Search-Based Motion Planning for Performance Autonomous Driving
| Autor: | Zlatan Ajanovic, Georg Stettinger, Antonella Ferrara, Enrico Regolin, Martin Horn |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
0209 industrial biotechnology
Computer science Work (physics) 020302 automobile design & engineering Trail braking Control engineering 02 engineering and technology Track (rail transport) Computer Science::Robotics Vehicle dynamics Nonlinear system 020901 industrial engineering & automation 0203 mechanical engineering 11. Sustainability Dynamic vehicle Code (cryptography) Motion planning |
| Zdroj: | Lecture Notes in Mechanical Engineering ISBN: 9783030380762 |
| DOI: | 10.1007/978-3-030-38077-9_134 |
| Popis: | 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. Our code is available at https://git.io/JenvB. |
| Databáze: | OpenAIRE |
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