Design, simulate, and test ADAS and autonomous driving systems

Automated Driving System Toolbox™ provides algorithms and tools for designing and testing ADAS and autonomous driving systems. You can automate ground-truth labeling, generate synthetic sensor data for driving scenarios, perform multisensor fusion, and design and simulate vision systems.

For open-loop testing, the system toolbox provides a customizable workflow app and evaluation tools that let you automate labeling of ground truth and test your algorithms against ground truth. For HIL and desktop simulation of sensor fusion and control logic, you can generate driving scenarios and simulate object lists from radar and camera sensors.

Automated Driving System Toolbox supports multisensor fusion development with Kalman filters, assignment algorithms, motion models, and a multiobject tracking framework. Algorithms for vision system design include lane marker detection, vehicle detection with machine learning, including deep learning, and image-to-vehicle coordinate transforms.


Capabilities

Ground-Truth Labeling

Automate labeling of ground-truth data, and compare output from the algorithm under test with ground-truth data.

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Sensor Fusion and Tracking

Perform multisensor fusion using multiobject tracking framework with Kalman filters.

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Vision System Design

Develop computer vision algorithms for vehicle and pedestrian detection, lane detection, and classification.

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Scenario Generation

Generate traffic scenarios and simulate radar and camera sensor outputs to test sensor fusion and control algorithms.

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Visualization Tools

Visualize output of camera, radar, and LiDAR sensors.

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Product Resources

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Documentation

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Functions

Browse the list of available Automated Driving System Toolbox functions.

System Requirements

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Avi

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Automated Driving System Toolbox Technical Expert

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Automated Driving System Toolbox requires: Image Processing Toolbox, Computer Vision System Toolbox, MATLAB


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