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Automated Driving Toolbox

Design, simulate, and test ADAS and autonomous driving systems

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 ASAM 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.

Automated Driving Toolbox provides reference application examples for common ADAS and automated driving features, including forward collision warning, autonomous emergency braking, adaptive cruise control, lane keeping assist, 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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Learn the basics of Automated Driving Toolbox

File I/O

Read and visualize automotive data from external sources

Ground Truth Labeling

Interactive ground truth labeling of multiple signals

Scenario Simulation

Author scenes, generate synthetic sensor data, build scenarios from real-world sensor data, create scenario variants, test algorithms in simulated environments

Detection and Tracking

Camera sensor configuration, visual perception, lidar processing, tracking and sensor fusion

Localization and Mapping

SLAM, HERE HD Live Map data analysis, map visualization

Planning and Control

Vehicle costmaps, optimal RRT* path planning, lateral and longitudinal controllers


Examples for design and testing of automated driving applications