2018.03.21. Matlab, Simulink get functions for autonomous driving and deep learning

The MathWorks developer tool Release 2018a, just unveiled, includes a number of new features for Matlab / Simulink. Examples include a predictive maintenance toolbox for designing and testing algorithms for condition monitoring and predictive maintenance and the Vehicle Dynamics Blockset for modeling and simulating vehicle dynamics in a virtual 3D environment.

The Vehicle Dynamics Blockset provides engineers with fully assembled reference application models that simulate driving maneuvers in a 3D environment. Users can visualize ready-made scenes with roads, traffic signs, trees and buildings or adapt these models with their own data.

The blockset provides a standard model architecture that can be used throughout the development process: It contains a library of components for modeling drive, steering, suspension, brakes and other vehicle components. It supports driving and handling analyses and the development of chassis controls.

By integrating vehicle dynamics models into a 3D environment, software for driver assistance systems and automated driving can be tested, for example the behavior of the vehicle during standard driving maneuvers such as a double lane change.

Other products also include new tools or extensions for the development of ADAS systems, e.g. the Automated Driving System Toolbox with the new Driving Scenario Designer App for interactive definition of actors and driving scenarios for testing control and sensor fusion algorithms and the Model Predictive Control Toolbox with ADAS blocks for designing, simulating and implementing adaptive algorithms for speed control and lane keeping.





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