Conditional Experimental Mode
Added toggles for "Conditional Experimental Mode". Conditions based on road curvature, turn signals, speed, lead speed, navigation instructions, and stop signs/stop lights are all individually toggleable. Co-Authored-By: eFini <16603033+efinilan@users.noreply.github.com> Co-Authored-By: Kumar <36933347+rav4kumar@users.noreply.github.com>
This commit is contained in:
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selfdrive/frogpilot/assets/toggle_icons/icon_conditional.png
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selfdrive/frogpilot/assets/toggle_icons/icon_conditional.png
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selfdrive/frogpilot/functions/conditional_experimental_mode.py
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selfdrive/frogpilot/functions/conditional_experimental_mode.py
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@@ -0,0 +1,191 @@
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from openpilot.common.conversions import Conversions as CV
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from openpilot.common.numpy_fast import interp
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from openpilot.selfdrive.frogpilot.functions.frogpilot_functions import CITY_SPEED_LIMIT, CRUISING_SPEED, MovingAverageCalculator, PROBABILITY
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# Lookup table for stop sign / stop light detection
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SLOW_DOWN_BP = [0., 10., 20., 30., 40., 50., 55., 60.]
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SLOW_DOWN_DISTANCE = [20, 30., 50., 70., 80., 90., 105., 120.]
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TRAJECTORY_SIZE = 33
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class ConditionalExperimentalMode:
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def __init__(self, params_memory):
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self.params_memory = params_memory
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self.curve_detected = False
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self.experimental_mode = False
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self.lead_detected = False
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self.lead_stopping = False
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self.red_light_detected = False
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self.slower_lead_detected = False
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self.previous_status_value = 0
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self.previous_v_ego = 0
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self.previous_v_lead = 0
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self.status_value = 0
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self.curvature_mac = MovingAverageCalculator()
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self.lead_detection_mac = MovingAverageCalculator()
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self.lead_slowing_down_mac = MovingAverageCalculator()
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self.slow_lead_mac = MovingAverageCalculator()
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self.slowing_down_mac = MovingAverageCalculator()
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self.stop_light_mac = MovingAverageCalculator()
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def update(self, carState, enabled, frogpilotNavigation, modelData, radarState, road_curvature, stop_distance, t_follow, v_ego):
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lead = radarState.leadOne
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v_lead = lead.vLead
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# Update Experimental Mode based on the current driving conditions
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condition_met = self.check_conditions(carState, frogpilotNavigation, lead, modelData, stop_distance, v_ego)
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if (not self.experimental_mode and condition_met) and enabled:
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self.experimental_mode = True
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elif (self.experimental_mode and not condition_met) or not enabled:
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self.experimental_mode = False
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self.status_value = 0
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# Update the onroad status bar
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if self.status_value != self.previous_status_value:
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self.params_memory.put_int("CEStatus", self.status_value)
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self.previous_status_value = self.status_value
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self.update_conditions(lead, modelData, radarState, road_curvature, stop_distance, t_follow, v_ego, v_lead)
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# Check conditions for the appropriate state of Experimental Mode
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def check_conditions(self, carState, frogpilotNavigation, lead, modelData, stop_distance, v_ego):
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if carState.standstill:
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self.status_value = 0
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return self.experimental_mode
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# Keep Experimental Mode active if stopping for a red light
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if self.status_value == 15 and self.slowing_down(v_ego):
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return True
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# Navigation check
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if self.navigation and modelData.navEnabled and (frogpilotNavigation.approachingIntersection or frogpilotNavigation.approachingTurn) and (self.navigation_lead or not self.lead_detected):
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self.status_value = 7 if frogpilotNavigation.approachingIntersection else 8
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return True
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# Speed check
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if (not self.lead_detected and v_ego <= self.limit) or (self.lead_detected and v_ego <= self.limit_lead):
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self.status_value = 10 if self.lead_detected else 11
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return True
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# Slower lead check
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if self.slower_lead and self.slower_lead_detected:
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self.status_value = 12
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return True
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# Turn signal check
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if self.signal and v_ego <= CITY_SPEED_LIMIT and (carState.leftBlinker or carState.rightBlinker):
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self.status_value = 13
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return True
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# Road curvature check
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if self.curves and self.curve_detected:
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self.status_value = 14
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return True
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# Stop sign and light check
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if self.stop_lights and self.red_light_detected:
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self.status_value = 15
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return True
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return False
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def update_conditions(self, lead, modelData, radarState, road_curvature, stop_distance, t_follow, v_ego, v_lead):
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self.lead_detection(lead)
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self.lead_slowing_down(lead, t_follow, v_lead)
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self.road_curvature(road_curvature)
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self.slow_lead(lead, stop_distance, t_follow, v_ego, v_lead)
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self.stop_sign_and_light(modelData, v_ego)
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# Lead detection
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def lead_detection(self, lead):
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lead_status = lead.status
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self.lead_detection_mac.add_data(lead_status)
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self.lead_detected = self.lead_detection_mac.get_moving_average() >= PROBABILITY
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def lead_slowing_down(self, lead, t_follow, v_lead):
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if self.lead_detected:
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lead_close = lead.dRel <= v_lead * t_follow
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lead_slowing_down = v_lead < self.previous_v_lead
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lead_stopped = v_lead < 1
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self.previous_v_lead = v_lead
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self.lead_slowing_down_mac.add_data(lead_close or lead_slowing_down or lead_stopped)
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self.lead_stopping = self.lead_slowing_down_mac.get_moving_average() >= PROBABILITY
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else:
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self.lead_slowing_down_mac.reset_data()
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self.lead_stopping = False
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self.previous_v_lead = 0
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# Determine if we're slowing down for a potential stop
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def slowing_down(self, v_ego):
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slowing_down = v_ego < self.previous_v_ego
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speed_check = v_ego < CRUISING_SPEED
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self.previous_v_ego = v_ego
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self.slowing_down_mac.add_data(slowing_down and speed_check)
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return self.slowing_down_mac.get_moving_average() >= PROBABILITY
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# Determine the road curvature - Credit goes to to Pfeiferj!
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def road_curvature(self, road_curvature):
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lead_check = self.curves_lead or not self.lead_detected
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if lead_check and not self.red_light_detected:
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# Setting a limit of 5.0 helps prevent it triggering for red lights
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curve_detected = 5.0 >= road_curvature > 1.6
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curve_active = road_curvature > 1.1 and self.curve_detected
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self.curvature_mac.add_data(curve_detected or curve_active)
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self.curve_detected = self.curvature_mac.get_moving_average() >= PROBABILITY
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else:
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self.curvature_mac.reset_data()
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self.curve_detected = False
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# Slower lead detection - Credit goes to the DragonPilot team!
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def slow_lead(self, lead, stop_distance, t_follow, v_ego, v_lead):
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if self.lead_detected:
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slower_lead_ahead = lead.dRel < (v_ego - 1) * t_follow
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self.slow_lead_mac.add_data(slower_lead_ahead)
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self.slower_lead_detected = self.slow_lead_mac.get_moving_average() >= PROBABILITY
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else:
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self.slow_lead_mac.reset_data()
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self.slower_lead_detected = False
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# Stop sign/stop light detection - Credit goes to the DragonPilot team!
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def stop_sign_and_light(self, modelData, v_ego):
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lead_check = self.stop_lights_lead or not self.lead_stopping
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# Check if the model data is consistent and wants to stop
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model_check = len(modelData.orientation.x) == len(modelData.position.x) == TRAJECTORY_SIZE
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model_stopping = modelData.position.x[TRAJECTORY_SIZE - 1] < interp(v_ego * CV.MS_TO_KPH, SLOW_DOWN_BP, SLOW_DOWN_DISTANCE)
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# Filter out any other reasons the model may want to slow down
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model_filtered = not (self.curve_detected or self.slower_lead_detected)
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self.stop_light_mac.add_data(lead_check and model_check and model_stopping and model_filtered)
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self.red_light_detected = self.stop_light_mac.get_moving_average() >= PROBABILITY
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def update_frogpilot_params(self, is_metric, params):
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self.curves = params.get_bool("CECurves")
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self.curves_lead = self.curves and params.get_bool("CECurvesLead")
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self.limit = params.get_int("CESpeed") * (CV.KPH_TO_MS if is_metric else CV.MPH_TO_MS)
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self.limit_lead = params.get_int("CESpeedLead") * (CV.KPH_TO_MS if is_metric else CV.MPH_TO_MS)
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self.navigation = params.get_bool("CENavigation")
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self.navigation_lead = self.navigation and params.get_bool("CENavigationLead")
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self.signal = params.get_bool("CESignal")
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self.slower_lead = params.get_bool("CESlowerLead")
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self.stop_lights = params.get_bool("CEStopLights")
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self.stop_lights_lead = self.stop_lights and params.get_bool("CEStopLightsLead")
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@@ -24,6 +24,28 @@ A_CRUISE_MAX_VALS_ECO = [3.5, 3.2, 2.3, 2.0, 1.15, .80, .58, .36, .30, .091]
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A_CRUISE_MIN_VALS_SPORT = [-0.50, -0.52, -0.55, -0.57, -0.60]
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A_CRUISE_MAX_VALS_SPORT = [3.5, 3.5, 3.3, 2.8, 1.5, 1.0, .75, .6, .38, .2]
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class MovingAverageCalculator:
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def __init__(self):
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self.data = []
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self.total = 0
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def add_data(self, value):
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if len(self.data) == THRESHOLD:
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self.total -= self.data.pop(0)
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self.data.append(value)
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self.total += value
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def get_moving_average(self):
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if len(self.data) == 0:
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return None
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return self.total / len(self.data)
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def reset_data(self):
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self.data = []
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self.total = 0
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class FrogPilotFunctions:
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def __init__(self) -> None:
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self.params = Params()
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@@ -57,3 +79,9 @@ class FrogPilotFunctions:
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distance_to_road_edge = np.mean(np.abs(current_y - road_edge_y_interp))
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return min(distance_to_lane, distance_to_road_edge)
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@staticmethod
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def road_curvature(modelData, v_ego):
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predicted_velocities = np.array(modelData.velocity.x)
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curvature_ratios = np.abs(np.array(modelData.acceleration.y)) / (predicted_velocities**2)
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return np.amax(curvature_ratios * (v_ego**2))
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@@ -3,10 +3,13 @@ import cereal.messaging as messaging
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from openpilot.common.conversions import Conversions as CV
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from openpilot.selfdrive.car.interfaces import ACCEL_MIN, ACCEL_MAX
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from openpilot.selfdrive.controls.lib.desire_helper import LANE_CHANGE_SPEED_MIN
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from openpilot.selfdrive.controls.lib.longitudinal_mpc_lib.long_mpc import STOP_DISTANCE
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from openpilot.selfdrive.controls.lib.longitudinal_planner import A_CRUISE_MIN, get_max_accel
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from openpilot.selfdrive.frogpilot.functions.frogpilot_functions import CRUISING_SPEED, FrogPilotFunctions
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from openpilot.selfdrive.frogpilot.functions.conditional_experimental_mode import ConditionalExperimentalMode
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class FrogPilotPlanner:
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def __init__(self, CP, params, params_memory):
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self.CP = CP
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@@ -14,6 +17,10 @@ class FrogPilotPlanner:
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self.fpf = FrogPilotFunctions()
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self.cem = ConditionalExperimentalMode(self.params_memory)
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self.road_curvature = 0
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self.stop_distance = 0
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self.v_cruise = 0
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self.accel_limits = [A_CRUISE_MIN, get_max_accel(0)]
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@@ -45,6 +52,10 @@ class FrogPilotPlanner:
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self.accel_limits = [min_accel, max_accel]
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# Update Conditional Experimental Mode
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if self.conditional_experimental_mode and self.CP.openpilotLongitudinalControl:
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self.cem.update(carState, enabled, sm['frogpilotNavigation'], modelData, sm['radarState'], self.road_curvature, self.stop_distance, mpc.t_follow, v_ego)
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# Update the current lane widths
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check_lane_width = self.blind_spot_path
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if check_lane_width and v_ego >= LANE_CHANGE_SPEED_MIN:
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@@ -54,6 +65,12 @@ class FrogPilotPlanner:
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self.lane_width_left = 0
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self.lane_width_right = 0
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# Update the current road curvature
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self.road_curvature = self.fpf.road_curvature(modelData, v_ego)
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# Update the desired stopping distance
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self.stop_distance = STOP_DISTANCE
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# Update the max allowed speed
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self.v_cruise = self.update_v_cruise(carState, controlsState, enabled, modelData, v_cruise, v_ego)
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@@ -75,6 +92,8 @@ class FrogPilotPlanner:
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frogpilot_plan_send.valid = sm.all_checks(service_list=['carState', 'controlsState'])
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frogpilotPlan = frogpilot_plan_send.frogpilotPlan
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frogpilotPlan.conditionalExperimental = self.cem.experimental_mode
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frogpilotPlan.laneWidthLeft = self.lane_width_left
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frogpilotPlan.laneWidthRight = self.lane_width_right
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@@ -83,6 +102,11 @@ class FrogPilotPlanner:
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def update_frogpilot_params(self, params):
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self.is_metric = params.get_bool("IsMetric")
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self.conditional_experimental_mode = params.get_bool("ConditionalExperimental")
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if self.conditional_experimental_mode:
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self.cem.update_frogpilot_params(self.is_metric, params)
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params.put_bool("ExperimentalMode", True)
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custom_ui = params.get_bool("CustomUI")
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self.blind_spot_path = custom_ui and params.get_bool("BlindSpotPath")
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@@ -4,6 +4,13 @@ FrogPilotControlsPanel::FrogPilotControlsPanel(SettingsWindow *parent) : FrogPil
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const std::vector<std::tuple<QString, QString, QString, QString>> controlToggles {
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{"AlwaysOnLateral", "Always on Lateral", "Maintain openpilot lateral control when the brake or gas pedals are used.\n\nDeactivation occurs only through the 'Cruise Control' button.", "../frogpilot/assets/toggle_icons/icon_always_on_lateral.png"},
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{"ConditionalExperimental", "Conditional Experimental Mode", "Automatically switches to 'Experimental Mode' under predefined conditions.", "../frogpilot/assets/toggle_icons/icon_conditional.png"},
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{"CECurves", "Curve Detected Ahead", "Switch to 'Experimental Mode' when a curve is detected.", ""},
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{"CENavigation", "Navigation Based", "Switch to 'Experimental Mode' based on navigation data. (i.e. Intersections, stop signs, etc.)", ""},
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{"CESlowerLead", "Slower Lead Detected Ahead", "Switch to 'Experimental Mode' when a slower lead vehicle is detected ahead.", ""},
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{"CEStopLights", "Stop Lights and Stop Signs", "Switch to 'Experimental Mode' when a stop light or stop sign is detected.", ""},
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{"CESignal", "Turn Signal When Below Highway Speeds", "Switch to 'Experimental Mode' when using turn signals below highway speeds to help assit with turns.", ""},
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{"LateralTune", "Lateral Tuning", "Modify openpilot's steering behavior.", "../frogpilot/assets/toggle_icons/icon_lateral_tune.png"},
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{"LongitudinalTune", "Longitudinal Tuning", "Modify openpilot's acceleration and braking behavior.", "../frogpilot/assets/toggle_icons/icon_longitudinal_tune.png"},
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@@ -34,6 +41,44 @@ FrogPilotControlsPanel::FrogPilotControlsPanel(SettingsWindow *parent) : FrogPil
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}
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});
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} else if (param == "ConditionalExperimental") {
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FrogPilotParamManageControl *conditionalExperimentalToggle = new FrogPilotParamManageControl(param, title, desc, icon, this);
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QObject::connect(conditionalExperimentalToggle, &FrogPilotParamManageControl::manageButtonClicked, this, [this]() {
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parentToggleClicked();
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conditionalSpeedsImperial->setVisible(!isMetric);
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conditionalSpeedsMetric->setVisible(isMetric);
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for (auto &[key, toggle] : toggles) {
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toggle->setVisible(conditionalExperimentalKeys.find(key.c_str()) != conditionalExperimentalKeys.end());
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}
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});
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toggle = conditionalExperimentalToggle;
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} else if (param == "CECurves") {
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FrogPilotParamValueControl *CESpeedImperial = new FrogPilotParamValueControl("CESpeed", "Below", "Switch to 'Experimental Mode' below this speed in absence of a lead vehicle.", "", 0, 99,
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std::map<int, QString>(), this, false, " mph");
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FrogPilotParamValueControl *CESpeedLeadImperial = new FrogPilotParamValueControl("CESpeedLead", " w/Lead", "Switch to 'Experimental Mode' below this speed when following a lead vehicle.", "", 0, 99,
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std::map<int, QString>(), this, false, " mph");
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conditionalSpeedsImperial = new FrogPilotDualParamControl(CESpeedImperial, CESpeedLeadImperial, this);
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addItem(conditionalSpeedsImperial);
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FrogPilotParamValueControl *CESpeedMetric = new FrogPilotParamValueControl("CESpeed", "Below", "Switch to 'Experimental Mode' below this speed in absence of a lead vehicle.", "", 0, 150,
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std::map<int, QString>(), this, false, " kph");
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FrogPilotParamValueControl *CESpeedLeadMetric = new FrogPilotParamValueControl("CESpeedLead", " w/Lead", "Switch to 'Experimental Mode' below this speed when following a lead vehicle.", "", 0, 150,
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std::map<int, QString>(), this, false, " kph");
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conditionalSpeedsMetric = new FrogPilotDualParamControl(CESpeedMetric, CESpeedLeadMetric, this);
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addItem(conditionalSpeedsMetric);
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std::vector<QString> curveToggles{"CECurvesLead"};
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std::vector<QString> curveToggleNames{tr("With Lead")};
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toggle = new FrogPilotParamToggleControl(param, title, desc, icon, curveToggles, curveToggleNames);
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} else if (param == "CENavigation") {
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std::vector<QString> navigationToggles{"CENavigationIntersections", "CENavigationTurns", "CENavigationLead"};
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std::vector<QString> navigationToggleNames{tr("Intersections"), tr("Turns"), tr("With Lead")};
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toggle = new FrogPilotParamToggleControl(param, title, desc, icon, navigationToggles, navigationToggleNames);
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} else if (param == "CEStopLights") {
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std::vector<QString> stopLightToggles{"CEStopLightsLead"};
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std::vector<QString> stopLightToggleNames{tr("With Lead")};
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toggle = new FrogPilotParamToggleControl(param, title, desc, icon, stopLightToggles, stopLightToggleNames);
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} else if (param == "LateralTune") {
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FrogPilotParamManageControl *lateralTuneToggle = new FrogPilotParamManageControl(param, title, desc, icon, this);
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QObject::connect(lateralTuneToggle, &FrogPilotParamManageControl::manageButtonClicked, this, [this]() {
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||||
@@ -151,6 +196,8 @@ void FrogPilotControlsPanel::updateMetric() {
|
||||
if (isMetric != previousIsMetric) {
|
||||
double distanceConversion = isMetric ? FOOT_TO_METER : METER_TO_FOOT;
|
||||
double speedConversion = isMetric ? MILE_TO_KM : KM_TO_MILE;
|
||||
params.putIntNonBlocking("CESpeed", std::nearbyint(params.getInt("CESpeed") * speedConversion));
|
||||
params.putIntNonBlocking("CESpeedLead", std::nearbyint(params.getInt("CESpeedLead") * speedConversion));
|
||||
}
|
||||
|
||||
if (isMetric) {
|
||||
@@ -161,6 +208,9 @@ void FrogPilotControlsPanel::updateMetric() {
|
||||
}
|
||||
|
||||
void FrogPilotControlsPanel::parentToggleClicked() {
|
||||
conditionalSpeedsImperial->setVisible(false);
|
||||
conditionalSpeedsMetric->setVisible(false);
|
||||
|
||||
openParentToggle();
|
||||
}
|
||||
|
||||
@@ -169,6 +219,9 @@ void FrogPilotControlsPanel::subParentToggleClicked() {
|
||||
}
|
||||
|
||||
void FrogPilotControlsPanel::hideSubToggles() {
|
||||
conditionalSpeedsImperial->setVisible(false);
|
||||
conditionalSpeedsMetric->setVisible(false);
|
||||
|
||||
for (auto &[key, toggle] : toggles) {
|
||||
bool subToggles = conditionalExperimentalKeys.find(key.c_str()) != conditionalExperimentalKeys.end() ||
|
||||
fireTheBabysitterKeys.find(key.c_str()) != fireTheBabysitterKeys.end() ||
|
||||
|
||||
@@ -29,7 +29,10 @@ private:
|
||||
void updateState(const UIState &s);
|
||||
void updateToggles();
|
||||
|
||||
std::set<QString> conditionalExperimentalKeys = {};
|
||||
FrogPilotDualParamControl *conditionalSpeedsImperial;
|
||||
FrogPilotDualParamControl *conditionalSpeedsMetric;
|
||||
|
||||
std::set<QString> conditionalExperimentalKeys = {"CECurves", "CECurvesLead", "CESlowerLead", "CENavigation", "CEStopLights", "CESignal"};
|
||||
std::set<QString> fireTheBabysitterKeys = {};
|
||||
std::set<QString> laneChangeKeys = {};
|
||||
std::set<QString> lateralTuneKeys = {};
|
||||
|
||||
Reference in New Issue
Block a user