Programmatic Scenario Authoring

Programmatically create driving scenarios by using adrivingScenarioobject

ThedrivingScenarioobject enables you to author driving scenarios from the MATLAB^®command line. Use this object to design complex road networks or parking lots and specify actors and their trajectories. You can then generate synthetic data from these scenarios by using sensor models and visualize this data on a bird's-eye plot.

The flexible interface of thedrivingScenarioobject enables you to create variations of a scenario for rapidly testing driving algorithms under various conditions. For more details, seeCreate Driving Scenario Variations Programmatically.

Functions

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Driving Scenarios

Scenarios

`drivingScenario`	Create driving scenario
`advance`	Advance driving scenario simulation by one time step
`plot`	Plot driving scenario
`record`	Run driving scenario and record actor states
`restart`	Restart driving scenario simulation from beginning
`updatePlots`	Update driving scenario plots
`export`	Export driving scenario toASAM OpenDRIVEorASAM OpenSCENARIOfile

Actors

`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
`state`	Inertial ground-truth state of actor
`actorPoses`	位置s, 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
`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 ego vehicle
`driving.scenario.targetsToEgo`	Convert target poses from scenario to ego coordinates
`driving.scenario.targetsToScenario`	Convert target poses from ego to scenario coordinates

Roads

`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
`roadGroup`	Add road junction or intersection to driving scenario

Lanes

`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
`laneSpecConnector`	Define road segment connector specifications

Parking Lots

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

Sensors

`drivingRadarDataGenerator`	Generate radar sensor detections and tracks from driving scenario
`visionDetectionGenerator`	Generate vision detections for driving scenario
`lidarPointCloudGenerator`	Generate lidar point cloud data for driving scenario
`insSensor`	Inertial navigation system and GNSS/GPS simulation model
`ultrasonicDetectionGenerator`	Generate ultrasonic range detections in driving scenario

Meshes for Lidar Simulation

Mesh Creation

`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

Prebuilt Meshes

`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
`driving.scenario.guardrailMesh`	Mesh representation of guardrail in driving scenario

Bird's-Eye Plot

Plotter Creation

`birdsEyePlot`	Plot detections, tracks, and sensor coverages around vehicle
`coverageAreaPlotter`	覆盖范围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

Plotter Display

`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
`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
`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
`plotTrack`	Display object tracks on bird's-eye plot

Plotter Utilities

`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

Topics

Driving Scenarios

Create Driving Scenario Programmatically
Programmatically create ground truth driving scenarios for synthetic sensor data and tracking algorithms.
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 theDriving Scenario Designer应用程序。
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.

Sensors

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™.

Featured Examples

Generate Scenario from Recorded GPS and Lidar Data

Generate a driving scenario by extracting recorded data from global positioning systems (GPS) and lidar sensors mounted on an ego vehicle. In this example, you use prerecorded sensor data and follow these steps to generate the scenario:

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Scenario Generation from Recorded Vehicle Data

Automatically generate virtual driving scenarios from recorded vehicle data.

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Automatic Scenario Generation

Automate scenario generation by using a drivingScenario object. In this example, you will automate:

Open Live Script

自动生成测试场景变体AEB Systems

Automatically generate variants of a seed scenario in which two actors collide. You can generate random variants of a collision scenario that you can use for the design and validation of autonomous driving applications such as automated emergency braking (AEB) systems. In this example, you generate the scenario variants by modifying the speed of the ego vehicle, actor dimensions, and the collision point. The collision point is a position on the ego vehicle at which the ego vehicle and target actor collide. This example assumes that the ego vehicle and the target actor always collide at 90 degrees, and the target actor collides with a point on the front edge of the ego vehicle. However, the collision time remains the same as in the seed scenario.

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Generate Lane Information from Recorded Data

Generate lane information for road network imported from standard definition map using recorded vehicle data.

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Improve Ego Vehicle Localization

Improve ego vehicle localization by fusing GPS and IMU sensor data and generate virtual driving scenario from recorded sensor data.

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