No uncertain ll (#2495)
* initial, needs tune * support metrics * a little more * wrong type * fixup * update refs
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@ -21,7 +21,7 @@ def eval_poly(poly, x):
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return poly[3] + poly[2]*x + poly[1]*x**2 + poly[0]*x**3
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def calc_d_poly(l_poly, r_poly, p_poly, l_prob, r_prob, lane_width, v_ego):
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def calc_d_poly(l_poly, r_poly, p_poly, l_prob, r_prob, lane_width, v_ego, l_std=0.05, r_std=0.05):
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# This will improve behaviour when lanes suddenly widen
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# these numbers were tested on 2000segments and found to work well
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lane_width = min(4.0, lane_width)
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@ -34,6 +34,13 @@ def calc_d_poly(l_poly, r_poly, p_poly, l_prob, r_prob, lane_width, v_ego):
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l_prob = mod * l_prob
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r_prob = mod * r_prob
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# Remove reliance on uncertain lanelines
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# these numbers were tested on 2000segments and found to work well
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l_std_mod = interp(l_std, [.15, .3], [1.0, 0.0])
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l_prob = l_std_mod * l_prob
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r_std_mod = interp(r_std, [.15, .3], [1.0, 0.0])
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r_prob = r_std_mod * r_prob
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path_from_left_lane = l_poly.copy()
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path_from_left_lane[3] -= lane_width / 2.0
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path_from_right_lane = r_poly.copy()
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@ -59,6 +66,9 @@ class LanePlanner():
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self.l_prob = 0.
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self.r_prob = 0.
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self.l_std = 0.
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self.r_std = 0.
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self.l_lane_change_prob = 0.
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self.r_lane_change_prob = 0.
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@ -68,7 +78,9 @@ class LanePlanner():
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def parse_model(self, md):
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if len(md.leftLane.poly):
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self.l_poly = np.array(md.leftLane.poly)
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self.l_std = float(md.leftLane.std)
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self.r_poly = np.array(md.rightLane.poly)
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self.r_std = float(md.rightLane.std)
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self.p_poly = np.array(md.path.poly)
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else:
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self.l_poly = model_polyfit(md.leftLane.points, self._path_pinv) # left line
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@ -94,7 +106,7 @@ class LanePlanner():
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self.lane_width = self.lane_width_certainty * self.lane_width_estimate + \
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(1 - self.lane_width_certainty) * speed_lane_width
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self.d_poly = calc_d_poly(self.l_poly, self.r_poly, self.p_poly, self.l_prob, self.r_prob, self.lane_width, v_ego)
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self.d_poly = calc_d_poly(self.l_poly, self.r_poly, self.p_poly, self.l_prob, self.r_prob, self.lane_width, v_ego, self.l_std, self.r_std)
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def update(self, v_ego, md):
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self.parse_model(md)
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@ -1 +1 @@
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804ee1ffcfa0639782f1322874d89f0c8c412c50
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2d717d808d568c2a3939627430fc56747c52e5bd
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