Search-based optimal motion planning for automated driving
| Autor: | Ajanovic, Zlatan, Lacevic, Bakir, Shyrokau, Barys, Stolz, Michael, Horn, Martin |
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| Rok vydání: | 2018 |
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| Druh dokumentu: | Working Paper |
| DOI: | 10.1109/IROS.2018.8593813 |
| Popis: | This paper presents a framework for fast and robust motion planning designed to facilitate automated driving. The framework allows for real-time computation even for horizons of several hundred meters and thus enabling automated driving in urban conditions. This is achieved through several features. Firstly, a convenient geometrical representation of both the search space and driving constraints enables the use of classical path planning approach. Thus, a wide variety of constraints can be tackled simultaneously (other vehicles, traffic lights, etc.). Secondly, an exact cost-to-go map, obtained by solving a relaxed problem, is then used by A*-based algorithm with model predictive flavour in order to compute the optimal motion trajectory. The algorithm takes into account both distance and time horizons. The approach is validated within a simulation study with realistic traffic scenarios. We demonstrate the capability of the algorithm to devise plans both in fast and slow driving conditions, even when full stop is required. Comment: Preprint accepted to 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2018). A supplementary video is available at https://youtu.be/D5XJ5ncSuqQ |
| Databáze: | arXiv |
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