SensorSimulation
Description
A SensorSimulation
object represents a sensor in a scenario
simulation. Use a SensorSimulation
object to:
Add sensors to actors in a scenario
Retrieve sensor detection and lane boundary data during simulation
Creation
Retrieve the SensorSimulation
object from a scenario simulation by using
the get
function of a
ScenarioSimulation
object with the "SensorSimulation"
option.
Object Functions
addSensors | Add sensors to vehicle actors in RoadRunner scenario |
targetPoses | Get positions and orientations of targets in sensor range relative to host vehicle |
laneBoundaries | Get lane boundaries relative to host vehicle |
Examples
Add Sensors to RoadRunner Scenario Using MATLAB
Define sensor models in MATLAB®, and add them to vehicle actors in a RoadRunner Scenario. Then, obtain ground truth measurements from RoadRunner Scenario, process them into detections for visualization.
Set Up RoadRunner Scenario — MATLAB Interface
Configure your RoadRunner installation and project folder properties. Open the RoadRunner app.
rrInstallationPath = "C:\Program Files\RoadRunner R2024a\bin\win64"; rrProjectPath = "D:\RR\TestProjects"; s = settings; s.roadrunner.application.InstallationFolder.PersonalValue = rrInstallationPath; rrApp = roadrunner(rrProjectPath);
To open the scenario this example uses, you must add the TrajectoryCutIn-longRun.rrscenario
file from the example folder to your RoadRunner project folder. Then, open the scenario.
copyfile("TrajectoryCutIn-longRun.rrscenario",fullfile(rrProjectPath,"Scenarios/")) openScenario(rrApp,"TrajectoryCutIn-longRun")
Create a ScenarioSimulation
object to connect MATLAB to the RoadRunner Scenario simulation and set the step size.
scenarioSim = createSimulation(rrApp);
stepSize = 0.1;
set(scenarioSim,"StepSize",stepSize);
Create a SensorSimulation
object to control the sensor configuration for the RoadRunner Scenario simulation.
sensorSim = get(scenarioSim,"SensorSimulation");
Configure Sensors and Add to RoadRunner Scenario
Configure sensor models for vision, radar and lidar sensors to add to the ego vehicle using visionDetectionGenerator
, drivingRadarDataGenerator
and lidarPointCloudGenerator
objects. Specify unique IDs for each sensor.
visionSensor = visionDetectionGenerator(SensorIndex=1, ... SensorLocation=[2.4 0], MaxRange=50, ... DetectorOutput="Lanes and objects", ... UpdateInterval=stepSize); radarSensor = drivingRadarDataGenerator(SensorIndex=2,... MountingLocation=[1.8 0 0.2], FieldOfView=[80 5],... AzimuthResolution=1,UpdateRate=1/stepSize); lidarSensor = lidarPointCloudGenerator(SensorIndex=3,UpdateInterval=stepSize);
Add the sensor to the ego vehicle actor in the RoadRunner scenario. Specify the Actor
ID
property for the vehicle.
egoVehicleID = 1; addSensors(sensorSim,{visionSensor,radarSensor,lidarSensor},egoVehicleID);
Set up bird's-eye-plot for visualization.
[visionDetPlotter,radarDetPlotter,pcPlotter,lbGTPlotter,lbDetPlotter,bepAxes] = helperSetupBEP(visionSensor,radarSensor);
Simulate RoadRunner Scenario and Visualize Sensor Data
Use the ScenarioSimulation
object to step through the RoadRunner scenario. Retrieve target poses in the sensor range using the targetPoses
function, and process them into detections using the sensor model. Visualize detections and ground truth lane boundaries using birdsEyePlot
.
simTime = 0.0; set(scenarioSim,"SimulationCommand","Step"); pause(0.1) legend(bepAxes,"show") while ~isequal(get(scenarioSim,"SimulationStatus"),"Stopped") % Get ground truth target poses and lane boundaries from the sensor tgtPoses = targetPoses(sensorSim,1); gTruthLbs = laneBoundaries(sensorSim,1,OutputOption="EgoAdjacentLanes",inHostCoordinate=true); if ~isempty(gTruthLbs) % Get detections from vision and radar sensors [visionDets,numVisionDets,visionDetsValid,lbDets,numLbDets,lbDetsValid] = visionSensor(tgtPoses,gTruthLbs,simTime); [radarDets,numRadarDets,radarDetsValid] = radarSensor(tgtPoses,simTime); % Get point cloud from lidar sensor [ptCloud,ptCloudValid] = lidarSensor(); % Plot ground-truth and detected lane boundaries helperPlotLaneBoundaries(lbGTPlotter,gTruthLbs) % Plot vision and radar detections if visionDetsValid detPos = cellfun(@(d)d.Measurement(1:2),visionDets,UniformOutput=false); detPos = vertcat(zeros(0,2),cell2mat(detPos')'); plotDetection(visionDetPlotter,detPos) end if lbDetsValid plotLaneBoundary(lbDetPlotter,vertcat(lbDets.LaneBoundaries)) end if radarDetsValid detPos = cellfun(@(d)d.Measurement(1:2),radarDets,UniformOutput=false); detPos = vertcat(zeros(0,2),cell2mat(detPos')'); plotDetection(radarDetPlotter,detPos) end % Plot lidar point cloud if ptCloudValid plotPointCloud(pcPlotter,ptCloud); end end if ~isequal(get(scenarioSim,"SimulationStatus"),"Stopped") set(scenarioSim,"SimulationCommand","Step"); end simTime = simTime + stepSize; pause(0.1) end
Helper Functions
helperSetupBEP
function creates a bird's-eye-plot and configures all the plotters for visualization.
helperPlotLaneBoundaries
function plots the lane boundaries on the birds'eye-plot.
Version History
Introduced in R2023a
See Also
ScenarioSimulation
| addSensors
| targetPoses
| laneBoundaries
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