Scenario Generation and Variation

Generate scenario from recorded real-world sensor data and create scenario variations from seed scenario

In automated driving applications, scenario generation is the process of building virtual scenarios from real-world vehicle data recorded from global positioning system (GPS), inertial measurement unit (IMU), camera, and lidar sensors. Automated Driving Toolbox™ provides functions and tools to automate scenario generation process. You can preprocess sensor data, extract roads, localize actors and get actor trajectories to create an accurate digital twin of a real-world scenario. Simulate the generated scenario and test your automated driving algorithms against real-world data.

To generate scenarios from recorded sensor data, download the Scenario Builder for Automated Driving Toolbox support package from the Add-On Explorer. For more information on downloading add-ons, see Get and Manage Add-Ons.

Scenario variation is the process of generating multiple variants from a seed scenario that is either manually created or generated from recorded sensor data. You can vary scene parameters, actor parameters, or event parameters of a seed scenario and provide your constraints to generate new scenarios. Use these scenario variations for safety assessment of different automated driving applications such as autonomous emergency braking (AEB), lane keep assist (LKA), and adaptive cruise control (ACC).

To generate scenario variations, download the Scenario Variant Generator for Automated Driving Toolbox support package from the Add-On Explorer. For more information on downloading add-ons, see Get and Manage Add-Ons.

Functions

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Scenario Generation

`getMapROI`	Geographic bounding box coordinates from GPS data
`roadprops`	Extract road properties from road network file or map data
`selectActorRoads`	Extract properties of roads in path of actor
`updateLaneSpec`	Update lane specifications using sensor detections
`actorprops`	Generate actor properties from track list
`actorTracklist`	Store recorded actor track list data with timestamps
`laneData`	Store recorded lane boundary data with timestamps
`laneBoundaryTracker`	Track lane boundaries

Scenario Variation

`getScenarioDescriptor`	Extract properties from input scenario to generate scenario variants
`getCollisionData`	Get collision information of colliding actors
`variationProperties`	Store actor and collision property variations
`generateVariants`	Generate variant scenario descriptors from seed scenario descriptor using specified variations
`getScenario`	Get scenario object from scenario descriptor object

Topics

Scenario Generation

Overview of Scenario Generation from Recorded Sensor Data
Learn the basics of generating scenarios from recorded sensor data.
Preprocess Lane Detections for Scenario Generation
Format lane detection data to update lane specifications for scenario generation.
Smooth GPS Waypoints for Ego Localization
Create jitter-limited ego trajectory by smoothing GPS and IMU sensor data.
Ego Vehicle Localization Using GPS and IMU Fusion for Scenario Generation
Localize ego vehicle by fusing GPS and IMU sensor data to generate virtual driving scenario.
Ego Localization Using Lane Detections and HD Map for Scenario Generation
Perform lane-level localization of ego vehicle using lane detections, HD map data, and GPS data.
Extract Lane Information from Recorded Camera Data for Scene Generation
Extract lane information from raw camera data to generate ASAM OpenDRIVE^® scene or RoadRunner scene.
Extract Vehicle Track List from Recorded Camera Data for Scenario Generation
Extract actor track list from raw camera data for scenario generation.
Extract Vehicle Track List from Recorded Lidar Data for Scenario Generation
Extract actor track list from recorded lidar data using pretrained vehicle detection model and JPDA tracker.
Generate Road Scene Using Lanes from Labeled Recorded Data
Generate road scene with lanes from labeled camera images and raw lidar data.
Fuse Prerecorded Lidar and Camera Data to Generate Vehicle Track List for Scenario Generation
Generate scenario by fusing and smoothing tracked lidar data and camera data.

Scenario Variation

Overview of Scenario Variant Generation
Learn the basics of generating scenario variations from a seed scenario.
Generate Scenario Variants by Modifying Actor Dimensions
Generate scenario variants from seed scenario by modifying actor dimensions.
Translocate Collision from Seed Scenario to Target Scene
Translocate collision from RoadRunner seed scenario to target scene.

Featured Examples

Generate Scenario from Actor Track List and GPS Data

Generate ASAM OpenSCENARIO^® v1.0 file using recorded actor tracklist and GPS data.

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Generate RoadRunner Scenario from Recorded Sensor Data

Generate RoadRunner Scenario from recorded GPS data and preprocessed actor track list.

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Generate RoadRunner Scene from Recorded Lidar Data

Generate RoadRunner HD map from recorded lidar data using pretrained deep learning model.

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Generate High Definition Scene from Lane Detections and OpenStreetMap

Generate HD road scene using recorded lane detections, GPS data, and OpenStreetMap^® data.

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Generate Scenario Variants for Lane Keep Assist Testing

Generate scenario variants to test lane keep assist (LKA) system using European New Car Assessment Programme (Euro NCAP) test scenario.

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Generate Scenario Variants for Testing ACC Systems

Modify speeds of the ego and target vehicles to generate scenario variants for testing adaptive cruise control (ACC) application using European New Car Assessment Programme (Euro NCAP) test scenario.

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Generate Variants of ACC Target Cut-In Scenario

Generate scenario variants to test adaptive cruise control (ACC) application using European New Car Assessment Programme (Euro NCAP) test scenario in which the target vehicle cuts in front of the ego vehicle.

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Generate Scenario Variants for Testing AEB Pedestrian Systems

Generate scenario variants to test automated emergency braking (AEB) system using car-to-pedestrian European New Car Assessment Programme (Euro NCAP) test scenario.

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