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116 lines
4.6 KiB
116 lines
4.6 KiB
import math
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import numpy as np
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from selfdrive.controls.lib.pid import PIController
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from selfdrive.controls.lib.drive_helpers import MPC_COST_LAT
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from selfdrive.controls.lib.lateral_mpc import libmpc_py
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from common.numpy_fast import interp
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from common.realtime import sec_since_boot
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from selfdrive.swaglog import cloudlog
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# 100ms is a rule of thumb estimation of lag from image processing to actuator command
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ACTUATORS_DELAY = 0.1
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_DT = 0.01 # 100Hz
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_DT_MPC = 0.05 # 20Hz
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def calc_states_after_delay(states, v_ego, steer_angle, curvature_factor, steer_ratio):
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states[0].x = v_ego * ACTUATORS_DELAY
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states[0].psi = v_ego * curvature_factor * math.radians(steer_angle) / steer_ratio * ACTUATORS_DELAY
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return states
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def get_steer_max(CP, v_ego):
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return interp(v_ego, CP.steerMaxBP, CP.steerMaxV)
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class LatControl(object):
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def __init__(self, VM):
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self.pid = PIController((VM.CP.steerKpBP, VM.CP.steerKpV),
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(VM.CP.steerKiBP, VM.CP.steerKiV),
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k_f=VM.CP.steerKf, pos_limit=1.0)
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self.last_cloudlog_t = 0.0
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self.setup_mpc(VM.CP.steerRateCost)
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def setup_mpc(self, steer_rate_cost):
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self.libmpc = libmpc_py.libmpc
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self.libmpc.init(MPC_COST_LAT.PATH, MPC_COST_LAT.LANE, MPC_COST_LAT.HEADING, steer_rate_cost)
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self.mpc_solution = libmpc_py.ffi.new("log_t *")
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self.cur_state = libmpc_py.ffi.new("state_t *")
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self.mpc_updated = False
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self.cur_state[0].x = 0.0
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self.cur_state[0].y = 0.0
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self.cur_state[0].psi = 0.0
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self.cur_state[0].delta = 0.0
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self.last_mpc_ts = 0.0
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self.angle_steers_des = 0.0
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self.angle_steers_des_mpc = 0.0
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self.angle_steers_des_prev = 0.0
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self.angle_steers_des_time = 0.0
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def reset(self):
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self.pid.reset()
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def update(self, active, v_ego, angle_steers, steer_override, d_poly, angle_offset, VM, PL):
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cur_time = sec_since_boot()
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self.mpc_updated = False
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if self.last_mpc_ts < PL.last_md_ts:
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self.last_mpc_ts = PL.last_md_ts
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self.angle_steers_des_prev = self.angle_steers_des_mpc
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curvature_factor = VM.curvature_factor(v_ego)
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l_poly = libmpc_py.ffi.new("double[4]", list(PL.PP.l_poly))
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r_poly = libmpc_py.ffi.new("double[4]", list(PL.PP.r_poly))
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p_poly = libmpc_py.ffi.new("double[4]", list(PL.PP.p_poly))
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# account for actuation delay
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self.cur_state = calc_states_after_delay(self.cur_state, v_ego, angle_steers, curvature_factor, VM.CP.steerRatio)
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v_ego_mpc = max(v_ego, 5.0) # avoid mpc roughness due to low speed
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self.libmpc.run_mpc(self.cur_state, self.mpc_solution,
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l_poly, r_poly, p_poly,
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PL.PP.l_prob, PL.PP.r_prob, PL.PP.p_prob, curvature_factor, v_ego_mpc, PL.PP.lane_width)
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# reset to current steer angle if not active or overriding
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if active:
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delta_desired = self.mpc_solution[0].delta[1]
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else:
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delta_desired = math.radians(angle_steers - angle_offset) / VM.CP.steerRatio
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self.cur_state[0].delta = delta_desired
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self.angle_steers_des_mpc = float(math.degrees(delta_desired * VM.CP.steerRatio) + angle_offset)
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self.angle_steers_des_time = cur_time
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self.mpc_updated = True
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# Check for infeasable MPC solution
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nans = np.any(np.isnan(list(self.mpc_solution[0].delta)))
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t = sec_since_boot()
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if nans:
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self.libmpc.init(MPC_COST_LAT.PATH, MPC_COST_LAT.LANE, MPC_COST_LAT.HEADING, VM.CP.steerRateCost)
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self.cur_state[0].delta = math.radians(angle_steers) / VM.CP.steerRatio
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if t > self.last_cloudlog_t + 5.0:
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self.last_cloudlog_t = t
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cloudlog.warning("Lateral mpc - nan: True")
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if v_ego < 0.3 or not active:
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output_steer = 0.0
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self.pid.reset()
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else:
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# TODO: ideally we should interp, but for tuning reasons we keep the mpc solution
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# constant for 0.05s.
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#dt = min(cur_time - self.angle_steers_des_time, _DT_MPC + _DT) + _DT # no greater than dt mpc + dt, to prevent too high extraps
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#self.angle_steers_des = self.angle_steers_des_prev + (dt / _DT_MPC) * (self.angle_steers_des_mpc - self.angle_steers_des_prev)
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self.angle_steers_des = self.angle_steers_des_mpc
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steers_max = get_steer_max(VM.CP, v_ego)
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self.pid.pos_limit = steers_max
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self.pid.neg_limit = -steers_max
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steer_feedforward = self.angle_steers_des * v_ego**2 # proportional to realigning tire momentum (~ lateral accel)
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output_steer = self.pid.update(self.angle_steers_des, angle_steers, check_saturation=(v_ego > 10), override=steer_override, feedforward=steer_feedforward, speed=v_ego)
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self.sat_flag = self.pid.saturated
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return output_steer, float(self.angle_steers_des)
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