Scenario Builder for Automated Driving Toolbox
Build simulation scenarios from real-world vehicle data recorded from GPS, IMU, camera, and lidar sensors
418.0 次下载
更新时间
2024/10/16
The Scenario Builder for Automated Driving Toolbox, allows users to generate simulation scenarios for automated driving applications. It provides functions that helps to generate scenarios from both raw real-world vehicle data and processed object list data from perception modules.
With RoadRunner Scene Builder, users can visualize the generated scenes with roads, lanes, and roadside objects in RoadRunner. These scenes can then be exported to ASAM OpenDRIVE® format. On the other hand, RoadRunner Scenario tool facilitates the simulation of scenario actors, such as vehicles, along their trajectories. The resulting scenarios can be exported to ASAM OpenSCENARIO® v1.x and v2.0 formats.
The generated scenes and scenarios can be used for designing and testing automated driving applications.
Getting Started
Features
Scenario generation using recorded sensor data is accomplished using below workflow:
Key event extraction
Ego vehicle trajectory generation and localization
- Smooth GPS Waypoints for Ego Localization
- Ego Vehicle Localization Using GPS and IMU Fusion
- Ego Localization Using Lane Detections and HD Map
Road reconstruction
- Generate RoadRunner Scene Using Labeled Camera Images and GPS Data
- Generate RoadRunner Scene Using Labeled Camera Images and Raw Lidar Data
- Generate RoadRunner Scene from Recorded Lidar Data
- Generate High Definition Scene from Lane Detections and OpenStreetMap
- Extract Lane Information from Recorded Camera Data for Scene Generation
- Preprocess Lane Detections for Scenario Generation
Roadside object reconstruction
- Generate RoadRunner Scene with Trees and Buildings Using Recorded Lidar Data
- Generate RoadRunner Scene with Traffic Signs using Recorded Sensor Data
- Generate RoadRunner Scene Using Aerial Lidar Data
- Generate RoadRunner Scene Using Aerial Hyperspectral and Lidar Data
- Georeference Sequence of Point Clouds for Scene Generation
- Georeference Aerial Point Cloud for Scene Generation
Target actor trajectory reconstruction
- Generate RoadRunner Scenario from Recorded Sensor Data
- Generate Scenario from Actor Track List and GPS Data
- Fuse Prerecorded Lidar and Camera Data to Generate Vehicle Track List
- Extract Vehicle Track List from Recorded Camera Data
- Extract Vehicle Track List from Recorded Lidar Data
- Extract 3D Vehicle Information from Recorded Monocular Camera Data for Scenario Generation
Overview Video
Technical Article
Customer Reference
Aptiv:
Scenario Harvesting Using Automated Driving Toolbox and RoadRunner Scenario, MathWorks Automotive Conference 2023, NA
Scene Sync: Bridging Real-World Scenarios with Virtual Environments for ADAS Development, MathWorks Automotive Conference 2024, NA
IAV:
AD/ADAS Country-Based Virtual Validation Using Real-World Data, MathWorks Automotive Conference 2024, Europe
Support
Notes
You can create multiple variations of a generated scenario to perform additional testing of automated driving functionalities. For more information, see Scenario Variant Generator for Automated Driving Toolbox.
MATLAB 版本兼容性
创建方式
R2022b
兼容 R2022b 到 R2024b 的版本
平台兼容性
Windows macOS (Apple 芯片) macOS (Intel) Linux标签
Community Treasure Hunt
Find the treasures in MATLAB Central and discover how the community can help you!
Start Hunting!
您也可以从以下列表中选择网站：
美洲
- América Latina (Español)
- Canada (English)
- United States (English)
欧洲
- Belgium (English)
- Denmark (English)
- Deutschland (Deutsch)
- España (Español)
- Finland (English)
- France (Français)
- Ireland (English)
- Italia (Italiano)
- Luxembourg (English)
- Netherlands (English)
- Norway (English)
- Österreich (Deutsch)
- Portugal (English)
- Sweden (English)
- Switzerland
- United Kingdom(English)
亚太
- Australia (English)
- India (English)
- New Zealand (English)
- 中国
- 日本Japanese (日本語)
- 한국Korean (한국어)