Search-Based Motion Planning for Performance Autonomous Driving
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Publication:6322292
arXiv1907.07825MaRDI QIDQ6322292
Author name not available (Why is that?)
Publication date: 17 July 2019
Abstract: Driving on the limits of vehicle dynamics requires predictive planning of future vehicle states. In this work, a search-based motion planning is used to generate suitable reference trajectories of dynamic vehicle states with the goal to achieve the minimum lap time on slippery roads. The search-based approach enables to explicitly consider a nonlinear vehicle dynamics model as well as constraints on states and inputs so that even challenging scenarios can be achieved in a safe and optimal way. The algorithm performance is evaluated in simulated driving on a track with segments of different curvatures.
Has companion code repository: https://github.com/zlatanajanovic/SBMP_PerfDriving
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