Automated Driving System Toolbox enables designing and testing of ADAS and autonomous driving systems

May 16, 2017
The Autonomous Driving System Toolbox provide algorithms and tools for designing and testing advanced driver assistance systems (ADAS) and autonomous driving systems.

The Autonomous Driving System Toolbox provide algorithms and tools for designing and testing advanced driver assistance systems (ADAS) and autonomous driving systems. Among the toolbox’s features are a ground-truth labeling workflow app to automate labeling, tools to compare simulation output with ground truth, sensor fusion and tracking algorithms (including Kalman filters), multi-object tracking framework, detection-track assignment, and motion models. Additionally, the toolbox enables driving scenario generation, sensor simulation for camera and radar, computer vision algorithms (including lane detection and classification, vehicle detection, and image-vehicle coordinate transforms), as well as visualizations and C-code generation for sensor fusion and tracking algorithms with MATLAB Coder.

To Learn More:

Contact: MathWorks
Headquarters
: Natick, MA, USA
Product:
Autonomous Driving System
Key Features:
Ground-truth labeling workflow app, sensor fusion and tracking algorithms, visualization and driving scenario generation, algorithms for detection and tracking.

What MathWorks says:
View more information on the toolbox.

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About the Author

James Carroll

Former VSD Editor James Carroll joined the team 2013.  Carroll covered machine vision and imaging from numerous angles, including application stories, industry news, market updates, and new products. In addition to writing and editing articles, Carroll managed the Innovators Awards program and webcasts.

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