Files
StarPilot/selfdrive/frogpilot/controls/frogpilot_planner.py
T

370 lines
18 KiB
Python

import cereal.messaging as messaging
from cereal import car
from openpilot.common.conversions import Conversions as CV
from openpilot.common.numpy_fast import clip, interp
from openpilot.common.params import Params
from openpilot.common.realtime import DT_MDL
from openpilot.selfdrive.car.interfaces import ACCEL_MIN, ACCEL_MAX
from openpilot.selfdrive.controls.lib.drive_helpers import V_CRUISE_UNSET
from openpilot.selfdrive.controls.lib.longitudinal_mpc_lib.long_mpc import A_CHANGE_COST, COMFORT_BRAKE, DANGER_ZONE_COST, J_EGO_COST, STOP_DISTANCE, \
get_jerk_factor, get_safe_obstacle_distance, get_stopped_equivalence_factor, get_T_FOLLOW
from openpilot.selfdrive.controls.lib.longitudinal_planner import A_CRUISE_MIN, Lead, get_max_accel
from openpilot.selfdrive.frogpilot.controls.lib.conditional_experimental_mode import MODEL_LENGTH, PLANNER_TIME, ConditionalExperimentalMode
from openpilot.selfdrive.frogpilot.controls.lib.frogpilot_functions import MovingAverageCalculator, calculate_lane_width, calculate_road_curvature
from openpilot.selfdrive.frogpilot.controls.lib.frogpilot_variables import CITY_SPEED_LIMIT, CRUISING_SPEED, PROBABILITY
from openpilot.selfdrive.frogpilot.controls.lib.map_turn_speed_controller import MapTurnSpeedController
from openpilot.selfdrive.frogpilot.controls.lib.speed_limit_controller import SpeedLimitController
GearShifter = car.CarState.GearShifter
A_CRUISE_MIN_ECO = A_CRUISE_MIN / 5
A_CRUISE_MIN_SPORT = A_CRUISE_MIN / 2
# MPH = [ 0., 11, 22, 34, 45, 56, 89]
A_CRUISE_MAX_BP_CUSTOM = [ 0., 5., 10., 15., 20., 25., 40.]
A_CRUISE_MAX_VALS_ECO = [1.4, 1.2, 1.0, 0.8, 0.6, 0.4, 0.2]
A_CRUISE_MAX_VALS_SPORT = [3.0, 2.5, 2.0, 1.0, 0.9, 0.8, 0.6]
A_CRUISE_MAX_VALS_SPORT_PLUS = [4.0, 3.5, 3.0, 1.0, 0.9, 0.8, 0.6]
TARGET_LAT_A = 1.9
TRAFFIC_MODE_BP = [0., CITY_SPEED_LIMIT]
def get_max_accel_eco(v_ego):
return interp(v_ego, A_CRUISE_MAX_BP_CUSTOM, A_CRUISE_MAX_VALS_ECO)
def get_max_accel_sport(v_ego):
return interp(v_ego, A_CRUISE_MAX_BP_CUSTOM, A_CRUISE_MAX_VALS_SPORT)
def get_max_accel_sport_plus(v_ego):
return interp(v_ego, A_CRUISE_MAX_BP_CUSTOM, A_CRUISE_MAX_VALS_SPORT_PLUS)
class FrogPilotPlanner:
def __init__(self):
self.params_memory = Params("/dev/shm/params")
self.cem = ConditionalExperimentalMode(self)
self.lead_one = Lead()
self.mtsc = MapTurnSpeedController()
self.forcing_stop = False
self.lead_departing = False
self.model_stopped = False
self.override_force_stop = False
self.override_slc = False
self.slower_lead = False
self.taking_curve_quickly = False
self.tracking_lead = False
self.acceleration_jerk = 0
self.danger_jerk = 0
self.model_length = 0
self.mtsc_target = 0
self.overridden_speed = 0
self.road_curvature = 0
self.slc_target = 0
self.speed_jerk = 0
self.tracked_model_length = 0
self.tracking_lead_distance = 0
self.v_cruise = 0
self.vtsc_target = 0
self.tracking_lead_mac = MovingAverageCalculator()
def update(self, carState, controlsState, frogpilotCarControl, frogpilotCarState, frogpilotNavigation, modelData, radarState, frogpilot_toggles):
if frogpilot_toggles.radarless_model:
model_leads = list(modelData.leadsV3)
if len(model_leads) > 0:
model_lead = model_leads[0]
self.lead_one.update(model_lead.x[0], model_lead.y[0], model_lead.v[0], model_lead.a[0], model_lead.prob)
else:
self.lead_one.reset()
else:
self.lead_one = radarState.leadOne
v_cruise = min(controlsState.vCruise, V_CRUISE_UNSET) * CV.KPH_TO_MS
v_ego = max(carState.vEgo, 0)
v_lead = self.lead_one.vLead
driving_gear = carState.gearShifter not in (GearShifter.neutral, GearShifter.park, GearShifter.reverse, GearShifter.unknown)
distance_offset = max(frogpilot_toggles.increased_stopping_distance + min(CITY_SPEED_LIMIT - v_ego, 0), 0) if not frogpilotCarState.trafficModeActive else 0
lead_distance = self.lead_one.dRel - distance_offset
stopping_distance = STOP_DISTANCE + distance_offset
run_cem = frogpilot_toggles.conditional_experimental_mode or frogpilot_toggles.force_stops or frogpilot_toggles.show_stopping_point
if run_cem and (controlsState.enabled or frogpilotCarControl.alwaysOnLateral) and driving_gear:
self.cem.update(carState, frogpilotNavigation, modelData, v_ego, v_lead, frogpilot_toggles)
check_lane_width = frogpilot_toggles.adjacent_lanes or frogpilot_toggles.blind_spot_path or frogpilot_toggles.lane_detection
if check_lane_width and v_ego >= frogpilot_toggles.minimum_lane_change_speed:
self.lane_width_left = calculate_lane_width(modelData.laneLines[0], modelData.laneLines[1], modelData.roadEdges[0])
self.lane_width_right = calculate_lane_width(modelData.laneLines[3], modelData.laneLines[2], modelData.roadEdges[1])
else:
self.lane_width_left = 0
self.lane_width_right = 0
if frogpilot_toggles.lead_departing_alert and self.tracking_lead and driving_gear and carState.standstill:
if self.tracking_lead_distance == 0:
self.tracking_lead_distance = lead_distance
self.lead_departing = lead_distance - self.tracking_lead_distance > 1
self.lead_departing &= v_lead > 1
else:
self.lead_departing = False
self.tracking_lead_distance = 0
self.model_length = modelData.position.x[MODEL_LENGTH - 1]
self.model_stopped = self.model_length < CRUISING_SPEED * PLANNER_TIME
self.model_stopped |= self.forcing_stop
self.override_force_stop |= carState.gasPressed
self.override_force_stop |= frogpilot_toggles.force_stops and carState.standstill and self.tracking_lead
self.override_force_stop |= frogpilotCarControl.resumePressed
self.road_curvature = calculate_road_curvature(modelData, v_ego) if not carState.standstill and driving_gear else 1
if frogpilot_toggles.random_events and v_ego > CRUISING_SPEED and driving_gear:
self.taking_curve_quickly = v_ego > (1 / self.road_curvature)**0.5 * 2 > CRUISING_SPEED * 2 and abs(carState.steeringAngleDeg) > 30
self.set_acceleration(controlsState, frogpilotCarState, v_cruise, v_ego, frogpilot_toggles)
self.set_follow_values(controlsState, frogpilotCarState, lead_distance, stopping_distance, v_ego, v_lead, frogpilot_toggles)
self.set_lead_status(lead_distance, stopping_distance, v_ego)
self.update_v_cruise(carState, controlsState, frogpilotCarState, frogpilotNavigation, modelData, v_cruise, v_ego, frogpilot_toggles)
def set_acceleration(self, controlsState, frogpilotCarState, v_cruise, v_ego, frogpilot_toggles):
eco_gear = frogpilotCarState.ecoGear
sport_gear = frogpilotCarState.sportGear
if self.tracking_lead and frogpilot_toggles.aggressive_acceleration:
self.max_accel = clip(self.lead_one.aLeadK, get_max_accel_sport_plus(v_ego), 2.0 if v_ego >= 20 else 4.0)
elif frogpilot_toggles.map_acceleration and (eco_gear or sport_gear):
if eco_gear:
self.max_accel = get_max_accel_eco(v_ego)
else:
if frogpilot_toggles.acceleration_profile == 3:
self.max_accel = get_max_accel_sport_plus(v_ego)
else:
self.max_accel = get_max_accel_sport(v_ego)
else:
if frogpilot_toggles.acceleration_profile == 1:
self.max_accel = get_max_accel_eco(v_ego)
elif frogpilot_toggles.acceleration_profile == 2:
self.max_accel = get_max_accel_sport(v_ego)
elif frogpilot_toggles.acceleration_profile == 3:
self.max_accel = get_max_accel_sport_plus(v_ego)
elif controlsState.experimentalMode:
self.max_accel = ACCEL_MAX
else:
self.max_accel = get_max_accel(v_ego)
if not self.tracking_lead:
self.max_accel = min(self.max_accel, self.max_accel * (self.v_cruise / CITY_SPEED_LIMIT))
if controlsState.experimentalMode:
self.min_accel = ACCEL_MIN
elif min(self.mtsc_target, self.vtsc_target) < v_cruise:
self.min_accel = A_CRUISE_MIN
elif frogpilot_toggles.map_deceleration and (eco_gear or sport_gear):
if eco_gear:
self.min_accel = A_CRUISE_MIN_ECO
else:
self.min_accel = A_CRUISE_MIN_SPORT
else:
if frogpilot_toggles.deceleration_profile == 1:
self.min_accel = A_CRUISE_MIN_ECO
elif frogpilot_toggles.deceleration_profile == 2:
self.min_accel = A_CRUISE_MIN_SPORT
else:
self.min_accel = A_CRUISE_MIN
def set_follow_values(self, controlsState, frogpilotCarState, lead_distance, stopping_distance, v_ego, v_lead, frogpilot_toggles):
if frogpilotCarState.trafficModeActive:
self.base_acceleration_jerk = interp(v_ego, TRAFFIC_MODE_BP, frogpilot_toggles.traffic_mode_jerk_acceleration)
self.base_danger_jerk = interp(v_ego, TRAFFIC_MODE_BP, frogpilot_toggles.traffic_mode_jerk_danger)
self.base_speed_jerk = interp(v_ego, TRAFFIC_MODE_BP, frogpilot_toggles.traffic_mode_jerk_speed)
self.t_follow = interp(v_ego, TRAFFIC_MODE_BP, frogpilot_toggles.traffic_mode_t_follow)
else:
self.base_acceleration_jerk, self.base_danger_jerk, self.base_speed_jerk = get_jerk_factor(
frogpilot_toggles.aggressive_jerk_acceleration, frogpilot_toggles.aggressive_jerk_danger, frogpilot_toggles.aggressive_jerk_speed,
frogpilot_toggles.standard_jerk_acceleration, frogpilot_toggles.standard_jerk_danger, frogpilot_toggles.standard_jerk_speed,
frogpilot_toggles.relaxed_jerk_acceleration, frogpilot_toggles.relaxed_jerk_danger, frogpilot_toggles.relaxed_jerk_speed,
frogpilot_toggles.custom_personalities, controlsState.personality
)
self.t_follow = get_T_FOLLOW(
frogpilot_toggles.aggressive_follow,
frogpilot_toggles.standard_follow,
frogpilot_toggles.relaxed_follow,
frogpilot_toggles.custom_personalities, controlsState.personality
)
if self.tracking_lead:
self.safe_obstacle_distance = int(get_safe_obstacle_distance(v_ego, self.t_follow))
self.safe_obstacle_distance_stock = self.safe_obstacle_distance
self.stopped_equivalence_factor = int(get_stopped_equivalence_factor(v_lead))
self.update_follow_values(lead_distance, stopping_distance, v_ego, v_lead, frogpilot_toggles)
else:
self.safe_obstacle_distance = 0
self.safe_obstacle_distance_stock = 0
self.stopped_equivalence_factor = 0
self.acceleration_jerk = self.base_acceleration_jerk
self.danger_jerk = self.base_danger_jerk
self.speed_jerk = self.base_speed_jerk
def set_lead_status(self, lead_distance, stopping_distance, v_ego):
following_lead = self.lead_one.status and 1 < lead_distance < self.model_length + stopping_distance
following_lead &= v_ego > CRUISING_SPEED or self.tracking_lead
self.tracking_lead_mac.add_data(following_lead)
self.tracking_lead = self.tracking_lead_mac.get_moving_average() >= PROBABILITY
def update_follow_values(self, lead_distance, stopping_distance, v_ego, v_lead, frogpilot_toggles):
# Offset by FrogAi for FrogPilot for a more natural approach to a faster lead
if frogpilot_toggles.aggressive_acceleration and v_lead > v_ego:
distance_factor = max(lead_distance - (v_ego * self.t_follow), 1)
standstill_offset = max(stopping_distance - v_ego, 0) * max(v_lead - v_ego, 0)
acceleration_offset = clip((v_lead - v_ego) + standstill_offset - COMFORT_BRAKE, 1, distance_factor)
self.acceleration_jerk = self.base_acceleration_jerk / acceleration_offset
self.danger_jerk = self.base_danger_jerk / acceleration_offset
self.speed_jerk = self.base_speed_jerk / acceleration_offset
self.t_follow /= acceleration_offset
# Offset by FrogAi for FrogPilot for a more natural approach to a slower lead
if (frogpilot_toggles.conditional_slower_lead or frogpilot_toggles.smoother_braking) and v_lead < v_ego:
distance_factor = max(lead_distance - (v_lead * self.t_follow), 1)
far_lead_offset = max(lead_distance - (v_ego * self.t_follow) - stopping_distance + (v_lead - CITY_SPEED_LIMIT), 0)
braking_offset = clip((v_ego - v_lead) + far_lead_offset - COMFORT_BRAKE, 1, distance_factor)
if frogpilot_toggles.smoother_braking:
self.acceleration_jerk = self.base_acceleration_jerk * min(braking_offset, COMFORT_BRAKE / 2)
self.speed_jerk = self.base_speed_jerk * min(braking_offset, COMFORT_BRAKE * 2)
self.t_follow /= braking_offset
self.slower_lead = braking_offset - far_lead_offset > 1
def update_v_cruise(self, carState, controlsState, frogpilotCarState, frogpilotNavigation, modelData, v_cruise, v_ego, frogpilot_toggles):
v_cruise_cluster = max(controlsState.vCruiseCluster, v_cruise) * CV.KPH_TO_MS
v_cruise_diff = v_cruise_cluster - v_cruise
v_ego_cluster = max(carState.vEgoCluster, v_ego)
v_ego_diff = v_ego_cluster - v_ego
# Pfeiferj's Map Turn Speed Controller
if frogpilot_toggles.map_turn_speed_controller and v_ego > CRUISING_SPEED and controlsState.enabled:
mtsc_active = self.mtsc_target < v_cruise
self.mtsc_target = clip(self.mtsc.target_speed(v_ego, carState.aEgo), CRUISING_SPEED, v_cruise)
if frogpilot_toggles.mtsc_curvature_check and self.road_curvature < 1.0 and not mtsc_active:
self.mtsc_target = v_cruise
if self.mtsc_target == CRUISING_SPEED:
self.mtsc_target = v_cruise
else:
self.mtsc_target = v_cruise if v_cruise != V_CRUISE_UNSET else 0
# Pfeiferj's Speed Limit Controller
if frogpilot_toggles.speed_limit_controller:
SpeedLimitController.update(frogpilotCarState.dashboardSpeedLimit, controlsState.enabled, frogpilotNavigation.navigationSpeedLimit, v_cruise, v_ego, frogpilot_toggles)
unconfirmed_slc_target = SpeedLimitController.desired_speed_limit
if frogpilot_toggles.speed_limit_confirmation and self.slc_target != 0:
if self.params_memory.get_bool("SLCConfirmed"):
self.slc_target = unconfirmed_slc_target
self.params_memory.put_bool("SLCConfirmed", False)
else:
self.slc_target = unconfirmed_slc_target
self.override_slc = self.overridden_speed > self.slc_target
self.override_slc |= carState.gasPressed and v_ego > self.slc_target
self.override_slc &= controlsState.enabled
if self.override_slc:
if frogpilot_toggles.speed_limit_controller_override_manual:
if carState.gasPressed:
self.overridden_speed = v_ego + v_ego_diff
self.overridden_speed = clip(self.overridden_speed, self.slc_target, v_cruise + v_cruise_diff)
elif frogpilot_toggles.speed_limit_controller_override_set_speed:
self.overridden_speed = v_cruise + v_cruise_diff
else:
self.overridden_speed = 0
else:
self.slc_target = 0
# Pfeiferj's Vision Turn Controller
if frogpilot_toggles.vision_turn_controller and v_ego > CRUISING_SPEED and controlsState.enabled:
adjusted_road_curvature = self.road_curvature * frogpilot_toggles.curve_sensitivity
adjusted_target_lat_a = TARGET_LAT_A * frogpilot_toggles.turn_aggressiveness
self.vtsc_target = (adjusted_target_lat_a / adjusted_road_curvature)**0.5
self.vtsc_target = clip(self.vtsc_target, CRUISING_SPEED, v_cruise)
else:
self.vtsc_target = v_cruise if v_cruise != V_CRUISE_UNSET else 0
if frogpilot_toggles.force_standstill and carState.standstill and not self.override_force_stop and controlsState.enabled:
self.forcing_stop = True
self.v_cruise = -1
elif frogpilot_toggles.force_stops and self.cem.stop_light_detected and not self.override_force_stop and controlsState.enabled:
if self.tracked_model_length == 0:
self.tracked_model_length = self.model_length
self.forcing_stop = True
self.tracked_model_length -= v_ego * DT_MDL
self.v_cruise = min((self.tracked_model_length / PLANNER_TIME) - 1, v_cruise)
else:
if not self.cem.stop_light_detected:
self.override_force_stop = False
self.forcing_stop = False
self.tracked_model_length = 0
targets = [self.mtsc_target, max(self.overridden_speed, self.slc_target) - v_ego_diff, self.vtsc_target]
self.v_cruise = float(min([target if target > CRUISING_SPEED else v_cruise for target in targets]))
def publish(self, sm, pm, frogpilot_toggles):
frogpilot_plan_send = messaging.new_message('frogpilotPlan')
frogpilot_plan_send.valid = sm.all_checks(service_list=['carState', 'controlsState'])
frogpilotPlan = frogpilot_plan_send.frogpilotPlan
frogpilotPlan.accelerationJerk = float(A_CHANGE_COST * self.acceleration_jerk)
frogpilotPlan.accelerationJerkStock = float(A_CHANGE_COST * self.base_acceleration_jerk)
frogpilotPlan.dangerJerk = float(DANGER_ZONE_COST * self.danger_jerk)
frogpilotPlan.speedJerk = float(J_EGO_COST * self.speed_jerk)
frogpilotPlan.speedJerkStock = float(J_EGO_COST * self.base_speed_jerk)
frogpilotPlan.tFollow = float(self.t_follow)
frogpilotPlan.adjustedCruise = float(min(self.mtsc_target, self.vtsc_target) * (CV.MS_TO_KPH if frogpilot_toggles.is_metric else CV.MS_TO_MPH))
frogpilotPlan.vtscControllingCurve = bool(self.mtsc_target > self.vtsc_target)
frogpilotPlan.conditionalExperimentalActive = self.cem.experimental_mode
frogpilotPlan.desiredFollowDistance = self.safe_obstacle_distance - self.stopped_equivalence_factor
frogpilotPlan.safeObstacleDistance = self.safe_obstacle_distance
frogpilotPlan.safeObstacleDistanceStock = self.safe_obstacle_distance_stock
frogpilotPlan.stoppedEquivalenceFactor = self.stopped_equivalence_factor
frogpilotPlan.forcingStop = self.forcing_stop
frogpilotPlan.greenLight = not self.model_stopped
frogpilotPlan.redLight = self.cem.stop_light_detected
frogpilotPlan.laneWidthLeft = self.lane_width_left
frogpilotPlan.laneWidthRight = self.lane_width_right
frogpilotPlan.leadDeparting = self.lead_departing
frogpilotPlan.maxAcceleration = float(self.max_accel)
frogpilotPlan.minAcceleration = float(self.min_accel)
frogpilotPlan.slcOverridden = bool(self.override_slc)
frogpilotPlan.slcOverriddenSpeed = float(self.overridden_speed)
frogpilotPlan.slcSpeedLimit = self.slc_target
frogpilotPlan.slcSpeedLimitOffset = SpeedLimitController.offset
frogpilotPlan.unconfirmedSlcSpeedLimit = SpeedLimitController.desired_speed_limit
frogpilotPlan.takingCurveQuickly = self.taking_curve_quickly
frogpilotPlan.vCruise = self.v_cruise
pm.send('frogpilotPlan', frogpilot_plan_send)