Upstream Lat

selfdrive/car/interfaces.py

@@ -37,7 +37,7 @@ EventName = car.CarEvent.EventName
 MAX_CTRL_SPEED = (V_CRUISE_MAX + 4) * CV.KPH_TO_MS
 ACCEL_MAX = 2.0
 ACCEL_MIN = -3.5
-FRICTION_THRESHOLD = 0.3
+FRICTION_THRESHOLD = 0.2
 
 TORQUE_PARAMS_PATH = os.path.join(BASEDIR, 'selfdrive/car/torque_data/params.toml')
 TORQUE_OVERRIDE_PATH = os.path.join(BASEDIR, 'selfdrive/car/torque_data/override.toml')

selfdrive/controls/lib/latcontrol_torque.py

@@ -3,9 +3,9 @@ import numpy as np
 from collections import deque
 
 from cereal import log
-from openpilot.common.filter_simple import FirstOrderFilter
 from openpilot.selfdrive.car.interfaces import FRICTION_THRESHOLD
 from openpilot.selfdrive.controls.lib.drive_helpers import MIN_SPEED, get_friction
+from openpilot.common.filter_simple import FirstOrderFilter
 from openpilot.selfdrive.controls.lib.latcontrol import LatControl
 from openpilot.selfdrive.controls.lib.pid import PIDController
 from openpilot.selfdrive.controls.lib.vehicle_model import ACCELERATION_DUE_TO_GRAVITY
@@ -16,29 +16,36 @@ from openpilot.selfdrive.controls.lib.vehicle_model import ACCELERATION_DUE_TO_G
 # wheel slip, or to speed.
 
 # This controller applies torque to achieve desired lateral
-# accelerations. To compensate for the low speed effects we
-# use a LOW_SPEED_FACTOR in the error. Additionally, there is
-# friction in the steering wheel that needs to be overcome to
-# move it at all, this is compensated for too.
+# accelerations. To compensate for the low speed effects the
+# proportional gain is increased at low speeds by the PID controller.
+# Additionally, there is friction in the steering wheel that needs
+# to be overcome to move it at all, this is compensated for too.
 
-LOW_SPEED_X = [0, 10, 20, 30]
-LOW_SPEED_Y = [15, 13, 10, 5]
+KP = 0.6
+KI = 0.15
 
-MAX_LAT_JERK_UP = 2.5            # m/s^3
+INTERP_SPEEDS = [1, 1.5, 2.0, 3.0, 5, 7.5, 10, 15, 30]
+KP_INTERP = [250, 120, 65, 30, 11.5, 5.5, 3.5, 2.0, KP]
+
+LP_FILTER_CUTOFF_HZ = 1.2
+JERK_LOOKAHEAD_SECONDS = 0.19
+JERK_GAIN = 0.3
+LAT_ACCEL_REQUEST_BUFFER_SECONDS = 1.0
+VERSION = 1
 
 class LatControlTorque(LatControl):
   def __init__(self, CP, CI, dt):
     super().__init__(CP, CI, dt)
-    self.torque_params = CP.lateralTuning.torque
+    self.torque_params = CP.lateralTuning.torque.as_builder()
     self.torque_from_lateral_accel = CI.torque_from_lateral_accel()
     self.lateral_accel_from_torque = CI.lateral_accel_from_torque()
-    self.pid = PIDController(self.torque_params.kp, self.torque_params.ki, rate=1/self.dt)
+    self.pid = PIDController([INTERP_SPEEDS, KP_INTERP], KI, rate=1/self.dt)
     self.update_limits()
     self.steering_angle_deadzone_deg = self.torque_params.steeringAngleDeadzoneDeg
-    self.LATACCEL_REQUEST_BUFFER_NUM_FRAMES = int(1 / self.dt)
-    self.requested_lateral_accel_buffer = deque([0.] * self.LATACCEL_REQUEST_BUFFER_NUM_FRAMES , maxlen=self.LATACCEL_REQUEST_BUFFER_NUM_FRAMES)
-    self.previous_measurement = 0.0
-    self.measurement_rate_filter = FirstOrderFilter(0.0, 1 / (2 * np.pi * (MAX_LAT_JERK_UP - 0.5)), self.dt)
+    self.lat_accel_request_buffer_len = int(LAT_ACCEL_REQUEST_BUFFER_SECONDS / self.dt)
+    self.lat_accel_request_buffer = deque([0.] * self.lat_accel_request_buffer_len , maxlen=self.lat_accel_request_buffer_len)
+    self.lookahead_frames = int(JERK_LOOKAHEAD_SECONDS / self.dt)
+    self.jerk_filter = FirstOrderFilter(0.0, 1 / (2 * np.pi * LP_FILTER_CUTOFF_HZ), self.dt)
 
   def update_live_torque_params(self, latAccelFactor, latAccelOffset, friction):
     self.torque_params.latAccelFactor = latAccelFactor
@@ -52,6 +59,7 @@ class LatControlTorque(LatControl):
 
   def update(self, active, CS, VM, params, steer_limited_by_safety, desired_curvature, curvature_limited, lat_delay, llk, model_data, frogpilot_toggles):
     pid_log = log.ControlsState.LateralTorqueState.new_message()
+    pid_log.version = VERSION
     if not active:
       output_torque = 0.0
       pid_log.active = False
@@ -61,37 +69,28 @@ class LatControlTorque(LatControl):
       curvature_deadzone = abs(VM.calc_curvature(math.radians(self.steering_angle_deadzone_deg), CS.vEgo, 0.0))
       lateral_accel_deadzone = curvature_deadzone * CS.vEgo ** 2
 
-      delay_frames = int(np.clip(lat_delay / self.dt, 1, self.LATACCEL_REQUEST_BUFFER_NUM_FRAMES))
-      expected_lateral_accel = self.requested_lateral_accel_buffer[-delay_frames]
-      # TODO factor out lateral jerk from error to later replace it with delay independent alternative
+      delay_frames = int(np.clip(lat_delay / self.dt, 1, self.lat_accel_request_buffer_len))
+      expected_lateral_accel = self.lat_accel_request_buffer[-delay_frames]
+      lookahead_idx = int(np.clip(-delay_frames + self.lookahead_frames, -self.lat_accel_request_buffer_len+1, -2))
+      raw_lateral_jerk = (self.lat_accel_request_buffer[lookahead_idx+1] - self.lat_accel_request_buffer[lookahead_idx-1]) / (2 * self.dt)
+      desired_lateral_jerk = self.jerk_filter.update(raw_lateral_jerk)
       future_desired_lateral_accel = desired_curvature * CS.vEgo ** 2
-      self.requested_lateral_accel_buffer.append(future_desired_lateral_accel)
+      self.lat_accel_request_buffer.append(future_desired_lateral_accel)
       gravity_adjusted_future_lateral_accel = future_desired_lateral_accel - roll_compensation
-      desired_lateral_jerk = (future_desired_lateral_accel - expected_lateral_accel) / lat_delay
+      setpoint = expected_lateral_accel
 
       measurement = measured_curvature * CS.vEgo ** 2
-      measurement_rate = self.measurement_rate_filter.update((measurement - self.previous_measurement) / self.dt)
-      self.previous_measurement = measurement
-
-      low_speed_factor = (np.interp(CS.vEgo, LOW_SPEED_X, LOW_SPEED_Y) / max(CS.vEgo, MIN_SPEED)) ** 2
-      setpoint = lat_delay * desired_lateral_jerk + expected_lateral_accel
       error = setpoint - measurement
-      error_lsf = error + low_speed_factor / self.torque_params.kp * error
 
       # do error correction in lateral acceleration space, convert at end to handle non-linear torque responses correctly
-      pid_log.error = float(error_lsf)
+      pid_log.error = float(error)
       ff = gravity_adjusted_future_lateral_accel
       # latAccelOffset corrects roll compensation bias from device roll misalignment relative to car roll
       ff -= self.torque_params.latAccelOffset
-      # TODO jerk is weighted by lat_delay for legacy reasons, but should be made independent of it
-      ff += get_friction(error, lateral_accel_deadzone, FRICTION_THRESHOLD, self.torque_params)
+      ff += get_friction(error + JERK_GAIN * desired_lateral_jerk, lateral_accel_deadzone, FRICTION_THRESHOLD, self.torque_params)
 
       freeze_integrator = steer_limited_by_safety or CS.steeringPressed or CS.vEgo < 5
-      output_lataccel = self.pid.update(pid_log.error,
-                                       -measurement_rate,
-                                        feedforward=ff,
-                                        speed=CS.vEgo,
-                                        freeze_integrator=freeze_integrator)
+      output_lataccel = self.pid.update(pid_log.error, speed=CS.vEgo, feedforward=ff, freeze_integrator=freeze_integrator)
       output_torque = self.torque_from_lateral_accel(output_lataccel, self.torque_params)
 
       pid_log.active = True
@@ -99,9 +98,10 @@ class LatControlTorque(LatControl):
       pid_log.i = float(self.pid.i)
       pid_log.d = float(self.pid.d)
       pid_log.f = float(self.pid.f)
-      pid_log.output = float(-output_torque)  # TODO: log lat accel?
+      pid_log.output = float(-output_torque) # TODO: log lat accel?
       pid_log.actualLateralAccel = float(measurement)
       pid_log.desiredLateralAccel = float(setpoint)
+      pid_log.desiredLateralJerk = float(desired_lateral_jerk)
       pid_log.saturated = bool(self._check_saturation(self.steer_max - abs(output_torque) < 1e-3, CS, steer_limited_by_safety, curvature_limited))
 
     # TODO left is positive in this convention