Название: MATLAB Automated Driving Toolbox User’s Guide (R2022b)Автор: MathWorks
Издательство: The MathWorks, Inc.
Год: September 2022
Страниц: 2060
Язык: английский
Формат: pdf (true)
Размер: 60.3 MB
Automated Driving Toolbox provides algorithms and tools for designing, simulating, and testing ADAS and autonomous driving systems. You can design and test vision and lidar perception systems, as well as sensor fusion, path planning, and vehicle controllers. Visualization tools include a bird’s-eye-view plot and scope for sensor coverage, detections and tracks, and displays for video, lidar, and maps. The toolbox lets you import and work with HERE HD Live Map data and OpenDRIVE road networks.
Using the Ground Truth Labeler app, you can automate the labeling of ground truth to train and evaluate perception algorithms. For hardware-in-the-loop (HIL) testing and desktop simulation of perception, sensor fusion, path planning, and control logic, you can generate and simulate driving scenarios. You can simulate camera, radar, and lidar sensor output in a photorealistic 3D environment and sensor detections of objects and lane boundaries in a 2.5D simulation environment.
World Coordinate System: All vehicles, sensors, and their related coordinate systems are placed in the world coordinate system. A world coordinate system is important in global path planning, localization, mapping, and driving scenario simulation. Automated Driving Toolbox uses the right-handed Cartesian world coordinate system defined in ISO 8855, where the Z-axis points up from the ground. Units are in meters.
In most Automated Driving Toolbox functionality, such as cuboid driving scenario simulations and visual perception algorithms, the origin of the vehicle coordinate system is on the ground, below the midpoint of the rear axle. In 3D driving scenario simulations, the origin is on ground, below the longitudinal and lateral center of the vehicle. For more details, see “Coordinate Systems for Unreal Engine Simulation in Automated Driving Toolbox”.
Automated Driving Toolbox provides reference application examples for common ADAS and automated driving features, including FCW, AEB, ACC, LKA, and parking valet. The toolbox supports C/C++ code generation for rapid prototyping and HIL testing, with support for sensor fusion, tracking, path planning, and vehicle controller algorithms.
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