selfdrive.controls.lib package

Subpackages

• selfdrive.controls.lib.lateral_mpc_lib package
  • Submodules
  • selfdrive.controls.lib.lateral_mpc_lib.lat_mpc module
    • LateralMpc
      • LateralMpc.reset()
      • LateralMpc.run()
      • LateralMpc.set_weights()
    • gen_lat_model()
    • gen_lat_ocp()
  • Module contents
• selfdrive.controls.lib.longitudinal_mpc_lib package
  • Submodules
  • selfdrive.controls.lib.longitudinal_mpc_lib.long_mpc module
    • LongitudinalMpc
      • LongitudinalMpc.extrapolate_lead()
      • LongitudinalMpc.process_lead()
      • LongitudinalMpc.reset()
      • LongitudinalMpc.run()
      • LongitudinalMpc.set_accel_limits()
      • LongitudinalMpc.set_cost_weights()
      • LongitudinalMpc.set_cur_state()
      • LongitudinalMpc.set_weights()
      • LongitudinalMpc.update()
    • desired_follow_distance()
    • gen_long_model()
    • gen_long_ocp()
    • get_T_FOLLOW()
    • get_jerk_factor()
    • get_safe_obstacle_distance()
    • get_stopped_equivalence_factor()
  • Module contents
• selfdrive.controls.lib.tests package
  • Submodules
  • selfdrive.controls.lib.tests.test_alertmanager module
    • TestAlertManager
      • TestAlertManager.test_duration()
  • selfdrive.controls.lib.tests.test_latcontrol module
    • TestLatControl
      • TestLatControl.test_saturation
      • TestLatControl.test_saturation_0_HONDA_CIVIC()
      • TestLatControl.test_saturation_1_TOYOTA_RAV4()
      • TestLatControl.test_saturation_2_NISSAN_LEAF()
  • selfdrive.controls.lib.tests.test_vehicle_model module
    • TestVehicleModel
      • TestVehicleModel.setUp()
      • TestVehicleModel.test_dyn_ss_sol_against_yaw_rate()
      • TestVehicleModel.test_round_trip_yaw_rate()
      • TestVehicleModel.test_syn_ss_sol_simulate()
  • Module contents

Submodules

selfdrive.controls.lib.alertmanager module

class selfdrive.controls.lib.alertmanager.AlertEntry(alert: openpilot.selfdrive.controls.lib.events.Alert | None = None, start_frame: int = -1, end_frame: int = -1)

Bases: object

active(frame: int) → bool

alert: Alert | None = None

end_frame: int = -1

start_frame: int = -1

class selfdrive.controls.lib.alertmanager.AlertManager

Bases: object

add_many(frame: int, alerts: list[Alert]) → None

process_alerts(frame: int, clear_event_types: set) → Alert | None

selfdrive.controls.lib.alertmanager.set_offroad_alert(alert: str, show_alert: bool, extra_text: str = None) → None

selfdrive.controls.lib.desire_helper module

class selfdrive.controls.lib.desire_helper.DesireHelper

Bases: object

update(carstate, lateral_active, lane_change_prob)

selfdrive.controls.lib.drive_helpers module

class selfdrive.controls.lib.drive_helpers.VCruiseHelper(CP)

Bases: object

initialize_v_cruise(CS, experimental_mode: bool) → None

update_button_timers(CS, enabled)

update_v_cruise(CS, enabled, is_metric)

property v_cruise_initialized

selfdrive.controls.lib.drive_helpers.apply_center_deadzone(error, deadzone)

selfdrive.controls.lib.drive_helpers.apply_deadzone(error, deadzone)

selfdrive.controls.lib.drive_helpers.clip_curvature(v_ego, prev_curvature, new_curvature)

selfdrive.controls.lib.drive_helpers.get_friction(lateral_accel_error: float, lateral_accel_deadzone: float, friction_threshold: float, torque_params: <capnp.lib.capnp._StructModule object at 0x7f3309048510>, friction_compensation: bool) → float

selfdrive.controls.lib.drive_helpers.get_speed_error(modelV2: <capnp.lib.capnp._StructModule object at 0x7f33092e4ad0>, v_ego: float) → float

selfdrive.controls.lib.drive_helpers.rate_limit(new_value, last_value, dw_step, up_step)

selfdrive.controls.lib.events module

class selfdrive.controls.lib.events.Alert(alert_text_1: str, alert_text_2: str, alert_status: <capnp.lib.capnp._EnumModule object at 0x7f33092d33d0>, alert_size: <capnp.lib.capnp._EnumModule object at 0x7f33092d3250>, priority: ~selfdrive.controls.lib.events.Priority, visual_alert: <capnp.lib.capnp._EnumModule object at 0x7f3309037250>, audible_alert: <capnp.lib.capnp._EnumModule object at 0x7f3309037450>, duration: float, alert_rate: float = 0.0, creation_delay: float = 0.0)

Bases: object

class selfdrive.controls.lib.events.ET

Bases: object

ENABLE = 'enable'

IMMEDIATE_DISABLE = 'immediateDisable'

NO_ENTRY = 'noEntry'

OVERRIDE_LATERAL = 'overrideLateral'

OVERRIDE_LONGITUDINAL = 'overrideLongitudinal'

PERMANENT = 'permanent'

PRE_ENABLE = 'preEnable'

SOFT_DISABLE = 'softDisable'

USER_DISABLE = 'userDisable'

WARNING = 'warning'

class selfdrive.controls.lib.events.EngagementAlert(audible_alert: <capnp.lib.capnp._EnumModule object at 0x7f3309037450>)

Bases: Alert

class selfdrive.controls.lib.events.Events

Bases: object

add(event_name: int, static: bool = False) → None

add_from_msg(events)

clear() → None

contains(event_type: str) → bool

create_alerts(event_types: list[str], callback_args=None)

property names: list[int]

to_msg()

class selfdrive.controls.lib.events.ImmediateDisableAlert(alert_text_2: str)

Bases: Alert

class selfdrive.controls.lib.events.NoEntryAlert(alert_text_2: str, alert_text_1: str = 'openpilot Unavailable', visual_alert: <capnp.lib.capnp._EnumModule object at 0x7f3309037250> = 0)

Bases: Alert

class selfdrive.controls.lib.events.NormalPermanentAlert(alert_text_1: str, alert_text_2: str = '', duration: float = 0.2, priority: Priority = Priority.LOWER, creation_delay: float = 0.0)

Bases: Alert

class selfdrive.controls.lib.events.Priority(value, names=None, *, module=None, qualname=None, type=None, start=1, boundary=None)

Bases: IntEnum

HIGH = 4

HIGHEST = 5

LOW = 2

LOWER = 1

LOWEST = 0

MID = 3

class selfdrive.controls.lib.events.SoftDisableAlert(alert_text_2: str)

Bases: Alert

class selfdrive.controls.lib.events.StartupAlert(alert_text_1: str, alert_text_2: str = 'Always keep hands on wheel and eyes on road', alert_status=0)

Bases: Alert

class selfdrive.controls.lib.events.UserSoftDisableAlert(alert_text_2: str)

Bases: SoftDisableAlert

selfdrive.controls.lib.events.below_engage_speed_alert(CP: <capnp.lib.capnp._StructModule object at 0x7f3309037850>, CS: <capnp.lib.capnp._StructModule object at 0x7f3309034f50>, sm: ~cereal.messaging.SubMaster, metric: bool, soft_disable_time: int) → Alert

selfdrive.controls.lib.events.below_steer_speed_alert(CP: <capnp.lib.capnp._StructModule object at 0x7f3309037850>, CS: <capnp.lib.capnp._StructModule object at 0x7f3309034f50>, sm: ~cereal.messaging.SubMaster, metric: bool, soft_disable_time: int) → Alert

selfdrive.controls.lib.events.calibration_incomplete_alert(CP: <capnp.lib.capnp._StructModule object at 0x7f3309037850>, CS: <capnp.lib.capnp._StructModule object at 0x7f3309034f50>, sm: ~cereal.messaging.SubMaster, metric: bool, soft_disable_time: int) → Alert

selfdrive.controls.lib.events.calibration_invalid_alert(CP: <capnp.lib.capnp._StructModule object at 0x7f3309037850>, CS: <capnp.lib.capnp._StructModule object at 0x7f3309034f50>, sm: ~cereal.messaging.SubMaster, metric: bool, soft_disable_time: int) → Alert

selfdrive.controls.lib.events.camera_malfunction_alert(CP: <capnp.lib.capnp._StructModule object at 0x7f3309037850>, CS: <capnp.lib.capnp._StructModule object at 0x7f3309034f50>, sm: ~cereal.messaging.SubMaster, metric: bool, soft_disable_time: int) → Alert

selfdrive.controls.lib.events.comm_issue_alert(CP: <capnp.lib.capnp._StructModule object at 0x7f3309037850>, CS: <capnp.lib.capnp._StructModule object at 0x7f3309034f50>, sm: ~cereal.messaging.SubMaster, metric: bool, soft_disable_time: int) → Alert

selfdrive.controls.lib.events.get_display_speed(speed_ms: float, metric: bool) → str

selfdrive.controls.lib.events.high_cpu_usage_alert(CP: <capnp.lib.capnp._StructModule object at 0x7f3309037850>, CS: <capnp.lib.capnp._StructModule object at 0x7f3309034f50>, sm: ~cereal.messaging.SubMaster, metric: bool, soft_disable_time: int) → Alert

selfdrive.controls.lib.events.joystick_alert(CP: <capnp.lib.capnp._StructModule object at 0x7f3309037850>, CS: <capnp.lib.capnp._StructModule object at 0x7f3309034f50>, sm: ~cereal.messaging.SubMaster, metric: bool, soft_disable_time: int) → Alert

selfdrive.controls.lib.events.low_memory_alert(CP: <capnp.lib.capnp._StructModule object at 0x7f3309037850>, CS: <capnp.lib.capnp._StructModule object at 0x7f3309034f50>, sm: ~cereal.messaging.SubMaster, metric: bool, soft_disable_time: int) → Alert

selfdrive.controls.lib.events.modeld_lagging_alert(CP: <capnp.lib.capnp._StructModule object at 0x7f3309037850>, CS: <capnp.lib.capnp._StructModule object at 0x7f3309034f50>, sm: ~cereal.messaging.SubMaster, metric: bool, soft_disable_time: int) → Alert

selfdrive.controls.lib.events.no_gps_alert(CP: <capnp.lib.capnp._StructModule object at 0x7f3309037850>, CS: <capnp.lib.capnp._StructModule object at 0x7f3309034f50>, sm: ~cereal.messaging.SubMaster, metric: bool, soft_disable_time: int) → Alert

selfdrive.controls.lib.events.out_of_space_alert(CP: <capnp.lib.capnp._StructModule object at 0x7f3309037850>, CS: <capnp.lib.capnp._StructModule object at 0x7f3309034f50>, sm: ~cereal.messaging.SubMaster, metric: bool, soft_disable_time: int) → Alert

selfdrive.controls.lib.events.overheat_alert(CP: <capnp.lib.capnp._StructModule object at 0x7f3309037850>, CS: <capnp.lib.capnp._StructModule object at 0x7f3309034f50>, sm: ~cereal.messaging.SubMaster, metric: bool, soft_disable_time: int) → Alert

selfdrive.controls.lib.events.posenet_invalid_alert(CP: <capnp.lib.capnp._StructModule object at 0x7f3309037850>, CS: <capnp.lib.capnp._StructModule object at 0x7f3309034f50>, sm: ~cereal.messaging.SubMaster, metric: bool, soft_disable_time: int) → Alert

selfdrive.controls.lib.events.process_not_running_alert(CP: <capnp.lib.capnp._StructModule object at 0x7f3309037850>, CS: <capnp.lib.capnp._StructModule object at 0x7f3309034f50>, sm: ~cereal.messaging.SubMaster, metric: bool, soft_disable_time: int) → Alert

selfdrive.controls.lib.events.soft_disable_alert(alert_text_2: str) → Alert]

selfdrive.controls.lib.events.startup_master_alert(CP: <capnp.lib.capnp._StructModule object at 0x7f3309037850>, CS: <capnp.lib.capnp._StructModule object at 0x7f3309034f50>, sm: ~cereal.messaging.SubMaster, metric: bool, soft_disable_time: int) → Alert

selfdrive.controls.lib.events.user_soft_disable_alert(alert_text_2: str) → Alert]

selfdrive.controls.lib.events.wrong_car_mode_alert(CP: <capnp.lib.capnp._StructModule object at 0x7f3309037850>, CS: <capnp.lib.capnp._StructModule object at 0x7f3309034f50>, sm: ~cereal.messaging.SubMaster, metric: bool, soft_disable_time: int) → Alert

selfdrive.controls.lib.latcontrol module

class selfdrive.controls.lib.latcontrol.LatControl(CP, CI)

Bases: ABC

reset()

abstract update(active, CS, VM, params, steer_limited, desired_curvature, llk)

selfdrive.controls.lib.latcontrol_angle module

class selfdrive.controls.lib.latcontrol_angle.LatControlAngle(CP, CI)

Bases: LatControl

update(active, CS, VM, params, steer_limited, desired_curvature, llk)

selfdrive.controls.lib.latcontrol_pid module

class selfdrive.controls.lib.latcontrol_pid.LatControlPID(CP, CI)

Bases: LatControl

reset()

update(active, CS, VM, params, steer_limited, desired_curvature, llk)

selfdrive.controls.lib.latcontrol_torque module

class selfdrive.controls.lib.latcontrol_torque.LatControlTorque(CP, CI)

Bases: LatControl

update(active, CS, VM, params, steer_limited, desired_curvature, llk)

update_live_torque_params(latAccelFactor, latAccelOffset, friction)

selfdrive.controls.lib.longcontrol module

class selfdrive.controls.lib.longcontrol.LongControl(CP)

Bases: object

reset(v_pid)

Reset PID controller and change setpoint

update(active, CS, long_plan, accel_limits, t_since_plan)

Update longitudinal control. This updates the state machine and runs a PID loop

selfdrive.controls.lib.longcontrol.long_control_state_trans(CP, active, long_control_state, v_ego, v_target, v_target_1sec, brake_pressed, cruise_standstill)

selfdrive.controls.lib.longitudinal_planner module

class selfdrive.controls.lib.longitudinal_planner.LongitudinalPlanner(CP, init_v=0.0, init_a=0.0, dt=0.05)

Bases: object

static parse_model(model_msg, model_error)

publish(sm, pm)

update(sm)

selfdrive.controls.lib.longitudinal_planner.get_max_accel(v_ego)

selfdrive.controls.lib.longitudinal_planner.limit_accel_in_turns(v_ego, angle_steers, a_target, CP)

This function returns a limited long acceleration allowed, depending on the existing lateral acceleration this should avoid accelerating when losing the target in turns

selfdrive.controls.lib.pid module

class selfdrive.controls.lib.pid.PIDController(k_p, k_i, k_f=0.0, k_d=0.0, pos_limit=1e+308, neg_limit=-1e+308, rate=100)

Bases: object

property error_integral

property k_d

property k_i

property k_p

reset()

update(error, error_rate=0.0, speed=0.0, override=False, feedforward=0.0, freeze_integrator=False)

selfdrive.controls.lib.vehicle_model module

Dynamic bicycle model from “The Science of Vehicle Dynamics (2014), M. Guiggiani”

The state is x = [v, r]^T with v lateral speed [m/s], and r rotational speed [rad/s]

The input u is the steering angle [rad], and roll [rad]

The system is defined by x_dot = A*x + B*u

A depends on longitudinal speed, u [m/s], and vehicle parameters CP

class selfdrive.controls.lib.vehicle_model.VehicleModel(CP: <capnp.lib.capnp._StructModule object at 0x7f3309037850>)

Bases: object

calc_curvature(sa: float, u: float, roll: float) → float

Returns the curvature. Multiplied by the speed this will give the yaw rate.

Args:

sa: Steering wheel angle [rad] u: Speed [m/s] roll: Road Roll [rad]

Returns:

Curvature factor [1/m]

curvature_factor(u: float) → float

Returns the curvature factor. Multiplied by wheel angle (not steering wheel angle) this will give the curvature.

Args:

u: Speed [m/s]

Returns:

Curvature factor [1/m]

get_steer_from_curvature(curv: float, u: float, roll: float) → float

Calculates the required steering wheel angle for a given curvature

Args:

curv: Desired curvature [1/m] u: Speed [m/s] roll: Road Roll [rad]

Returns:

Steering wheel angle [rad]

get_steer_from_yaw_rate(yaw_rate: float, u: float, roll: float) → float

Calculates the required steering wheel angle for a given yaw_rate

Args:

yaw_rate: Desired yaw rate [rad/s] u: Speed [m/s] roll: Road Roll [rad]

Returns:

Steering wheel angle [rad]

roll_compensation(roll: float, u: float) → float

Calculates the roll-compensation to curvature

Args:

roll: Road Roll [rad] u: Speed [m/s]

Returns:

Roll compensation curvature [rad]

steady_state_sol(sa: float, u: float, roll: float) → ndarray

Returns the steady state solution.

If the speed is too low we can’t use the dynamic model (tire slip is undefined), we then have to use the kinematic model

Args:

sa: Steering wheel angle [rad] u: Speed [m/s] roll: Road Roll [rad]

Returns:

2x1 matrix with steady state solution (lateral speed, rotational speed)

update_params(stiffness_factor: float, steer_ratio: float) → None

Update the vehicle model with a new stiffness factor and steer ratio

yaw_rate(sa: float, u: float, roll: float) → float

Calculate yaw rate

Args:

sa: Steering wheel angle [rad] u: Speed [m/s] roll: Road Roll [rad]

Returns:

Yaw rate [rad/s]

selfdrive.controls.lib.vehicle_model.calc_slip_factor(VM: VehicleModel) → float

The slip factor is a measure of how the curvature changes with speed it’s positive for Oversteering vehicle, negative (usual case) otherwise.

selfdrive.controls.lib.vehicle_model.create_dyn_state_matrices(u: float, VM: VehicleModel) → tuple[ndarray, ndarray]

Returns the A and B matrix for the dynamics system

Args:

u: Vehicle speed [m/s] VM: Vehicle model

Returns:

A tuple with the 2x2 A matrix, and 2x2 B matrix

Parameters in the vehicle model:

cF: Tire stiffness Front [N/rad] cR: Tire stiffness Front [N/rad] aF: Distance from CG to front wheels [m] aR: Distance from CG to rear wheels [m] m: Mass [kg] j: Rotational inertia [kg m^2] sR: Steering ratio [-] chi: Steer ratio rear [-]

selfdrive.controls.lib.vehicle_model.dyn_ss_sol(sa: float, u: float, roll: float, VM: VehicleModel) → ndarray

Calculate the steady state solution when x_dot = 0, Ax + Bu = 0 => x = -A^{-1} B u

Args:

sa: Steering angle [rad] u: Speed [m/s] roll: Road Roll [rad] VM: Vehicle model

Returns:

2x1 matrix with steady state solution

selfdrive.controls.lib.vehicle_model.kin_ss_sol(sa: float, u: float, VM: VehicleModel) → ndarray

Calculate the steady state solution at low speeds At low speeds the tire slip is undefined, so a kinematic model is used.

Args:

sa: Steering angle [rad] u: Speed [m/s] VM: Vehicle model

Returns:

2x1 matrix with steady state solution

Module contents