bunch more typing

selfdrive/car/data_structures.py

@@ -73,9 +73,92 @@ class CarParams:
 
   notCar: bool = auto_field()  # flag for non-car robotics platforms
 
+  pcmCruise: bool = auto_field()  # is openpilot's state tied to the PCM's cruise state?
+  enableDsu: bool = auto_field()  # driving support unit
+  enableBsm: bool = auto_field()  # blind spot monitoring
+  flags: int = auto_field()  # flags for car specific quirks
+  experimentalLongitudinalAvailable: bool = auto_field()
+
+  minEnableSpeed: float = auto_field()
+  minSteerSpeed: float = auto_field()
+  # safetyConfigs: list[SafetyConfig] = auto_field()
+  alternativeExperience: int = auto_field()  # panda flag for features like no disengage on gas
+
+  maxLateralAccel: float = auto_field()
+  autoResumeSng: bool = auto_field()  # describes whether car can resume from a stop automatically
+
+  mass: float = auto_field()  # [kg] curb weight: all fluids no cargo
+  wheelbase: float = auto_field()  # [m] distance from rear axle to front axle
+  centerToFront: float = auto_field()  # [m] distance from center of mass to front axle
+  steerRatio: float = auto_field()  # [] ratio of steering wheel angle to front wheel angle
+  steerRatioRear: float = auto_field()  # [] ratio of steering wheel angle to rear wheel angle (usually 0)
+
+  rotationalInertia: float = auto_field()  # [kg*m2] body rotational inertia
+  tireStiffnessFactor: float = auto_field()  # scaling factor used in calculating tireStiffness[Front,Rear]
+  tireStiffnessFront: float = auto_field()  # [N/rad] front tire coeff of stiff
+  tireStiffnessRear: float = auto_field()  # [N/rad] rear tire coeff of stiff
+
+  longitudinalTuning: 'LongitudinalPIDTuning' = field(default_factory=lambda: CarParams.LongitudinalPIDTuning())
+  # lateralParams: LateralParams = auto_field()
+  lateralTuning: 'CarParams.LateralPIDTuning | CarParams.LateralTorqueTuning' = field(default_factory=lambda: CarParams.LateralPIDTuning())
+
+  @dataclass
+  @apply_auto_fields
+  class LateralPIDTuning:
+    kpBP: list[float] = auto_field()
+    kpV: list[float] = auto_field()
+    kiBP: list[float] = auto_field()
+    kiV: list[float] = auto_field()
+    kf: float = auto_field()
+
+  @dataclass
+  @apply_auto_fields
+  class LateralTorqueTuning:
+    useSteeringAngle: bool = auto_field()
+    kp: float = auto_field()
+    ki: float = auto_field()
+    friction: float = auto_field()
+    kf: float = auto_field()
+    steeringAngleDeadzoneDeg: float = auto_field()
+    latAccelFactor: float = auto_field()
+    latAccelOffset: float = auto_field()
+
+  steerLimitAlert: bool = auto_field()
+  steerLimitTimer: float = auto_field()  # time before steerLimitAlert is issued
+
+  vEgoStopping: float = auto_field()  # Speed at which the car goes into stopping state
+  vEgoStarting: float = auto_field()  # Speed at which the car goes into starting state
+  stoppingControl: bool = auto_field()  # Does the car allow full control even at lows speeds when stopping
+  steerControlType: 'CarParams.SteerControlType' = field(default_factory=lambda: CarParams.SteerControlType.torque)
+  radarUnavailable: bool = auto_field()  # True when radar objects aren't visible on CAN or aren't parsed out
+  stopAccel: float = auto_field()  # Required acceleration to keep vehicle stationary
+  stoppingDecelRate: float = auto_field()  # m/s^2/s while trying to stop
+  startAccel: float = auto_field()  # Required acceleration to get car moving
+  startingState: bool = auto_field()  # Does this car make use of special starting state
+
+  steerActuatorDelay: float = auto_field()  # Steering wheel actuator delay in seconds
+  longitudinalActuatorDelay: float = auto_field()  # Gas/Brake actuator delay in seconds
+  openpilotLongitudinalControl: bool = auto_field()  # is openpilot doing the longitudinal control?
+  carVin: str = auto_field()  # VIN number queried during fingerprinting
+  dashcamOnly: bool = auto_field()
+  passive: bool = auto_field()  # is openpilot in control?
+  # transmissionType: TransmissionType = auto_field()
   carFw: list['CarParams.CarFw'] = auto_field()
 
-  carVin: str = auto_field()
+  radarTimeStep: float = auto_field()  # time delta between radar updates, 20Hz is very standard
+  # fingerprintSource: FingerprintSource = auto_field()
+  # networkLocation: NetworkLocation = auto_field()  # Where Panda/C2 is integrated into the car's CAN network
+
+  wheelSpeedFactor: float = auto_field()  # Multiplier on wheels speeds to computer actual speeds
+
+  @dataclass
+  @apply_auto_fields
+  class LongitudinalPIDTuning:
+    kpBP: list[float] = auto_field()
+    kpV: list[float] = auto_field()
+    kiBP: list[float] = auto_field()
+    kiV: list[float] = auto_field()
+    kf: float = auto_field()
 
   class SteerControlType(StrEnum):
     torque = auto()
@@ -126,15 +209,3 @@ class CarParams:
     programmedFuelInjection = auto()
 
     debug = auto()
-
-  @dataclass
-  @apply_auto_fields
-  class LateralTorqueTuning:
-    useSteeringAngle: bool = auto_field()
-    kp: float = auto_field()
-    ki: float = auto_field()
-    friction: float = auto_field()
-    kf: float = auto_field()
-    steeringAngleDeadzoneDeg: float = auto_field()
-    latAccelFactor: float = auto_field()
-    latAccelOffset: float = auto_field()

selfdrive/car/gm/interface.py

@@ -1,5 +1,6 @@
 #!/usr/bin/env python3
 import os
+from typing import cast
 from cereal import car
 from math import fabs, exp
 from panda import Panda
@@ -63,7 +64,7 @@ class CarInterface(CarInterfaceBase):
     # An important thing to consider is that the slope at 0 should be > 0 (ideally >1)
     # This has big effect on the stability about 0 (noise when going straight)
     # ToDo: To generalize to other GMs, explore tanh function as the nonlinear
-    non_linear_torque_params = NON_LINEAR_TORQUE_PARAMS.get(self.CP.carFingerprint)
+    non_linear_torque_params = NON_LINEAR_TORQUE_PARAMS.get(cast(CAR, self.CP.carFingerprint))
     assert non_linear_torque_params, "The params are not defined"
     a, b, c, _ = non_linear_torque_params
     steer_torque = (sig(latcontrol_inputs.lateral_acceleration * a) * b) + (latcontrol_inputs.lateral_acceleration * c)

selfdrive/car/interfaces.py

@@ -88,7 +88,7 @@ def get_torque_params():
 # generic car and radar interfaces
 
 class CarInterfaceBase(ABC):
-  def __init__(self, CP, CarController, CarState):
+  def __init__(self, CP: CarParams, CarController, CarState):
     self.CP = CP
 
     self.frame = 0
@@ -178,8 +178,8 @@ class CarInterfaceBase(ABC):
 
   # returns a set of default params to avoid repetition in car specific params
   @staticmethod
-  def get_std_params(candidate):
-    ret = car.CarParams.new_message()
+  def get_std_params(candidate) -> CarParams:
+    ret = CarParams()
     ret.carFingerprint = candidate
 
     # Car docs fields
@@ -212,18 +212,20 @@ class CarInterfaceBase(ABC):
     return ret
 
   @staticmethod
-  def configure_torque_tune(candidate, tune, steering_angle_deadzone_deg=0.0, use_steering_angle=True):
+  def configure_torque_tune(candidate: str, ret: CarParams, steering_angle_deadzone_deg: float = 0.0, use_steering_angle: bool = True):
     params = get_torque_params()[candidate]
 
-    tune.init('torque')
-    tune.torque.useSteeringAngle = use_steering_angle
-    tune.torque.kp = 1.0
-    tune.torque.kf = 1.0
-    tune.torque.ki = 0.1
-    tune.torque.friction = params['FRICTION']
-    tune.torque.latAccelFactor = params['LAT_ACCEL_FACTOR']
-    tune.torque.latAccelOffset = 0.0
-    tune.torque.steeringAngleDeadzoneDeg = steering_angle_deadzone_deg
+    tune = CarParams.LateralTorqueTuning()
+    tune.useSteeringAngle = use_steering_angle
+    tune.kp = 1.0
+    tune.kf = 1.0
+    tune.ki = 0.1
+    tune.friction = params['FRICTION']
+    tune.latAccelFactor = params['LAT_ACCEL_FACTOR']
+    tune.latAccelOffset = 0.0
+    tune.steeringAngleDeadzoneDeg = steering_angle_deadzone_deg
+
+    ret.lateralTuning = tune
 
   @abstractmethod
   def _update(self, c: car.CarControl) -> car.CarState:
@@ -343,10 +345,10 @@ class CarInterfaceBase(ABC):
 
 
 class RadarInterfaceBase(ABC):
-  def __init__(self, CP):
+  def __init__(self, CP: CarParams):
     self.CP = CP
     self.rcp = None
-    self.pts = {}
+    self.pts: dict[int, RadarData.RadarPoint] = {}
     self.delay = 0
     self.radar_ts = CP.radarTimeStep
     self.frame = 0
@@ -359,7 +361,7 @@ class RadarInterfaceBase(ABC):
 
 
 class CarStateBase(ABC):
-  def __init__(self, CP):
+  def __init__(self, CP: CarParams):
     self.CP = CP
     self.car_fingerprint = CP.carFingerprint
     self.out = car.CarState.new_message()
@@ -463,7 +465,7 @@ class CarStateBase(ABC):
 
 
 class CarControllerBase(ABC):
-  def __init__(self, dbc_name: str, CP):
+  def __init__(self, dbc_name: str, CP: CarParams):
     self.CP = CP
     self.frame = 0
 

selfdrive/car/tests/test_car_interfaces.py

@@ -8,6 +8,7 @@ from parameterized import parameterized
 from cereal import car, messaging
 from openpilot.selfdrive.car import DT_CTRL, gen_empty_fingerprint
 from openpilot.selfdrive.car.car_helpers import interfaces
+from openpilot.selfdrive.car.data_structures import CarParams
 from openpilot.selfdrive.car.fingerprints import all_known_cars
 from openpilot.selfdrive.car.fw_versions import FW_VERSIONS, FW_QUERY_CONFIGS
 from openpilot.selfdrive.car.interfaces import get_interface_attr
@@ -42,8 +43,8 @@ def get_fuzzy_car_interface_args(draw: DrawType) -> dict:
   })
 
   params: dict = draw(params_strategy)
-  params['car_fw'] = [car.CarParams.CarFw(ecu=fw[0], address=fw[1], subAddress=fw[2] or 0,
-                                          request=draw(st.sampled_from(sorted(ALL_REQUESTS))))
+  params['car_fw'] = [CarParams.CarFw(ecu=fw[0], address=fw[1], subAddress=fw[2] or 0,
+                                      request=draw(st.sampled_from(sorted(ALL_REQUESTS))))
                       for fw in params['car_fw']]
   return params
 
@@ -62,7 +63,7 @@ class TestCarInterfaces:
 
     car_params = CarInterface.get_params(car_name, args['fingerprints'], args['car_fw'],
                                          experimental_long=args['experimental_long'], docs=False)
-    car_params = car_params.as_reader()
+    # car_params = car_params.as_reader()
     car_interface = CarInterface(car_params, CarController, CarState)
     assert car_params
     assert car_interface
@@ -78,16 +79,16 @@ class TestCarInterfaces:
     assert len(car_params.longitudinalTuning.kiV) == len(car_params.longitudinalTuning.kiBP)
 
     # Lateral sanity checks
-    if car_params.steerControlType != car.CarParams.SteerControlType.angle:
+    if car_params.steerControlType != CarParams.SteerControlType.angle:
       tune = car_params.lateralTuning
-      if tune.which() == 'pid':
-        assert not math.isnan(tune.pid.kf) and tune.pid.kf > 0
-        assert len(tune.pid.kpV) > 0 and len(tune.pid.kpV) == len(tune.pid.kpBP)
-        assert len(tune.pid.kiV) > 0 and len(tune.pid.kiV) == len(tune.pid.kiBP)
+      if isinstance(tune, CarParams.LateralPIDTuning):
+        assert not math.isnan(tune.kf) and tune.kf > 0
+        assert len(tune.kpV) > 0 and len(tune.kpV) == len(tune.kpBP)
+        assert len(tune.kiV) > 0 and len(tune.kiV) == len(tune.kiBP)
 
-      elif tune.which() == 'torque':
-        assert not math.isnan(tune.torque.kf) and tune.torque.kf > 0
-        assert not math.isnan(tune.torque.friction) and tune.torque.friction > 0
+      elif isinstance(tune, CarParams.LateralTorqueTuning):
+        assert not math.isnan(tune.kf) and tune.kf > 0
+        assert not math.isnan(tune.friction) and tune.friction > 0
 
     cc_msg = FuzzyGenerator.get_random_msg(data.draw, car.CarControl, real_floats=True)
     # Run car interface
@@ -109,11 +110,11 @@ class TestCarInterfaces:
     # TODO: wait until card refactor is merged to run controller a few times,
     #  hypothesis also slows down significantly with just one more message draw
     LongControl(car_params)
-    if car_params.steerControlType == car.CarParams.SteerControlType.angle:
+    if car_params.steerControlType == CarParams.SteerControlType.angle:
       LatControlAngle(car_params, car_interface)
-    elif car_params.lateralTuning.which() == 'pid':
+    elif isinstance(car_params.lateralTuning, CarParams.LateralPIDTuning):
       LatControlPID(car_params, car_interface)
-    elif car_params.lateralTuning.which() == 'torque':
+    elif isinstance(car_params.lateralTuning, CarParams.LateralTorqueTuning):
       LatControlTorque(car_params, car_interface)
 
     # Test radar interface

selfdrive/car/toyota/interface.py

@@ -4,6 +4,7 @@ from panda.python import uds
 from openpilot.selfdrive.car.toyota.values import Ecu, CAR, DBC, ToyotaFlags, CarControllerParams, TSS2_CAR, RADAR_ACC_CAR, NO_DSU_CAR, \
                                         MIN_ACC_SPEED, EPS_SCALE, UNSUPPORTED_DSU_CAR, NO_STOP_TIMER_CAR, ANGLE_CONTROL_CAR
 from openpilot.selfdrive.car import create_button_events, get_safety_config
+from openpilot.selfdrive.car.data_structures import CarParams
 from openpilot.selfdrive.car.disable_ecu import disable_ecu
 from openpilot.selfdrive.car.interfaces import CarInterfaceBase
 
@@ -35,7 +36,7 @@ class CarInterface(CarInterfaceBase):
       ret.steerActuatorDelay = 0.18
       ret.steerLimitTimer = 0.8
     else:
-      CarInterfaceBase.configure_torque_tune(candidate, ret.lateralTuning)
+      CarInterfaceBase.configure_torque_tune(candidate, ret)
 
       ret.steerActuatorDelay = 0.12  # Default delay, Prius has larger delay
       ret.steerLimitTimer = 0.4
@@ -66,20 +67,20 @@ class CarInterface(CarInterfaceBase):
       stop_and_go = candidate != CAR.TOYOTA_AVALON
 
     elif candidate in (CAR.TOYOTA_RAV4_TSS2, CAR.TOYOTA_RAV4_TSS2_2022, CAR.TOYOTA_RAV4_TSS2_2023):
-      ret.lateralTuning.init('pid')
-      ret.lateralTuning.pid.kiBP = [0.0]
-      ret.lateralTuning.pid.kpBP = [0.0]
-      ret.lateralTuning.pid.kpV = [0.6]
-      ret.lateralTuning.pid.kiV = [0.1]
-      ret.lateralTuning.pid.kf = 0.00007818594
+      ret.lateralTuning = CarParams.LateralPIDTuning()
+      ret.lateralTuning.kiBP = [0.0]
+      ret.lateralTuning.kpBP = [0.0]
+      ret.lateralTuning.kpV = [0.6]
+      ret.lateralTuning.kiV = [0.1]
+      ret.lateralTuning.kf = 0.00007818594
 
       # 2019+ RAV4 TSS2 uses two different steering racks and specific tuning seems to be necessary.
       # See https://github.com/commaai/openpilot/pull/21429#issuecomment-873652891
       for fw in car_fw:
         if fw.ecu == "eps" and (fw.fwVersion.startswith(b'\x02') or fw.fwVersion in [b'8965B42181\x00\x00\x00\x00\x00\x00']):
-          ret.lateralTuning.pid.kpV = [0.15]
-          ret.lateralTuning.pid.kiV = [0.05]
-          ret.lateralTuning.pid.kf = 0.00004
+          ret.lateralTuning.kpV = [0.15]
+          ret.lateralTuning.kiV = [0.05]
+          ret.lateralTuning.kf = 0.00004
           break
 
     elif candidate in (CAR.TOYOTA_CHR, CAR.TOYOTA_CAMRY, CAR.TOYOTA_SIENNA, CAR.LEXUS_CTH, CAR.LEXUS_NX):

selfdrive/car/toyota/radar_interface.py

@@ -1,6 +1,6 @@
 #!/usr/bin/env python3
 from opendbc.can.parser import CANParser
-from cereal import car
+from openpilot.selfdrive.car.data_structures import RadarData
 from openpilot.selfdrive.car.toyota.values import DBC, TSS2_CAR
 from openpilot.selfdrive.car.interfaces import RadarInterfaceBase
 
@@ -54,7 +54,7 @@ class RadarInterface(RadarInterfaceBase):
     return rr
 
   def _update(self, updated_messages):
-    ret = car.RadarData.new_message()
+    ret = RadarData()
     errors = []
     if not self.rcp.can_valid:
       errors.append("canError")
@@ -77,7 +77,7 @@ class RadarInterface(RadarInterfaceBase):
         # radar point only valid if it's a valid measurement and score is above 50
         if cpt['VALID'] or (score > 50 and cpt['LONG_DIST'] < 255 and self.valid_cnt[ii] > 0):
           if ii not in self.pts or cpt['NEW_TRACK']:
-            self.pts[ii] = car.RadarData.RadarPoint.new_message()
+            self.pts[ii] = RadarData.RadarPoint()
             self.pts[ii].trackId = self.track_id
             self.track_id += 1
           self.pts[ii].dRel = cpt['LONG_DIST']  # from front of car

selfdrive/car/toyota/values.py

@@ -31,8 +31,8 @@ class CarControllerParams:
   ANGLE_RATE_LIMIT_UP = AngleRateLimit(speed_bp=[5, 25], angle_v=[0.3, 0.15])
   ANGLE_RATE_LIMIT_DOWN = AngleRateLimit(speed_bp=[5, 25], angle_v=[0.36, 0.26])
 
-  def __init__(self, CP):
-    if CP.lateralTuning.which == 'torque':
+  def __init__(self, CP: CarParams):
+    if isinstance(CP.lateralTuning, CarParams.LateralTorqueTuning):
       self.STEER_DELTA_UP = 15       # 1.0s time to peak torque
       self.STEER_DELTA_DOWN = 25     # always lower than 45 otherwise the Rav4 faults (Prius seems ok with 50)
     else:

selfdrive/controls/lib/latcontrol_pid.py

@@ -8,9 +8,9 @@ from openpilot.selfdrive.controls.lib.pid import PIDController
 class LatControlPID(LatControl):
   def __init__(self, CP, CI):
     super().__init__(CP, CI)
-    self.pid = PIDController((CP.lateralTuning.pid.kpBP, CP.lateralTuning.pid.kpV),
-                             (CP.lateralTuning.pid.kiBP, CP.lateralTuning.pid.kiV),
-                             k_f=CP.lateralTuning.pid.kf, pos_limit=self.steer_max, neg_limit=-self.steer_max)
+    self.pid = PIDController((CP.lateralTuning.kpBP, CP.lateralTuning.kpV),
+                             (CP.lateralTuning.kiBP, CP.lateralTuning.kiV),
+                             k_f=CP.lateralTuning.kf, pos_limit=self.steer_max, neg_limit=-self.steer_max)
     self.get_steer_feedforward = CI.get_steer_feedforward_function()
 
   def reset(self):

selfdrive/controls/lib/latcontrol_torque.py

@@ -25,7 +25,7 @@ LOW_SPEED_Y = [15, 13, 10, 5]
 class LatControlTorque(LatControl):
   def __init__(self, CP, CI):
     super().__init__(CP, CI)
-    self.torque_params = CP.lateralTuning.torque.as_builder()
+    self.torque_params = CP.lateralTuning
     self.pid = PIDController(self.torque_params.kp, self.torque_params.ki,
                              k_f=self.torque_params.kf, pos_limit=self.steer_max, neg_limit=-self.steer_max)
     self.torque_from_lateral_accel = CI.torque_from_lateral_accel()