프로그래밍 방식 시나리오 작성

drivingScenario 객체를 사용하여 프로그래밍 방식으로 주행 시나리오 생성

drivingScenario 객체를 사용하면 MATLAB^® 명령줄에서 주행 시나리오를 작성할 수 있습니다. 이 객체를 사용하여 복잡한 도로망이나 주차장을 설계하고 액터와 그 궤적을 지정합니다. 그런 다음 센서 모델을 사용하여 이러한 시나리오에서 합성 데이터를 생성하고 이 데이터를 조감도 플롯에 시각화할 수 있습니다.

drivingScenario 객체의 유연한 인터페이스를 통해 시나리오의 변형을 생성하여 주행 알고리즘을 다양한 조건에서 신속하게 테스트할 수 있습니다. 자세한 내용은 Create Driving Scenario Variations Programmatically 항목을 참조하십시오.

함수

모두 확장

주행 시나리오

시나리오

`drivingScenario`	Create driving scenario
`advance`	Advance driving scenario simulation by one time step
`plot`	Plot driving scenario
`plotSim3d`	Plot driving scenario in Unreal Engine viewer (R2024a 이후)
`record`	Run driving scenario and record actor states
`restart`	Restart driving scenario simulation from beginning
`updatePlots`	Update driving scenario plots
`export`	Export driving scenario to ASAM OpenDRIVE, ASAM OpenSCENARIO XML or RoadRunner HD Map file
`getRoadRunnerHDMap`	Get RoadRunner HD Map from Driving Scenario in MATLAB (R2023a 이후)
`addSensors`	Add sensors to specific host vehicle (R2023a 이후)
`startRoadRunnerForScenario`	Create and launch RoadRunner scenario from driving scenario (R2024a 이후)

액터

`actor`	Add actor to driving scenario
`vehicle`	Add vehicle to driving scenario
`trajectory`	Create actor or vehicle trajectory in driving scenario
`smoothTrajectory`	Create smooth, jerk-limited actor trajectory in driving scenario (R2021a 이후)
`getReferencePosition`	Get reference position of vehicle (R2024b 이후)
`state`	Inertial ground-truth state of actor (R2021a 이후)
`actorPoses`	Positions, velocities, and orientations of actors in driving scenario
`actorProfiles`	Physical and radar characteristics of actors in driving scenario
`barrier`	Add a barrier to a driving scenario (R2021a 이후)
`chasePlot`	Ego-centric projective perspective plot
`targetMeshes`	Mesh vertices and faces relative to specific actor
`targetOutlines`	Outlines of targets viewed by actor
`targetPoses`	Target positions and orientations relative to host vehicle
`driving.scenario.targetsToEgo`	Convert target poses from scenario to ego coordinates
`driving.scenario.targetsToScenario`	Convert target poses from ego to scenario coordinates

도로

`road`	Add road to driving scenario or road group
`roadNetwork`	Add road network to driving scenario
`roadBoundaries`	Get road boundaries
`driving.scenario.roadBoundariesToEgo`	Convert road boundaries to ego vehicle coordinates
`roadMesh`	Mesh representation of roads near actor
`driving.scenario.RoadGroup`	Store specifications for road junction or intersection (R2021a 이후)
`roadGroup`	Add road junction or intersection to driving scenario (R2021a 이후)

차선

`lanespec`	Create road lane specifications
`laneType`	Create road lane type object
`laneMarking`	Create road lane marking object
`laneMarkingVertices`	Lane marking vertices and faces in driving scenario
`currentLane`	Get current lane of actor
`laneBoundaries`	Get lane boundaries of actor lane
`clothoidLaneBoundary`	Clothoid-shaped lane boundary model
`computeBoundaryModel`	Compute lane boundary points from clothoid lane boundary model
`compositeLaneSpec`	Create multiple lane specifications for road (R2021a 이후)
`laneSpecConnector`	Define road segment connector specifications (R2021a 이후)

주차장

`parkingLot`	Add parking lot to driving scenario (R2021b 이후)
`parkingSpace`	Define parking space for parking lot (R2021b 이후)
`insertParkingSpaces`	Insert parking spaces into parking lot (R2021b 이후)
`parkingLaneMarkingVertices`	Parking lane marking vertices and faces in driving scenario (R2021b 이후)

센서

`drivingRadarDataGenerator`	Generate radar sensor detections or track reports from driving scenario or RoadRunner Scenario (R2021a 이후)
`visionDetectionGenerator`	Generate vision detections for driving scenario or RoadRunner Scenario
`lidarPointCloudGenerator`	Generate lidar point cloud data for driving scenario or RoadRunner Scenario using ray tracing
`insSensor`	Inertial navigation system and GNSS/GPS simulation model (R2021a 이후)
`ultrasonicDetectionGenerator`	Generate ultrasonic range detections in driving scenario or RoadRunner Scenario (R2022a 이후)
`idealGroundTruthSensor`	Generate ground truth measurements as sensor detections or track reports from driving scenario or RoadRunner Scenario (R2025a 이후)
`addSensors`	Add sensors to specific host vehicle (R2023a 이후)

라이다 시뮬레이션을 위한 메시

메시 생성

`extendedObjectMesh`	Mesh representation of extended object
`translate`	Translate mesh along coordinate axes
`rotate`	Rotate mesh about coordinate axes
`scale`	Scale mesh in each dimension
`applyTransform`	Apply forward transformation to mesh vertices
`join`	Join two object meshes
`scaleToFit`	Auto-scale object mesh to match specified cuboid dimensions
`show`	Display the mesh as a patch on the current axes

사전 구성된 메시

`driving.scenario.bicycleMesh`	Mesh representation of bicycle in driving scenario
`driving.scenario.carMesh`	Mesh representation of car in driving scenario
`driving.scenario.pedestrianMesh`	Mesh representation of pedestrian in driving scenario
`driving.scenario.truckMesh`	Mesh representation of truck in driving scenario
`driving.scenario.jerseyBarrierMesh`	Mesh representation of Jersey barrier in driving scenario (R2021a 이후)
`driving.scenario.guardrailMesh`	Mesh representation of guardrail in driving scenario (R2021a 이후)

조감도 플롯

플로터 생성

`birdsEyePlot`	Plot detections, tracks, and sensor coverages around vehicle
`coverageAreaPlotter`	Coverage area plotter for bird's-eye plot
`detectionPlotter`	Detection plotter for bird's-eye plot
`trackPlotter`	Track plotter for bird's-eye plot
`laneBoundaryPlotter`	Lane boundary plotter for bird's-eye plot
`laneMarkingPlotter`	Lane marking plotter for bird's-eye plot
`meshPlotter`	Mesh plotter for bird's-eye plot
`pathPlotter`	Path plotter for bird's-eye plot
`pointCloudPlotter`	Point cloud plotter for bird's-eye plot
`outlinePlotter`	Outline plotter for bird's-eye plot
`rangeDetectionPlotter`	Range detection plotter for bird's-eye plot (R2022a 이후)

플로터 표시

`plotCoverageArea`	Display sensor coverage area on bird's-eye plot
`plotDetection`	Display object detections on bird's-eye plot
`plotLaneBoundary`	Display lane boundaries on bird’s-eye plot
`plotLaneMarking`	Display lane markings on bird’s-eye plot
`plotParkingLaneMarking`	Display parking lane markings on bird’s-eye plot (R2021b 이후)
`plotMesh`	Display object meshes on bird's-eye plot
`plotOutline`	Display object outlines on bird's-eye plot
`plotBarrierOutline`	Display barrier outlines on bird's-eye plot (R2021a 이후)
`plotPath`	Display actor paths on bird’s-eye plot
`plotPointCloud`	Display generated point cloud on bird's-eye plot
`plotRangeDetection`	Display range detections on bird's-eye plot (R2022a 이후)
`plotTrack`	Display object tracks on bird's-eye plot

플로터 유틸리티

`findPlotter`	Find plotters associated with bird’s-eye plot
`clearData`	Clear data from specific plotter of bird’s-eye plot
`clearPlotterData`	Clear data from bird’s-eye plot

도움말 항목

주행 시나리오

프로그래밍 방식으로 주행 시나리오 만들기
합성 센서 데이터 및 추적 알고리즘의 ground truth 주행 시나리오를 프로그래밍 방식으로 생성합니다.
Define Road Layouts Programmatically
Programmatically create road junctions and combine these junctions to create more complicated road networks.
Simulate Vehicle Parking Maneuver in Driving Scenario
Simulate a parking maneuver and generate sensor detections in a large parking lot using a cuboid driving scenario.
Create Actor and Vehicle Trajectories Programmatically
Programmatically create actor and vehicle trajectories for a driving scenario.
Create Driving Scenario Variations Programmatically
Programmatically create variations of a driving scenario that was built using the Driving Scenario Designer app.
Visualize Sensor Coverage, Detections, and Tracks
Configure and use a bird's-eye plot to display sensor coverage, detections, and tracking results around the ego vehicle.
Automate Control of Intelligent Vehicles by Using Stateflow Charts
Model a highway scenario with intelligent vehicles that are controlled by decision logic defined by a Stateflow^® chart.

센서

Model Radar Sensor Detections
Model and simulate the output of an automotive radar sensor for various driving scenarios.
Radar Signal Simulation and Processing for Automated Driving
Model the hardware, signal processing, and propagation environment of a radar for a driving scenario.
Simulate Radar Ghosts Due to Multipath Return
Generate ghost targets that occur when signal energy is reflected off another target before returning to the radar.
Model Vision Sensor Detections
Model and simulate the output of an automotive vision sensor for various driving scenarios.
Simulate Inertial Sensor Readings from a Driving Scenario (Navigation Toolbox)
Generate synthetic sensor data from IMU, GPS, and wheel encoders using driving scenario generation tools from Automated Driving Toolbox™.