: 8, 552: 4, 560: 7, 562: 6, 581: 5, 608: 8, 610: 8, 643: 7, 713: 8, 728: 8, 740: 5, 761: 8, 764: 8, 800: 8, 810: 2, 812: 8, 818: 8, 824: 8, 829: 2, 830: 7, 835: 8, 836: 8, 869: 7, 870: 7, 871: 2, 888: 8, 889: 8, 898: 8, 900: 6, 902: 6, 905: 8, 913: 8, 918: 8, 921: 8, 933: 8, 934: 8, 935: 8, 944: 8, 945: 8, 950: 8, 951: 8, 953: 8, 955: 8, 956: 8, 971: 7, 975: 5, 993: 8, 998: 5, 999: 7, 1000: 8, 1001: 8, 1002: 8, 1014: 8, 1017: 8, 1020: 8, 1041: 8, 1042: 8, 1044: 8, 1056: 8, 1057: 8, 1059: 1, 1071: 8, 1076: 8, 1077: 8, 1084: 8, 1085: 8, 1086: 8, 1114: 8, 1132: 8, 1161: 8, 1162: 8, 1163: 8, 1164: 8, 1165: 8, 1166: 8, 1167: 8, 1228: 8, 1235: 8, 1237: 8, 1264: 8, 1279: 8, 1541: 8, 1552: 8, 1553: 8, 1556: 8, 1557: 8, 1568: 8, 1570: 8, 1571: 8, 1572: 8, 1595: 8, 1745: 8, 1779: 8, 1786: 8, 1787: 8, 1788: 8, 1789: 8, 1904: 8, 1912: 8, 1990: 8, 1998: 8
36: 8, 37: 8, 166: 8, 170: 8, 180: 8, 295: 8, 296: 8, 426: 6, 452: 8, 466: 8, 467: 8, 550: 8, 552: 4, 560: 7, 562: 6, 581: 5, 608: 8, 610: 8, 643: 7, 713: 8, 728: 8, 740: 5, 761: 8, 764: 8, 767:4, 800: 8, 810: 2, 812: 8, 818: 8, 824: 8, 829: 2, 830: 7, 835: 8, 836: 8, 869: 7, 870: 7, 871: 2, 888: 8, 889: 8, 898: 8, 900: 6, 902: 6, 905: 8, 913: 8, 918: 8, 921: 8, 933: 8, 934: 8, 935: 8, 944: 8, 945: 8, 950: 8, 951: 8, 953: 8, 955: 8, 956: 8, 971: 7, 975: 5, 993: 8, 998: 5, 999: 7, 1000: 8, 1001: 8, 1002: 8, 1014: 8, 1017: 8, 1020: 8, 1041: 8, 1042: 8, 1044: 8, 1056: 8, 1057: 8, 1059: 1, 1071: 8, 1076: 8, 1077: 8, 1084: 8, 1085: 8, 1086: 8, 1114: 8, 1132: 8, 1161: 8, 1162: 8, 1163: 8, 1164: 8, 1165: 8, 1166: 8, 1167: 8, 1228: 8, 1235: 8, 1237: 8, 1264: 8, 1279: 8, 1541: 8, 1552: 8, 1553: 8, 1556: 8, 1557: 8, 1568: 8, 1570: 8, 1571: 8, 1572: 8, 1595: 8, 1745: 8, 1779: 8, 1786: 8, 1787: 8, 1788: 8, 1789: 8, 1904: 8, 1912: 8, 1990: 8, 1998: 8
},
#XLE
{
36: 8, 37: 8, 166: 8, 170: 8, 180: 8, 295: 8, 296: 8, 426: 6, 452: 8, 466: 8, 467: 8, 550: 8, 552: 4, 560: 7, 562: 6, 581: 5, 608: 8, 610: 8, 643: 7, 658: 8, 713: 8, 728: 8, 740: 5, 761: 8, 764: 8, 800: 8, 810: 2, 812: 8, 814: 8, 818: 8, 824: 8, 829: 2, 830: 7, 835: 8, 836: 8, 869: 7, 870: 7, 871: 2, 888: 8, 889: 8, 898: 8, 900: 6, 902: 6, 905: 8, 918: 8, 921: 8, 933: 8, 934: 8, 935: 8, 944: 8, 945: 8, 950: 8, 951: 8, 953: 8, 955: 8, 956: 8, 971: 7, 975: 5, 983: 8, 984: 8, 993: 8, 998: 5, 999: 7, 1000: 8, 1001: 8, 1002: 8, 1011: 8, 1014: 8, 1017: 8, 1020: 8, 1041: 8, 1042: 8, 1044: 8, 1056: 8, 1057: 8, 1059: 1, 1071: 8, 1076: 8, 1077: 8, 1082: 8, 1084: 8, 1085: 8, 1086: 8, 1114: 8, 1132: 8, 1161: 8, 1162: 8, 1163: 8, 1164: 8, 1165: 8, 1166: 8, 1167: 8, 1228: 8, 1235: 8, 1237: 8, 1264: 8, 1279: 8, 1541: 8, 1552: 8, 1553: 8, 1556: 8, 1557: 8, 1568: 8, 1570: 8, 1571: 8, 1572: 8, 1595: 8, 1745: 8, 1779: 8, 1786: 8, 1787: 8, 1788: 8, 1789: 8, 1904: 8, 1912: 8, 1990: 8, 1998: 8
36: 8, 37: 8, 166: 8, 170: 8, 180: 8, 295: 8, 296: 8, 426: 6, 452: 8, 466: 8, 467: 8, 550: 8, 552: 4, 560: 7, 562: 6, 581: 5, 608: 8, 610: 8, 643: 7, 658: 8, 713: 8, 728: 8, 740: 5, 761: 8, 764: 8, 767:4, 800: 8, 810: 2, 812: 8, 814: 8, 818: 8, 824: 8, 829: 2, 830: 7, 835: 8, 836: 8, 869: 7, 870: 7, 871: 2, 888: 8, 889: 8, 898: 8, 900: 6, 902: 6, 905: 8, 918: 8, 921: 8, 933: 8, 934: 8, 935: 8, 944: 8, 945: 8, 950: 8, 951: 8, 953: 8, 955: 8, 956: 8, 971: 7, 975: 5, 983: 8, 984: 8, 993: 8, 998: 5, 999: 7, 1000: 8, 1001: 8, 1002: 8, 1011: 8, 1014: 8, 1017: 8, 1020: 8, 1041: 8, 1042: 8, 1044: 8, 1056: 8, 1057: 8, 1059: 1, 1071: 8, 1076: 8, 1077: 8, 1082: 8, 1084: 8, 1085: 8, 1086: 8, 1114: 8, 1132: 8, 1161: 8, 1162: 8, 1163: 8, 1164: 8, 1165: 8, 1166: 8, 1167: 8, 1228: 8, 1235: 8, 1237: 8, 1264: 8, 1279: 8, 1541: 8, 1552: 8, 1553: 8, 1556: 8, 1557: 8, 1568: 8, 1570: 8, 1571: 8, 1572: 8, 1595: 8, 1745: 8, 1779: 8, 1786: 8, 1787: 8, 1788: 8, 1789: 8, 1904: 8, 1912: 8, 1990: 8, 1998: 8
}],
CAR.HIGHLANDER: [{
36: 8, 37: 8, 114: 5, 119: 6, 120: 4, 170: 8, 180: 8, 186: 4, 238: 4, 355: 5, 426: 6, 452: 8, 464: 8, 466: 8, 467: 8, 544: 4, 545: 5, 550: 8, 552: 4, 608: 8, 610: 5, 643: 7, 705: 8, 725: 2, 740: 5, 800: 8, 835: 8, 836: 8, 849: 4, 869: 7, 870: 7, 871: 2, 896: 8, 900: 6, 902: 6, 905: 8, 911: 8, 916: 3, 921: 8, 922: 8, 933: 8, 944: 8, 945: 8, 951: 8, 955: 8, 956: 8, 979: 2, 998: 5, 999: 7, 1000: 8, 1001: 8, 1008: 2, 1014: 8, 1017: 8, 1020: 8, 1041: 8, 1042: 8, 1043: 8, 1044: 8, 1056: 8, 1059: 1, 1114: 8, 1161: 8, 1162: 8, 1163: 8, 1176: 8, 1177: 8, 1178: 8, 1179: 8, 1180: 8, 1181: 8, 1182: 8, 1183: 8, 1189: 8, 1190: 8, 1191: 8, 1192: 8, 1196: 8, 1197: 8, 1198: 8, 1199: 8, 1206: 8, 1207: 8, 1212: 8, 1227: 8, 1235: 8, 1237: 8, 1279: 8, 1408: 8, 1409: 8, 1410: 8, 1552: 8, 1553: 8, 1554: 8, 1556: 8, 1557: 8, 1561: 8, 1562: 8, 1568: 8, 1569: 8, 1570: 8, 1571: 8, 1572: 8, 1584: 8, 1589: 8, 1592: 8, 1593: 8, 1595: 8, 1599: 8, 1656: 8, 1666: 8, 1667: 8, 1728: 8, 1745: 8, 1779: 8, 1872: 8, 1880: 8, 1904: 8, 1912: 8, 1984: 8, 1988: 8, 1992: 8, 1996: 8, 1990: 8, 1998: 8
36: 8, 37: 8, 114: 5, 119: 6, 120: 4, 170: 8, 180: 8, 186: 4, 238: 4, 355: 5, 426: 6, 452: 8, 464: 8, 466: 8, 467: 8, 544: 4, 545: 5, 550: 8, 552: 4, 608: 8, 610: 5, 643: 7, 705: 8, 725: 2, 740: 5, 767:4, 800: 8, 835: 8, 836: 8, 849: 4, 869: 7, 870: 7, 871: 2, 896: 8, 900: 6, 902: 6, 905: 8, 911: 8, 916: 3, 921: 8, 922: 8, 933: 8, 944: 8, 945: 8, 951: 8, 955: 8, 956: 8, 979: 2, 998: 5, 999: 7, 1000: 8, 1001: 8, 1008: 2, 1014: 8, 1017: 8, 1020: 8, 1041: 8, 1042: 8, 1043: 8, 1044: 8, 1056: 8, 1059: 1, 1114: 8, 1161: 8, 1162: 8, 1163: 8, 1176: 8, 1177: 8, 1178: 8, 1179: 8, 1180: 8, 1181: 8, 1182: 8, 1183: 8, 1189: 8, 1190: 8, 1191: 8, 1192: 8, 1196: 8, 1197: 8, 1198: 8, 1199: 8, 1206: 8, 1207: 8, 1212: 8, 1227: 8, 1235: 8, 1237: 8, 1279: 8, 1408: 8, 1409: 8, 1410: 8, 1552: 8, 1553: 8, 1554: 8, 1556: 8, 1557: 8, 1561: 8, 1562: 8, 1568: 8, 1569: 8, 1570: 8, 1571: 8, 1572: 8, 1584: 8, 1589: 8, 1592: 8, 1593: 8, 1595: 8, 1599: 8, 1656: 8, 1666: 8, 1667: 8, 1728: 8, 1745: 8, 1779: 8, 1872: 8, 1880: 8, 1904: 8, 1912: 8, 1984: 8, 1988: 8, 1992: 8, 1996: 8, 1990: 8, 1998: 8
},
# 2019 Highlander XLE
{
36: 8, 37: 8, 114: 5, 119: 6, 120: 4, 170: 8, 180: 8, 186: 4, 238: 4, 355: 5, 426: 6, 452: 8, 464: 8, 466: 8, 467: 8, 544: 4, 545: 5, 550: 8, 552: 4, 608: 8, 610: 5, 643: 7, 705: 8, 725: 2, 740: 5, 800: 8, 835: 8, 836: 8, 849: 4, 869: 7, 870: 7, 871: 2, 896: 8, 900: 6, 902: 6, 905: 8, 911: 8, 916: 3, 921: 8, 922: 8, 933: 8, 944: 8, 945: 8, 951: 8, 955: 8, 956: 8, 979: 2, 992: 8, 998: 5, 999: 7, 1000: 8, 1001: 8, 1008: 2, 1014: 8, 1017: 8, 1020: 8, 1041: 8, 1042: 8, 1043: 8, 1044: 8, 1056: 8, 1059: 1, 1076: 8, 1077: 8, 1114: 8, 1161: 8, 1162: 8, 1163: 8, 1176: 8, 1177: 8, 1178: 8, 1179: 8, 1180: 8, 1181: 8, 1182: 8, 1183: 8, 1189: 8, 1190: 8, 1191: 8, 1192: 8, 1196: 8, 1197: 8, 1198: 8, 1199: 8, 1206: 8, 1207: 8, 1212: 8, 1227: 8, 1235: 8, 1237: 8, 1279: 8, 1408: 8, 1409: 8, 1410: 8, 1552: 8, 1553: 8, 1554: 8, 1556: 8, 1557: 8, 1561: 8, 1562: 8, 1568: 8, 1569: 8, 1570: 8, 1571: 8, 1572: 8, 1584: 8, 1589: 8, 1592: 8, 1593: 8, 1595: 8, 1599: 8, 1656: 8, 1728: 8, 1745: 8, 1779: 8, 1904: 8, 1912: 8, 1990: 8, 1998: 8
36: 8, 37: 8, 114: 5, 119: 6, 120: 4, 170: 8, 180: 8, 186: 4, 238: 4, 355: 5, 426: 6, 452: 8, 464: 8, 466: 8, 467: 8, 544: 4, 545: 5, 550: 8, 552: 4, 608: 8, 610: 5, 643: 7, 705: 8, 725: 2, 740: 5, 767:4, 800: 8, 835: 8, 836: 8, 849: 4, 869: 7, 870: 7, 871: 2, 896: 8, 900: 6, 902: 6, 905: 8, 911: 8, 916: 3, 921: 8, 922: 8, 933: 8, 944: 8, 945: 8, 951: 8, 955: 8, 956: 8, 979: 2, 992: 8, 998: 5, 999: 7, 1000: 8, 1001: 8, 1008: 2, 1014: 8, 1017: 8, 1020: 8, 1041: 8, 1042: 8, 1043: 8, 1044: 8, 1056: 8, 1059: 1, 1076: 8, 1077: 8, 1114: 8, 1161: 8, 1162: 8, 1163: 8, 1176: 8, 1177: 8, 1178: 8, 1179: 8, 1180: 8, 1181: 8, 1182: 8, 1183: 8, 1189: 8, 1190: 8, 1191: 8, 1192: 8, 1196: 8, 1197: 8, 1198: 8, 1199: 8, 1206: 8, 1207: 8, 1212: 8, 1227: 8, 1235: 8, 1237: 8, 1279: 8, 1408: 8, 1409: 8, 1410: 8, 1552: 8, 1553: 8, 1554: 8, 1556: 8, 1557: 8, 1561: 8, 1562: 8, 1568: 8, 1569: 8, 1570: 8, 1571: 8, 1572: 8, 1584: 8, 1589: 8, 1592: 8, 1593: 8, 1595: 8, 1599: 8, 1656: 8, 1728: 8, 1745: 8, 1779: 8, 1904: 8, 1912: 8, 1990: 8, 1998: 8
},
# 2017 Highlander Limited
{
36: 8, 37: 8, 114: 5, 119: 6, 120: 4, 170: 8, 180: 8, 186: 4, 238: 4, 355: 5, 426: 6, 452: 8, 464: 8, 466: 8, 467: 8, 544: 4, 545: 5, 550: 8, 552: 4, 608: 8, 610: 5, 643: 7, 705: 8, 725: 2, 740: 5, 800: 8, 835: 8, 836: 8, 849: 4, 869: 7, 870: 7, 871: 2, 896: 8, 900: 6, 902: 6, 905: 8, 911: 8, 916: 3, 918: 7, 921: 8, 922: 8, 933: 8, 944: 8, 945: 8, 951: 8, 955: 8, 956: 8, 979: 2, 998: 5, 999: 7, 1000: 8, 1001: 8, 1005: 2, 1008: 2, 1014: 8, 1017: 8, 1020: 8, 1041: 8, 1042: 8, 1043: 8, 1044: 8, 1056: 8, 1059: 1, 1114: 8, 1161: 8, 1162: 8, 1163: 8, 1176: 8, 1177: 8, 1178: 8, 1179: 8, 1180: 8, 1181: 8, 1182: 8, 1183: 8, 1189: 8, 1190: 8, 1191: 8, 1192: 8, 1196: 8, 1197: 8, 1198: 8, 1199: 8, 1206: 8, 1207: 8, 1212: 8, 1227: 8, 1235: 8, 1237: 8, 1264: 8, 1279: 8, 1408: 8, 1409: 8, 1410: 8, 1552: 8, 1553: 8, 1554: 8, 1556: 8, 1557: 8, 1561: 8, 1562: 8, 1568: 8, 1569: 8, 1570: 8, 1571: 8, 1572: 8, 1584: 8, 1589: 8, 1592: 8, 1593: 8, 1595: 8, 1599: 8, 1656: 8, 1728: 8, 1745: 8, 1779: 8, 1904: 8, 1912: 8, 1990: 8, 1998: 8
36: 8, 37: 8, 114: 5, 119: 6, 120: 4, 170: 8, 180: 8, 186: 4, 238: 4, 355: 5, 426: 6, 452: 8, 464: 8, 466: 8, 467: 8, 544: 4, 545: 5, 550: 8, 552: 4, 608: 8, 610: 5, 643: 7, 705: 8, 725: 2, 740: 5, 767:4, 800: 8, 835: 8, 836: 8, 849: 4, 869: 7, 870: 7, 871: 2, 896: 8, 900: 6, 902: 6, 905: 8, 911: 8, 916: 3, 918: 7, 921: 8, 922: 8, 933: 8, 944: 8, 945: 8, 951: 8, 955: 8, 956: 8, 979: 2, 998: 5, 999: 7, 1000: 8, 1001: 8, 1005: 2, 1008: 2, 1014: 8, 1017: 8, 1020: 8, 1041: 8, 1042: 8, 1043: 8, 1044: 8, 1056: 8, 1059: 1, 1114: 8, 1161: 8, 1162: 8, 1163: 8, 1176: 8, 1177: 8, 1178: 8, 1179: 8, 1180: 8, 1181: 8, 1182: 8, 1183: 8, 1189: 8, 1190: 8, 1191: 8, 1192: 8, 1196: 8, 1197: 8, 1198: 8, 1199: 8, 1206: 8, 1207: 8, 1212: 8, 1227: 8, 1235: 8, 1237: 8, 1264: 8, 1279: 8, 1408: 8, 1409: 8, 1410: 8, 1552: 8, 1553: 8, 1554: 8, 1556: 8, 1557: 8, 1561: 8, 1562: 8, 1568: 8, 1569: 8, 1570: 8, 1571: 8, 1572: 8, 1584: 8, 1589: 8, 1592: 8, 1593: 8, 1595: 8, 1599: 8, 1656: 8, 1728: 8, 1745: 8, 1779: 8, 1904: 8, 1912: 8, 1990: 8, 1998: 8
},
# 2018 Highlander Limited Platinum
{
36: 8, 37: 8, 114: 5, 119: 6, 120: 4, 170: 8, 180: 8, 186: 4, 238: 4, 355: 5, 426: 6, 452: 8, 464: 8, 466: 8, 467: 8, 544: 4, 545: 5, 550: 8, 552: 4, 608: 8, 610: 5, 643: 7, 705: 8, 725: 2, 740: 5, 800: 8, 835: 8, 836: 8, 849: 4, 869: 7, 870: 7, 871: 2, 896: 8, 900: 6, 902: 6, 905: 8, 911: 8, 916: 3, 918: 7, 921: 8, 922: 8, 933: 8, 944: 8, 945: 8, 951: 8, 955: 8, 956: 8, 979: 2, 998: 5, 999: 7, 1000: 8, 1001: 8, 1008: 2, 1014: 8, 1017: 8, 1020: 8, 1041: 8, 1042: 8, 1043: 8, 1044: 8, 1056: 8, 1059: 1, 1114: 8, 1161: 8, 1162: 8, 1163: 8, 1176: 8, 1177: 8, 1178: 8, 1179: 8, 1180: 8, 1181: 8, 1182: 8, 1183: 8, 1189: 8, 1190: 8, 1191: 8, 1192: 8, 1196: 8, 1197: 8, 1198: 8, 1199: 8, 1206: 8, 1207: 8, 1212: 8, 1227: 8, 1235: 8, 1237: 8, 1263: 8, 1279: 8, 1408: 8, 1409: 8, 1410: 8, 1552: 8, 1553: 8, 1554: 8, 1556: 8, 1557: 8, 1561: 8, 1562: 8, 1568: 8, 1569: 8, 1570: 8, 1571: 8, 1572: 8, 1584: 8, 1585: 8, 1589: 8, 1592: 8, 1593: 8, 1595: 8, 1599: 8, 1656: 8, 1728: 8, 1745: 8, 1779: 8, 1872: 8, 1880: 8, 1904: 8, 1912: 8, 1988: 8, 1990: 8, 1996: 8, 1998: 8, 2015: 8, 2016: 8, 2024: 8
36: 8, 37: 8, 114: 5, 119: 6, 120: 4, 170: 8, 180: 8, 186: 4, 238: 4, 355: 5, 426: 6, 452: 8, 464: 8, 466: 8, 467: 8, 544: 4, 545: 5, 550: 8, 552: 4, 608: 8, 610: 5, 643: 7, 705: 8, 725: 2, 740: 5, 767:4, 800: 8, 835: 8, 836: 8, 849: 4, 869: 7, 870: 7, 871: 2, 896: 8, 900: 6, 902: 6, 905: 8, 911: 8, 916: 3, 918: 7, 921: 8, 922: 8, 933: 8, 944: 8, 945: 8, 951: 8, 955: 8, 956: 8, 979: 2, 998: 5, 999: 7, 1000: 8, 1001: 8, 1008: 2, 1014: 8, 1017: 8, 1020: 8, 1041: 8, 1042: 8, 1043: 8, 1044: 8, 1056: 8, 1059: 1, 1114: 8, 1161: 8, 1162: 8, 1163: 8, 1176: 8, 1177: 8, 1178: 8, 1179: 8, 1180: 8, 1181: 8, 1182: 8, 1183: 8, 1189: 8, 1190: 8, 1191: 8, 1192: 8, 1196: 8, 1197: 8, 1198: 8, 1199: 8, 1206: 8, 1207: 8, 1212: 8, 1227: 8, 1235: 8, 1237: 8, 1263: 8, 1279: 8, 1408: 8, 1409: 8, 1410: 8, 1552: 8, 1553: 8, 1554: 8, 1556: 8, 1557: 8, 1561: 8, 1562: 8, 1568: 8, 1569: 8, 1570: 8, 1571: 8, 1572: 8, 1584: 8, 1585: 8, 1589: 8, 1592: 8, 1593: 8, 1595: 8, 1599: 8, 1656: 8, 1728: 8, 1745: 8, 1779: 8, 1872: 8, 1880: 8, 1904: 8, 1912: 8, 1988: 8, 1990: 8, 1996: 8, 1998: 8, 2015: 8, 2016: 8, 2024: 8
}],
CAR.HIGHLANDER_TSS2: [{
# 2020 highlander limited
36: 8, 37: 8, 114: 5, 119: 6, 120: 4, 170: 8, 180: 8, 186: 4, 355: 5, 401: 8, 426: 6, 452: 8, 464: 8, 466: 8, 467: 8, 544: 4, 550: 8, 552: 4, 562: 6, 565: 8, 608: 8, 610: 8, 643: 7, 658: 8, 705: 8, 728: 8, 740: 5, 761: 8, 764: 8, 765: 8, 767:4, 800: 8, 810: 2, 812: 8, 814: 8, 818: 8, 824: 8, 830: 7, 835: 8, 836: 8, 865: 8, 869: 7, 870: 7, 871: 2, 877: 8, 881: 8, 885: 8, 889: 8, 896: 8, 898: 8, 900: 6, 902: 6, 905: 8, 918: 8, 921: 8, 933: 8, 934: 8, 935: 8, 944: 8, 945: 8, 951: 8, 955: 8, 956: 8, 976: 1, 987: 8, 998: 5, 999: 7, 1000: 8, 1001: 8, 1002: 8, 1014: 8, 1017: 8, 1020: 8, 1041: 8, 1042: 8, 1044: 8, 1056: 8, 1059: 1, 1063: 8, 1076: 8, 1077: 8, 1082: 8, 1114: 8, 1161: 8, 1162: 8, 1163: 8, 1164: 8, 1165: 8, 1166: 8, 1167: 8, 1228: 8, 1235: 8, 1237: 8, 1264: 8, 1279: 8, 1541: 8, 1552: 8, 1553: 8, 1556: 8, 1557: 8, 1568: 8, 1570: 8, 1571: 8, 1572: 8, 1592: 8, 1594: 8, 1595: 8, 1649: 8, 1696: 8, 1775: 8, 1779: 8, 1786: 8, 1787: 8, 1788: 8, 1789: 8, 1808: 8, 1816: 8, 1904: 8, 1912: 8, 1952: 8, 1960: 8, 1990: 8, 1998: 8
}],
CAR.HIGHLANDERH: [{
36: 8, 37: 8, 170: 8, 180: 8, 296: 8, 426: 6, 452: 8, 466: 8, 467: 8, 550: 8, 552: 4, 560: 7, 581: 5, 608: 8, 610: 5, 643: 7, 713: 8, 740: 5, 800: 8, 835: 8, 836: 8, 849: 4, 869: 7, 870: 7, 871: 2, 896: 8, 897: 8, 900: 6, 902: 6, 905: 8, 911: 8, 916: 3, 918: 7, 921: 8, 933: 8, 944: 8, 945: 8, 950: 8, 951: 8, 953: 3, 955: 8, 956: 8, 979: 2, 998: 5, 999: 7, 1000: 8, 1001: 8, 1005: 2, 1014: 8, 1017: 8, 1020: 8, 1041: 8, 1042: 8, 1043: 8, 1044: 8, 1056: 8, 1059: 1, 1112: 8, 1114: 8, 1161: 8, 1162: 8, 1163: 8, 1176: 8, 1177: 8, 1178: 8, 1179: 8, 1180: 8, 1181: 8, 1184: 8, 1185: 8, 1186: 8, 1189: 8, 1190: 8, 1191: 8, 1192: 8, 1196: 8, 1197: 8, 1198: 8, 1199: 8, 1206: 8, 1212: 8, 1227: 8, 1232: 8, 1235: 8, 1237: 8, 1263: 8, 1264: 8, 1279: 8, 1552: 8, 1553: 8, 1554: 8, 1556: 8, 1557: 8, 1561: 8, 1562: 8, 1568: 8, 1569: 8, 1570: 8, 1571: 8, 1572: 8, 1584: 8, 1589: 8, 1592: 8, 1593: 8, 1595: 8, 1599: 8, 1656: 8, 1728: 8, 1745: 8, 1779: 8, 1904: 8, 1912: 8, 1990: 8, 1998: 8
36: 8, 37: 8, 170: 8, 180: 8, 296: 8, 426: 6, 452: 8, 466: 8, 467: 8, 550: 8, 552: 4, 560: 7, 581: 5, 608: 8, 610: 5, 643: 7, 713: 8, 740: 5, 767:4, 800: 8, 835: 8, 836: 8, 849: 4, 869: 7, 870: 7, 871: 2, 896: 8, 897: 8, 900: 6, 902: 6, 905: 8, 911: 8, 916: 3, 918: 7, 921: 8, 933: 8, 944: 8, 945: 8, 950: 8, 951: 8, 953: 3, 955: 8, 956: 8, 979: 2, 998: 5, 999: 7, 1000: 8, 1001: 8, 1005: 2, 1014: 8, 1017: 8, 1020: 8, 1041: 8, 1042: 8, 1043: 8, 1044: 8, 1056: 8, 1059: 1, 1112: 8, 1114: 8, 1161: 8, 1162: 8, 1163: 8, 1176: 8, 1177: 8, 1178: 8, 1179: 8, 1180: 8, 1181: 8, 1184: 8, 1185: 8, 1186: 8, 1189: 8, 1190: 8, 1191: 8, 1192: 8, 1196: 8, 1197: 8, 1198: 8, 1199: 8, 1206: 8, 1212: 8, 1227: 8, 1232: 8, 1235: 8, 1237: 8, 1263: 8, 1264: 8, 1279: 8, 1552: 8, 1553: 8, 1554: 8, 1556: 8, 1557: 8, 1561: 8, 1562: 8, 1568: 8, 1569: 8, 1570: 8, 1571: 8, 1572: 8, 1584: 8, 1589: 8, 1592: 8, 1593: 8, 1595: 8, 1599: 8, 1656: 8, 1728: 8, 1745: 8, 1779: 8, 1904: 8, 1912: 8, 1990: 8, 1998: 8
},
{
# 2019 Highlander Hybrid Limited Platinum
36: 8, 37: 8, 170: 8, 180: 8, 296: 8, 426: 6, 452: 8, 466: 8, 467: 8, 550: 8, 552: 4, 560: 7, 581: 5, 608: 8, 610: 5, 643: 7, 713: 8, 740: 5, 800: 8, 835: 8, 836: 8, 849: 4, 869: 7, 870: 7, 871: 2, 896: 8, 897: 8, 900: 6, 902: 6, 905: 8, 911: 8, 916: 3, 918: 7, 921: 8, 933: 8, 944: 8, 945: 8, 950: 8, 951: 8, 953: 3, 955: 8, 956: 8, 979: 2, 992: 8, 998: 5, 999: 7, 1000: 8, 1001: 8, 1014: 8, 1017: 8, 1020: 8, 1041: 8, 1042: 8, 1043: 8, 1044: 8, 1056: 8, 1057: 8, 1059: 1, 1076: 8, 1077: 8, 1112: 8, 1114: 8, 1161: 8, 1162: 8, 1163: 8, 1176: 8, 1177: 8, 1178: 8, 1179: 8, 1180: 8, 1181: 8, 1184: 8, 1185: 8, 1186: 8, 1189: 8, 1190: 8, 1191: 8, 1192: 8, 1196: 8, 1197: 8, 1198: 8, 1199: 8, 1206: 8, 1212: 8, 1227: 8, 1232: 8, 1235: 8, 1237: 8, 1263: 8, 1279: 8, 1552: 8, 1553: 8, 1554: 8, 1556: 8, 1557: 8, 1561: 8, 1562: 8, 1568: 8, 1569: 8, 1570: 8, 1571: 8, 1572: 8, 1584: 8, 1589: 8, 1592: 8, 1593: 8, 1595: 8, 1599: 8, 1656: 8, 1666: 8, 1667: 8, 1728: 8, 1745: 8, 1779: 8, 1904: 8, 1912: 8, 1990: 8, 1998: 8
36: 8, 37: 8, 170: 8, 180: 8, 296: 8, 426: 6, 452: 8, 466: 8, 467: 8, 550: 8, 552: 4, 560: 7, 581: 5, 608: 8, 610: 5, 643: 7, 713: 8, 740: 5, 767:4, 800: 8, 835: 8, 836: 8, 849: 4, 869: 7, 870: 7, 871: 2, 896: 8, 897: 8, 900: 6, 902: 6, 905: 8, 911: 8, 916: 3, 918: 7, 921: 8, 933: 8, 944: 8, 945: 8, 950: 8, 951: 8, 953: 3, 955: 8, 956: 8, 979: 2, 992: 8, 998: 5, 999: 7, 1000: 8, 1001: 8, 1014: 8, 1017: 8, 1020: 8, 1041: 8, 1042: 8, 1043: 8, 1044: 8, 1056: 8, 1057: 8, 1059: 1, 1076: 8, 1077: 8, 1112: 8, 1114: 8, 1161: 8, 1162: 8, 1163: 8, 1176: 8, 1177: 8, 1178: 8, 1179: 8, 1180: 8, 1181: 8, 1184: 8, 1185: 8, 1186: 8, 1189: 8, 1190: 8, 1191: 8, 1192: 8, 1196: 8, 1197: 8, 1198: 8, 1199: 8, 1206: 8, 1212: 8, 1227: 8, 1232: 8, 1235: 8, 1237: 8, 1263: 8, 1279: 8, 1552: 8, 1553: 8, 1554: 8, 1556: 8, 1557: 8, 1561: 8, 1562: 8, 1568: 8, 1569: 8, 1570: 8, 1571: 8, 1572: 8, 1584: 8, 1589: 8, 1592: 8, 1593: 8, 1595: 8, 1599: 8, 1656: 8, 1666: 8, 1667: 8, 1728: 8, 1745: 8, 1779: 8, 1904: 8, 1912: 8, 1990: 8, 1998: 8
}],
CAR.AVALON: [{
36: 8, 37: 8, 170: 8, 180: 8, 426: 6, 452: 8, 464: 8, 466: 8, 467: 8, 547: 8, 550: 8, 552: 4, 562: 6, 608: 8, 610: 5, 643: 7, 705: 8, 740: 5, 800: 8, 835: 8, 836: 8, 849: 4, 869: 7, 870: 7, 871: 2, 896: 8, 897: 8, 905: 8, 911: 1, 916: 2, 921: 8, 933: 6, 944: 8, 945: 8, 951: 8, 955: 8, 956: 8, 979: 2, 1005: 2, 1014: 8, 1017: 8, 1041: 8, 1042: 8, 1044: 8, 1056: 8, 1059: 1, 1114: 8, 1161: 8, 1162: 8, 1163: 8, 1176: 8, 1177: 8, 1178: 8, 1179: 8, 1180: 8, 1181: 8, 1190: 8, 1191: 8, 1192: 8, 1196: 8, 1200: 8, 1201: 8, 1202: 8, 1203: 8, 1206: 8, 1227: 8, 1235: 8, 1237: 8, 1264: 8, 1279: 8, 1552: 8, 1553: 8, 1554: 8, 1555: 8, 1556: 8, 1557: 8, 1558: 8, 1561: 8, 1562: 8, 1568: 8, 1569: 8, 1570: 8, 1571: 8, 1572: 8, 1584: 8, 1589: 8, 1592: 8, 1593: 8, 1595: 8, 1596: 8, 1597: 8, 1664: 8, 1728: 8, 1779: 8, 1904: 8, 1912: 8, 1990: 8, 1998: 8
36: 8, 37: 8, 170: 8, 180: 8, 426: 6, 452: 8, 464: 8, 466: 8, 467: 8, 547: 8, 550: 8, 552: 4, 562: 6, 608: 8, 610: 5, 643: 7, 705: 8, 740: 5, 767:4, 800: 8, 835: 8, 836: 8, 849: 4, 869: 7, 870: 7, 871: 2, 896: 8, 897: 8, 905: 8, 911: 1, 916: 2, 921: 8, 933: 6, 944: 8, 945: 8, 951: 8, 955: 8, 956: 8, 979: 2, 1005: 2, 1014: 8, 1017: 8, 1041: 8, 1042: 8, 1044: 8, 1056: 8, 1059: 1, 1114: 8, 1161: 8, 1162: 8, 1163: 8, 1176: 8, 1177: 8, 1178: 8, 1179: 8, 1180: 8, 1181: 8, 1190: 8, 1191: 8, 1192: 8, 1196: 8, 1200: 8, 1201: 8, 1202: 8, 1203: 8, 1206: 8, 1227: 8, 1235: 8, 1237: 8, 1264: 8, 1279: 8, 1552: 8, 1553: 8, 1554: 8, 1555: 8, 1556: 8, 1557: 8, 1558: 8, 1561: 8, 1562: 8, 1568: 8, 1569: 8, 1570: 8, 1571: 8, 1572: 8, 1584: 8, 1589: 8, 1592: 8, 1593: 8, 1595: 8, 1596: 8, 1597: 8, 1664: 8, 1728: 8, 1779: 8, 1904: 8, 1912: 8, 1990: 8, 1998: 8
}],
CAR.RAV4_TSS2: [
# LE
{
36: 8, 37: 8, 170: 8, 180: 8, 186: 4, 355: 5, 401: 8, 426: 6, 452: 8, 464: 8, 466: 8, 467: 8, 544: 4, 550: 8, 552: 4, 562: 6, 565: 8, 608: 8, 610: 8, 643: 7, 705: 8, 728: 8, 740: 5, 742: 8, 743: 8, 761: 8, 764: 8, 765: 8, 800: 8, 810: 2, 812: 8, 824: 8, 829: 2, 830: 7, 835: 8, 836: 8, 865: 8, 869: 7, 870: 7, 871: 2, 877: 8, 881: 8, 882: 8, 885: 8, 896: 8, 898: 8, 900: 6, 902: 6, 905: 8, 921: 8, 933: 8, 934: 8, 935: 8, 944: 8, 945: 8, 951: 8, 955: 8, 956: 8, 976: 1, 998: 5, 999: 7, 1000: 8, 1001: 8, 1002: 8, 1017: 8, 1020: 8, 1041: 8, 1042: 8, 1044: 8, 1056: 8, 1059: 1, 1063: 8, 1076: 8, 1077: 8,1114: 8, 1161: 8, 1162: 8, 1163: 8, 1164: 8, 1165: 8, 1166: 8, 1167: 8, 1172: 8, 1235: 8, 1279: 8, 1541: 8, 1552: 8, 1553:8, 1556: 8, 1557: 8, 1568: 8, 1570: 8, 1571: 8, 1572: 8, 1592: 8, 1594: 8, 1595: 8, 1649: 8, 1745: 8, 1775: 8, 1779: 8, 1786: 8, 1787: 8, 1788: 8, 1789: 8, 1904: 8, 1912: 8, 1990: 8, 1998: 8
36: 8, 37: 8, 170: 8, 180: 8, 186: 4, 355: 5, 401: 8, 426: 6, 452: 8, 464: 8, 466: 8, 467: 8, 544: 4, 550: 8, 552: 4, 562: 6, 565: 8, 608: 8, 610: 8, 643: 7, 705: 8, 728: 8, 740: 5, 742: 8, 743: 8, 761: 8, 764: 8, 765: 8, 767:4, 800: 8, 810: 2, 812: 8, 824: 8, 829: 2, 830: 7, 835: 8, 836: 8, 865: 8, 869: 7, 870: 7, 871: 2, 877: 8, 881: 8, 882: 8, 885: 8, 896: 8, 898: 8, 900: 6, 902: 6, 905: 8, 921: 8, 933: 8, 934: 8, 935: 8, 944: 8, 945: 8, 951: 8, 955: 8, 956: 8, 976: 1, 998: 5, 999: 7, 1000: 8, 1001: 8, 1002: 8, 1017: 8, 1020: 8, 1041: 8, 1042: 8, 1044: 8, 1056: 8, 1059: 1, 1063: 8, 1076: 8, 1077: 8,1114: 8, 1161: 8, 1162: 8, 1163: 8, 1164: 8, 1165: 8, 1166: 8, 1167: 8, 1172: 8, 1235: 8, 1279: 8, 1541: 8, 1552: 8, 1553:8, 1556: 8, 1557: 8, 1568: 8, 1570: 8, 1571: 8, 1572: 8, 1592: 8, 1594: 8, 1595: 8, 1649: 8, 1745: 8, 1775: 8, 1779: 8, 1786: 8, 1787: 8, 1788: 8, 1789: 8, 1904: 8, 1912: 8, 1990: 8, 1998: 8
},
# XLE, Limited, and AWD
{
36: 8, 37: 8, 170: 8, 180: 8, 186: 4, 401: 8, 426: 6, 452: 8, 464: 8, 466: 8, 467: 8, 544: 4, 550: 8, 552: 4, 562: 6, 565: 8, 608: 8, 610: 8, 643: 7, 658: 8, 705: 8, 728: 8, 740: 5, 742: 8, 743: 8, 761: 8, 764: 8, 765: 8, 800: 8, 810: 2, 812: 8, 814: 8, 818: 8, 822: 8, 824: 8, 829: 2, 830: 7, 835: 8, 836: 8, 865: 8, 869: 7, 870: 7, 871: 2, 877: 8, 881: 8, 882: 8, 885: 8, 889: 8, 891: 8, 896: 8, 898: 8, 900: 6, 902: 6, 905: 8, 918: 8, 921: 8, 933: 8, 934: 8, 935: 8, 944: 8, 945: 8, 951: 8, 955: 8, 956: 8, 976: 1, 987: 8, 998: 5, 999: 7, 1000: 8, 1001: 8, 1002: 8, 1014: 8, 1017: 8, 1020: 8, 1041: 8, 1042: 8, 1044: 8, 1056: 8, 1059: 1, 1063: 8, 1076: 8, 1077: 8, 1082: 8, 1084: 8, 1085: 8, 1086: 8, 1114: 8, 1132: 8, 1161: 8, 1162: 8, 1163: 8, 1164: 8, 1165: 8, 1166: 8, 1167: 8, 1172: 8, 1228: 8, 1235: 8, 1237: 8, 1263: 8, 1264: 8, 1279: 8, 1541: 8, 1552: 8, 1553: 8, 1556: 8, 1557: 8, 1568: 8, 1570: 8, 1571: 8, 1572: 8, 1592: 8, 1594: 8, 1595: 8, 1649: 8, 1696: 8, 1745: 8, 1775: 8, 1779: 8, 1786: 8, 1787: 8, 1788: 8, 1789: 8, 1904: 8, 1912: 8, 1990: 8, 1998: 8, 2015: 8, 2016: 8, 2024: 8
36: 8, 37: 8, 170: 8, 180: 8, 186: 4, 401: 8, 426: 6, 452: 8, 464: 8, 466: 8, 467: 8, 544: 4, 550: 8, 552: 4, 562: 6, 565: 8, 608: 8, 610: 8, 643: 7, 658: 8, 705: 8, 728: 8, 740: 5, 742: 8, 743: 8, 761: 8, 764: 8, 765: 8, 767:4, 800: 8, 810: 2, 812: 8, 814: 8, 818: 8, 822: 8, 824: 8, 829: 2, 830: 7, 835: 8, 836: 8, 865: 8, 869: 7, 870: 7, 871: 2, 877: 8, 881: 8, 882: 8, 885: 8, 889: 8, 891: 8, 896: 8, 898: 8, 900: 6, 902: 6, 905: 8, 918: 8, 921: 8, 933: 8, 934: 8, 935: 8, 944: 8, 945: 8, 951: 8, 955: 8, 956: 8, 976: 1, 987: 8, 998: 5, 999: 7, 1000: 8, 1001: 8, 1002: 8, 1014: 8, 1017: 8, 1020: 8, 1041: 8, 1042: 8, 1044: 8, 1056: 8, 1059: 1, 1063: 8, 1076: 8, 1077: 8, 1082: 8, 1084: 8, 1085: 8, 1086: 8, 1114: 8, 1132: 8, 1161: 8, 1162: 8, 1163: 8, 1164: 8, 1165: 8, 1166: 8, 1167: 8, 1172: 8, 1228: 8, 1235: 8, 1237: 8, 1263: 8, 1264: 8, 1279: 8, 1541: 8, 1552: 8, 1553: 8, 1556: 8, 1557: 8, 1568: 8, 1570: 8, 1571: 8, 1572: 8, 1592: 8, 1594: 8, 1595: 8, 1649: 8, 1696: 8, 1745: 8, 1775: 8, 1779: 8, 1786: 8, 1787: 8, 1788: 8, 1789: 8, 1904: 8, 1912: 8, 1990: 8, 1998: 8, 2015: 8, 2016: 8, 2024: 8
}],
CAR.COROLLA_TSS2: [
# hatch 2019+ and sedan 2020+
{
36: 8, 37: 8, 114: 5, 170: 8, 180: 8, 186: 4, 401: 8, 426: 6, 452: 8, 464: 8, 466: 8, 467: 8, 544: 4, 550: 8, 552: 4, 562: 6, 608: 8, 610: 8, 643: 7, 705: 8, 728: 8, 740: 5, 742: 8, 743: 8, 761: 8, 764: 8, 765: 8, 800: 8, 810: 2, 812: 8, 824: 8, 829: 2, 830: 7, 835: 8, 836: 8, 865: 8, 869: 7, 870: 7, 871: 2, 877: 8, 881: 8, 896: 8, 898: 8, 900: 6, 902: 6, 905: 8, 913: 8, 921: 8, 933: 8, 934: 8, 935: 8, 944: 8, 945: 8, 951: 8, 955: 8, 956: 8, 976: 1, 998: 5, 999: 7, 1000: 8, 1001: 8, 1002: 8, 1014: 8, 1017: 8, 1020: 8, 1041: 8, 1042: 8, 1044: 8, 1056: 8, 1059: 1, 1076: 8, 1077: 8, 1114: 8, 1161: 8, 1162: 8, 1163: 8, 1164: 8, 1165: 8, 1166: 8, 1167: 8, 1172: 8, 1235: 8, 1237: 8, 1279: 8, 1541: 8, 1552: 8, 1553: 8, 1556: 8, 1557: 8, 1568: 8, 1570: 8, 1571: 8, 1572: 8, 1592: 8, 1595: 8, 1649: 8, 1745: 8, 1775: 8, 1779: 8, 1786: 8, 1787: 8, 1788: 8, 1789: 8, 1808: 8, 1809: 8, 1816: 8, 1817: 8, 1840: 8, 1848: 8, 1904: 8, 1912: 8, 1940: 8, 1941: 8, 1948: 8, 1949: 8, 1952: 8, 1960: 8, 1981: 8, 1986: 8, 1990: 8, 1994: 8, 1998: 8, 2004: 8
36: 8, 37: 8, 114: 5, 170: 8, 180: 8, 186: 4, 401: 8, 426: 6, 452: 8, 464: 8, 466: 8, 467: 8, 544: 4, 550: 8, 552: 4, 562: 6, 608: 8, 610: 8, 643: 7, 705: 8, 728: 8, 740: 5, 742: 8, 743: 8, 761: 8, 764: 8, 765: 8, 767:4, 800: 8, 810: 2, 812: 8, 824: 8, 829: 2, 830: 7, 835: 8, 836: 8, 865: 8, 869: 7, 870: 7, 871: 2, 877: 8, 881: 8, 896: 8, 898: 8, 900: 6, 902: 6, 905: 8, 913: 8, 921: 8, 933: 8, 934: 8, 935: 8, 944: 8, 945: 8, 951: 8, 955: 8, 956: 8, 976: 1, 998: 5, 999: 7, 1000: 8, 1001: 8, 1002: 8, 1014: 8, 1017: 8, 1020: 8, 1041: 8, 1042: 8, 1044: 8, 1056: 8, 1059: 1, 1076: 8, 1077: 8, 1114: 8, 1161: 8, 1162: 8, 1163: 8, 1164: 8, 1165: 8, 1166: 8, 1167: 8, 1172: 8, 1235: 8, 1237: 8, 1279: 8, 1541: 8, 1552: 8, 1553: 8, 1556: 8, 1557: 8, 1568: 8, 1570: 8, 1571: 8, 1572: 8, 1592: 8, 1595: 8, 1649: 8, 1745: 8, 1775: 8, 1779: 8, 1786: 8, 1787: 8, 1788: 8, 1789: 8, 1808: 8, 1809: 8, 1816: 8, 1817: 8, 1840: 8, 1848: 8, 1904: 8, 1912: 8, 1940: 8, 1941: 8, 1948: 8, 1949: 8, 1952: 8, 1960: 8, 1981: 8, 1986: 8, 1990: 8, 1994: 8, 1998: 8, 2004: 8
}],
CAR.COROLLAH_TSS2: [
# 2019 Taiwan Altis Hybrid
{
36: 8, 37: 8, 166: 8, 170: 8, 180: 8, 295: 8, 296: 8, 401: 8, 426: 6, 452: 8, 466: 8, 467: 8, 550: 8, 552: 4, 560: 7, 562: 6, 581: 5, 608: 8, 610: 8, 643: 7, 713: 8, 728: 8, 740: 5, 742: 8, 743: 8, 761: 8, 765: 8, 800: 8, 810: 2, 829: 2, 830: 7, 835: 8, 836: 8, 865: 8, 869: 7, 870: 7, 871: 2, 877: 8, 881: 8, 885: 8, 896: 8, 898: 8, 918: 7, 921: 8, 944: 8, 945: 8, 950: 8, 951: 8, 953: 8, 955: 8, 956: 8, 971: 7, 975: 5, 987: 8, 993: 8, 1002: 8, 1014: 8, 1017: 8, 1020: 8, 1041: 8, 1042: 8, 1044: 8, 1056: 8, 1057: 8, 1059: 1, 1071: 8, 1082: 8, 1112: 8, 1114: 8, 1161: 8, 1162: 8, 1163: 8, 1172: 8, 1235: 8, 1237: 8, 1279: 8, 1541: 8, 1552: 8, 1553: 8, 1556: 8, 1557: 8, 1568: 8, 1570: 8, 1571: 8, 1572: 8, 1592: 8, 1594: 8, 1595: 8, 1745: 8, 1775: 8, 1779: 8
36: 8, 37: 8, 166: 8, 170: 8, 180: 8, 295: 8, 296: 8, 401: 8, 426: 6, 452: 8, 466: 8, 467: 8, 550: 8, 552: 4, 560: 7, 562: 6, 581: 5, 608: 8, 610: 8, 643: 7, 713: 8, 728: 8, 740: 5, 742: 8, 743: 8, 761: 8, 765: 8, 767:4, 800: 8, 810: 2, 829: 2, 830: 7, 835: 8, 836: 8, 865: 8, 869: 7, 870: 7, 871: 2, 877: 8, 881: 8, 885: 8, 896: 8, 898: 8, 918: 7, 921: 8, 944: 8, 945: 8, 950: 8, 951: 8, 953: 8, 955: 8, 956: 8, 971: 7, 975: 5, 987: 8, 993: 8, 1002: 8, 1014: 8, 1017: 8, 1020: 8, 1041: 8, 1042: 8, 1044: 8, 1056: 8, 1057: 8, 1059: 1, 1071: 8, 1082: 8, 1112: 8, 1114: 8, 1161: 8, 1162: 8, 1163: 8, 1172: 8, 1235: 8, 1237: 8, 1279: 8, 1541: 8, 1552: 8, 1553: 8, 1556: 8, 1557: 8, 1568: 8, 1570: 8, 1571: 8, 1572: 8, 1592: 8, 1594: 8, 1595: 8, 1745: 8, 1775: 8, 1779: 8
},
# 2019 Chinese Levin Hybrid
{
36: 8, 37: 8, 166: 8, 170: 8, 180: 8, 295: 8, 296: 8, 401: 8, 426: 6, 452: 8, 466: 8, 467: 8, 550: 8, 552: 4, 560: 7, 562: 6, 581: 5, 608: 8, 610: 8, 643: 7, 713: 8, 728: 8, 740: 5, 742: 8, 743: 8, 761: 8, 765: 8, 800: 8, 810: 2, 812: 8, 829: 2, 830: 7, 835: 8, 836: 8, 865: 8, 869: 7, 870: 7, 871: 2, 877: 8, 881: 8, 885: 8, 896: 8, 898: 8, 921: 8, 944: 8, 945: 8, 950: 8, 951: 8, 953: 8, 955: 8, 956: 8, 971: 7, 975: 5, 993: 8, 1002: 8, 1017: 8, 1020: 8, 1041: 8, 1042: 8, 1044: 8, 1056: 8, 1057: 8, 1059: 1, 1071: 8, 1114: 8, 1161: 8, 1162: 8, 1163: 8, 1172: 8, 1235: 8, 1279: 8, 1541: 8, 1552: 8, 1553: 8, 1556: 8, 1557: 8, 1568: 8, 1570: 8, 1571: 8, 1572: 8, 1592: 8, 1594: 8, 1595: 8, 1600: 8, 1649: 8, 1745: 8, 1775: 8, 1779: 8
36: 8, 37: 8, 166: 8, 170: 8, 180: 8, 295: 8, 296: 8, 401: 8, 426: 6, 452: 8, 466: 8, 467: 8, 550: 8, 552: 4, 560: 7, 562: 6, 581: 5, 608: 8, 610: 8, 643: 7, 713: 8, 728: 8, 740: 5, 742: 8, 743: 8, 761: 8, 765: 8, 767:4, 800: 8, 810: 2, 812: 8, 829: 2, 830: 7, 835: 8, 836: 8, 865: 8, 869: 7, 870: 7, 871: 2, 877: 8, 881: 8, 885: 8, 896: 8, 898: 8, 921: 8, 944: 8, 945: 8, 950: 8, 951: 8, 953: 8, 955: 8, 956: 8, 971: 7, 975: 5, 993: 8, 1002: 8, 1017: 8, 1020: 8, 1041: 8, 1042: 8, 1044: 8, 1056: 8, 1057: 8, 1059: 1, 1071: 8, 1114: 8, 1161: 8, 1162: 8, 1163: 8, 1172: 8, 1235: 8, 1279: 8, 1541: 8, 1552: 8, 1553: 8, 1556: 8, 1557: 8, 1568: 8, 1570: 8, 1571: 8, 1572: 8, 1592: 8, 1594: 8, 1595: 8, 1600: 8, 1649: 8, 1745: 8, 1775: 8, 1779: 8
}
],
CAR.LEXUS_ES_TSS2: [{
36: 8, 37: 8, 114: 5, 119: 6, 120: 4, 170: 8, 180: 8, 186: 4, 401: 8, 426: 6, 452: 8, 464: 8, 466: 8, 467: 8, 544: 4, 550: 8, 552: 4, 562: 6, 608: 8, 610: 8, 643: 7, 658: 8, 705: 8, 728: 8, 740: 5, 761: 8, 764: 8, 765: 8, 800: 8, 810: 2, 812: 8, 814: 8, 818: 8, 824: 8, 830: 7, 835: 8, 836: 8, 865: 8, 869: 7, 870: 7, 871: 2, 877: 8, 881: 8, 882: 8, 885: 8, 889: 8, 896: 8, 898: 8, 900: 6, 902: 6, 905: 8, 913: 8, 918: 8, 921: 8, 933: 8, 934: 8, 935: 8, 944: 8, 945: 8, 951: 8, 955: 8, 956: 8, 976: 1, 987: 8, 998: 5, 999: 7, 1000: 8, 1001: 8, 1002: 8, 1014: 8, 1017: 8, 1020: 8, 1041: 8, 1042: 8, 1044: 8, 1056: 8, 1059: 1, 1076: 8, 1077: 8, 1082: 8, 1114: 8, 1161: 8, 1162: 8, 1163: 8, 1164: 8, 1165: 8, 1166: 8, 1167: 8, 1172: 8, 1228: 8, 1235: 8, 1237: 8, 1264: 8, 1279: 8, 1541: 8, 1552: 8, 1553: 8, 1556: 8, 1557: 8, 1568: 8, 1570: 8, 1571: 8, 1572: 8, 1575: 8, 1592: 8, 1594: 8, 1595: 8, 1649: 8, 1696: 8, 1775: 8, 1777: 8, 1779: 8, 1786: 8, 1787: 8, 1788: 8, 1789: 8, 1904: 8, 1912: 8
36: 8, 37: 8, 114: 5, 119: 6, 120: 4, 170: 8, 180: 8, 186: 4, 401: 8, 426: 6, 452: 8, 464: 8, 466: 8, 467: 8, 544: 4, 550: 8, 552: 4, 562: 6, 608: 8, 610: 8, 643: 7, 658: 8, 705: 8, 728: 8, 740: 5, 761: 8, 764: 8, 765: 8, 767:4, 800: 8, 810: 2, 812: 8, 814: 8, 818: 8, 824: 8, 830: 7, 835: 8, 836: 8, 865: 8, 869: 7, 870: 7, 871: 2, 877: 8, 881: 8, 882: 8, 885: 8, 889: 8, 896: 8, 898: 8, 900: 6, 902: 6, 905: 8, 913: 8, 918: 8, 921: 8, 933: 8, 934: 8, 935: 8, 944: 8, 945: 8, 951: 8, 955: 8, 956: 8, 976: 1, 987: 8, 998: 5, 999: 7, 1000: 8, 1001: 8, 1002: 8, 1014: 8, 1017: 8, 1020: 8, 1041: 8, 1042: 8, 1044: 8, 1056: 8, 1059: 1, 1076: 8, 1077: 8, 1082: 8, 1114: 8, 1161: 8, 1162: 8, 1163: 8, 1164: 8, 1165: 8, 1166: 8, 1167: 8, 1172: 8, 1228: 8, 1235: 8, 1237: 8, 1264: 8, 1279: 8, 1541: 8, 1552: 8, 1553: 8, 1556: 8, 1557: 8, 1568: 8, 1570: 8, 1571: 8, 1572: 8, 1575: 8, 1592: 8, 1594: 8, 1595: 8, 1649: 8, 1696: 8, 1775: 8, 1777: 8, 1779: 8, 1786: 8, 1787: 8, 1788: 8, 1789: 8, 1904: 8, 1912: 8, 1990: 8, 1998: 8,
}],
CAR.LEXUS_ESH_TSS2: [
{
36: 8, 37: 8, 166: 8, 170: 8, 180: 8, 295: 8, 296: 8, 401: 8, 426: 6, 452: 8, 466: 8, 467: 8, 550: 8, 552: 4, 560: 7, 562: 6, 581: 5, 608: 8, 610: 8, 643: 7, 658: 8, 713: 8, 728: 8, 740: 5, 742: 8, 743: 8, 744: 8, 761: 8, 764: 8, 765: 8, 800: 8, 810: 2, 812: 8, 814: 8, 818: 8, 824: 8, 829: 2, 830: 7, 835: 8, 836: 8, 863: 8, 865: 8, 869: 7, 870: 7, 871: 2, 877: 8, 881: 8, 882: 8, 885: 8, 889: 8, 896: 8, 898: 8, 900: 6, 902: 6, 905: 8, 913: 8, 918: 8, 921: 8, 933: 8, 934: 8, 935: 8, 944: 8, 945: 8, 950: 8, 951: 8, 953: 8, 955: 8, 956: 8, 971: 7, 975: 5, 987: 8, 993: 8, 998: 5, 999: 7, 1000: 8, 1001: 8, 1002: 8, 1017: 8, 1020: 8, 1041: 8, 1042: 8, 1056: 8, 1057: 8, 1059: 1, 1071: 8, 1076: 8, 1077: 8, 1082: 8, 1084: 8, 1085: 8, 1086: 8, 1114: 8, 1132: 8, 1161: 8, 1162: 8, 1163: 8, 1164: 8, 1165: 8, 1166: 8, 1167: 8, 1172: 8, 1228: 8, 1235: 8, 1264: 8, 1279: 8, 1541: 8, 1552: 8, 1553: 8, 1556: 8, 1557: 8, 1568: 8, 1570: 8, 1571: 8, 1572: 8, 1575: 8, 1592: 8, 1594: 8, 1595: 8, 1649: 8, 1696: 8, 1775: 8, 1777: 8, 1779: 8, 1786: 8, 1787: 8, 1788: 8, 1789: 8, 1904: 8, 1912: 8, 1990: 8, 1998: 8
36: 8, 37: 8, 166: 8, 170: 8, 180: 8, 295: 8, 296: 8, 401: 8, 426: 6, 452: 8, 466: 8, 467: 8, 550: 8, 552: 4, 560: 7, 562: 6, 581: 5, 608: 8, 610: 8, 643: 7, 658: 8, 713: 8, 728: 8, 740: 5, 742: 8, 743: 8, 744: 8, 761: 8, 764: 8, 765: 8, 767:4, 800: 8, 810: 2, 812: 8, 814: 8, 818: 8, 824: 8, 829: 2, 830: 7, 835: 8, 836: 8, 863: 8, 865: 8, 869: 7, 870: 7, 871: 2, 877: 8, 881: 8, 882: 8, 885: 8, 889: 8, 896: 8, 898: 8, 900: 6, 902: 6, 905: 8, 913: 8, 918: 8, 921: 8, 933: 8, 934: 8, 935: 8, 944: 8, 945: 8, 950: 8, 951: 8, 953: 8, 955: 8, 956: 8, 971: 7, 975: 5, 987: 8, 993: 8, 998: 5, 999: 7, 1000: 8, 1001: 8, 1002: 8, 1017: 8, 1020: 8, 1041: 8, 1042: 8, 1056: 8, 1057: 8, 1059: 1, 1071: 8, 1076: 8, 1077: 8, 1082: 8, 1084: 8, 1085: 8, 1086: 8, 1114: 8, 1132: 8, 1161: 8, 1162: 8, 1163: 8, 1164: 8, 1165: 8, 1166: 8, 1167: 8, 1172: 8, 1228: 8, 1235: 8, 1264: 8, 1279: 8, 1541: 8, 1552: 8, 1553: 8, 1556: 8, 1557: 8, 1568: 8, 1570: 8, 1571: 8, 1572: 8, 1575: 8, 1592: 8, 1594: 8, 1595: 8, 1649: 8, 1696: 8, 1775: 8, 1777: 8, 1779: 8, 1786: 8, 1787: 8, 1788: 8, 1789: 8, 1904: 8, 1912: 8, 1990: 8, 1998: 8
}],
CAR.SIENNA: [
{
36: 8, 37: 8, 114: 5, 119: 6, 120: 4, 170: 8, 180: 8, 186: 4, 426: 6, 452: 8, 464: 8, 466: 8, 467: 8, 544: 4, 545: 5, 548: 8, 550: 8, 552: 4, 562: 4, 608: 8, 610: 5, 643: 7, 705: 8, 725: 2, 740: 5, 764: 8, 800: 8, 824: 8, 835: 8, 836: 8, 849: 4, 869: 7, 870: 7, 871: 2, 888: 8, 896: 8, 900: 6, 902: 6, 905: 8, 911: 8, 916: 1, 918: 7, 921: 8, 933: 8, 944: 6, 945: 8, 951: 8, 955: 8, 956: 8, 979: 2, 992: 8, 998: 5, 999: 7, 1000: 8, 1001: 8, 1002: 8, 1008: 2, 1014: 8, 1017: 8, 1041: 8, 1042: 8, 1043: 8, 1056: 8, 1059: 1, 1076: 8, 1077: 8, 1114: 8, 1160: 8, 1161: 8, 1162: 8, 1163: 8, 1164: 8, 1165: 8, 1166: 8, 1167: 8, 1176: 8, 1177: 8, 1178: 8, 1179: 8, 1180: 8, 1181: 8, 1182: 8, 1183: 8, 1191: 8, 1192: 8, 1196: 8, 1197: 8, 1198: 8, 1199: 8, 1200: 8, 1201: 8, 1202: 8, 1203: 8, 1212: 8, 1227: 8, 1228: 8, 1235: 8, 1237: 8, 1279: 8, 1552: 8, 1553: 8, 1555: 8, 1556: 8, 1557: 8, 1561: 8, 1562: 8, 1568: 8, 1569: 8, 1570: 8, 1571: 8, 1572: 8, 1584: 8, 1589: 8, 1592: 8, 1593: 8, 1595: 8, 1656: 8, 1664: 8, 1666: 8, 1667: 8, 1728: 8, 1745: 8, 1779: 8, 1904: 8, 1912: 8, 1990: 8, 1998: 8
36: 8, 37: 8, 114: 5, 119: 6, 120: 4, 170: 8, 180: 8, 186: 4, 426: 6, 452: 8, 464: 8, 466: 8, 467: 8, 544: 4, 545: 5, 548: 8, 550: 8, 552: 4, 562: 4, 608: 8, 610: 5, 643: 7, 705: 8, 725: 2, 740: 5, 764: 8, 767:4, 800: 8, 824: 8, 835: 8, 836: 8, 849: 4, 869: 7, 870: 7, 871: 2, 888: 8, 896: 8, 900: 6, 902: 6, 905: 8, 911: 8, 916: 1, 918: 7, 921: 8, 933: 8, 944: 6, 945: 8, 951: 8, 955: 8, 956: 8, 979: 2, 992: 8, 998: 5, 999: 7, 1000: 8, 1001: 8, 1002: 8, 1008: 2, 1014: 8, 1017: 8, 1041: 8, 1042: 8, 1043: 8, 1056: 8, 1059: 1, 1076: 8, 1077: 8, 1114: 8, 1160: 8, 1161: 8, 1162: 8, 1163: 8, 1164: 8, 1165: 8, 1166: 8, 1167: 8, 1176: 8, 1177: 8, 1178: 8, 1179: 8, 1180: 8, 1181: 8, 1182: 8, 1183: 8, 1191: 8, 1192: 8, 1196: 8, 1197: 8, 1198: 8, 1199: 8, 1200: 8, 1201: 8, 1202: 8, 1203: 8, 1212: 8, 1227: 8, 1228: 8, 1235: 8, 1237: 8, 1279: 8, 1552: 8, 1553: 8, 1555: 8, 1556: 8, 1557: 8, 1561: 8, 1562: 8, 1568: 8, 1569: 8, 1570: 8, 1571: 8, 1572: 8, 1584: 8, 1589: 8, 1592: 8, 1593: 8, 1595: 8, 1656: 8, 1664: 8, 1666: 8, 1667: 8, 1728: 8, 1745: 8, 1779: 8, 1904: 8, 1912: 8, 1990: 8, 1998: 8
},
# XLE AWD 2018
{
36: 8, 37: 8, 114: 5, 119: 6, 120: 4, 170: 8, 180: 8, 186: 4, 238: 4, 426: 6, 452: 8, 464: 8, 466: 8, 467: 8, 544: 4, 545: 5, 548: 8, 550: 8, 552: 4, 562: 4, 608: 8, 610: 5, 643: 7, 705: 8, 725: 2, 740: 5, 764: 8, 800: 8, 824: 8, 835: 8, 836: 8, 849: 4, 869: 7, 870: 7, 871: 2, 896: 8, 900: 6, 902: 6, 905: 8, 911: 8, 916: 1, 921: 8, 933: 8, 944: 6, 945: 8, 951: 8, 955: 8, 956: 8, 979: 2, 992: 8, 998: 5, 999: 7, 1000: 8, 1001: 8, 1002: 8, 1008: 2, 1014: 8, 1017: 8, 1041: 8, 1042: 8, 1043: 8, 1056: 8, 1059: 1, 1076: 8, 1077: 8, 1114: 8, 1160: 8, 1161: 8, 1162: 8, 1163: 8, 1164: 8, 1165: 8, 1166: 8, 1167: 8, 1176: 8, 1177: 8, 1178: 8, 1179: 8, 1180: 8, 1181: 8, 1182: 8, 1183: 8, 1191: 8, 1192: 8, 1196: 8, 1197: 8, 1198: 8, 1199: 8, 1200: 8, 1201: 8, 1202: 8, 1203: 8, 1212: 8, 1227: 8, 1235: 8, 1237: 8, 1279: 8, 1552: 8, 1553: 8, 1555: 8, 1556: 8, 1557: 8, 1561: 8, 1562: 8, 1568: 8, 1569: 8, 1570: 8, 1571: 8, 1572: 8, 1584: 8, 1589: 8, 1592: 8, 1593: 8, 1595: 8, 1656: 8, 1664: 8, 1666: 8, 1667: 8, 1728: 8, 1745: 8, 1779: 8, 1904: 8, 1912: 8, 1990: 8, 1998: 8
36: 8, 37: 8, 114: 5, 119: 6, 120: 4, 170: 8, 180: 8, 186: 4, 238: 4, 426: 6, 452: 8, 464: 8, 466: 8, 467: 8, 544: 4, 545: 5, 548: 8, 550: 8, 552: 4, 562: 4, 608: 8, 610: 5, 643: 7, 705: 8, 725: 2, 740: 5, 764: 8, 767:4, 800: 8, 824: 8, 835: 8, 836: 8, 849: 4, 869: 7, 870: 7, 871: 2, 896: 8, 900: 6, 902: 6, 905: 8, 911: 8, 916: 1, 921: 8, 933: 8, 944: 6, 945: 8, 951: 8, 955: 8, 956: 8, 979: 2, 992: 8, 998: 5, 999: 7, 1000: 8, 1001: 8, 1002: 8, 1008: 2, 1014: 8, 1017: 8, 1041: 8, 1042: 8, 1043: 8, 1056: 8, 1059: 1, 1076: 8, 1077: 8, 1114: 8, 1160: 8, 1161: 8, 1162: 8, 1163: 8, 1164: 8, 1165: 8, 1166: 8, 1167: 8, 1176: 8, 1177: 8, 1178: 8, 1179: 8, 1180: 8, 1181: 8, 1182: 8, 1183: 8, 1191: 8, 1192: 8, 1196: 8, 1197: 8, 1198: 8, 1199: 8, 1200: 8, 1201: 8, 1202: 8, 1203: 8, 1212: 8, 1227: 8, 1235: 8, 1237: 8, 1279: 8, 1552: 8, 1553: 8, 1555: 8, 1556: 8, 1557: 8, 1561: 8, 1562: 8, 1568: 8, 1569: 8, 1570: 8, 1571: 8, 1572: 8, 1584: 8, 1589: 8, 1592: 8, 1593: 8, 1595: 8, 1656: 8, 1664: 8, 1666: 8, 1667: 8, 1728: 8, 1745: 8, 1779: 8, 1904: 8, 1912: 8, 1990: 8, 1998: 8
}],
CAR.LEXUS_IS: [
# IS300 2018
{
36: 8, 37: 8, 114: 5, 119: 6, 120: 4, 170: 8, 180: 8, 186: 4, 238: 4, 400: 6, 426: 6, 452: 8, 464: 8, 466: 8, 467: 5, 544: 4, 550: 8, 552: 4, 608: 8, 610: 5, 643: 7, 705: 8, 740: 5, 800: 8, 836: 8, 845: 5, 849: 4, 869: 7, 870: 7, 871: 2, 896: 8, 897: 8, 900: 6, 902: 6, 905: 8, 911: 8, 913: 8, 916: 3, 918: 7, 921: 8, 933: 8, 944: 8, 945: 8, 951: 8, 955: 8, 956: 8, 979: 2, 992: 8, 998: 5, 999: 7, 1000: 8, 1001: 8, 1005: 2, 1008: 2, 1009: 8, 1014: 8, 1017: 8, 1020: 8, 1041: 8, 1042: 8, 1043: 8, 1044: 8, 1056: 8, 1059: 1, 1112: 8, 1114: 8, 1161: 8, 1162: 8, 1163: 8, 1164: 8, 1165: 8, 1166: 8, 1167: 8, 1168: 1, 1176: 8, 1177: 8, 1178: 8, 1179: 8, 1180: 8, 1181: 8, 1182: 8, 1183: 8, 1184: 8, 1185: 8, 1186: 8, 1187: 8, 1189: 8, 1190: 8, 1191: 8, 1192: 8, 1196: 8, 1197: 8, 1198: 8, 1199: 8, 1206: 8, 1208: 8, 1212: 8, 1227: 8, 1235: 8, 1237: 8, 1279: 8, 1408: 8, 1409: 8, 1410: 8, 1552: 8, 1553: 8, 1554: 8, 1555: 8, 1556: 8, 1557: 8, 1561: 8, 1568: 8, 1569: 8, 1570: 8, 1571: 8, 1572: 8, 1575: 8, 1584: 8, 1589: 8, 1590: 8, 1592: 8, 1593: 8, 1595: 8, 1599: 8, 1648: 8, 1666: 8, 1667: 8, 1728: 8, 1745: 8, 1779: 8, 1904: 8, 1912: 8, 1990: 8, 1998: 8
36: 8, 37: 8, 114: 5, 119: 6, 120: 4, 170: 8, 180: 8, 186: 4, 238: 4, 400: 6, 426: 6, 452: 8, 464: 8, 466: 8, 467: 5, 544: 4, 550: 8, 552: 4, 608: 8, 610: 5, 643: 7, 705: 8, 740: 5, 767:4, 800: 8, 836: 8, 845: 5, 849: 4, 869: 7, 870: 7, 871: 2, 896: 8, 897: 8, 900: 6, 902: 6, 905: 8, 911: 8, 913: 8, 916: 3, 918: 7, 921: 8, 933: 8, 944: 8, 945: 8, 951: 8, 955: 8, 956: 8, 979: 2, 992: 8, 998: 5, 999: 7, 1000: 8, 1001: 8, 1005: 2, 1008: 2, 1009: 8, 1014: 8, 1017: 8, 1020: 8, 1041: 8, 1042: 8, 1043: 8, 1044: 8, 1056: 8, 1059: 1, 1112: 8, 1114: 8, 1161: 8, 1162: 8, 1163: 8, 1164: 8, 1165: 8, 1166: 8, 1167: 8, 1168: 1, 1176: 8, 1177: 8, 1178: 8, 1179: 8, 1180: 8, 1181: 8, 1182: 8, 1183: 8, 1184: 8, 1185: 8, 1186: 8, 1187: 8, 1189: 8, 1190: 8, 1191: 8, 1192: 8, 1196: 8, 1197: 8, 1198: 8, 1199: 8, 1206: 8, 1208: 8, 1212: 8, 1227: 8, 1235: 8, 1237: 8, 1279: 8, 1408: 8, 1409: 8, 1410: 8, 1552: 8, 1553: 8, 1554: 8, 1555: 8, 1556: 8, 1557: 8, 1561: 8, 1568: 8, 1569: 8, 1570: 8, 1571: 8, 1572: 8, 1575: 8, 1584: 8, 1589: 8, 1590: 8, 1592: 8, 1593: 8, 1595: 8, 1599: 8, 1648: 8, 1666: 8, 1667: 8, 1728: 8, 1745: 8, 1779: 8, 1904: 8, 1912: 8, 1990: 8, 1998: 8
},
# IS300H 2017
{
36: 8, 37: 8, 170: 8, 180: 8, 295: 8, 296: 8, 400: 6, 426: 6, 452: 8, 466: 8, 467: 8, 550: 8, 552: 4, 560: 7, 581: 5, 608: 8, 610: 5, 643: 7, 713: 8, 740: 5, 800: 8, 836: 8, 845: 5, 849: 4, 869: 7, 870: 7, 871: 2, 896: 8, 897: 8, 900: 6, 902: 6, 905: 8, 911: 8, 913: 8, 916: 3, 918: 7, 921: 7, 933: 8, 944: 8, 945: 8, 950: 8, 951: 8, 953: 3, 955: 8, 956: 8, 979: 2, 992: 8, 998: 5, 999: 7, 1000: 8, 1001: 8, 1009: 8, 1017: 8, 1020: 8, 1041: 8, 1042: 8, 1043: 8, 1044: 8, 1056: 8, 1057: 8, 1059: 1, 1112: 8, 1114: 8, 1161: 8, 1162: 8, 1163: 8, 1164: 8, 1165: 8, 1166: 8, 1167: 8, 1168: 1, 1176: 8, 1177: 8, 1178: 8, 1179: 8, 1180: 8, 1181: 8, 1184: 8, 1185: 8, 1186: 8, 1187: 8, 1189: 8, 1190: 8, 1191: 8, 1192: 8, 1196: 8, 1197: 8, 1198: 8, 1199: 8, 1206: 8, 1208: 8, 1212: 8, 1227: 8, 1232: 8, 1235: 8, 1279: 8, 1408: 8, 1409: 8, 1410: 8, 1552: 8, 1553: 8, 1554: 8, 1555: 8, 1556: 8, 1557: 8, 1561: 8, 1568: 8, 1569: 8, 1570: 8, 1571: 8, 1572: 8, 1575: 8, 1584: 8, 1589: 8, 1592: 8, 1593: 8, 1595: 8, 1599: 8, 1728: 8, 1779: 8, 1904: 8, 1912: 8, 1990: 8, 1998: 8
36: 8, 37: 8, 170: 8, 180: 8, 295: 8, 296: 8, 400: 6, 426: 6, 452: 8, 466: 8, 467: 8, 550: 8, 552: 4, 560: 7, 581: 5, 608: 8, 610: 5, 643: 7, 713: 8, 740: 5, 767:4, 800: 8, 836: 8, 845: 5, 849: 4, 869: 7, 870: 7, 871: 2, 896: 8, 897: 8, 900: 6, 902: 6, 905: 8, 911: 8, 913: 8, 916: 3, 918: 7, 921: 7, 933: 8, 944: 8, 945: 8, 950: 8, 951: 8, 953: 3, 955: 8, 956: 8, 979: 2, 992: 8, 998: 5, 999: 7, 1000: 8, 1001: 8, 1009: 8, 1017: 8, 1020: 8, 1041: 8, 1042: 8, 1043: 8, 1044: 8, 1056: 8, 1057: 8, 1059: 1, 1112: 8, 1114: 8, 1161: 8, 1162: 8, 1163: 8, 1164: 8, 1165: 8, 1166: 8, 1167: 8, 1168: 1, 1176: 8, 1177: 8, 1178: 8, 1179: 8, 1180: 8, 1181: 8, 1184: 8, 1185: 8, 1186: 8, 1187: 8, 1189: 8, 1190: 8, 1191: 8, 1192: 8, 1196: 8, 1197: 8, 1198: 8, 1199: 8, 1206: 8, 1208: 8, 1212: 8, 1227: 8, 1232: 8, 1235: 8, 1279: 8, 1408: 8, 1409: 8, 1410: 8, 1552: 8, 1553: 8, 1554: 8, 1555: 8, 1556: 8, 1557: 8, 1561: 8, 1568: 8, 1569: 8, 1570: 8, 1571: 8, 1572: 8, 1575: 8, 1584: 8, 1589: 8, 1592: 8, 1593: 8, 1595: 8, 1599: 8, 1728: 8, 1779: 8, 1904: 8, 1912: 8, 1990: 8, 1998: 8
}],
CAR.RAV4H_TSS2: [
#Hybrid Limited
{
36: 8, 37: 8, 166: 8, 170: 8, 180: 8, 295: 8, 296: 8, 401: 8, 426: 6, 452: 8, 466: 8, 467: 8, 550: 8, 552: 4, 560: 7, 562: 6, 581: 5, 608: 8, 610: 8, 643: 7, 658: 8, 713: 8, 728: 8, 740: 5, 742: 8, 743: 8, 761: 8, 764: 8, 765: 8, 800: 8, 810: 2, 812: 8, 814: 8, 818: 8, 822: 8, 824: 8, 829: 2, 830: 7, 835: 8, 836: 8, 863: 8, 865: 8, 869: 7, 870: 7, 871: 2, 877: 8, 881: 8, 882: 8, 885: 8, 889: 8, 891: 8, 896: 8, 898: 8, 900: 6, 902: 6, 905: 8, 913:8, 918: 8, 921: 8, 933: 8, 934: 8, 935: 8, 944: 8, 945: 8, 950: 8, 951: 8, 953: 8, 955: 8, 956: 8, 971: 7, 975: 5, 987: 8, 993: 8, 998: 5, 999: 7, 1000: 8, 1001: 8, 1002: 8, 1014: 8, 1017: 8, 1020: 8, 1041: 8, 1042: 8, 1044: 8, 1056: 8, 1057: 8, 1059: 1, 1063: 8, 1071: 8, 1076: 8, 1077: 8, 1082: 8, 1084: 8, 1085: 8, 1086: 8, 1114: 8, 1132: 8, 1161: 8, 1162: 8, 1163: 8, 1164: 8, 1165: 8, 1166: 8, 1167: 8, 1172: 8, 1228: 8, 1235: 8, 1237: 8, 1263: 8, 1264: 8, 1279: 8, 1541: 8, 1552: 8, 1553: 8, 1556: 8, 1557: 8, 1568: 8, 1570: 8, 1571: 8, 1572: 8, 1592: 8, 1594: 8, 1595: 8, 1649: 8, 1696: 8, 1745: 8, 1775: 8, 1779: 8, 1786: 8, 1787: 8, 1788: 8, 1789: 8, 1808: 8, 1810: 8, 1816: 8, 1818: 8, 1904: 8, 1912: 8, 1990: 8, 1998: 8
36: 8, 37: 8, 166: 8, 170: 8, 180: 8, 295: 8, 296: 8, 401: 8, 426: 6, 452: 8, 466: 8, 467: 8, 550: 8, 552: 4, 560: 7, 562: 6, 581: 5, 608: 8, 610: 8, 643: 7, 658: 8, 713: 8, 728: 8, 740: 5, 742: 8, 743: 8, 761: 8, 764: 8, 765: 8, 767:4, 800: 8, 810: 2, 812: 8, 814: 8, 818: 8, 822: 8, 824: 8, 829: 2, 830: 7, 835: 8, 836: 8, 863: 8, 865: 8, 869: 7, 870: 7, 871: 2, 877: 8, 881: 8, 882: 8, 885: 8, 889: 8, 891: 8, 896: 8, 898: 8, 900: 6, 902: 6, 905: 8, 913:8, 918: 8, 921: 8, 933: 8, 934: 8, 935: 8, 944: 8, 945: 8, 950: 8, 951: 8, 953: 8, 955: 8, 956: 8, 971: 7, 975: 5, 987: 8, 993: 8, 998: 5, 999: 7, 1000: 8, 1001: 8, 1002: 8, 1014: 8, 1017: 8, 1020: 8, 1041: 8, 1042: 8, 1044: 8, 1056: 8, 1057: 8, 1059: 1, 1063: 8, 1071: 8, 1076: 8, 1077: 8, 1082: 8, 1084: 8, 1085: 8, 1086: 8, 1114: 8, 1132: 8, 1161: 8, 1162: 8, 1163: 8, 1164: 8, 1165: 8, 1166: 8, 1167: 8, 1172: 8, 1228: 8, 1235: 8, 1237: 8, 1263: 8, 1264: 8, 1279: 8, 1541: 8, 1552: 8, 1553: 8, 1556: 8, 1557: 8, 1568: 8, 1570: 8, 1571: 8, 1572: 8, 1592: 8, 1594: 8, 1595: 8, 1649: 8, 1696: 8, 1745: 8, 1775: 8, 1779: 8, 1786: 8, 1787: 8, 1788: 8, 1789: 8, 1808: 8, 1810: 8, 1816: 8, 1818: 8, 1904: 8, 1912: 8, 1990: 8, 1998: 8
},
# German Lounge
{
36: 8, 37: 8, 166: 8, 170: 8, 180: 8, 295: 8, 296: 8, 401: 8, 426: 6, 452: 8, 466: 8, 467: 8, 550: 8, 552: 4, 560: 7, 562: 6, 581: 5, 608: 8, 610: 8, 643: 7, 658: 8, 713: 8, 728: 8, 740: 5, 742: 8, 743: 8, 761: 8, 764: 8, 765: 8, 800: 8, 810: 2, 812: 8, 814: 8, 818: 8, 822: 8, 824: 8, 829: 2, 830: 7, 835: 8, 836: 8, 863: 8, 865: 8, 869: 7, 870: 7, 871: 2, 877: 8, 881: 8, 882: 8, 885: 8, 889: 8, 891: 8, 896: 8, 898: 8, 900: 6, 902: 6, 905: 8, 913: 8, 918: 8, 921: 8, 933: 8, 934: 8, 935: 8, 944: 8, 945: 8, 950: 8, 951: 8, 953: 8, 955: 8, 956: 8, 971: 7, 975: 5, 987: 8, 993: 8, 998: 5, 999: 7, 1000: 8, 1001: 8, 1002: 8, 1014: 8, 1017: 8, 1020: 8, 1041: 8, 1042: 8, 1044: 8, 1056: 8, 1057: 8, 1059: 1, 1063: 8, 1071: 8, 1076: 8, 1077: 8, 1082: 8, 1114: 8, 1161: 8, 1162: 8, 1163: 8, 1164: 8, 1165: 8, 1166: 8, 1167: 8, 1172: 8, 1228: 8, 1235: 8, 1237: 8, 1263: 8, 1264: 8, 1279: 8, 1541: 8, 1552: 8, 1553: 8, 1556: 8, 1557: 8, 1568: 8, 1570: 8, 1571: 8, 1572: 8, 1592: 8, 1594: 8, 1595: 8, 1649: 8, 1696: 8, 1745: 8, 1775: 8, 1779: 8, 1786: 8, 1787: 8, 1788: 8, 1789: 8, 1792: 8, 1800: 8, 1872: 8, 1880: 8, 1904: 8, 1912: 8, 1937: 8, 1945: 8, 1953: 8, 1961: 8, 1968: 8, 1976: 8, 1990: 8, 1998: 8, 2015: 8, 2016: 8, 2024: 8
}],
],
CAR.LEXUS_CTH: [{
36: 8, 37: 8, 170: 8, 180: 8, 288: 8, 426: 6, 452: 8, 466: 8, 467: 8, 548: 8, 552: 4, 560: 7, 581: 5, 608: 8, 610: 5, 643: 7, 713: 8, 740: 5, 800: 8, 810: 2, 832: 8, 835: 8, 836: 8, 849: 4, 869: 7, 870: 7, 871: 2, 897: 8, 900: 6, 902: 6, 905: 8, 911: 8, 916: 1, 921: 8, 933: 8, 944: 6, 945: 8, 950: 8, 951: 8, 953: 3, 955: 4, 956: 8, 979: 2, 992: 8, 998: 5, 999: 7, 1000: 8, 1001: 8, 1017: 8, 1041: 8, 1042: 8, 1043: 8, 1056: 8, 1057: 8, 1059: 1, 1076: 8, 1077: 8, 1114: 8, 1116: 8, 1160: 8, 1161: 8, 1162: 8, 1163: 8, 1164: 8, 1165: 8, 1166: 8, 1167: 8, 1176: 8, 1177: 8, 1178: 8, 1179: 8, 1180: 8, 1181: 8, 1184: 8, 1185: 8, 1186: 8, 1190: 8, 1191: 8, 1192: 8, 1227: 8, 1235: 8, 1279: 8, 1552: 8, 1553: 8, 1554: 8, 1555: 8, 1556: 8, 1557: 8, 1558: 8, 1561: 8, 1562: 8, 1568: 8, 1569: 8, 1570: 8, 1571: 8, 1572: 8, 1575: 8, 1584: 8, 1589: 8, 1592: 8, 1593: 8, 1595: 8, 1664: 8, 1728: 8, 1779: 8, 1904: 8, 1912: 8, 1990: 8, 1998: 8
}],
CAR.LEXUS_NXH: [{
36: 8, 37: 8, 170: 8, 180: 8, 295: 8, 296: 8, 426: 6, 452: 8, 466: 8, 467: 8, 550: 8, 552: 4, 560: 7, 562: 6, 581: 5, 608: 8, 610: 5, 643: 7, 713: 8, 740: 5, 742: 8, 743: 8, 764: 8, 800: 8, 810: 2, 812: 3, 818: 8, 822: 8, 824: 8, 835: 8, 836: 8, 845: 5, 849: 4, 869: 7, 870: 7, 871: 2, 889: 8, 891: 8, 896: 8, 897: 8, 900: 6, 902: 6, 905: 8, 911: 8, 913: 8, 916: 3, 918: 8, 921: 8, 933: 8, 944: 8, 945: 8, 950: 8, 951: 8, 953: 3, 955: 8, 956: 8, 979: 2, 987: 8, 992: 8, 998: 5, 999: 7, 1000: 8, 1001: 8, 1002: 8, 1006: 8, 1014: 8, 1017: 8, 1020: 8, 1041: 8, 1042: 8, 1043: 8, 1056: 8, 1057: 8, 1059: 1, 1076: 8, 1077: 8, 1082: 8, 1114: 8, 1161: 8, 1162: 8, 1163: 8, 1164: 8, 1165: 8, 1166: 8, 1167: 8, 1168: 1, 1176: 8, 1177: 8, 1178: 8, 1179: 8, 1180: 8, 1181: 8, 1184: 8, 1185: 8, 1186: 8, 1189: 8, 1190: 8, 1191: 8, 1192: 8, 1195: 8, 1196: 8, 1197: 8, 1198: 8, 1199: 8, 1206: 8, 1208: 8, 1212: 8, 1227: 8, 1228: 8, 1232: 8, 1235: 8, 1237: 8, 1263: 8, 1264: 8, 1279: 8, 1408: 8, 1409: 8, 1410: 8, 1552: 8, 1553: 8, 1554: 8, 1555: 8, 1556: 8, 1557: 8, 1561: 8, 1568: 8, 1569: 8, 1570: 8, 1571: 8, 1572: 8, 1575: 8, 1584: 8, 1589: 8, 1592: 8, 1593: 8, 1595: 8, 1599: 8, 1656: 8, 1728: 8, 1745: 8, 1777: 8, 1779: 8, 1904: 8, 1912: 8, 1990: 8, 1998: 8
}]
}
# Don't use theses fingerprints for fingerprinting, they are still needed for ECU detection
IGNORED_FINGERPRINTS = [CAR.RAV4H_TSS2]
FW_VERSIONS = {
CAR.AVALON: {
(Ecu.esp, 0x7b0, None): [b'F152607060\x00\x00\x00\x00\x00\x00'],
@ -267,6 +280,7 @@ FW_VERSIONS = {
},
CAR.CAMRY: {
(Ecu.engine, 0x700, None): [
b'\x018966306L5200\x00\x00\x00\x00',
b'\x018966333P4200\x00\x00\x00\x00',
b'\x018966333P4300\x00\x00\x00\x00',
b'\x018966333P4400\x00\x00\x00\x00',
@ -325,9 +339,18 @@ FW_VERSIONS = {
b'8646F0605000 ',
],
},
CAR.CHR: {
(Ecu.dsu, 0x791, None): [b'8821FF404100 '],
(Ecu.esp, 0x7b0, None): [b'F1526F4122\x00\x00\x00\x00\x00\x00'],
(Ecu.eps, 0x7a1, None): [b'8965B10040\x00\x00\x00\x00\x00\x00'],
(Ecu.engine, 0x7e0, None): [b'\x033F424000\x00\x00\x00\x00\x00\x00\x00\x00A0202000\x00\x00\x00\x00\x00\x00\x00\x00895231203202\x00\x00\x00\x00'],
(Ecu.fwdRadar, 0x750, 0xf): [b'8821FF404100 '],
(Ecu.fwdCamera, 0x750, 0x6d): [b'8646FF404000 '],
},
CAR.COROLLA: {
(Ecu.engine, 0x7e0, None): [
b'\x01896630E88000\x00\x00\x00\x00',
b'\x0230ZC2000\x00\x00\x00\x00\x00\x00\x00\x0050212000\x00\x00\x00\x00\x00\x00\x00\x00',
b'\x0230ZC2100\x00\x00\x00\x00\x00\x00\x00\x0050212000\x00\x00\x00\x00\x00\x00\x00\x00',
b'\x0230ZC2200\x00\x00\x00\x00\x00\x00\x00\x0050212000\x00\x00\x00\x00\x00\x00\x00\x00',
b'\x0230ZC2300\x00\x00\x00\x00\x00\x00\x00\x0050212000\x00\x00\x00\x00\x00\x00\x00\x00',
@ -494,9 +517,11 @@ FW_VERSIONS = {
b'\x02896634774100\x00\x00\x00\x008966A4703000\x00\x00\x00\x00',
b'\x02896634774200\x00\x00\x00\x008966A4703000\x00\x00\x00\x00',
b'\x02896634782000\x00\x00\x00\x008966A4703000\x00\x00\x00\x00',
b'\x02896634784000\x00\x00\x00\x008966A4703000\x00\x00\x00\x00',
b'\x03896634759200\x00\x00\x00\x008966A4703000\x00\x00\x00\x00897CF4701003\x00\x00\x00\x00',
b'\x03896634759300\x00\x00\x00\x008966A4703000\x00\x00\x00\x00897CF4701004\x00\x00\x00\x00',
b'\x03896634760000\x00\x00\x00\x008966A4703000\x00\x00\x00\x00897CF4701002\x00\x00\x00\x00',
b'\x03896634760100\x00\x00\x00\x008966A4703000\x00\x00\x00\x00897CF4701003\x00\x00\x00\x00',
b'\x03896634760200\x00\x00\x00\x008966A4703000\x00\x00\x00\x00897CF4701003\x00\x00\x00\x00',
b'\x03896634760200\x00\x00\x00\x008966A4703000\x00\x00\x00\x00897CF4701004\x00\x00\x00\x00',
b'\x03896634768000\x00\x00\x00\x008966A4703000\x00\x00\x00\x00897CF4703001\x00\x00\x00\x00',
@ -551,6 +576,7 @@ FW_VERSIONS = {
},
CAR.RAV4: {
(Ecu.engine, 0x7e0, None): [
b'\x02342Q1000\x00\x00\x00\x00\x00\x00\x00\x0054212000\x00\x00\x00\x00\x00\x00\x00\x00',
b'\x02342Q1100\x00\x00\x00\x00\x00\x00\x00\x0054212000\x00\x00\x00\x00\x00\x00\x00\x00',
b'\x02342Q1300\x00\x00\x00\x00\x00\x00\x00\x0054212000\x00\x00\x00\x00\x00\x00\x00\x00',
b'\x02342Q2000\x00\x00\x00\x00\x00\x00\x00\x0054213000\x00\x00\x00\x00\x00\x00\x00\x00',
@ -561,6 +587,7 @@ FW_VERSIONS = {
b'8965B42083\x00\x00\x00\x00\x00\x00',
],
(Ecu.esp, 0x7b0, None): [
b'F15260R102\x00\x00\x00\x00\x00\x00',
b'F15260R103\x00\x00\x00\x00\x00\x00',
b'F152642493\x00\x00\x00\x00\x00\x00',
],
@ -619,9 +646,11 @@ FW_VERSIONS = {
b'\x018966342V3100\x00\x00\x00\x00',
b'\x018966342X5000\x00\x00\x00\x00',
b'\x01896634A05000\x00\x00\x00\x00',
b'\x01896634A19000\x00\x00\x00\x00',
b'\x01896634A22000\x00\x00\x00\x00',
b'\x01F152642551\x00\x00\x00\x00\x00\x00',
b'\x028966342Y8000\x00\x00\x00\x00897CF1201001\x00\x00\x00\x00',
b'\x02896634A18000\x00\x00\x00\x00897CF1201001\x00\x00\x00\x00',
],
(Ecu.esp, 0x7b0, None): [
b'F152606230\x00\x00\x00\x00\x00\x00',
@ -695,9 +724,17 @@ FW_VERSIONS = {
(Ecu.fwdCamera, 0x750, 0x6d): [b'8646F5301400\x00\x00\x00\x00'],
},
CAR.SIENNA: {
(Ecu.engine, 0x700, None): [b'\x01896630832100\x00\x00\x00\x00'],
(Ecu.engine, 0x700, None): [
b'\x01896630832100\x00\x00\x00\x00',
b'\x01896630842000\x00\x00\x00\x00',
b'\x01896630851100\x00\x00\x00\x00',
b'\x01896630860000\x00\x00\x00\x00',
],
(Ecu.eps, 0x7a1, None): [b'8965B45070\x00\x00\x00\x00\x00\x00'],
(Ecu.fwdRadar, 0x750, 0xf): [b'8821F4702100\x00\x00\x00\x00'],
(Ecu.fwdRadar, 0x750, 0xf): [
b'8821F4702100\x00\x00\x00\x00',
b'8821F4702300\x00\x00\x00\x00',
],
(Ecu.fwdCamera, 0x750, 0x6d): [b'8646F0801100\x00\x00\x00\x00'],
},
CAR.LEXUS_RXH: {
@ -747,6 +784,7 @@ DBC = {
CAR.CAMRY: dbc_dict('toyota_nodsu_pt_generated', 'toyota_adas'),
CAR.CAMRYH: dbc_dict('toyota_camry_hybrid_2018_pt_generated', 'toyota_adas'),
CAR.HIGHLANDER: dbc_dict('toyota_highlander_2017_pt_generated', 'toyota_adas'),
CAR.HIGHLANDER_TSS2: dbc_dict('toyota_nodsu_pt_generated', 'toyota_tss2_adas'),
CAR.HIGHLANDERH: dbc_dict('toyota_highlander_hybrid_2018_pt_generated', 'toyota_adas'),
CAR.AVALON: dbc_dict('toyota_avalon_2017_pt_generated', 'toyota_adas'),
CAR.RAV4_TSS2: dbc_dict('toyota_nodsu_pt_generated', 'toyota_tss2_adas'),
@ -758,8 +796,9 @@ DBC = {
CAR.LEXUS_IS: dbc_dict('lexus_is_2018_pt_generated', 'toyota_adas'),
CAR.LEXUS_CTH: dbc_dict('lexus_ct200h_2018_pt_generated', 'toyota_adas'),
CAR.RAV4H_TSS2: dbc_dict('toyota_nodsu_hybrid_pt_generated', 'toyota_tss2_adas'),
CAR.LEXUS_NXH: dbc_dict('lexus_nx300h_2018_pt_generated', 'toyota_adas'),
}
NO_DSU_CAR = [CAR.CHR, CAR.CHRH, CAR.CAMRY, CAR.CAMRYH, CAR.RAV4_TSS2, CAR.COROLLA_TSS2, CAR.COROLLAH_TSS2, CAR.LEXUS_ES_TSS2, CAR.LEXUS_ESH_TSS2, CAR.RAV4H_TSS2, CAR.LEXUS_RX_TSS2]
TSS2_CAR = [CAR.RAV4_TSS2, CAR.COROLLA_TSS2, CAR.COROLLAH_TSS2, CAR.LEXUS_ES_TSS2, CAR.LEXUS_ESH_TSS2, CAR.RAV4H_TSS2, CAR.LEXUS_RX_TSS2]
NO_STOP_TIMER_CAR = [CAR.RAV4H, CAR.HIGHLANDERH, CAR.HIGHLANDER, CAR.RAV4_TSS2, CAR.COROLLA_TSS2, CAR.COROLLAH_TSS2, CAR.LEXUS_ES_TSS2, CAR.LEXUS_ESH_TSS2, CAR.SIENNA, CAR.RAV4H_TSS2, CAR.LEXUS_RX_TSS2] # no resume button press required
NO_DSU_CAR = [CAR.CHR, CAR.CHRH, CAR.CAMRY, CAR.CAMRYH, CAR.RAV4_TSS2, CAR.COROLLA_TSS2, CAR.COROLLAH_TSS2, CAR.LEXUS_ES_TSS2, CAR.LEXUS_ESH_TSS2, CAR.RAV4H_TSS2, CAR.LEXUS_RX_TSS2, CAR.HIGHLANDER_TSS2]
TSS2_CAR = [CAR.RAV4_TSS2, CAR.COROLLA_TSS2, CAR.COROLLAH_TSS2, CAR.LEXUS_ES_TSS2, CAR.LEXUS_ESH_TSS2, CAR.RAV4H_TSS2, CAR.LEXUS_RX_TSS2, CAR.HIGHLANDER_TSS2]
NO_STOP_TIMER_CAR = [CAR.RAV4H, CAR.HIGHLANDERH, CAR.HIGHLANDER, CAR.RAV4_TSS2, CAR.COROLLA_TSS2, CAR.COROLLAH_TSS2, CAR.LEXUS_ES_TSS2, CAR.LEXUS_ESH_TSS2, CAR.SIENNA, CAR.RAV4H_TSS2, CAR.LEXUS_RX_TSS2, CAR.HIGHLANDER_TSS2] # no resume button press required

35
selfdrive/car/volkswagen/carstate.py
View File

@ -1,13 +1,10 @@
import numpy as np
from cereal import car
from common.kalman.simple_kalman import KF1D
from selfdrive.config import Conversions as CV
from selfdrive.car.interfaces import CarStateBase
from opendbc.can.parser import CANParser
from opendbc.can.can_define import CANDefine
from selfdrive.car.volkswagen.values import DBC, BUTTON_STATES, CarControllerParams
GEAR = car.CarState.GearShifter
def get_mqb_pt_can_parser(CP, canbus):
# this function generates lists for signal, messages and initial values
signals = [
@ -99,29 +96,14 @@ def get_mqb_cam_can_parser(CP, canbus):
return CANParser(DBC[CP.carFingerprint]['pt'], signals, checks, canbus.cam)
def parse_gear_shifter(gear):
# Return mapping of gearshift position to selected gear.
return {'P': GEAR.park, 'R': GEAR.reverse, 'N': GEAR.neutral,
'D': GEAR.drive, 'E': GEAR.eco, 'S': GEAR.sport, 'T': GEAR.manumatic}.get(gear, GEAR.unknown)
class CarState():
class CarState(CarStateBase):
def __init__(self, CP, canbus):
# initialize can parser
self.CP = CP
self.car_fingerprint = CP.carFingerprint
self.can_define = CANDefine(DBC[CP.carFingerprint]['pt'])
self.shifter_values = self.can_define.dv["Getriebe_11"]['GE_Fahrstufe']
super().__init__(CP)
can_define = CANDefine(DBC[CP.carFingerprint]['pt'])
self.shifter_values = can_define.dv["Getriebe_11"]['GE_Fahrstufe']
self.buttonStates = BUTTON_STATES.copy()
# vEgo Kalman filter
dt = 0.01
self.v_ego_kf = KF1D(x0=[[0.], [0.]],
A=[[1., dt], [0., 1.]],
C=[1., 0.],
K=[[0.12287673], [0.29666309]])
def update(self, pt_cp):
# Update vehicle speed and acceleration from ABS wheel speeds.
self.wheelSpeedFL = pt_cp.vl["ESP_19"]['ESP_VL_Radgeschw_02'] * CV.KPH_TO_MS
@ -130,9 +112,8 @@ class CarState():
self.wheelSpeedRR = pt_cp.vl["ESP_19"]['ESP_HR_Radgeschw_02'] * CV.KPH_TO_MS
self.vEgoRaw = float(np.mean([self.wheelSpeedFL, self.wheelSpeedFR, self.wheelSpeedRL, self.wheelSpeedRR]))
v_ego_x = self.v_ego_kf.update(self.vEgoRaw)
self.vEgo = float(v_ego_x[0])
self.aEgo = float(v_ego_x[1])
self.vEgo, self.aEgo = self.update_speed_kf(self.vEgoRaw)
self.standstill = self.vEgoRaw < 0.1
# Update steering angle, rate, yaw rate, and driver input torque. VW send
@ -152,7 +133,7 @@ class CarState():
# Update gear and/or clutch position data.
can_gear_shifter = int(pt_cp.vl["Getriebe_11"]['GE_Fahrstufe'])
self.gearShifter = parse_gear_shifter(self.shifter_values.get(can_gear_shifter, None))
self.gearShifter = self.parse_gear_shifter(self.shifter_values.get(can_gear_shifter, None))
# Update door and trunk/hatch lid open status.
self.doorOpen = any([pt_cp.vl["Gateway_72"]['ZV_FT_offen'],

2
selfdrive/common/version.h
View File

@ -1 +1 @@
#define COMMA_VERSION "0.7.2-release"
#define COMMA_VERSION "0.7.3-release"

4
selfdrive/controls/lib/pathplanner.py
View File

@ -6,6 +6,7 @@ from selfdrive.controls.lib.lateral_mpc import libmpc_py
from selfdrive.controls.lib.drive_helpers import MPC_COST_LAT
from selfdrive.controls.lib.lane_planner import LanePlanner
from selfdrive.config import Conversions as CV
from common.params import Params
import cereal.messaging as messaging
from cereal import log
@ -53,6 +54,7 @@ class PathPlanner():
self.setup_mpc()
self.solution_invalid_cnt = 0
self.lane_change_enabled = Params().get('LaneChangeEnabled') == b'1'
self.lane_change_state = LaneChangeState.off
self.lane_change_direction = LaneChangeDirection.none
self.lane_change_timer = 0.0
@ -97,7 +99,7 @@ class PathPlanner():
elif sm['carState'].rightBlinker:
self.lane_change_direction = LaneChangeDirection.right
if (not active) or (self.lane_change_timer > LANE_CHANGE_TIME_MAX) or (not one_blinker):
if (not active) or (self.lane_change_timer > LANE_CHANGE_TIME_MAX) or (not one_blinker) or (not self.lane_change_enabled):
self.lane_change_state = LaneChangeState.off
self.lane_change_direction = LaneChangeDirection.none
else:

96
selfdrive/debug/live_cpu_and_temp.py
View File

@ -1,64 +1,72 @@
#!/usr/bin/env python3
import argparse
import numpy as np
from cereal.messaging import SubMaster
def cputime_total(ct):
return ct.user + ct.nice + ct.system + ct.idle + ct.iowait + ct.irq + ct.softirq
return ct.user + ct.nice + ct.system + ct.idle + ct.iowait + ct.irq + ct.softirq
def cputime_busy(ct):
return ct.user + ct.nice + ct.system + ct.irq + ct.softirq
return ct.user + ct.nice + ct.system + ct.irq + ct.softirq
if __name__ == "__main__":
parser = argparse.ArgumentParser()
parser.add_argument('--mem', action='store_true')
args = parser.parse_args()
sm = SubMaster(['thermal', 'procLog'])
sm = SubMaster(['thermal', 'procLog'])
last_temp = 0.0
last_mem = 0.0
total_times = [0., 0., 0., 0.]
busy_times = [0., 0., 0.0, 0.]
last_temp = 0.0
last_mem = 0.0
total_times = [0., 0., 0., 0.]
busy_times = [0., 0., 0.0, 0.]
while True:
sm.update()
if sm.updated['thermal']:
t = sm['thermal']
last_temp = np.mean([t.cpu0, t.cpu1, t.cpu2, t.cpu3]) / 10.
last_mem = t.memUsedPercent
if sm.updated['procLog']:
m = sm['procLog']
while True:
sm.update()
cores = [0., 0., 0., 0.]
total_times_new = [0., 0., 0., 0.]
busy_times_new = [0., 0., 0.0, 0.]
if sm.updated['thermal']:
t = sm['thermal']
last_temp = np.mean([t.cpu0, t.cpu1, t.cpu2, t.cpu3]) / 10.
last_mem = t.memUsedPercent
for c in m.cpuTimes:
n = c.cpuNum
total_times_new[n] = cputime_total(c)
busy_times_new[n] = cputime_busy(c)
if sm.updated['procLog']:
m = sm['procLog']
for n in range(4):
t_busy = busy_times_new[n] - busy_times[n]
t_total = total_times_new[n] - total_times[n]
cores[n] = t_busy / t_total
mems = {}
for proc in m.procs:
name = proc.name
if len(proc.cmdline):
name = proc.cmdline[0]
if len(proc.exe):
name = proc.exe + " - " + name
mems[name] = float(proc.memRss) / 1e6
total_times = total_times_new[:]
busy_times = busy_times_new[:]
cores = [0., 0., 0., 0.]
total_times_new = [0., 0., 0., 0.]
busy_times_new = [0., 0., 0.0, 0.]
print("CPU %.2f%% - RAM: %.2f - Temp %.2f" % (100. * np.mean(cores), last_mem, last_temp))
for c in m.cpuTimes:
n = c.cpuNum
total_times_new[n] = cputime_total(c)
busy_times_new[n] = cputime_busy(c)
for n in range(4):
t_busy = busy_times_new[n] - busy_times[n]
t_total = total_times_new[n] - total_times[n]
cores[n] = t_busy / t_total
total_times = total_times_new[:]
busy_times = busy_times_new[:]
print()
print("CPU %.2f%% - RAM: %.2f - Temp %.2f" % (100. * np.mean(cores), last_mem, last_temp))
print("Top memory usage:")
for k, v in sorted(mems.items(), key=lambda item: item[1], reverse=True)[:10]:
print(f"{k.rjust(70)} {v:.2f} MB")
if args.mem:
mems = {}
for proc in m.procs:
name = proc.name
if len(proc.cmdline):
name = proc.cmdline[0]
if len(proc.exe):
name = proc.exe + " - " + name
mems[name] = float(proc.memRss) / 1e6
print("Top memory usage:")
for k, v in sorted(mems.items(), key=lambda item: item[1], reverse=True)[:10]:
print(f"{k.rjust(70)} {v:.2f} MB")
print()

10
selfdrive/debug/test_fw_query_on_routes.py
View File

@ -1,4 +1,5 @@
#!/usr/bin/env python3
import os
import traceback
import sys
from tqdm import tqdm
@ -13,14 +14,19 @@ from selfdrive.car.honda.values import FINGERPRINTS as HONDA_FINGERPRINTS
if __name__ == "__main__":
if len(sys.argv) < 2:
print("Usage: ./test_fw_query_on_routes.py <route_list>")
print("Usage: ./test_fw_query_on_routes.py <route_list>/<route>")
sys.exit(1)
if os.path.exists(sys.argv[1]):
routes = list(open(sys.argv[1]))
else:
routes = [sys.argv[1]]
wrong = 0
good = 0
dongles = []
for route in tqdm(list(open(sys.argv[1]))):
for route in tqdm(routes):
route = route.rstrip()
dongle_id, time = route.split('|')
qlog_path = f"cd:/{dongle_id}/{time}/0/qlog.bz2"

1
selfdrive/locationd/kalman/.gitignore vendored 100644
View File

@ -0,0 +1 @@
generated/

52
selfdrive/locationd/kalman/README.md 100644
View File

@ -0,0 +1,52 @@
# Kalman filter library
## Introduction
The kalman filter framework described here is an incredibly powerful tool for any optimization problem,
but particularly for visual odometry, sensor fusion localization or SLAM. It is designed to provide very
accurate results, work online or offline, be fairly computationally efficient, be easy to design filters with in
python.
## Feature walkthrough
### Extended Kalman Filter with symbolic Jacobian computation
Most dynamic systems can be described as a Hidden Markov Process. To estimate the state of such a system with noisy
measurements one can use a Recursive Bayesian estimator. For a linear Markov Process a regular linear Kalman filter is optimal.
Unfortunately, a lot of systems are non-linear. Extended Kalman Filters can model systems by linearizing the non-linear
system at every step, this provides a close to optimal estimator when the linearization is good enough. If the linearization
introduces too much noise, one can use an Iterated Extended Kalman Filter, Unscented Kalman Filter or a Particle Filter. For
most applications those estimators are overkill and introduce too much complexity and require a lot of additional compute.
Conventionally Extended Kalman Filters are implemented by writing the system's dynamic equations and then manually symbolically
calculating the Jacobians for the linearization. For complex systems this is time consuming and very prone to calculation errors.
This library symbolically computes the Jacobians using sympy to simplify the system's definition and remove the possiblity of introducing calculation errors.
### Error State Kalman Filter
3D localization algorithms ussually also require estimating orientation of an object in 3D. Orientation is generally represented
with euler angles or quaternions.
Euler angles have several problems, there are mulitple ways to represent the same orientation,
gimbal lock can cause the loss of a degree of freedom and lastly their behaviour is very non-linear when errors are large.
Quaternions with one strictly positive dimension don't suffer from these issues, but have another set of problems.
Quaternions need to be normalized otherwise they will grow unbounded, this is cannot be cleanly enforced in a kalman filter.
Most importantly though a quaternion has 4 dimensions, but only represents 3 degrees of freedom, so there is one redundant dimension.
Kalman filters are designed to minimize the error of the system's state. It is possible to have a kalman filter where state and the error of the state are represented in a different space. As long as there is an error function that can compute the error based on the true state and estimated state. It is problematic to have redundant dimensions in the error of the kalman filter, but not in the state. A good compromise then, is to use the quaternion to represent the system's attitude state and use euler angles to describe the error in attitude. This library supports and defining an arbitrary error that is in a different space than the state. [Joan Solà](https://arxiv.org/abs/1711.02508) has written a comprehensive description of using ESKFs for robust 3D orientation estimation.
### Multi-State Constraint Kalman Filter
How do you integrate feature-based visual odometry with a Kalman filter? The problem is that one cannot write an observation equation for 2D feature observations in image space for a localization kalman filter. One needs to give the feature observation a depth so it has a 3D position, then one can write an obvervation equation in the kalman filter. This is possible by tracking the feature across frames and then estimating the depth. However, the solution is not that simple, the depth estimated by tracking the feature across frames depends on the location of the camera at those frames, and thus the state of the kalman filter. This creates a positive feedback loop where the kalman filter wrongly gains confidence in it's position because the feature position updates reinforce it.
The solution is to use an [MSCKF](http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.437.1085&rep=rep1&type=pdf), which this library fully supports.
### Rauch–Tung–Striebel smoothing
When doing offline estimation with a kalman filter there can be an initialization period where states are badly estimated.
Global estimators don't suffer from this, to make our kalman filter competitive with global optimizers we can run the filter
backwards using an RTS smoother. Those combined with potentially multiple forward and backwards passes of the data should make
performance very close to global optimization.
### Mahalanobis distance outlier rejector
A lot of measurements do not come from a Gaussian distribution and as such have outliers that do not fit the statistical model
of the Kalman filter. This can cause a lot of performance issues if not dealt with. This library allows the use of a mahalanobis
distance statistical test on the incoming measurements to deal with this. Note that good initialization is critical to prevent
good measurements from being rejected.

31
selfdrive/locationd/kalman/SConscript 100644
View File

@ -0,0 +1,31 @@
Import('env')
templates = Glob('templates/*')
sympy_helpers = "helpers/sympy_helpers.py"
ekf_sym = "helpers/ekf_sym.py"
to_build = {
'pos_computer_4': 'helpers/lst_sq_computer.py',
'pos_computer_5': 'helpers/lst_sq_computer.py',
'feature_handler_5': 'helpers/feature_handler.py',
'gnss': 'models/gnss_kf.py',
'loc_4': 'models/loc_kf.py',
'live': 'models/live_kf.py',
'lane': '#xx/pipeline/lib/ekf/lane_kf.py',
}
found = {}
for target, command in to_build.items():
if File(command).exists():
found[target] = command
for target, command in found.items():
target_files = File([f'generated/{target}.cpp', f'generated/{target}.h'])
command_file = File(command)
env.Command(target_files,
[templates, command_file, sympy_helpers, ekf_sym],
command_file.get_abspath()+" "+target
)
env.SharedLibrary('generated/' + target, target_files[0])

0
selfdrive/locationd/kalman/__init__.py 100644
View File

191
selfdrive/locationd/kalman/helpers/__init__.py 100644
View File

@ -0,0 +1,191 @@
import numpy as np
import os
from bisect import bisect
from tqdm import tqdm
from cffi import FFI
TEMPLATE_DIR = os.path.abspath(os.path.join(os.path.dirname(__file__), '..', 'templates'))
GENERATED_DIR = os.path.abspath(os.path.join(os.path.dirname(__file__), '..', 'generated'))
def write_code(name, code, header):
if not os.path.exists(GENERATED_DIR):
os.mkdir(GENERATED_DIR)
open(os.path.join(GENERATED_DIR, f"{name}.cpp"), 'w').write(code)
open(os.path.join(GENERATED_DIR, f"{name}.h"), 'w').write(header)
def load_code(name):
shared_fn = os.path.join(GENERATED_DIR, f"lib{name}.so")
header_fn = os.path.join(GENERATED_DIR, f"{name}.h")
header = open(header_fn).read()
ffi = FFI()
ffi.cdef(header)
return (ffi, ffi.dlopen(shared_fn))
class KalmanError(Exception):
pass
class ObservationKind():
UNKNOWN = 0
NO_OBSERVATION = 1
GPS_NED = 2
ODOMETRIC_SPEED = 3
PHONE_GYRO = 4
GPS_VEL = 5
PSEUDORANGE_GPS = 6
PSEUDORANGE_RATE_GPS = 7
SPEED = 8
NO_ROT = 9
PHONE_ACCEL = 10
ORB_POINT = 11
ECEF_POS = 12
CAMERA_ODO_TRANSLATION = 13
CAMERA_ODO_ROTATION = 14
ORB_FEATURES = 15
MSCKF_TEST = 16
FEATURE_TRACK_TEST = 17
LANE_PT = 18
IMU_FRAME = 19
PSEUDORANGE_GLONASS = 20
PSEUDORANGE_RATE_GLONASS = 21
PSEUDORANGE = 22
PSEUDORANGE_RATE = 23
names = ['Unknown',
'No observation',
'GPS NED',
'Odometric speed',
'Phone gyro',
'GPS velocity',
'GPS pseudorange',
'GPS pseudorange rate',
'Speed',
'No rotation',
'Phone acceleration',
'ORB point',
'ECEF pos',
'camera odometric translation',
'camera odometric rotation',
'ORB features',
'MSCKF test',
'Feature track test',
'Lane ecef point',
'imu frame eulers',
'GLONASS pseudorange',
'GLONASS pseudorange rate']
@classmethod
def to_string(cls, kind):
return cls.names[kind]
SAT_OBS = [ObservationKind.PSEUDORANGE_GPS,
ObservationKind.PSEUDORANGE_RATE_GPS,
ObservationKind.PSEUDORANGE_GLONASS,
ObservationKind.PSEUDORANGE_RATE_GLONASS]
def run_car_ekf_offline(kf, observations_by_kind):
from laika.raw_gnss import GNSSMeasurement
observations = []
# create list of observations with element format: [kind, time, data]
for kind in observations_by_kind:
for t, data in zip(observations_by_kind[kind][0], observations_by_kind[kind][1]):
observations.append([t, kind, data])
observations.sort(key=lambda obs: obs[0])
times, estimates = run_observations_through_filter(kf, observations)
forward_states = np.stack(e[1] for e in estimates)
forward_covs = np.stack(e[3] for e in estimates)
smoothed_states, smoothed_covs = kf.rts_smooth(estimates)
observations_dict = {}
# TODO assuming observations and estimates
# are same length may not work with VO
for e in estimates:
t = e[4]
kind = str(int(e[5]))
res = e[6]
z = e[7]
ea = e[8]
if len(z) == 0:
continue
if kind not in observations_dict:
observations_dict[kind] = {}
observations_dict[kind]['t'] = np.array(len(z)*[t])
observations_dict[kind]['z'] = np.array(z)
observations_dict[kind]['ea'] = np.array(ea)
observations_dict[kind]['residual'] = np.array(res)
else:
observations_dict[kind]['t'] = np.append(observations_dict[kind]['t'], np.array(len(z)*[t]))
observations_dict[kind]['z'] = np.vstack((observations_dict[kind]['z'], np.array(z)))
observations_dict[kind]['ea'] = np.vstack((observations_dict[kind]['ea'], np.array(ea)))
observations_dict[kind]['residual'] = np.vstack((observations_dict[kind]['residual'], np.array(res)))
# add svIds to gnss data
for kind in map(str, SAT_OBS):
if int(kind) in observations_by_kind and kind in observations_dict:
observations_dict[kind]['svIds'] = np.array([])
observations_dict[kind]['CNO'] = np.array([])
observations_dict[kind]['std'] = np.array([])
for obs in observations_by_kind[int(kind)][1]:
observations_dict[kind]['svIds'] = np.append(observations_dict[kind]['svIds'],
np.array([obs[:,GNSSMeasurement.PRN]]))
observations_dict[kind]['std'] = np.append(observations_dict[kind]['std'],
np.array([obs[:,GNSSMeasurement.PR_STD]]))
return smoothed_states, smoothed_covs, forward_states, forward_covs, times, observations_dict
def run_observations_through_filter(kf, observations, filter_time=None):
estimates = []
for obs in tqdm(observations):
t = obs[0]
kind = obs[1]
data = obs[2]
estimates.append(kf.predict_and_observe(t, kind, data))
times = [x[4] for x in estimates]
return times, estimates
def save_residuals_plot(obs, save_path, data_name):
import matplotlib.pyplot as plt
import mpld3 # pylint: disable=import-error
fig = plt.figure(figsize=(10,20))
fig.suptitle('Residuals of ' + data_name, fontsize=24)
n = len(list(obs.keys()))
start_times = [obs[kind]['t'][0] for kind in obs]
start_time = min(start_times)
xlims = [start_time + 3, start_time + 60]
for i, kind in enumerate(obs):
ax = fig.add_subplot(n, 1, i+1)
ax.set_xlim(xlims)
t = obs[kind]['t']
res = obs[kind]['residual']
start_idx = bisect(t, xlims[0])
if len(res) == start_idx:
continue
ylim = max(np.linalg.norm(res[start_idx:], axis=1))
ax.set_ylim([-ylim, ylim])
if int(kind) in SAT_OBS:
svIds = obs[kind]['svIds']
for svId in set(svIds):
svId_idx = (svIds == svId)
t = obs[kind]['t'][svId_idx]
res = obs[kind]['residual'][svId_idx]
ax.plot(t, res, label='SV ' + str(int(svId)))
ax.legend(loc='right')
else:
ax.plot(t, res)
plt.title('Residual of kind ' + ObservationKind.to_string(int(kind)), fontsize=20)
plt.tight_layout()
os.makedirs(save_path)
mpld3.save_html(fig, save_path + 'residuals_plot.html')

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selfdrive/locationd/kalman/helpers/chi2_lookup.py 100644
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import os
import numpy as np
def gen_chi2_ppf_lookup(max_dim=200):
from scipy.stats import chi2
table = np.zeros((max_dim, 98))
for dim in range(1, max_dim):
table[dim] = chi2.ppf(np.arange(.01, .99, .01), dim)
np.save('chi2_lookup_table', table)
def chi2_ppf(p, dim):
table = np.load(os.path.dirname(os.path.realpath(__file__)) + '/chi2_lookup_table.npy')
result = np.interp(p, np.arange(.01, .99, .01), table[dim])
return result
if __name__ == "__main__":
gen_chi2_ppf_lookup()

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selfdrive/locationd/kalman/helpers/chi2_lookup_table.npy 100644
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selfdrive/locationd/kalman/helpers/ekf_sym.py 100644
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import os
from bisect import bisect_right
import numpy as np
import sympy as sp
from numpy import dot
from selfdrive.locationd.kalman.helpers.sympy_helpers import sympy_into_c
from selfdrive.locationd.kalman.helpers import (TEMPLATE_DIR, load_code,
write_code)
from selfdrive.locationd.kalman.helpers.chi2_lookup import chi2_ppf
def solve(a, b):
if a.shape[0] == 1 and a.shape[1] == 1:
return b / a[0][0]
else:
return np.linalg.solve(a, b)
def null(H, eps=1e-12):
u, s, vh = np.linalg.svd(H)
padding = max(0, np.shape(H)[1] - np.shape(s)[0])
null_mask = np.concatenate(((s <= eps), np.ones((padding,), dtype=bool)), axis=0)
null_space = np.compress(null_mask, vh, axis=0)
return np.transpose(null_space)
def gen_code(name, f_sym, dt_sym, x_sym, obs_eqs, dim_x, dim_err, eskf_params=None, msckf_params=None, maha_test_kinds=[]):
# optional state transition matrix, H modifier
# and err_function if an error-state kalman filter (ESKF)
# is desired. Best described in "Quaternion kinematics
# for the error-state Kalman filter" by Joan Sola
if eskf_params:
err_eqs = eskf_params[0]
inv_err_eqs = eskf_params[1]
H_mod_sym = eskf_params[2]
f_err_sym = eskf_params[3]
x_err_sym = eskf_params[4]
else:
nom_x = sp.MatrixSymbol('nom_x', dim_x, 1)
true_x = sp.MatrixSymbol('true_x', dim_x, 1)
delta_x = sp.MatrixSymbol('delta_x', dim_x, 1)
err_function_sym = sp.Matrix(nom_x + delta_x)
inv_err_function_sym = sp.Matrix(true_x - nom_x)
err_eqs = [err_function_sym, nom_x, delta_x]
inv_err_eqs = [inv_err_function_sym, nom_x, true_x]
H_mod_sym = sp.Matrix(np.eye(dim_x))
f_err_sym = f_sym
x_err_sym = x_sym
# This configures the multi-state augmentation
# needed for EKF-SLAM with MSCKF (Mourikis et al 2007)
if msckf_params:
msckf = True
dim_main = msckf_params[0] # size of the main state
dim_augment = msckf_params[1] # size of one augment state chunk
dim_main_err = msckf_params[2]
dim_augment_err = msckf_params[3]
N = msckf_params[4]
feature_track_kinds = msckf_params[5]
assert dim_main + dim_augment * N == dim_x
assert dim_main_err + dim_augment_err * N == dim_err
else:
msckf = False
dim_main = dim_x
dim_augment = 0
dim_main_err = dim_err
dim_augment_err = 0
N = 0
# linearize with jacobians
F_sym = f_err_sym.jacobian(x_err_sym)
for sym in x_err_sym:
F_sym = F_sym.subs(sym, 0)
for i in range(len(obs_eqs)):
obs_eqs[i].append(obs_eqs[i][0].jacobian(x_sym))
if msckf and obs_eqs[i][1] in feature_track_kinds:
obs_eqs[i].append(obs_eqs[i][0].jacobian(obs_eqs[i][2]))
else:
obs_eqs[i].append(None)
# collect sympy functions
sympy_functions = []
# error functions
sympy_functions.append(('err_fun', err_eqs[0], [err_eqs[1], err_eqs[2]]))
sympy_functions.append(('inv_err_fun', inv_err_eqs[0], [inv_err_eqs[1], inv_err_eqs[2]]))
# H modifier for ESKF updates
sympy_functions.append(('H_mod_fun', H_mod_sym, [x_sym]))
# state propagation function
sympy_functions.append(('f_fun', f_sym, [x_sym, dt_sym]))
sympy_functions.append(('F_fun', F_sym, [x_sym, dt_sym]))
# observation functions
for h_sym, kind, ea_sym, H_sym, He_sym in obs_eqs:
sympy_functions.append(('h_%d' % kind, h_sym, [x_sym, ea_sym]))
sympy_functions.append(('H_%d' % kind, H_sym, [x_sym, ea_sym]))
if msckf and kind in feature_track_kinds:
sympy_functions.append(('He_%d' % kind, He_sym, [x_sym, ea_sym]))
# Generate and wrap all th c code
header, code = sympy_into_c(sympy_functions)
extra_header = "#define DIM %d\n" % dim_x
extra_header += "#define EDIM %d\n" % dim_err
extra_header += "#define MEDIM %d\n" % dim_main_err
extra_header += "typedef void (*Hfun)(double *, double *, double *);\n"
extra_header += "\nvoid predict(double *x, double *P, double *Q, double dt);"
extra_post = ""
for h_sym, kind, ea_sym, H_sym, He_sym in obs_eqs:
if msckf and kind in feature_track_kinds:
He_str = 'He_%d' % kind
# ea_dim = ea_sym.shape[0]
else:
He_str = 'NULL'
# ea_dim = 1 # not really dim of ea but makes c function work
maha_thresh = chi2_ppf(0.95, int(h_sym.shape[0])) # mahalanobis distance for outlier detection
maha_test = kind in maha_test_kinds
extra_post += """
void update_%d(double *in_x, double *in_P, double *in_z, double *in_R, double *in_ea) {
update<%d,%d,%d>(in_x, in_P, h_%d, H_%d, %s, in_z, in_R, in_ea, MAHA_THRESH_%d);
}
""" % (kind, h_sym.shape[0], 3, maha_test, kind, kind, He_str, kind)
extra_header += "\nconst static double MAHA_THRESH_%d = %f;" % (kind, maha_thresh)
extra_header += "\nvoid update_%d(double *, double *, double *, double *, double *);" % kind
code += '\nextern "C"{\n' + extra_header + "\n}\n"
code += "\n" + open(os.path.join(TEMPLATE_DIR, "ekf_c.c")).read()
code += '\nextern "C"{\n' + extra_post + "\n}\n"
header += "\n" + extra_header
write_code(name, code, header)
class EKF_sym():
def __init__(self, name, Q, x_initial, P_initial, dim_main, dim_main_err,
N=0, dim_augment=0, dim_augment_err=0, maha_test_kinds=[]):
"""Generates process function and all observation functions for the kalman filter."""
self.msckf = N > 0
self.N = N
self.dim_augment = dim_augment
self.dim_augment_err = dim_augment_err
self.dim_main = dim_main
self.dim_main_err = dim_main_err
# state
x_initial = x_initial.reshape((-1, 1))
self.dim_x = x_initial.shape[0]
self.dim_err = P_initial.shape[0]
assert dim_main + dim_augment * N == self.dim_x
assert dim_main_err + dim_augment_err * N == self.dim_err
assert Q.shape == P_initial.shape
# kinds that should get mahalanobis distance
# tested for outlier rejection
self.maha_test_kinds = maha_test_kinds
# process noise
self.Q = Q
# rewind stuff
self.rewind_t = []
self.rewind_states = []
self.rewind_obscache = []
self.init_state(x_initial, P_initial, None)
ffi, lib = load_code(name)
kinds, self.feature_track_kinds = [], []
for func in dir(lib):
if func[:2] == 'h_':
kinds.append(int(func[2:]))
if func[:3] == 'He_':
self.feature_track_kinds.append(int(func[3:]))
# wrap all the sympy functions
def wrap_1lists(name):
func = eval("lib.%s" % name, {"lib": lib})
def ret(lst1, out):
func(ffi.cast("double *", lst1.ctypes.data),
ffi.cast("double *", out.ctypes.data))
return ret
def wrap_2lists(name):
func = eval("lib.%s" % name, {"lib": lib})
def ret(lst1, lst2, out):
func(ffi.cast("double *", lst1.ctypes.data),
ffi.cast("double *", lst2.ctypes.data),
ffi.cast("double *", out.ctypes.data))
return ret
def wrap_1list_1float(name):
func = eval("lib.%s" % name, {"lib": lib})
def ret(lst1, fl, out):
func(ffi.cast("double *", lst1.ctypes.data),
ffi.cast("double", fl),
ffi.cast("double *", out.ctypes.data))
return ret
self.f = wrap_1list_1float("f_fun")
self.F = wrap_1list_1float("F_fun")
self.err_function = wrap_2lists("err_fun")
self.inv_err_function = wrap_2lists("inv_err_fun")
self.H_mod = wrap_1lists("H_mod_fun")
self.hs, self.Hs, self.Hes = {}, {}, {}
for kind in kinds:
self.hs[kind] = wrap_2lists("h_%d" % kind)
self.Hs[kind] = wrap_2lists("H_%d" % kind)
if self.msckf and kind in self.feature_track_kinds:
self.Hes[kind] = wrap_2lists("He_%d" % kind)
# wrap the C++ predict function
def _predict_blas(x, P, dt):
lib.predict(ffi.cast("double *", x.ctypes.data),
ffi.cast("double *", P.ctypes.data),
ffi.cast("double *", self.Q.ctypes.data),
ffi.cast("double", dt))
return x, P
# wrap the C++ update function
def fun_wrapper(f, kind):
f = eval("lib.%s" % f, {"lib": lib})
def _update_inner_blas(x, P, z, R, extra_args):
f(ffi.cast("double *", x.ctypes.data),
ffi.cast("double *", P.ctypes.data),
ffi.cast("double *", z.ctypes.data),
ffi.cast("double *", R.ctypes.data),
ffi.cast("double *", extra_args.ctypes.data))
if self.msckf and kind in self.feature_track_kinds:
y = z[:-len(extra_args)]
else:
y = z
return x, P, y
return _update_inner_blas
self._updates = {}
for kind in kinds:
self._updates[kind] = fun_wrapper("update_%d" % kind, kind)
def _update_blas(x, P, kind, z, R, extra_args=[]):
return self._updates[kind](x, P, z, R, extra_args)
# assign the functions
self._predict = _predict_blas
# self._predict = self._predict_python
self._update = _update_blas
# self._update = self._update_python
def init_state(self, state, covs, filter_time):
self.x = np.array(state.reshape((-1, 1))).astype(np.float64)
self.P = np.array(covs).astype(np.float64)
self.filter_time = filter_time
self.augment_times = [0] * self.N
self.rewind_obscache = []
self.rewind_t = []
self.rewind_states = []
def augment(self):
# TODO this is not a generalized way of doing this and implies that the augmented states
# are simply the first (dim_augment_state) elements of the main state.
assert self.msckf
d1 = self.dim_main
d2 = self.dim_main_err
d3 = self.dim_augment
d4 = self.dim_augment_err
# push through augmented states
self.x[d1:-d3] = self.x[d1 + d3:]
self.x[-d3:] = self.x[:d3]
assert self.x.shape == (self.dim_x, 1)
# push through augmented covs
assert self.P.shape == (self.dim_err, self.dim_err)
P_reduced = self.P
P_reduced = np.delete(P_reduced, np.s_[d2:d2 + d4], axis=1)
P_reduced = np.delete(P_reduced, np.s_[d2:d2 + d4], axis=0)
assert P_reduced.shape == (self.dim_err - d4, self.dim_err - d4)
to_mult = np.zeros((self.dim_err, self.dim_err - d4))
to_mult[:-d4, :] = np.eye(self.dim_err - d4)
to_mult[-d4:, :d4] = np.eye(d4)
self.P = to_mult.dot(P_reduced.dot(to_mult.T))
self.augment_times = self.augment_times[1:]
self.augment_times.append(self.filter_time)
assert self.P.shape == (self.dim_err, self.dim_err)
def state(self):
return np.array(self.x).flatten()
def covs(self):
return self.P
def rewind(self, t):
# find where we are rewinding to
idx = bisect_right(self.rewind_t, t)
assert self.rewind_t[idx - 1] <= t
assert self.rewind_t[idx] > t # must be true, or rewind wouldn't be called
# set the state to the time right before that
self.filter_time = self.rewind_t[idx - 1]
self.x[:] = self.rewind_states[idx - 1][0]
self.P[:] = self.rewind_states[idx - 1][1]
# return the observations we rewound over for fast forwarding
ret = self.rewind_obscache[idx:]
# throw away the old future
# TODO: is this making a copy?
self.rewind_t = self.rewind_t[:idx]
self.rewind_states = self.rewind_states[:idx]
self.rewind_obscache = self.rewind_obscache[:idx]
return ret
def checkpoint(self, obs):
# push to rewinder
self.rewind_t.append(self.filter_time)
self.rewind_states.append((np.copy(self.x), np.copy(self.P)))
self.rewind_obscache.append(obs)
# only keep a certain number around
REWIND_TO_KEEP = 512
self.rewind_t = self.rewind_t[-REWIND_TO_KEEP:]
self.rewind_states = self.rewind_states[-REWIND_TO_KEEP:]
self.rewind_obscache = self.rewind_obscache[-REWIND_TO_KEEP:]
def predict_and_update_batch(self, t, kind, z, R, extra_args=[[]], augment=False):
# TODO handle rewinding at this level"
# rewind
if self.filter_time is not None and t < self.filter_time:
if len(self.rewind_t) == 0 or t < self.rewind_t[0] or t < self.rewind_t[-1] - 1.0:
print("observation too old at %.3f with filter at %.3f, ignoring" % (t, self.filter_time))
return None
rewound = self.rewind(t)
else:
rewound = []
ret = self._predict_and_update_batch(t, kind, z, R, extra_args, augment)
# optional fast forward
for r in rewound:
self._predict_and_update_batch(*r)
return ret
def _predict_and_update_batch(self, t, kind, z, R, extra_args, augment=False):
"""The main kalman filter function
Predicts the state and then updates a batch of observations
dim_x: dimensionality of the state space
dim_z: dimensionality of the observation and depends on kind
n: number of observations
Args:
t (float): Time of observation
kind (int): Type of observation
z (vec [n,dim_z]): Measurements
R (mat [n,dim_z, dim_z]): Measurement Noise
extra_args (list, [n]): Values used in H computations
"""
# initialize time
if self.filter_time is None:
self.filter_time = t
# predict
dt = t - self.filter_time
assert dt >= 0
self.x, self.P = self._predict(self.x, self.P, dt)
self.filter_time = t
xk_km1, Pk_km1 = np.copy(self.x).flatten(), np.copy(self.P)
# update batch
y = []
for i in range(len(z)):
# these are from the user, so we canonicalize them
z_i = np.array(z[i], dtype=np.float64, order='F')
R_i = np.array(R[i], dtype=np.float64, order='F')
extra_args_i = np.array(extra_args[i], dtype=np.float64, order='F')
# update
self.x, self.P, y_i = self._update(self.x, self.P, kind, z_i, R_i, extra_args=extra_args_i)
y.append(y_i)
xk_k, Pk_k = np.copy(self.x).flatten(), np.copy(self.P)
if augment:
self.augment()
# checkpoint
self.checkpoint((t, kind, z, R, extra_args))
return xk_km1, xk_k, Pk_km1, Pk_k, t, kind, y, z, extra_args
def _predict_python(self, x, P, dt):
x_new = np.zeros(x.shape, dtype=np.float64)
self.f(x, dt, x_new)
F = np.zeros(P.shape, dtype=np.float64)
self.F(x, dt, F)
if not self.msckf:
P = dot(dot(F, P), F.T)
else:
# Update the predicted state covariance:
# Pk+1|k = |F*Pii*FT + Q*dt F*Pij |
# |PijT*FT Pjj |
# Where F is the jacobian of the main state
# predict function, Pii is the main state's
# covariance and Q its process noise. Pij
# is the covariance between the augmented
# states and the main state.
#
d2 = self.dim_main_err # known at compile time
F_curr = F[:d2, :d2]
P[:d2, :d2] = (F_curr.dot(P[:d2, :d2])).dot(F_curr.T)
P[:d2, d2:] = F_curr.dot(P[:d2, d2:])
P[d2:, :d2] = P[d2:, :d2].dot(F_curr.T)
P += dt * self.Q
return x_new, P
def _update_python(self, x, P, kind, z, R, extra_args=[]):
# init vars
z = z.reshape((-1, 1))
h = np.zeros(z.shape, dtype=np.float64)
H = np.zeros((z.shape[0], self.dim_x), dtype=np.float64)
# C functions
self.hs[kind](x, extra_args, h)
self.Hs[kind](x, extra_args, H)
# y is the "loss"
y = z - h
# *** same above this line ***
if self.msckf and kind in self.Hes:
# Do some algebraic magic to decorrelate
He = np.zeros((z.shape[0], len(extra_args)), dtype=np.float64)
self.Hes[kind](x, extra_args, He)
# TODO: Don't call a function here, do projection locally
A = null(He.T)
y = A.T.dot(y)
H = A.T.dot(H)
R = A.T.dot(R.dot(A))
# TODO If nullspace isn't the dimension we want
if A.shape[1] + He.shape[1] != A.shape[0]:
print('Warning: null space projection failed, measurement ignored')
return x, P, np.zeros(A.shape[0] - He.shape[1])
# if using eskf
H_mod = np.zeros((x.shape[0], P.shape[0]), dtype=np.float64)
self.H_mod(x, H_mod)
H = H.dot(H_mod)
# Do mahalobis distance test
# currently just runs on msckf observations
# could run on anything if needed
if self.msckf and kind in self.maha_test_kinds:
a = np.linalg.inv(H.dot(P).dot(H.T) + R)
maha_dist = y.T.dot(a.dot(y))
if maha_dist > chi2_ppf(0.95, y.shape[0]):
R = 10e16 * R
# *** same below this line ***
# Outlier resilient weighting as described in:
# "A Kalman Filter for Robust Outlier Detection - Jo-Anne Ting, ..."
weight = 1 # (1.5)/(1 + np.sum(y**2)/np.sum(R))
S = dot(dot(H, P), H.T) + R / weight
K = solve(S, dot(H, P.T)).T
I_KH = np.eye(P.shape[0]) - dot(K, H)
# update actual state
delta_x = dot(K, y)
P = dot(dot(I_KH, P), I_KH.T) + dot(dot(K, R), K.T)
# inject observed error into state
x_new = np.zeros(x.shape, dtype=np.float64)
self.err_function(x, delta_x, x_new)
return x_new, P, y.flatten()
def maha_test(self, x, P, kind, z, R, extra_args=[], maha_thresh=0.95):
# init vars
z = z.reshape((-1, 1))
h = np.zeros(z.shape, dtype=np.float64)
H = np.zeros((z.shape[0], self.dim_x), dtype=np.float64)
# C functions
self.hs[kind](x, extra_args, h)
self.Hs[kind](x, extra_args, H)
# y is the "loss"
y = z - h
# if using eskf
H_mod = np.zeros((x.shape[0], P.shape[0]), dtype=np.float64)
self.H_mod(x, H_mod)
H = H.dot(H_mod)
a = np.linalg.inv(H.dot(P).dot(H.T) + R)
maha_dist = y.T.dot(a.dot(y))
if maha_dist > chi2_ppf(maha_thresh, y.shape[0]):
return False
else:
return True
def rts_smooth(self, estimates, norm_quats=False):
'''
Returns rts smoothed results of
kalman filter estimates
If the kalman state is augmented with
old states only the main state is smoothed
'''
xk_n = estimates[-1][0]
Pk_n = estimates[-1][2]
Fk_1 = np.zeros(Pk_n.shape, dtype=np.float64)
states_smoothed = [xk_n]
covs_smoothed = [Pk_n]
for k in range(len(estimates) - 2, -1, -1):
xk1_n = xk_n
if norm_quats:
xk1_n[3:7] /= np.linalg.norm(xk1_n[3:7])
Pk1_n = Pk_n
xk1_k, _, Pk1_k, _, t2, _, _, _, _ = estimates[k + 1]
_, xk_k, _, Pk_k, t1, _, _, _, _ = estimates[k]
dt = t2 - t1
self.F(xk_k, dt, Fk_1)
d1 = self.dim_main
d2 = self.dim_main_err
Ck = np.linalg.solve(Pk1_k[:d2, :d2], Fk_1[:d2, :d2].dot(Pk_k[:d2, :d2].T)).T
xk_n = xk_k
delta_x = np.zeros((Pk_n.shape[0], 1), dtype=np.float64)
self.inv_err_function(xk1_k, xk1_n, delta_x)
delta_x[:d2] = Ck.dot(delta_x[:d2])
x_new = np.zeros((xk_n.shape[0], 1), dtype=np.float64)
self.err_function(xk_k, delta_x, x_new)
xk_n[:d1] = x_new[:d1, 0]
Pk_n = Pk_k
Pk_n[:d2, :d2] = Pk_k[:d2, :d2] + Ck.dot(Pk1_n[:d2, :d2] - Pk1_k[:d2, :d2]).dot(Ck.T)
states_smoothed.append(xk_n)
covs_smoothed.append(Pk_n)
return np.flipud(np.vstack(states_smoothed)), np.stack(covs_smoothed, 0)[::-1]

158
selfdrive/locationd/kalman/helpers/feature_handler.py 100755
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@ -0,0 +1,158 @@
#!/usr/bin/env python3
import os
import numpy as np
import common.transformations.orientation as orient
from selfdrive.locationd.kalman.helpers import (TEMPLATE_DIR, load_code,
write_code)
from selfdrive.locationd.kalman.helpers.sympy_helpers import quat_matrix_l
def sane(track):
img_pos = track[1:, 2:4]
diffs_x = abs(img_pos[1:, 0] - img_pos[:-1, 0])
diffs_y = abs(img_pos[1:, 1] - img_pos[:-1, 1])
for i in range(1, len(diffs_x)):
if ((diffs_x[i] > 0.05 or diffs_x[i - 1] > 0.05) and
(diffs_x[i] > 2 * diffs_x[i - 1] or
diffs_x[i] < .5 * diffs_x[i - 1])) or \
((diffs_y[i] > 0.05 or diffs_y[i - 1] > 0.05) and
(diffs_y[i] > 2 * diffs_y[i - 1] or
diffs_y[i] < .5 * diffs_y[i - 1])):
return False
return True
class FeatureHandler():
name = 'feature_handler'
@staticmethod
def generate_code(K=5):
# Wrap c code for slow matching
c_header = "\nvoid merge_features(double *tracks, double *features, long long *empty_idxs);"
c_code = "#include <math.h>\n"
c_code += "#include <string.h>\n"
c_code += "#define K %d\n" % K
c_code += "\n" + open(os.path.join(TEMPLATE_DIR, "feature_handler.c")).read()
filename = f"{FeatureHandler.name}_{K}"
write_code(filename, c_code, c_header)
def __init__(self, K=5):
self.MAX_TRACKS = 6000
self.K = K
# Array of tracks, each track has K 5D features preceded
# by 5 params that inidicate [f_idx, last_idx, updated, complete, valid]
# f_idx: idx of current last feature in track
# idx of of last feature in frame
# bool for whether this track has been update
# bool for whether this track is complete
# bool for whether this track is valid
self.tracks = np.zeros((self.MAX_TRACKS, K + 1, 5))
self.tracks[:] = np.nan
name = f"{FeatureHandler.name}_{K}"
ffi, lib = load_code(name)
def merge_features_c(tracks, features, empty_idxs):
lib.merge_features(ffi.cast("double *", tracks.ctypes.data),
ffi.cast("double *", features.ctypes.data),
ffi.cast("long long *", empty_idxs.ctypes.data))
# self.merge_features = self.merge_features_python
self.merge_features = merge_features_c
def reset(self):
self.tracks[:] = np.nan
def merge_features_python(self, tracks, features, empty_idxs):
empty_idx = 0
for f in features:
match_idx = int(f[4])
if tracks[match_idx, 0, 1] == match_idx and tracks[match_idx, 0, 2] == 0:
tracks[match_idx, 0, 0] += 1
tracks[match_idx, 0, 1] = f[1]
tracks[match_idx, 0, 2] = 1
tracks[match_idx, int(tracks[match_idx, 0, 0])] = f
if tracks[match_idx, 0, 0] == self.K:
tracks[match_idx, 0, 3] = 1
if sane(tracks[match_idx]):
tracks[match_idx, 0, 4] = 1
else:
if empty_idx == len(empty_idxs):
print('need more empty space')
continue
tracks[empty_idxs[empty_idx], 0, 0] = 1
tracks[empty_idxs[empty_idx], 0, 1] = f[1]
tracks[empty_idxs[empty_idx], 0, 2] = 1
tracks[empty_idxs[empty_idx], 1] = f
empty_idx += 1
def update_tracks(self, features):
last_idxs = np.copy(self.tracks[:, 0, 1])
real = np.isfinite(last_idxs)
self.tracks[last_idxs[real].astype(int)] = self.tracks[real]
mask = np.ones(self.MAX_TRACKS, np.bool)
mask[last_idxs[real].astype(int)] = 0
empty_idxs = np.arange(self.MAX_TRACKS)[mask]
self.tracks[empty_idxs] = np.nan
self.tracks[:, 0, 2] = 0
self.merge_features(self.tracks, features, empty_idxs)
def handle_features(self, features):
self.update_tracks(features)
valid_idxs = self.tracks[:, 0, 4] == 1
complete_idxs = self.tracks[:, 0, 3] == 1
stale_idxs = self.tracks[:, 0, 2] == 0
valid_tracks = self.tracks[valid_idxs]
self.tracks[complete_idxs] = np.nan
self.tracks[stale_idxs] = np.nan
return valid_tracks[:, 1:, :4].reshape((len(valid_tracks), self.K * 4))
def generate_orient_error_jac(K):
import sympy as sp
from selfdrive.locationd.kalman.helpers.sympy_helpers import quat_rotate
x_sym = sp.MatrixSymbol('abr', 3, 1)
dtheta = sp.MatrixSymbol('dtheta', 3, 1)
delta_quat = sp.Matrix(np.ones(4))
delta_quat[1:, :] = sp.Matrix(0.5 * dtheta[0:3, :])
poses_sym = sp.MatrixSymbol('poses', 7 * K, 1)
img_pos_sym = sp.MatrixSymbol('img_positions', 2 * K, 1)
alpha, beta, rho = x_sym
to_c = sp.Matrix(orient.rot_matrix(-np.pi / 2, -np.pi / 2, 0))
pos_0 = sp.Matrix(np.array(poses_sym[K * 7 - 7:K * 7 - 4])[:, 0])
q = quat_matrix_l(poses_sym[K * 7 - 4:K * 7]) * delta_quat
quat_rot = quat_rotate(*q)
rot_g_to_0 = to_c * quat_rot.T
rows = []
for i in range(K):
pos_i = sp.Matrix(np.array(poses_sym[i * 7:i * 7 + 3])[:, 0])
q = quat_matrix_l(poses_sym[7 * i + 3:7 * i + 7]) * delta_quat
quat_rot = quat_rotate(*q)
rot_g_to_i = to_c * quat_rot.T
rot_0_to_i = rot_g_to_i * (rot_g_to_0.T)
trans_0_to_i = rot_g_to_i * (pos_0 - pos_i)
funct_vec = rot_0_to_i * sp.Matrix([alpha, beta, 1]) + rho * trans_0_to_i
h1, h2, h3 = funct_vec
rows.append(h1 / h3 - img_pos_sym[i * 2 + 0])
rows.append(h2 / h3 - img_pos_sym[i * 2 + 1])
img_pos_residual_sym = sp.Matrix(rows)
# sympy into c
sympy_functions = []
sympy_functions.append(('orient_error_jac', img_pos_residual_sym.jacobian(dtheta), [x_sym, poses_sym, img_pos_sym, dtheta]))
return sympy_functions
if __name__ == "__main__":
# TODO: get K from argparse
FeatureHandler.generate_code()

176
selfdrive/locationd/kalman/helpers/lst_sq_computer.py 100755
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@ -0,0 +1,176 @@
#!/usr/bin/env python3
import os
import sys
import numpy as np
import sympy as sp
import common.transformations.orientation as orient
from selfdrive.locationd.kalman.helpers import (TEMPLATE_DIR, load_code,
write_code)
from selfdrive.locationd.kalman.helpers.sympy_helpers import (quat_rotate,
sympy_into_c)
def generate_residual(K):
x_sym = sp.MatrixSymbol('abr', 3, 1)
poses_sym = sp.MatrixSymbol('poses', 7 * K, 1)
img_pos_sym = sp.MatrixSymbol('img_positions', 2 * K, 1)
alpha, beta, rho = x_sym
to_c = sp.Matrix(orient.rot_matrix(-np.pi / 2, -np.pi / 2, 0))
pos_0 = sp.Matrix(np.array(poses_sym[K * 7 - 7:K * 7 - 4])[:, 0])
q = poses_sym[K * 7 - 4:K * 7]
quat_rot = quat_rotate(*q)
rot_g_to_0 = to_c * quat_rot.T
rows = []
for i in range(K):
pos_i = sp.Matrix(np.array(poses_sym[i * 7:i * 7 + 3])[:, 0])
q = poses_sym[7 * i + 3:7 * i + 7]
quat_rot = quat_rotate(*q)
rot_g_to_i = to_c * quat_rot.T
rot_0_to_i = rot_g_to_i * rot_g_to_0.T
trans_0_to_i = rot_g_to_i * (pos_0 - pos_i)
funct_vec = rot_0_to_i * sp.Matrix([alpha, beta, 1]) + rho * trans_0_to_i
h1, h2, h3 = funct_vec
rows.append(h1 / h3 - img_pos_sym[i * 2 + 0])
rows.append(h2 / h3 - img_pos_sym[i * 2 + 1])
img_pos_residual_sym = sp.Matrix(rows)
# sympy into c
sympy_functions = []
sympy_functions.append(('res_fun', img_pos_residual_sym, [x_sym, poses_sym, img_pos_sym]))
sympy_functions.append(('jac_fun', img_pos_residual_sym.jacobian(x_sym), [x_sym, poses_sym, img_pos_sym]))
return sympy_functions
class LstSqComputer():
name = 'pos_computer'
@staticmethod
def generate_code(K=4):
sympy_functions = generate_residual(K)
header, code = sympy_into_c(sympy_functions)
code += "\n#define KDIM %d\n" % K
code += "\n" + open(os.path.join(TEMPLATE_DIR, "compute_pos.c")).read()
header += """
void compute_pos(double *to_c, double *in_poses, double *in_img_positions, double *param, double *pos);
"""
filename = f"{LstSqComputer.name}_{K}"
write_code(filename, code, header)
def __init__(self, K=4, MIN_DEPTH=2, MAX_DEPTH=500):
self.to_c = orient.rot_matrix(-np.pi / 2, -np.pi / 2, 0)
self.MAX_DEPTH = MAX_DEPTH
self.MIN_DEPTH = MIN_DEPTH
name = f"{LstSqComputer.name}_{K}"
ffi, lib = load_code(name)
# wrap c functions
def residual_jac(x, poses, img_positions):
out = np.zeros(((K * 2, 3)), dtype=np.float64)
lib.jac_fun(ffi.cast("double *", x.ctypes.data),
ffi.cast("double *", poses.ctypes.data),
ffi.cast("double *", img_positions.ctypes.data),
ffi.cast("double *", out.ctypes.data))
return out
self.residual_jac = residual_jac
def residual(x, poses, img_positions):
out = np.zeros((K * 2), dtype=np.float64)
lib.res_fun(ffi.cast("double *", x.ctypes.data),
ffi.cast("double *", poses.ctypes.data),
ffi.cast("double *", img_positions.ctypes.data),
ffi.cast("double *", out.ctypes.data))
return out
self.residual = residual
def compute_pos_c(poses, img_positions):
pos = np.zeros(3, dtype=np.float64)
param = np.zeros(3, dtype=np.float64)
# Can't be a view for the ctype
img_positions = np.copy(img_positions)
lib.compute_pos(ffi.cast("double *", self.to_c.ctypes.data),
ffi.cast("double *", poses.ctypes.data),
ffi.cast("double *", img_positions.ctypes.data),
ffi.cast("double *", param.ctypes.data),
ffi.cast("double *", pos.ctypes.data))
return pos, param
self.compute_pos_c = compute_pos_c
def compute_pos(self, poses, img_positions, debug=False):
pos, param = self.compute_pos_c(poses, img_positions)
# pos, param = self.compute_pos_python(poses, img_positions)
depth = 1 / param[2]
if debug:
# orient_err_jac = self.orient_error_jac(param, poses, img_positions, np.zeros(3)).reshape((-1,2,3))
jac = self.residual_jac(param, poses, img_positions).reshape((-1, 2, 3))
res = self.residual(param, poses, img_positions).reshape((-1, 2))
return pos, param, res, jac # , orient_err_jac
elif (self.MIN_DEPTH < depth < self.MAX_DEPTH):
return pos
else:
return None
def gauss_newton(self, fun, jac, x, args):
poses, img_positions = args
delta = 1
counter = 0
while abs(np.linalg.norm(delta)) > 1e-4 and counter < 30:
delta = np.linalg.pinv(jac(x, poses, img_positions)).dot(fun(x, poses, img_positions))
x = x - delta
counter += 1
return [x]
def compute_pos_python(self, poses, img_positions, check_quality=False):
import scipy.optimize as opt
# This procedure is also described
# in the MSCKF paper (Mourikis et al. 2007)
x = np.array([img_positions[-1][0],
img_positions[-1][1], 0.1])
res = opt.leastsq(self.residual, x, Dfun=self.residual_jac, args=(poses, img_positions)) # scipy opt
# res = self.gauss_newton(self.residual, self.residual_jac, x, (poses, img_positions)) # diy gauss_newton
alpha, beta, rho = res[0]
rot_0_to_g = (orient.rotations_from_quats(poses[-1, 3:])).dot(self.to_c.T)
return (rot_0_to_g.dot(np.array([alpha, beta, 1]))) / rho + poses[-1, :3]
# EXPERIMENTAL CODE
def unroll_shutter(img_positions, poses, v, rot_rates, ecef_pos):
# only speed correction for now
t_roll = 0.016 # 16ms rolling shutter?
vroll, vpitch, vyaw = rot_rates
A = 0.5 * np.array([[-1, -vroll, -vpitch, -vyaw],
[vroll, 0, vyaw, -vpitch],
[vpitch, -vyaw, 0, vroll],
[vyaw, vpitch, -vroll, 0]])
q_dot = A.dot(poses[-1][3:7])
v = np.append(v, q_dot)
v = np.array([v[0], v[1], v[2], 0, 0, 0, 0])
current_pose = poses[-1] + v * 0.05
poses = np.vstack((current_pose, poses))
dt = -img_positions[:, 1] * t_roll / 0.48
errs = project(poses, ecef_pos) - project(poses + np.atleast_2d(dt).T.dot(np.atleast_2d(v)), ecef_pos)
return img_positions - errs
def project(poses, ecef_pos):
img_positions = np.zeros((len(poses), 2))
for i, p in enumerate(poses):
cam_frame = orient.rotations_from_quats(p[3:]).T.dot(ecef_pos - p[:3])
img_positions[i] = np.array([cam_frame[1] / cam_frame[0], cam_frame[2] / cam_frame[0]])
return img_positions
if __name__ == "__main__":
K = int(sys.argv[1].split("_")[-1])
LstSqComputer.generate_code(K=K)

51
common/sympy_helpers.py → selfdrive/locationd/kalman/helpers/sympy_helpers.py
View File

@ -2,31 +2,35 @@
import sympy as sp
import numpy as np
def cross(x):
ret = sp.Matrix(np.zeros((3,3)))
ret[0,1], ret[0,2] = -x[2], x[1]
ret[1,0], ret[1,2] = x[2], -x[0]
ret[2,0], ret[2,1] = -x[1], x[0]
ret = sp.Matrix(np.zeros((3, 3)))
ret[0, 1], ret[0, 2] = -x[2], x[1]
ret[1, 0], ret[1, 2] = x[2], -x[0]
ret[2, 0], ret[2, 1] = -x[1], x[0]
return ret
def euler_rotate(roll, pitch, yaw):
# make symbolic rotation matrix from eulers
matrix_roll = sp.Matrix([[1, 0, 0],
[0, sp.cos(roll), -sp.sin(roll)],
[0, sp.sin(roll), sp.cos(roll)]])
matrix_pitch = sp.Matrix([[sp.cos(pitch), 0, sp.sin(pitch)],
[0, 1, 0],
[-sp.sin(pitch), 0, sp.cos(pitch)]])
matrix_yaw = sp.Matrix([[sp.cos(yaw), -sp.sin(yaw), 0],
[sp.sin(yaw), sp.cos(yaw), 0],
[0, 0, 1]])
return matrix_yaw*matrix_pitch*matrix_roll
matrix_roll = sp.Matrix([[1, 0, 0],
[0, sp.cos(roll), -sp.sin(roll)],
[0, sp.sin(roll), sp.cos(roll)]])
matrix_pitch = sp.Matrix([[sp.cos(pitch), 0, sp.sin(pitch)],
[0, 1, 0],
[-sp.sin(pitch), 0, sp.cos(pitch)]])
matrix_yaw = sp.Matrix([[sp.cos(yaw), -sp.sin(yaw), 0],
[sp.sin(yaw), sp.cos(yaw), 0],
[0, 0, 1]])
return matrix_yaw * matrix_pitch * matrix_roll
def quat_rotate(q0, q1, q2, q3):
# make symbolic rotation matrix from quat
return sp.Matrix([[q0**2 + q1**2 - q2**2 - q3**2, 2*(q1*q2 + q0*q3), 2*(q1*q3 - q0*q2)],
[2*(q1*q2 - q0*q3), q0**2 - q1**2 + q2**2 - q3**2, 2*(q2*q3 + q0*q1)],
[2*(q1*q3 + q0*q2), 2*(q2*q3 - q0*q1), q0**2 - q1**2 - q2**2 + q3**2]]).T
return sp.Matrix([[q0**2 + q1**2 - q2**2 - q3**2, 2 * (q1 * q2 + q0 * q3), 2 * (q1 * q3 - q0 * q2)],
[2 * (q1 * q2 - q0 * q3), q0**2 - q1**2 + q2**2 - q3**2, 2 * (q2 * q3 + q0 * q1)],
[2 * (q1 * q3 + q0 * q2), 2 * (q2 * q3 - q0 * q1), q0**2 - q1**2 - q2**2 + q3**2]]).T
def quat_matrix_l(p):
return sp.Matrix([[p[0], -p[1], -p[2], -p[3]],
@ -34,6 +38,7 @@ def quat_matrix_l(p):
[p[2], p[3], p[0], -p[1]],
[p[3], -p[2], p[1], p[0]]])
def quat_matrix_r(p):
return sp.Matrix([[p[0], -p[1], -p[2], -p[3]],
[p[1], p[0], p[3], -p[2]],
@ -49,10 +54,11 @@ def sympy_into_c(sympy_functions):
# argument ordering input to sympy is broken with function with output arguments
nargs = []
# reorder the input arguments
for aa in args:
if aa is None:
nargs.append(codegen.InputArgument(sp.Symbol('unused'), dimensions=[1,1]))
nargs.append(codegen.InputArgument(sp.Symbol('unused'), dimensions=[1, 1]))
continue
found = False
for a in r.arguments:
@ -62,20 +68,23 @@ def sympy_into_c(sympy_functions):
break
if not found:
# [1,1] is a hack for Matrices
nargs.append(codegen.InputArgument(aa, dimensions=[1,1]))
nargs.append(codegen.InputArgument(aa, dimensions=[1, 1]))
# add the output arguments
for a in r.arguments:
if type(a) == codegen.OutputArgument:
nargs.append(a)
#assert len(r.arguments) == len(args)+1
# assert len(r.arguments) == len(args)+1
r.arguments = nargs
# add routine to list
routines.append(r)
[(c_name, c_code), (h_name, c_header)] = codegen.get_code_generator('C', 'ekf', 'C99').write(routines, "ekf")
c_header = '\n'.join(x for x in c_header.split("\n") if len(x) > 0 and x[0] != '#')
c_code = '\n'.join(x for x in c_code.split("\n") if len(x) > 0 and x[0] != '#')
c_header = '\n'.join(x for x in c_header.split("\n") if len(x) > 0 and x[0] != '#')
c_code = 'extern "C" {\n#include <math.h>\n' + c_code + "\n}\n"
return c_header, c_code

284
selfdrive/locationd/kalman/models/live_kf.py 100755
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@ -0,0 +1,284 @@
#!/usr/bin/env python3
import numpy as np
import sympy as sp
from selfdrive.locationd.kalman.helpers import KalmanError, ObservationKind
from selfdrive.locationd.kalman.helpers.ekf_sym import EKF_sym, gen_code
from selfdrive.locationd.kalman.helpers.sympy_helpers import (euler_rotate,
quat_matrix_r,
quat_rotate)
from selfdrive.swaglog import cloudlog
EARTH_GM = 3.986005e14 # m^3/s^2 (gravitational constant * mass of earth)
class States():
ECEF_POS = slice(0, 3) # x, y and z in ECEF in meters
ECEF_ORIENTATION = slice(3, 7) # quat for pose of phone in ecef
ECEF_VELOCITY = slice(7, 10) # ecef velocity in m/s
ANGULAR_VELOCITY = slice(10, 13) # roll, pitch and yaw rates in device frame in radians/s
GYRO_BIAS = slice(13, 16) # roll, pitch and yaw biases
ODO_SCALE = slice(16, 17) # odometer scale
ACCELERATION = slice(17, 20) # Acceleration in device frame in m/s**2
IMU_OFFSET = slice(20, 23) # imu offset angles in radians
# Error-state has different slices because it is an ESKF
ECEF_POS_ERR = slice(0, 3)
ECEF_ORIENTATION_ERR = slice(3, 6) # euler angles for orientation error
ECEF_VELOCITY_ERR = slice(6, 9)
ANGULAR_VELOCITY_ERR = slice(9, 12)
GYRO_BIAS_ERR = slice(12, 15)
ODO_SCALE_ERR = slice(15, 16)
ACCELERATION_ERR = slice(16, 19)
IMU_OFFSET_ERR = slice(19, 22)
class LiveKalman():
name = 'live'
initial_x = np.array([-2.7e6, 4.2e6, 3.8e6,
1, 0, 0, 0,
0, 0, 0,
0, 0, 0,
0, 0, 0,
1,
0, 0, 0,
0, 0, 0])
# state covariance
initial_P_diag = np.array([10000**2, 10000**2, 10000**2,
10**2, 10**2, 10**2,
10**2, 10**2, 10**2,
1**2, 1**2, 1**2,
0.05**2, 0.05**2, 0.05**2,
0.02**2,
1**2, 1**2, 1**2,
(0.01)**2, (0.01)**2, (0.01)**2])
# process noise
Q = np.diag([0.03**2, 0.03**2, 0.03**2,
0.0**2, 0.0**2, 0.0**2,
0.0**2, 0.0**2, 0.0**2,
0.1**2, 0.1**2, 0.1**2,
(0.005 / 100)**2, (0.005 / 100)**2, (0.005 / 100)**2,
(0.02 / 100)**2,
3**2, 3**2, 3**2,
(0.05 / 60)**2, (0.05 / 60)**2, (0.05 / 60)**2])
@staticmethod
def generate_code():
name = LiveKalman.name
dim_state = LiveKalman.initial_x.shape[0]
dim_state_err = LiveKalman.initial_P_diag.shape[0]
state_sym = sp.MatrixSymbol('state', dim_state, 1)
state = sp.Matrix(state_sym)
x, y, z = state[States.ECEF_POS, :]
q = state[States.ECEF_ORIENTATION, :]
v = state[States.ECEF_VELOCITY, :]
vx, vy, vz = v
omega = state[States.ANGULAR_VELOCITY, :]
vroll, vpitch, vyaw = omega
roll_bias, pitch_bias, yaw_bias = state[States.GYRO_BIAS, :]
odo_scale = state[States.ODO_SCALE, :][0,:]
acceleration = state[States.ACCELERATION, :]
imu_angles = state[States.IMU_OFFSET, :]
dt = sp.Symbol('dt')
# calibration and attitude rotation matrices
quat_rot = quat_rotate(*q)
# Got the quat predict equations from here
# A New Quaternion-Based Kalman Filter for
# Real-Time Attitude Estimation Using the Two-Step
# Geometrically-Intuitive Correction Algorithm
A = 0.5 * sp.Matrix([[0, -vroll, -vpitch, -vyaw],
[vroll, 0, vyaw, -vpitch],
[vpitch, -vyaw, 0, vroll],
[vyaw, vpitch, -vroll, 0]])
q_dot = A * q
# Time derivative of the state as a function of state
state_dot = sp.Matrix(np.zeros((dim_state, 1)))
state_dot[States.ECEF_POS, :] = v
state_dot[States.ECEF_ORIENTATION, :] = q_dot
state_dot[States.ECEF_VELOCITY, 0] = quat_rot * acceleration
# Basic descretization, 1st order intergrator
# Can be pretty bad if dt is big
f_sym = state + dt * state_dot
state_err_sym = sp.MatrixSymbol('state_err', dim_state_err, 1)
state_err = sp.Matrix(state_err_sym)
quat_err = state_err[States.ECEF_ORIENTATION_ERR, :]
v_err = state_err[States.ECEF_VELOCITY_ERR, :]
omega_err = state_err[States.ANGULAR_VELOCITY_ERR, :]
acceleration_err = state_err[States.ACCELERATION_ERR, :]
# Time derivative of the state error as a function of state error and state
quat_err_matrix = euler_rotate(quat_err[0], quat_err[1], quat_err[2])
q_err_dot = quat_err_matrix * quat_rot * (omega + omega_err)
state_err_dot = sp.Matrix(np.zeros((dim_state_err, 1)))
state_err_dot[States.ECEF_POS_ERR, :] = v_err
state_err_dot[States.ECEF_ORIENTATION_ERR, :] = q_err_dot
state_err_dot[States.ECEF_VELOCITY_ERR, :] = quat_err_matrix * quat_rot * (acceleration + acceleration_err)
f_err_sym = state_err + dt * state_err_dot
# Observation matrix modifier
H_mod_sym = sp.Matrix(np.zeros((dim_state, dim_state_err)))
H_mod_sym[States.ECEF_POS, States.ECEF_POS_ERR] = np.eye(States.ECEF_POS.stop - States.ECEF_POS.start)
H_mod_sym[States.ECEF_ORIENTATION, States.ECEF_ORIENTATION_ERR] = 0.5 * quat_matrix_r(state[3:7])[:, 1:]
H_mod_sym[States.ECEF_ORIENTATION.stop:, States.ECEF_ORIENTATION_ERR.stop:] = np.eye(dim_state - States.ECEF_ORIENTATION.stop)
# these error functions are defined so that say there
# is a nominal x and true x:
# true x = err_function(nominal x, delta x)
# delta x = inv_err_function(nominal x, true x)
nom_x = sp.MatrixSymbol('nom_x', dim_state, 1)
true_x = sp.MatrixSymbol('true_x', dim_state, 1)
delta_x = sp.MatrixSymbol('delta_x', dim_state_err, 1)
err_function_sym = sp.Matrix(np.zeros((dim_state, 1)))
delta_quat = sp.Matrix(np.ones((4)))
delta_quat[1:, :] = sp.Matrix(0.5 * delta_x[States.ECEF_ORIENTATION_ERR, :])
err_function_sym[States.ECEF_POS, :] = sp.Matrix(nom_x[States.ECEF_POS, :] + delta_x[States.ECEF_POS_ERR, :])
err_function_sym[States.ECEF_ORIENTATION, 0] = quat_matrix_r(nom_x[States.ECEF_ORIENTATION, 0]) * delta_quat
err_function_sym[States.ECEF_ORIENTATION.stop:, :] = sp.Matrix(nom_x[States.ECEF_ORIENTATION.stop:, :] + delta_x[States.ECEF_ORIENTATION_ERR.stop:, :])
inv_err_function_sym = sp.Matrix(np.zeros((dim_state_err, 1)))
inv_err_function_sym[States.ECEF_POS_ERR, 0] = sp.Matrix(-nom_x[States.ECEF_POS, 0] + true_x[States.ECEF_POS, 0])
delta_quat = quat_matrix_r(nom_x[States.ECEF_ORIENTATION, 0]).T * true_x[States.ECEF_ORIENTATION, 0]
inv_err_function_sym[States.ECEF_ORIENTATION_ERR, 0] = sp.Matrix(2 * delta_quat[1:])
inv_err_function_sym[States.ECEF_ORIENTATION_ERR.stop:, 0] = sp.Matrix(-nom_x[States.ECEF_ORIENTATION.stop:, 0] + true_x[States.ECEF_ORIENTATION.stop:, 0])
eskf_params = [[err_function_sym, nom_x, delta_x],
[inv_err_function_sym, nom_x, true_x],
H_mod_sym, f_err_sym, state_err_sym]
#
# Observation functions
#
imu_rot = euler_rotate(*imu_angles)
h_gyro_sym = imu_rot * sp.Matrix([vroll + roll_bias,
vpitch + pitch_bias,
vyaw + yaw_bias])
pos = sp.Matrix([x, y, z])
gravity = quat_rot.T * ((EARTH_GM / ((x**2 + y**2 + z**2)**(3.0 / 2.0))) * pos)
h_acc_sym = imu_rot * (gravity + acceleration)
h_phone_rot_sym = sp.Matrix([vroll, vpitch, vyaw])
speed = sp.sqrt(vx**2 + vy**2 + vz**2)
h_speed_sym = sp.Matrix([speed * odo_scale])
h_pos_sym = sp.Matrix([x, y, z])
h_imu_frame_sym = sp.Matrix(imu_angles)
h_relative_motion = sp.Matrix(quat_rot.T * v)
obs_eqs = [[h_speed_sym, ObservationKind.ODOMETRIC_SPEED, None],
[h_gyro_sym, ObservationKind.PHONE_GYRO, None],
[h_phone_rot_sym, ObservationKind.NO_ROT, None],
[h_acc_sym, ObservationKind.PHONE_ACCEL, None],
[h_pos_sym, ObservationKind.ECEF_POS, None],
[h_relative_motion, ObservationKind.CAMERA_ODO_TRANSLATION, None],
[h_phone_rot_sym, ObservationKind.CAMERA_ODO_ROTATION, None],
[h_imu_frame_sym, ObservationKind.IMU_FRAME, None]]
gen_code(name, f_sym, dt, state_sym, obs_eqs, dim_state, dim_state_err, eskf_params)
def __init__(self):
self.dim_state = self.initial_x.shape[0]
self.dim_state_err = self.initial_P_diag.shape[0]
self.obs_noise = {ObservationKind.ODOMETRIC_SPEED: np.atleast_2d(0.2**2),
ObservationKind.PHONE_GYRO: np.diag([0.025**2, 0.025**2, 0.025**2]),
ObservationKind.PHONE_ACCEL: np.diag([.5**2, .5**2, .5**2]),
ObservationKind.CAMERA_ODO_ROTATION: np.diag([0.05**2, 0.05**2, 0.05**2]),
ObservationKind.IMU_FRAME: np.diag([0.05**2, 0.05**2, 0.05**2]),
ObservationKind.NO_ROT: np.diag([0.00025**2, 0.00025**2, 0.00025**2]),
ObservationKind.ECEF_POS: np.diag([5**2, 5**2, 5**2])}
# init filter
self.filter = EKF_sym(self.name, self.Q, self.initial_x, np.diag(self.initial_P_diag), self.dim_state, self.dim_state_err)
@property
def x(self):
return self.filter.state()
@property
def t(self):
return self.filter.filter_time
@property
def P(self):
return self.filter.covs()
def rts_smooth(self, estimates):
return self.filter.rts_smooth(estimates, norm_quats=True)
def init_state(self, state, covs_diag=None, covs=None, filter_time=None):
if covs_diag is not None:
P = np.diag(covs_diag)
elif covs is not None:
P = covs
else:
P = self.filter.covs()
self.filter.init_state(state, P, filter_time)
def predict_and_observe(self, t, kind, data):
if len(data) > 0:
data = np.atleast_2d(data)
if kind == ObservationKind.CAMERA_ODO_TRANSLATION:
r = self.predict_and_update_odo_trans(data, t, kind)
elif kind == ObservationKind.CAMERA_ODO_ROTATION:
r = self.predict_and_update_odo_rot(data, t, kind)
elif kind == ObservationKind.ODOMETRIC_SPEED:
r = self.predict_and_update_odo_speed(data, t, kind)
else:
r = self.filter.predict_and_update_batch(t, kind, data, self.get_R(kind, len(data)))
# Normalize quats
quat_norm = np.linalg.norm(self.filter.x[3:7, 0])
# Should not continue if the quats behave this weirdly
if not (0.1 < quat_norm < 10):
cloudlog.error("Kalman filter quaternions unstable")
raise KalmanError
self.filter.x[States.ECEF_ORIENTATION, 0] = self.filter.x[States.ECEF_ORIENTATION, 0] / quat_norm
return r
def get_R(self, kind, n):
obs_noise = self.obs_noise[kind]
dim = obs_noise.shape[0]
R = np.zeros((n, dim, dim))
for i in range(n):
R[i, :, :] = obs_noise
return R
def predict_and_update_odo_speed(self, speed, t, kind):
z = np.array(speed)
R = np.zeros((len(speed), 1, 1))
for i, _ in enumerate(z):
R[i, :, :] = np.diag([0.2**2])
return self.filter.predict_and_update_batch(t, kind, z, R)
def predict_and_update_odo_trans(self, trans, t, kind):
z = trans[:, :3]
R = np.zeros((len(trans), 3, 3))
for i, _ in enumerate(z):
R[i, :, :] = np.diag(trans[i, 3:]**2)
return self.filter.predict_and_update_batch(t, kind, z, R)
def predict_and_update_odo_rot(self, rot, t, kind):
z = rot[:, :3]
R = np.zeros((len(rot), 3, 3))
for i, _ in enumerate(z):
R[i, :, :] = np.diag(rot[i, 3:]**2)
return self.filter.predict_and_update_batch(t, kind, z, R)
if __name__ == "__main__":
LiveKalman.generate_code()

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#include <Eigen/QR>
#include <Eigen/Dense>
#include <iostream>
typedef Eigen::Matrix<double, KDIM*2, 3, Eigen::RowMajor> R3M;
typedef Eigen::Matrix<double, KDIM*2, 1> R1M;
typedef Eigen::Matrix<double, 3, 1> O1M;
typedef Eigen::Matrix<double, 3, 3, Eigen::RowMajor> M3D;
extern "C" {
void gauss_newton(double *in_x, double *in_poses, double *in_img_positions) {
double res[KDIM*2] = {0};
double jac[KDIM*6] = {0};
O1M x(in_x);
O1M delta;
int counter = 0;
while ((delta.squaredNorm() > 0.0001 and counter < 30) or counter == 0){
res_fun(in_x, in_poses, in_img_positions, res);
jac_fun(in_x, in_poses, in_img_positions, jac);
R1M E(res); R3M J(jac);
delta = (J.transpose()*J).inverse() * J.transpose() * E;
x = x - delta;
memcpy(in_x, x.data(), 3 * sizeof(double));
counter = counter + 1;
}
}
void compute_pos(double *to_c, double *poses, double *img_positions, double *param, double *pos) {
param[0] = img_positions[KDIM*2-2];
param[1] = img_positions[KDIM*2-1];
param[2] = 0.1;
gauss_newton(param, poses, img_positions);
Eigen::Quaterniond q;
q.w() = poses[KDIM*7-4];
q.x() = poses[KDIM*7-3];
q.y() = poses[KDIM*7-2];
q.z() = poses[KDIM*7-1];
M3D RC(to_c);
Eigen::Matrix3d R = q.normalized().toRotationMatrix();
Eigen::Matrix3d rot = R * RC.transpose();
pos[0] = param[0]/param[2];
pos[1] = param[1]/param[2];
pos[2] = 1.0/param[2];
O1M ecef_offset(poses + KDIM*7-7);
O1M ecef_output(pos);
ecef_output = rot*ecef_output + ecef_offset;
memcpy(pos, ecef_output.data(), 3 * sizeof(double));
}
}

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#include <eigen3/Eigen/Dense>
#include <iostream>
typedef Eigen::Matrix<double, DIM, DIM, Eigen::RowMajor> DDM;
typedef Eigen::Matrix<double, EDIM, EDIM, Eigen::RowMajor> EEM;
typedef Eigen::Matrix<double, DIM, EDIM, Eigen::RowMajor> DEM;
void predict(double *in_x, double *in_P, double *in_Q, double dt) {
typedef Eigen::Matrix<double, MEDIM, MEDIM, Eigen::RowMajor> RRM;
double nx[DIM] = {0};
double in_F[EDIM*EDIM] = {0};
// functions from sympy
f_fun(in_x, dt, nx);
F_fun(in_x, dt, in_F);
EEM F(in_F);
EEM P(in_P);
EEM Q(in_Q);
RRM F_main = F.topLeftCorner(MEDIM, MEDIM);
P.topLeftCorner(MEDIM, MEDIM) = (F_main * P.topLeftCorner(MEDIM, MEDIM)) * F_main.transpose();
P.topRightCorner(MEDIM, EDIM - MEDIM) = F_main * P.topRightCorner(MEDIM, EDIM - MEDIM);
P.bottomLeftCorner(EDIM - MEDIM, MEDIM) = P.bottomLeftCorner(EDIM - MEDIM, MEDIM) * F_main.transpose();
P = P + dt*Q;
// copy out state
memcpy(in_x, nx, DIM * sizeof(double));
memcpy(in_P, P.data(), EDIM * EDIM * sizeof(double));
}
// note: extra_args dim only correct when null space projecting
// otherwise 1
template <int ZDIM, int EADIM, bool MAHA_TEST>
void update(double *in_x, double *in_P, Hfun h_fun, Hfun H_fun, Hfun Hea_fun, double *in_z, double *in_R, double *in_ea, double MAHA_THRESHOLD) {
typedef Eigen::Matrix<double, ZDIM, ZDIM, Eigen::RowMajor> ZZM;
typedef Eigen::Matrix<double, ZDIM, DIM, Eigen::RowMajor> ZDM;
typedef Eigen::Matrix<double, Eigen::Dynamic, EDIM, Eigen::RowMajor> XEM;
//typedef Eigen::Matrix<double, EDIM, ZDIM, Eigen::RowMajor> EZM;
typedef Eigen::Matrix<double, Eigen::Dynamic, 1> X1M;
typedef Eigen::Matrix<double, Eigen::Dynamic, Eigen::Dynamic, Eigen::RowMajor> XXM;
double in_hx[ZDIM] = {0};
double in_H[ZDIM * DIM] = {0};
double in_H_mod[EDIM * DIM] = {0};
double delta_x[EDIM] = {0};
double x_new[DIM] = {0};
// state x, P
Eigen::Matrix<double, ZDIM, 1> z(in_z);
EEM P(in_P);
ZZM pre_R(in_R);
// functions from sympy
h_fun(in_x, in_ea, in_hx);
H_fun(in_x, in_ea, in_H);
ZDM pre_H(in_H);
// get y (y = z - hx)
Eigen::Matrix<double, ZDIM, 1> pre_y(in_hx); pre_y = z - pre_y;
X1M y; XXM H; XXM R;
if (Hea_fun){
typedef Eigen::Matrix<double, ZDIM, EADIM, Eigen::RowMajor> ZAM;
double in_Hea[ZDIM * EADIM] = {0};
Hea_fun(in_x, in_ea, in_Hea);
ZAM Hea(in_Hea);
XXM A = Hea.transpose().fullPivLu().kernel();
y = A.transpose() * pre_y;
H = A.transpose() * pre_H;
R = A.transpose() * pre_R * A;
} else {
y = pre_y;
H = pre_H;
R = pre_R;
}
// get modified H
H_mod_fun(in_x, in_H_mod);
DEM H_mod(in_H_mod);
XEM H_err = H * H_mod;
// Do mahalobis distance test
if (MAHA_TEST){
XXM a = (H_err * P * H_err.transpose() + R).inverse();
double maha_dist = y.transpose() * a * y;
if (maha_dist > MAHA_THRESHOLD){
R = 1.0e16 * R;
}
}
// Outlier resilient weighting
double weight = 1;//(1.5)/(1 + y.squaredNorm()/R.sum());
// kalman gains and I_KH
XXM S = ((H_err * P) * H_err.transpose()) + R/weight;
XEM KT = S.fullPivLu().solve(H_err * P.transpose());
//EZM K = KT.transpose(); TODO: WHY DOES THIS NOT COMPILE?
//EZM K = S.fullPivLu().solve(H_err * P.transpose()).transpose();
//std::cout << "Here is the matrix rot:\n" << K << std::endl;
EEM I_KH = Eigen::Matrix<double, EDIM, EDIM>::Identity() - (KT.transpose() * H_err);
// update state by injecting dx
Eigen::Matrix<double, EDIM, 1> dx(delta_x);
dx = (KT.transpose() * y);
memcpy(delta_x, dx.data(), EDIM * sizeof(double));
err_fun(in_x, delta_x, x_new);
Eigen::Matrix<double, DIM, 1> x(x_new);
// update cov
P = ((I_KH * P) * I_KH.transpose()) + ((KT.transpose() * R) * KT);
// copy out state
memcpy(in_x, x.data(), DIM * sizeof(double));
memcpy(in_P, P.data(), EDIM * EDIM * sizeof(double));
memcpy(in_z, y.data(), y.rows() * sizeof(double));
}

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extern "C"{
bool sane(double track [K + 1][5]) {
double diffs_x [K-1];
double diffs_y [K-1];
int i;
for (i = 0; i < K-1; i++) {
diffs_x[i] = fabs(track[i+2][2] - track[i+1][2]);
diffs_y[i] = fabs(track[i+2][3] - track[i+1][3]);
}
for (i = 1; i < K-1; i++) {
if (((diffs_x[i] > 0.05 or diffs_x[i-1] > 0.05) and
(diffs_x[i] > 2*diffs_x[i-1] or
diffs_x[i] < .5*diffs_x[i-1])) or
((diffs_y[i] > 0.05 or diffs_y[i-1] > 0.05) and
(diffs_y[i] > 2*diffs_y[i-1] or
diffs_y[i] < .5*diffs_y[i-1]))){
return false;
}
}
return true;
}
void merge_features(double *tracks, double *features, long long *empty_idxs) {
double feature_arr [3000][5];
memcpy(feature_arr, features, 3000 * 5 * sizeof(double));
double track_arr [6000][K + 1][5];
memcpy(track_arr, tracks, (K+1) * 6000 * 5 * sizeof(double));
int match;
int empty_idx = 0;
int idx;
for (int i = 0; i < 3000; i++) {
match = feature_arr[i][4];
if (track_arr[match][0][1] == match and track_arr[match][0][2] == 0){
track_arr[match][0][0] = track_arr[match][0][0] + 1;
track_arr[match][0][1] = feature_arr[i][1];
track_arr[match][0][2] = 1;
idx = track_arr[match][0][0];
memcpy(track_arr[match][idx], feature_arr[i], 5 * sizeof(double));
if (idx == K){
// label complete
track_arr[match][0][3] = 1;
if (sane(track_arr[match])){
// label valid
track_arr[match][0][4] = 1;
}
}
} else {
// gen new track with this feature
track_arr[empty_idxs[empty_idx]][0][0] = 1;
track_arr[empty_idxs[empty_idx]][0][1] = feature_arr[i][1];
track_arr[empty_idxs[empty_idx]][0][2] = 1;
memcpy(track_arr[empty_idxs[empty_idx]][1], feature_arr[i], 5 * sizeof(double));
empty_idx = empty_idx + 1;
}
}
memcpy(tracks, track_arr, (K+1) * 6000 * 5 * sizeof(double));
}
}

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#!/usr/bin/env python3
import math
import numpy as np
import cereal.messaging as messaging
import common.transformations.coordinates as coord
from common.transformations.orientation import (ecef_euler_from_ned,
euler2quat,
ned_euler_from_ecef,
quat2euler,
rotations_from_quats)
from selfdrive.locationd.kalman.helpers import ObservationKind, KalmanError
from selfdrive.locationd.kalman.models.live_kf import LiveKalman, States
from selfdrive.swaglog import cloudlog
VISION_DECIMATION = 2
SENSOR_DECIMATION = 10
class Localizer():
def __init__(self, disabled_logs=[], dog=None):
self.kf = LiveKalman()
self.reset_kalman()
self.max_age = .2 # seconds
self.disabled_logs = disabled_logs
def liveLocationMsg(self, time):
fix = messaging.log.LiveLocationData.new_message()
predicted_state = self.kf.x
fix_ecef = predicted_state[States.ECEF_POS]
fix_pos_geo = coord.ecef2geodetic(fix_ecef)
fix.lat = float(fix_pos_geo[0])
fix.lon = float(fix_pos_geo[1])
fix.alt = float(fix_pos_geo[2])
fix.speed = float(np.linalg.norm(predicted_state[States.ECEF_VELOCITY]))
orientation_ned_euler = ned_euler_from_ecef(fix_ecef, quat2euler(predicted_state[States.ECEF_ORIENTATION]))
fix.roll = math.degrees(orientation_ned_euler[0])
fix.pitch = math.degrees(orientation_ned_euler[1])
fix.heading = math.degrees(orientation_ned_euler[2])
fix.gyro = [float(predicted_state[10]), float(predicted_state[11]), float(predicted_state[12])]
fix.accel = [float(predicted_state[19]), float(predicted_state[20]), float(predicted_state[21])]
ned_vel = self.converter.ecef2ned(predicted_state[States.ECEF_POS] + predicted_state[States.ECEF_VELOCITY]) - self.converter.ecef2ned(predicted_state[States.ECEF_POS])
fix.vNED = [float(ned_vel[0]), float(ned_vel[1]), float(ned_vel[2])]
fix.source = 'kalman'
#local_vel = rotations_from_quats(predicted_state[States.ECEF_ORIENTATION]).T.dot(predicted_state[States.ECEF_VELOCITY])
#fix.pitchCalibration = math.degrees(math.atan2(local_vel[2], local_vel[0]))
#fix.yawCalibration = math.degrees(math.atan2(local_vel[1], local_vel[0]))
imu_frame = predicted_state[States.IMU_OFFSET]
fix.imuFrame = [math.degrees(imu_frame[0]), math.degrees(imu_frame[1]), math.degrees(imu_frame[2])]
return fix
def update_kalman(self, time, kind, meas):
if self.filter_ready:
try:
self.kf.predict_and_observe(time, kind, meas)
except KalmanError:
cloudlog.error("Error in predict and observe, kalman reset")
self.reset_kalman()
#idx = bisect_right([x[0] for x in self.observation_buffer], time)
#self.observation_buffer.insert(idx, (time, kind, meas))
#while len(self.observation_buffer) > 0 and self.observation_buffer[-1][0] - self.observation_buffer[0][0] > self.max_age:
# else:
# self.observation_buffer.pop(0)
def handle_gps(self, current_time, log):
self.converter = coord.LocalCoord.from_geodetic([log.latitude, log.longitude, log.altitude])
fix_ecef = self.converter.ned2ecef([0, 0, 0])
# TODO initing with bad bearing not allowed, maybe not bad?
if not self.filter_ready and log.speed > 5:
self.filter_ready = True
initial_ecef = fix_ecef
gps_bearing = math.radians(log.bearing)
initial_pose_ecef = ecef_euler_from_ned(initial_ecef, [0, 0, gps_bearing])
initial_pose_ecef_quat = euler2quat(initial_pose_ecef)
gps_speed = log.speed
quat_uncertainty = 0.2**2
initial_pose_ecef_quat = euler2quat(initial_pose_ecef)
initial_state = LiveKalman.initial_x
initial_covs_diag = LiveKalman.initial_P_diag
initial_state[States.ECEF_POS] = initial_ecef
initial_state[States.ECEF_ORIENTATION] = initial_pose_ecef_quat
initial_state[States.ECEF_VELOCITY] = rotations_from_quats(initial_pose_ecef_quat).dot(np.array([gps_speed, 0, 0]))
initial_covs_diag[States.ECEF_POS_ERR] = 10**2
initial_covs_diag[States.ECEF_ORIENTATION_ERR] = quat_uncertainty
initial_covs_diag[States.ECEF_VELOCITY_ERR] = 1**2
self.kf.init_state(initial_state, covs=np.diag(initial_covs_diag), filter_time=current_time)
cloudlog.info("Filter initialized")
elif self.filter_ready:
self.update_kalman(current_time, ObservationKind.ECEF_POS, fix_ecef)
gps_est_error = np.sqrt((self.kf.x[0] - fix_ecef[0])**2 +
(self.kf.x[1] - fix_ecef[1])**2 +
(self.kf.x[2] - fix_ecef[2])**2)
if gps_est_error > 50:
cloudlog.error("Locationd vs ubloxLocation difference too large, kalman reset")
self.reset_kalman()
def handle_car_state(self, current_time, log):
self.speed_counter += 1
if self.speed_counter % SENSOR_DECIMATION == 0:
self.update_kalman(current_time, ObservationKind.ODOMETRIC_SPEED, [log.vEgo])
if log.vEgo == 0:
self.update_kalman(current_time, ObservationKind.NO_ROT, [0, 0, 0])
def handle_cam_odo(self, current_time, log):
self.cam_counter += 1
if self.cam_counter % VISION_DECIMATION == 0:
self.update_kalman(current_time,
ObservationKind.CAMERA_ODO_ROTATION,
np.concatenate([log.rot, log.rotStd]))
self.update_kalman(current_time,
ObservationKind.CAMERA_ODO_TRANSLATION,
np.concatenate([log.trans, log.transStd]))
def handle_sensors(self, current_time, log):
# TODO does not yet account for double sensor readings in the log
for sensor_reading in log:
# Gyro Uncalibrated
if sensor_reading.sensor == 5 and sensor_reading.type == 16:
self.gyro_counter += 1
if self.gyro_counter % SENSOR_DECIMATION == 0:
if max(abs(self.kf.x[States.IMU_OFFSET])) > 0.07:
cloudlog.info('imu frame angles exceeded, correcting')
self.update_kalman(current_time, ObservationKind.IMU_FRAME, [0, 0, 0])
v = sensor_reading.gyroUncalibrated.v
self.update_kalman(current_time, ObservationKind.PHONE_GYRO, [-v[2], -v[1], -v[0]])
# Accelerometer
if sensor_reading.sensor == 1 and sensor_reading.type == 1:
self.acc_counter += 1
if self.acc_counter % SENSOR_DECIMATION == 0:
v = sensor_reading.acceleration.v
self.update_kalman(current_time, ObservationKind.PHONE_ACCEL, [-v[2], -v[1], -v[0]])
def reset_kalman(self):
self.filter_time = None
self.filter_ready = False
self.observation_buffer = []
self.gyro_counter = 0
self.acc_counter = 0
self.speed_counter = 0
self.cam_counter = 0
def locationd_thread(sm, pm, disabled_logs=[]):
if sm is None:
sm = messaging.SubMaster(['gpsLocationExternal', 'sensorEvents', 'cameraOdometry'])
if pm is None:
pm = messaging.PubMaster(['liveLocation'])
localizer = Localizer(disabled_logs=disabled_logs)
while True:
sm.update()
for sock, updated in sm.updated.items():
if updated:
t = sm.logMonoTime[sock] * 1e-9
if sock == "sensorEvents":
localizer.handle_sensors(t, sm[sock])
elif sock == "gpsLocationExternal":
localizer.handle_gps(t, sm[sock])
elif sock == "carState":
localizer.handle_car_state(t, sm[sock])
elif sock == "cameraOdometry":
localizer.handle_cam_odo(t, sm[sock])
if localizer.filter_ready and sm.updated['gpsLocationExternal']:
t = sm.logMonoTime['gpsLocationExternal']
msg = messaging.new_message()
msg.logMonoTime = t
msg.init('liveLocation')
msg.liveLocation = localizer.liveLocationMsg(t * 1e-9)
pm.send('liveLocation', msg)
def main(sm=None, pm=None):
locationd_thread(sm, pm)
if __name__ == "__main__":
import os
os.environ["OMP_NUM_THREADS"] = "1"
main()

2
selfdrive/locationd/locationd_yawrate.cc
View File

@ -3,7 +3,7 @@
#include <capnp/message.h>
#include <capnp/serialize-packed.h>
#include <eigen3/Eigen/Dense>
#include <Eigen/Dense>
#include "cereal/gen/cpp/log.capnp.h"

2
selfdrive/locationd/locationd_yawrate.h
View File

@ -1,6 +1,6 @@
#pragma once
#include <eigen3/Eigen/Dense>
#include <Eigen/Dense>
#include "cereal/gen/cpp/log.capnp.h"
#define DEGREES_TO_RADIANS 0.017453292519943295

10
selfdrive/loggerd/deleter.py
View File

@ -3,15 +3,19 @@ import os
import shutil
import threading
from selfdrive.swaglog import cloudlog
from selfdrive.loggerd.config import ROOT, get_available_bytes
from selfdrive.loggerd.config import ROOT, get_available_bytes, get_available_percent
from selfdrive.loggerd.uploader import listdir_by_creation
MIN_BYTES = 5 * 1024 * 1024 * 1024
MIN_PERCENT = 10
def deleter_thread(exit_event):
while not exit_event.is_set():
available_bytes = get_available_bytes()
out_of_bytes = get_available_bytes(default=MIN_BYTES + 1) < MIN_BYTES
out_of_percent = get_available_percent(default=MIN_PERCENT + 1) < MIN_PERCENT
if available_bytes is not None and available_bytes < (5 * 1024 * 1024 * 1024):
if out_of_percent or out_of_bytes:
# remove the earliest directory we can
dirs = listdir_by_creation(ROOT)
for delete_dir in dirs:

5
selfdrive/loggerd/loggerd.cc
View File

@ -588,7 +588,6 @@ int main(int argc, char** argv) {
for (const auto& it : services) {
std::string name = it.name;
int qlog_freq = it.decimation ? it.decimation : 0;
if (it.should_log) {
SubSocket * sock = SubSocket::create(s.ctx, name);
@ -601,8 +600,8 @@ int main(int argc, char** argv) {
frame_sock = sock;
}
qlog_counter[sock] = (qlog_freq == 0) ? -1 : 0;
qlog_freqs[sock] = qlog_freq;
qlog_counter[sock] = (it.decimation == -1) ? -1 : 0;
qlog_freqs[sock] = it.decimation;
}
}

25
selfdrive/manager.py
View File

@ -14,7 +14,7 @@ from common.android import ANDROID
sys.path.append(os.path.join(BASEDIR, "pyextra"))
os.environ['BASEDIR'] = BASEDIR
TOTAL_SCONS_NODES = 1170
TOTAL_SCONS_NODES = 1195
prebuilt = os.path.exists(os.path.join(BASEDIR, 'prebuilt'))
# Create folders needed for msgq
@ -142,6 +142,7 @@ managed_processes = {
"ubloxd": ("selfdrive/locationd", ["./ubloxd"]),
"loggerd": ("selfdrive/loggerd", ["./loggerd"]),
"logmessaged": "selfdrive.logmessaged",
"locationd": "selfdrive.locationd.locationd",
"tombstoned": "selfdrive.tombstoned",
"logcatd": ("selfdrive/logcatd", ["./logcatd"]),
"proclogd": ("selfdrive/proclogd", ["./proclogd"]),
@ -204,6 +205,7 @@ car_started_processes = [
'modeld',
'proclogd',
'ubloxd',
'locationd',
]
if ANDROID:
car_started_processes += [
@ -289,6 +291,15 @@ def prepare_managed_process(p):
subprocess.check_call(["make", "clean"], cwd=os.path.join(BASEDIR, proc[0]))
subprocess.check_call(["make", "-j4"], cwd=os.path.join(BASEDIR, proc[0]))
def join_process(process, timeout):
# Process().join(timeout) will hang due to a python 3 bug: https://bugs.python.org/issue28382
# We have to poll the exitcode instead
t = time.time()
while time.time() - t < timeout and process.exitcode is None:
time.sleep(0.001)
def kill_managed_process(name):
if name not in running or name not in managed_processes:
return
@ -302,18 +313,12 @@ def kill_managed_process(name):
else:
running[name].terminate()
# Process().join(timeout) will hang due to a python 3 bug: https://bugs.python.org/issue28382
# We have to poll the exitcode instead
# running[name].join(5.0)
t = time.time()
while time.time() - t < 5 and running[name].exitcode is None:
time.sleep(0.001)
join_process(running[name], 5)
if running[name].exitcode is None:
if name in unkillable_processes:
cloudlog.critical("unkillable process %s failed to exit! rebooting in 15 if it doesn't die" % name)
running[name].join(15.0)
join_process(running[name], 15)
if running[name].exitcode is None:
cloudlog.critical("FORCE REBOOTING PHONE!")
os.system("date >> /sdcard/unkillable_reboot")
@ -502,6 +507,8 @@ def main():
params.put("LastUpdateTime", t.encode('utf8'))
if params.get("OpenpilotEnabledToggle") is None:
params.put("OpenpilotEnabledToggle", "1")
if params.get("LaneChangeEnabled") is None:
params.put("LaneChangeEnabled", "1")
# is this chffrplus?
if os.getenv("PASSIVE") is not None:

2
selfdrive/test/process_replay/ref_commit
View File

@ -1 +1 @@
bc89e6f25e88a904ad905296d516aaebb77e2207
917e6889be1691fb96e7566a92e0c6bbefc861a4

17
selfdrive/test/test_car_models.py
View File

@ -58,7 +58,6 @@ def get_route_log(route_name):
sys.exit(-1)
routes = {
"975b26878285314d|2018-12-25--14-42-13": {
'carFingerprint': CHRYSLER.PACIFICA_2018_HYBRID,
'enableCamera': True,
@ -290,6 +289,7 @@ routes = {
"7e34a988419b5307|2019-12-18--19-13-30": {
'carFingerprint': TOYOTA.RAV4H_TSS2,
'enableCamera': True,
'fingerprintSource': 'fixed'
},
"e6a24be49a6cd46e|2019-10-29--10-52-42": {
'carFingerprint': TOYOTA.LEXUS_ES_TSS2,
@ -325,6 +325,11 @@ routes = {
'carFingerprint': TOYOTA.LEXUS_RX_TSS2,
'enableCamera': True,
},
"ec429c0f37564e3c|2020-02-01--17-28-12": {
'carFingerprint': TOYOTA.LEXUS_NXH,
'enableCamera': True,
'enableDsu': False,
},
#FIXME: This works sometimes locally, but never in CI. Timing issue?
#"b0f5a01cf604185c|2018-01-31--20-11-39": {
# 'carFingerprint': TOYOTA.LEXUS_RXH,
@ -368,6 +373,11 @@ routes = {
# 'enableDsu': False,
# },
# TODO: missingsome combos for highlander
"0a302ffddbb3e3d3|2020-02-08--16-19-08": {
'carFingerprint': TOYOTA.HIGHLANDER_TSS2,
'enableCamera': True,
'enableDsu': False,
},
"aa659debdd1a7b54|2018-08-31--11-12-01": {
'carFingerprint': TOYOTA.HIGHLANDER,
'enableCamera': False,
@ -507,6 +517,11 @@ if __name__ == "__main__":
params.put("CommunityFeaturesToggle", "1")
params.put("Passive", "1" if route in passive_routes else "0")
if checks.get('fingerprintSource', None) == 'fixed':
os.environ['FINGERPRINT'] = checks['carFingerprint']
else:
os.environ['FINGERPRINT'] = ""
print("testing ", route, " ", checks['carFingerprint'])
print("Starting processes")
for p in tested_procs:

4
selfdrive/test/test_fingerprints.py
View File

@ -77,6 +77,10 @@ valid = True
for idx1, f1 in enumerate(fingerprints_flat):
for idx2, f2 in enumerate(fingerprints_flat):
if idx1 < idx2 and not check_fingerprint_consistency(f1, f2):
if car_names[idx1] == car_names[idx2]:
print(f"Warning, overlap in {car_names[idx1]}")
continue
valid = False
print("Those two fingerprints are inconsistent {0} {1}".format(car_names[idx1], car_names[idx2]))
print("")

204
selfdrive/test/test_openpilot.py
View File

@ -105,118 +105,118 @@ def test_uploader():
print("UPLOADER")
time.sleep(10.0)
# @phone_only
# def test_athena():
# print("ATHENA")
# start_daemon_process("manage_athenad")
# params = Params()
# manage_athenad_pid = params.get("AthenadPid")
# assert manage_athenad_pid is not None
# try:
# os.kill(int(manage_athenad_pid), 0)
# # process is running
# except OSError:
# assert False, "manage_athenad is dead"
@phone_only
def test_athena():
print("ATHENA")
start_daemon_process("manage_athenad")
params = Params()
manage_athenad_pid = params.get("AthenadPid")
assert manage_athenad_pid is not None
try:
os.kill(int(manage_athenad_pid), 0)
# process is running
except OSError:
assert False, "manage_athenad is dead"
# def expect_athena_starts(timeout=30):
# now = time.time()
# athenad_pid = None
# while athenad_pid is None:
# try:
# athenad_pid = subprocess.check_output(["pgrep", "-P", manage_athenad_pid], encoding="utf-8").strip()
# return athenad_pid
# except subprocess.CalledProcessError:
# if time.time() - now > timeout:
# assert False, f"Athena did not start within {timeout} seconds"
# time.sleep(0.5)
def expect_athena_starts(timeout=30):
now = time.time()
athenad_pid = None
while athenad_pid is None:
try:
athenad_pid = subprocess.check_output(["pgrep", "-P", manage_athenad_pid], encoding="utf-8").strip()
return athenad_pid
except subprocess.CalledProcessError:
if time.time() - now > timeout:
assert False, f"Athena did not start within {timeout} seconds"
time.sleep(0.5)
# def athena_post(payload, max_retries=5, wait=5):
# tries = 0
# while 1:
# try:
# resp = requests.post(
# "https://athena.comma.ai/" + params.get("DongleId", encoding="utf-8"),
# headers={
# "Authorization": "JWT " + os.getenv("COMMA_JWT"),
# "Content-Type": "application/json"
# },
# data=json.dumps(payload),
# timeout=30
# )
# resp_json = resp.json()
# if resp_json.get('error'):
# raise Exception(resp_json['error'])
# return resp_json
# except Exception as e:
# time.sleep(wait)
# tries += 1
# if tries == max_retries:
# raise
# else:
# print(f'athena_post failed {e}. retrying...')
def athena_post(payload, max_retries=5, wait=5):
tries = 0
while 1:
try:
resp = requests.post(
"https://athena.comma.ai/" + params.get("DongleId", encoding="utf-8"),
headers={
"Authorization": "JWT " + os.getenv("COMMA_JWT"),
"Content-Type": "application/json"
},
data=json.dumps(payload),
timeout=30
)
resp_json = resp.json()
if resp_json.get('error'):
raise Exception(resp_json['error'])
return resp_json
except Exception as e:
time.sleep(wait)
tries += 1
if tries == max_retries:
raise
else:
print(f'athena_post failed {e}. retrying...')
# def expect_athena_registers():
# resp = athena_post({
# "method": "echo",
# "params": ["hello"],
# "id": 0,
# "jsonrpc": "2.0"
# }, max_retries=12, wait=5)
# assert resp.get('result') == "hello", f'Athena failed to register ({resp})'
def expect_athena_registers():
resp = athena_post({
"method": "echo",
"params": ["hello"],
"id": 0,
"jsonrpc": "2.0"
}, max_retries=12, wait=5)
assert resp.get('result') == "hello", f'Athena failed to register ({resp})'
# try:
# athenad_pid = expect_athena_starts()
# # kill athenad and ensure it is restarted (check_output will throw if it is not)
# os.kill(int(athenad_pid), signal.SIGINT)
# expect_athena_starts()
try:
athenad_pid = expect_athena_starts()
# kill athenad and ensure it is restarted (check_output will throw if it is not)
os.kill(int(athenad_pid), signal.SIGINT)
expect_athena_starts()
# if not os.getenv('COMMA_JWT'):
# print('WARNING: COMMA_JWT env not set, will not test requests to athena.comma.ai')
# return
if not os.getenv('COMMA_JWT'):
print('WARNING: COMMA_JWT env not set, will not test requests to athena.comma.ai')
return
# expect_athena_registers()
expect_athena_registers()
# print("ATHENA: getSimInfo")
# resp = athena_post({
# "method": "getSimInfo",
# "id": 0,
# "jsonrpc": "2.0"
# })
# assert resp.get('result'), resp
# assert 'sim_id' in resp['result'], resp['result']
print("ATHENA: getSimInfo")
resp = athena_post({
"method": "getSimInfo",
"id": 0,
"jsonrpc": "2.0"
})
assert resp.get('result'), resp
assert 'sim_id' in resp['result'], resp['result']
# print("ATHENA: takeSnapshot")
# resp = athena_post({
# "method": "takeSnapshot",
# "id": 0,
# "jsonrpc": "2.0"
# })
# assert resp.get('result'), resp
# assert resp['result']['jpegBack'], resp['result']
print("ATHENA: takeSnapshot")
resp = athena_post({
"method": "takeSnapshot",
"id": 0,
"jsonrpc": "2.0"
})
assert resp.get('result'), resp
assert resp['result']['jpegBack'], resp['result']
# @with_processes(["thermald"])
# def test_athena_thermal():
# print("ATHENA: getMessage(thermal)")
# resp = athena_post({
# "method": "getMessage",
# "params": {"service": "thermal", "timeout": 5000},
# "id": 0,
# "jsonrpc": "2.0"
# })
# assert resp.get('result'), resp
# assert resp['result']['thermal'], resp['result']
# test_athena_thermal()
# finally:
# try:
# athenad_pid = subprocess.check_output(["pgrep", "-P", manage_athenad_pid], encoding="utf-8").strip()
# except subprocess.CalledProcessError:
# athenad_pid = None
@with_processes(["thermald"])
def test_athena_thermal():
print("ATHENA: getMessage(thermal)")
resp = athena_post({
"method": "getMessage",
"params": {"service": "thermal", "timeout": 5000},
"id": 0,
"jsonrpc": "2.0"
})
assert resp.get('result'), resp
assert resp['result']['thermal'], resp['result']
test_athena_thermal()
finally:
try:
athenad_pid = subprocess.check_output(["pgrep", "-P", manage_athenad_pid], encoding="utf-8").strip()
except subprocess.CalledProcessError:
athenad_pid = None
# try:
# os.kill(int(manage_athenad_pid), signal.SIGINT)
# os.kill(int(athenad_pid), signal.SIGINT)
# except (OSError, TypeError):
# pass
try:
os.kill(int(manage_athenad_pid), signal.SIGINT)
os.kill(int(athenad_pid), signal.SIGINT)
except (OSError, TypeError):
pass
# TODO: re-enable when jenkins test has /data/pythonpath -> /data/openpilot
# @phone_only

19
selfdrive/thermald.py
View File

@ -130,7 +130,7 @@ def handle_fan_eon(max_cpu_temp, bat_temp, fan_speed, ignition):
def handle_fan_uno(max_cpu_temp, bat_temp, fan_speed, ignition):
new_speed = int(interp(max_cpu_temp, [40.0, 80.0], [0, 100]))
new_speed = int(interp(max_cpu_temp, [40.0, 80.0], [0, 80]))
if not ignition:
new_speed = min(30, new_speed)
@ -192,10 +192,12 @@ def thermald_thread():
if health is not None:
usb_power = health.health.usbPowerMode != log.HealthData.UsbPowerMode.client
try:
network_type = get_network_type()
except subprocess.CalledProcessError:
pass
# get_network_type is an expensive call. update every 10s
if (count % int(10. / DT_TRML)) == 0:
try:
network_type = get_network_type()
except subprocess.CalledProcessError:
pass
msg.thermal.freeSpace = get_available_percent(default=100.0) / 100.0
msg.thermal.memUsedPercent = int(round(psutil.virtual_memory().percent))
@ -272,13 +274,16 @@ def thermald_thread():
last_update = now
dt = now - last_update
if dt.days > DAYS_NO_CONNECTIVITY_MAX:
update_failed_count = params.get("UpdateFailedCount")
update_failed_count = 0 if update_failed_count is None else int(update_failed_count)
if dt.days > DAYS_NO_CONNECTIVITY_MAX and update_failed_count > 1:
if current_connectivity_alert != "expired":
current_connectivity_alert = "expired"
params.delete("Offroad_ConnectivityNeededPrompt")
params.put("Offroad_ConnectivityNeeded", json.dumps(OFFROAD_ALERTS["Offroad_ConnectivityNeeded"]))
elif dt.days > DAYS_NO_CONNECTIVITY_PROMPT:
remaining_time = str(DAYS_NO_CONNECTIVITY_MAX - dt.days)
remaining_time = str(max(DAYS_NO_CONNECTIVITY_MAX - dt.days, 0))
if current_connectivity_alert != "prompt" + remaining_time:
current_connectivity_alert = "prompt" + remaining_time
alert_connectivity_prompt = copy.copy(OFFROAD_ALERTS["Offroad_ConnectivityNeededPrompt"])

5
selfdrive/updated.py
View File

@ -293,6 +293,7 @@ def attempt_update():
def main(gctx=None):
update_failed_count = 0
overlay_init_done = False
wait_helper = WaitTimeHelper()
params = Params()
@ -312,6 +313,7 @@ def main(gctx=None):
raise RuntimeError("couldn't get overlay lock; is another updated running?")
while True:
update_failed_count += 1
time_wrong = datetime.datetime.now().year < 2019
ping_failed = subprocess.call(["ping", "-W", "4", "-c", "1", "8.8.8.8"])
@ -335,6 +337,7 @@ def main(gctx=None):
if params.get("IsOffroad") == b"1":
attempt_update()
update_failed_count = 0
else:
cloudlog.info("not running updater, openpilot running")
@ -348,8 +351,8 @@ def main(gctx=None):
overlay_init_done = False
except Exception:
cloudlog.exception("uncaught updated exception, shouldn't happen")
overlay_init_done = False
params.put("UpdateFailedCount", str(update_failed_count))
wait_between_updates(wait_helper.ready_event)
if wait_helper.shutdown:
break