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68 lines
1.7 KiB
68 lines
1.7 KiB
from common.numpy_fast import clip
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from cereal import car
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class MPC_COST_LAT:
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PATH = 1.0
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LANE = 3.0
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HEADING = 1.0
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STEER_RATE = 1.0
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class MPC_COST_LONG:
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TTC = 5.0
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DISTANCE = 0.1
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ACCELERATION = 10.0
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JERK = 20.0
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class EventTypes:
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ENABLE = 'enable'
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PRE_ENABLE = 'preEnable'
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NO_ENTRY = 'noEntry'
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WARNING = 'warning'
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USER_DISABLE = 'userDisable'
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SOFT_DISABLE = 'softDisable'
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IMMEDIATE_DISABLE = 'immediateDisable'
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PERMANENT = 'permanent'
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def create_event(name, types):
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event = car.CarEvent.new_message()
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event.name = name
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for t in types:
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setattr(event, t, True)
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return event
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def get_events(events, types):
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out = []
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for e in events:
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for t in types:
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if getattr(e, t):
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out.append(e.name)
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return out
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def rate_limit(new_value, last_value, dw_step, up_step):
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return clip(new_value, last_value + dw_step, last_value + up_step)
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def learn_angle_offset(lateral_control, v_ego, angle_offset, c_poly, c_prob, angle_steers, steer_override):
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# simple integral controller that learns how much steering offset to put to have the car going straight
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# while being in the middle of the lane
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min_offset = -5. # deg
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max_offset = 5. # deg
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alpha = 1./36000. # correct by 1 deg in 2 mins, at 30m/s, with 50cm of error, at 20Hz
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min_learn_speed = 1.
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# learn less at low speed or when turning
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slow_factor = 1. / (1. + 0.02 * abs(angle_steers) * v_ego)
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alpha_v = alpha * c_prob * (max(v_ego - min_learn_speed, 0.)) * slow_factor
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# only learn if lateral control is active and if driver is not overriding:
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if lateral_control and not steer_override:
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angle_offset += c_poly[3] * alpha_v
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angle_offset = clip(angle_offset, min_offset, max_offset)
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return angle_offset
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