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On-Road Motion Planning for Autonomous Vehicles
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  • 作者:Tianyu Gu (22)
    John M. Dolan (22)
  • 关键词:Motion Planning ; Dynamic Programming ; On ; road Autonomous Driving
  • 刊名:Lecture Notes in Computer Science
  • 出版年:2012
  • 出版时间:2012
  • 年:2012
  • 卷:7508
  • 期:1
  • 页码:598-607
  • 全文大小:488KB
  • 参考文献:1. Kelly, A., et al.: Reactive nonholonomic trajectory generation via parametric optimal control. International Journal of Robotics Research?22(7), 583-01 (2003) CrossRef
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    13. Ziegler, J., Stiller, C.: Spatiotemporal state lattices for fast trajectory planning in dynamic on-road driving scenarios. In: The International Conference on Intelligent Robots and Systems (2009)
  • 作者单位:Tianyu Gu (22)
    John M. Dolan (22)

    22. Carnegie Mellon University, 5000 Forbes Avenue, Pittsburgh, 15213, PA, USA
文摘
We present a motion planner for autonomous on-road driving, especially on highways. It adapts the idea of a on-road state lattice. A focused search is performed in the previously identified region in which the optimal trajectory is most likely to exist. The main contribution of this paper is a computationally efficient planner which handles dynamic environments generically. The Dynamic Programming algorithm is used to explore in spatiotemporal space and find a coarse trajectory solution first that encodes desirable maneuvers. Then a focused trajectory search is conducted using the ”generate-and-test-approach, and the best trajectory is selected based on the smoothness of the trajectory. Analysis shows that our scheme provides a principled way to focus trajectory sampling, thus greatly reduces the search space. Simulation results show robust performance in several challenging scenarios.

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