from math import atan2 from cereal import car from common.numpy_fast import interp from common.realtime import DT_DMON from selfdrive.hardware import TICI from common.filter_simple import FirstOrderFilter from common.stat_live import RunningStatFilter EventName = car.CarEvent.EventName # ****************************************************************************************** # NOTE: To fork maintainers. # Disabling or nerfing safety features will get you and your users banned from our servers. # We recommend that you do not change these numbers from the defaults. # ****************************************************************************************** class DRIVER_MONITOR_SETTINGS(): def __init__(self, TICI=TICI, DT_DMON=DT_DMON): self._DT_DMON = DT_DMON # ref (page15-16): https://eur-lex.europa.eu/legal-content/EN/TXT/PDF/?uri=CELEX:42018X1947&rid=2 self._AWARENESS_TIME = 30. # passive wheeltouch total timeout self._AWARENESS_PRE_TIME_TILL_TERMINAL = 15. self._AWARENESS_PROMPT_TIME_TILL_TERMINAL = 6. self._DISTRACTED_TIME = 11. # active monitoring total timeout self._DISTRACTED_PRE_TIME_TILL_TERMINAL = 8. self._DISTRACTED_PROMPT_TIME_TILL_TERMINAL = 6. self._FACE_THRESHOLD = 0.5 self._PARTIAL_FACE_THRESHOLD = 0.8 if TICI else 0.45 self._EYE_THRESHOLD = 0.55 self._SG_THRESHOLD = 0.88 if TICI else 0.86 self._BLINK_THRESHOLD = 0.61 if TICI else 0.59 self._BLINK_THRESHOLD_SLACK = 0.8 if TICI else 0.75 self._BLINK_THRESHOLD_STRICT = self._BLINK_THRESHOLD self._EE_THRESH11 = 0.75 if TICI else 0.4 self._EE_THRESH12 = 3.25 if TICI else 2.45 self._EE_THRESH21 = 0.01 self._EE_THRESH22 = 0.35 self._POSE_PITCH_THRESHOLD = 0.3237 self._POSE_PITCH_THRESHOLD_SLACK = 0.3657 self._POSE_PITCH_THRESHOLD_STRICT = self._POSE_PITCH_THRESHOLD self._POSE_YAW_THRESHOLD = 0.3109 self._POSE_YAW_THRESHOLD_SLACK = 0.4294 self._POSE_YAW_THRESHOLD_STRICT = self._POSE_YAW_THRESHOLD self._PITCH_NATURAL_OFFSET = 0.057 # initial value before offset is learned self._YAW_NATURAL_OFFSET = 0.11 # initial value before offset is learned self._PITCH_MAX_OFFSET = 0.124 self._PITCH_MIN_OFFSET = -0.0881 self._YAW_MAX_OFFSET = 0.289 self._YAW_MIN_OFFSET = -0.0246 self._POSESTD_THRESHOLD = 0.315 self._HI_STD_FALLBACK_TIME = int(10 / self._DT_DMON) # fall back to wheel touch if model is uncertain for 10s self._DISTRACTED_FILTER_TS = 0.25 # 0.6Hz self._POSE_CALIB_MIN_SPEED = 13 # 30 mph self._POSE_OFFSET_MIN_COUNT = int(60 / self._DT_DMON) # valid data counts before calibration completes, 1min cumulative self._POSE_OFFSET_MAX_COUNT = int(360 / self._DT_DMON) # stop deweighting new data after 6 min, aka "short term memory" self._RECOVERY_FACTOR_MAX = 5. # relative to minus step change self._RECOVERY_FACTOR_MIN = 1.25 # relative to minus step change self._MAX_TERMINAL_ALERTS = 3 # not allowed to engage after 3 terminal alerts self._MAX_TERMINAL_DURATION = int(30 / self._DT_DMON) # not allowed to engage after 30s of terminal alerts # model output refers to center of cropped image, so need to apply the x displacement offset RESIZED_FOCAL = 320.0 H, W, FULL_W = 320, 160, 426 class DistractedType: NOT_DISTRACTED = 0 DISTRACTED_POSE = 1 DISTRACTED_BLINK = 2 DISTRACTED_E2E = 4 def face_orientation_from_net(angles_desc, pos_desc, rpy_calib, is_rhd): # the output of these angles are in device frame # so from driver's perspective, pitch is up and yaw is right pitch_net, yaw_net, roll_net = angles_desc face_pixel_position = ((pos_desc[0] + .5)*W - W + FULL_W, (pos_desc[1]+.5)*H) yaw_focal_angle = atan2(face_pixel_position[0] - FULL_W//2, RESIZED_FOCAL) pitch_focal_angle = atan2(face_pixel_position[1] - H//2, RESIZED_FOCAL) pitch = pitch_net + pitch_focal_angle yaw = -yaw_net + yaw_focal_angle # no calib for roll pitch -= rpy_calib[1] yaw -= rpy_calib[2] * (1 - 2 * int(is_rhd)) # lhd -> -=, rhd -> += return roll_net, pitch, yaw class DriverPose(): def __init__(self, max_trackable): self.yaw = 0. self.pitch = 0. self.roll = 0. self.yaw_std = 0. self.pitch_std = 0. self.roll_std = 0. self.pitch_offseter = RunningStatFilter(max_trackable=max_trackable) self.yaw_offseter = RunningStatFilter(max_trackable=max_trackable) self.low_std = True self.cfactor_pitch = 1. self.cfactor_yaw = 1. class DriverBlink(): def __init__(self): self.left_blink = 0. self.right_blink = 0. self.cfactor = 1. class DriverStatus(): def __init__(self, rhd=False, settings=DRIVER_MONITOR_SETTINGS()): # init policy settings self.settings = settings # init driver status self.is_rhd_region = rhd self.pose = DriverPose(self.settings._POSE_OFFSET_MAX_COUNT) self.pose_calibrated = False self.blink = DriverBlink() self.eev1 = 0. self.eev2 = 1. self.ee1_offseter = RunningStatFilter(max_trackable=self.settings._POSE_OFFSET_MAX_COUNT) self.ee2_offseter = RunningStatFilter(max_trackable=self.settings._POSE_OFFSET_MAX_COUNT) self.ee1_calibrated = False self.ee2_calibrated = False self.awareness = 1. self.awareness_active = 1. self.awareness_passive = 1. self.distracted_types = [] self.driver_distracted = False self.driver_distraction_filter = FirstOrderFilter(0., self.settings._DISTRACTED_FILTER_TS, self.settings._DT_DMON) self.face_detected = False self.face_partial = False self.terminal_alert_cnt = 0 self.terminal_time = 0 self.step_change = 0. self.active_monitoring_mode = True self.is_model_uncertain = False self.hi_stds = 0 self.threshold_pre = self.settings._DISTRACTED_PRE_TIME_TILL_TERMINAL / self.settings._DISTRACTED_TIME self.threshold_prompt = self.settings._DISTRACTED_PROMPT_TIME_TILL_TERMINAL / self.settings._DISTRACTED_TIME self._set_timers(active_monitoring=True) def _set_timers(self, active_monitoring): if self.active_monitoring_mode and self.awareness <= self.threshold_prompt: if active_monitoring: self.step_change = self.settings._DT_DMON / self.settings._DISTRACTED_TIME else: self.step_change = 0. return # no exploit after orange alert elif self.awareness <= 0.: return if active_monitoring: # when falling back from passive mode to active mode, reset awareness to avoid false alert if not self.active_monitoring_mode: self.awareness_passive = self.awareness self.awareness = self.awareness_active self.threshold_pre = self.settings._DISTRACTED_PRE_TIME_TILL_TERMINAL / self.settings._DISTRACTED_TIME self.threshold_prompt = self.settings._DISTRACTED_PROMPT_TIME_TILL_TERMINAL / self.settings._DISTRACTED_TIME self.step_change = self.settings._DT_DMON / self.settings._DISTRACTED_TIME self.active_monitoring_mode = True else: if self.active_monitoring_mode: self.awareness_active = self.awareness self.awareness = self.awareness_passive self.threshold_pre = self.settings._AWARENESS_PRE_TIME_TILL_TERMINAL / self.settings._AWARENESS_TIME self.threshold_prompt = self.settings._AWARENESS_PROMPT_TIME_TILL_TERMINAL / self.settings._AWARENESS_TIME self.step_change = self.settings._DT_DMON / self.settings._AWARENESS_TIME self.active_monitoring_mode = False def _get_distracted_types(self): distracted_types = [] if not self.pose_calibrated: pitch_error = self.pose.pitch - self.settings._PITCH_NATURAL_OFFSET yaw_error = self.pose.yaw - self.settings._YAW_NATURAL_OFFSET else: pitch_error = self.pose.pitch - min(max(self.pose.pitch_offseter.filtered_stat.mean(), self.settings._PITCH_MIN_OFFSET), self.settings._PITCH_MAX_OFFSET) yaw_error = self.pose.yaw - min(max(self.pose.yaw_offseter.filtered_stat.mean(), self.settings._YAW_MIN_OFFSET), self.settings._YAW_MAX_OFFSET) pitch_error = 0 if pitch_error > 0 else abs(pitch_error) # no positive pitch limit yaw_error = abs(yaw_error) if pitch_error > self.settings._POSE_PITCH_THRESHOLD*self.pose.cfactor_pitch or \ yaw_error > self.settings._POSE_YAW_THRESHOLD*self.pose.cfactor_yaw: distracted_types.append(DistractedType.DISTRACTED_POSE) if (self.blink.left_blink + self.blink.right_blink)*0.5 > self.settings._BLINK_THRESHOLD*self.blink.cfactor: distracted_types.append(DistractedType.DISTRACTED_BLINK) if self.ee1_calibrated: ee1_dist = self.eev1 > self.ee1_offseter.filtered_stat.M * self.settings._EE_THRESH12 else: ee1_dist = self.eev1 > self.settings._EE_THRESH11 if self.ee2_calibrated: ee2_dist = self.eev2 < self.ee2_offseter.filtered_stat.M * self.settings._EE_THRESH22 else: ee2_dist = self.eev2 < self.settings._EE_THRESH21 if ee1_dist or ee2_dist: distracted_types.append(DistractedType.DISTRACTED_E2E) return distracted_types def set_policy(self, model_data, car_speed): ep = min(model_data.meta.engagedProb, 0.8) / 0.8 # engaged prob bp = model_data.meta.disengagePredictions.brakeDisengageProbs[0] # brake disengage prob in next 2s # TODO: retune adaptive blink self.blink.cfactor = interp(ep, [0, 0.5, 1], [self.settings._BLINK_THRESHOLD_STRICT, self.settings._BLINK_THRESHOLD, self.settings._BLINK_THRESHOLD_SLACK]) / self.settings._BLINK_THRESHOLD k1 = max(-0.00156*((car_speed-16)**2)+0.6, 0.2) bp_normal = max(min(bp / k1, 0.5),0) self.pose.cfactor_pitch = interp(bp_normal, [0, 0.5], [self.settings._POSE_PITCH_THRESHOLD_SLACK, self.settings._POSE_PITCH_THRESHOLD_STRICT]) / self.settings._POSE_PITCH_THRESHOLD self.pose.cfactor_yaw = interp(bp_normal, [0, 0.5], [self.settings._POSE_YAW_THRESHOLD_SLACK, self.settings._POSE_YAW_THRESHOLD_STRICT]) / self.settings._POSE_YAW_THRESHOLD def update_states(self, driver_state, cal_rpy, car_speed, op_engaged): if not all(len(x) > 0 for x in (driver_state.faceOrientation, driver_state.facePosition, driver_state.faceOrientationStd, driver_state.facePositionStd, driver_state.readyProb, driver_state.notReadyProb)): return self.face_partial = driver_state.partialFace > self.settings._PARTIAL_FACE_THRESHOLD self.face_detected = driver_state.faceProb > self.settings._FACE_THRESHOLD or self.face_partial self.pose.roll, self.pose.pitch, self.pose.yaw = face_orientation_from_net(driver_state.faceOrientation, driver_state.facePosition, cal_rpy, self.is_rhd_region) self.pose.pitch_std = driver_state.faceOrientationStd[0] self.pose.yaw_std = driver_state.faceOrientationStd[1] # self.pose.roll_std = driver_state.faceOrientationStd[2] model_std_max = max(self.pose.pitch_std, self.pose.yaw_std) self.pose.low_std = model_std_max < self.settings._POSESTD_THRESHOLD and not self.face_partial self.blink.left_blink = driver_state.leftBlinkProb * (driver_state.leftEyeProb > self.settings._EYE_THRESHOLD) * (driver_state.sunglassesProb < self.settings._SG_THRESHOLD) self.blink.right_blink = driver_state.rightBlinkProb * (driver_state.rightEyeProb > self.settings._EYE_THRESHOLD) * (driver_state.sunglassesProb < self.settings._SG_THRESHOLD) self.eev1 = driver_state.notReadyProb[1] self.eev2 = driver_state.readyProb[0] self.distracted_types = self._get_distracted_types() self.driver_distracted = (DistractedType.DISTRACTED_POSE in self.distracted_types or DistractedType.DISTRACTED_BLINK in self.distracted_types) and \ driver_state.faceProb > self.settings._FACE_THRESHOLD and self.pose.low_std self.driver_distraction_filter.update(self.driver_distracted) # update offseter # only update when driver is actively driving the car above a certain speed if self.face_detected and car_speed > self.settings._POSE_CALIB_MIN_SPEED and self.pose.low_std and (not op_engaged or not self.driver_distracted): self.pose.pitch_offseter.push_and_update(self.pose.pitch) self.pose.yaw_offseter.push_and_update(self.pose.yaw) self.ee1_offseter.push_and_update(self.eev1) self.ee2_offseter.push_and_update(self.eev2) self.pose_calibrated = self.pose.pitch_offseter.filtered_stat.n > self.settings._POSE_OFFSET_MIN_COUNT and \ self.pose.yaw_offseter.filtered_stat.n > self.settings._POSE_OFFSET_MIN_COUNT self.ee1_calibrated = self.ee1_offseter.filtered_stat.n > self.settings._POSE_OFFSET_MIN_COUNT self.ee2_calibrated = self.ee2_offseter.filtered_stat.n > self.settings._POSE_OFFSET_MIN_COUNT self.is_model_uncertain = self.hi_stds > self.settings._HI_STD_FALLBACK_TIME self._set_timers(self.face_detected and not self.is_model_uncertain) if self.face_detected and not self.pose.low_std and not self.driver_distracted: self.hi_stds += 1 elif self.face_detected and self.pose.low_std: self.hi_stds = 0 def update_events(self, events, driver_engaged, ctrl_active, standstill): if (driver_engaged and self.awareness > 0) or not ctrl_active: # reset only when on disengagement if red reached self.awareness = 1. self.awareness_active = 1. self.awareness_passive = 1. return driver_attentive = self.driver_distraction_filter.x < 0.37 awareness_prev = self.awareness if (driver_attentive and self.face_detected and self.pose.low_std and self.awareness > 0): # only restore awareness when paying attention and alert is not red self.awareness = min(self.awareness + ((self.settings._RECOVERY_FACTOR_MAX-self.settings._RECOVERY_FACTOR_MIN)*(1.-self.awareness)+self.settings._RECOVERY_FACTOR_MIN)*self.step_change, 1.) if self.awareness == 1.: self.awareness_passive = min(self.awareness_passive + self.step_change, 1.) # don't display alert banner when awareness is recovering and has cleared orange if self.awareness > self.threshold_prompt: return standstill_exemption = standstill and self.awareness - self.step_change <= self.threshold_prompt certainly_distracted = self.driver_distraction_filter.x > 0.63 and self.driver_distracted and self.face_detected maybe_distracted = self.hi_stds > self.settings._HI_STD_FALLBACK_TIME or not self.face_detected if certainly_distracted or maybe_distracted: # should always be counting if distracted unless at standstill and reaching orange if not standstill_exemption: self.awareness = max(self.awareness - self.step_change, -0.1) alert = None if self.awareness <= 0.: # terminal red alert: disengagement required alert = EventName.driverDistracted if self.active_monitoring_mode else EventName.driverUnresponsive self.terminal_time += 1 if awareness_prev > 0.: self.terminal_alert_cnt += 1 elif self.awareness <= self.threshold_prompt: # prompt orange alert alert = EventName.promptDriverDistracted if self.active_monitoring_mode else EventName.promptDriverUnresponsive elif self.awareness <= self.threshold_pre: # pre green alert alert = EventName.preDriverDistracted if self.active_monitoring_mode else EventName.preDriverUnresponsive if alert is not None: events.add(alert)