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Carnegie Mellon Robotics Institute

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Abstract

We present a motion planner for autonomous highway driving that adapts the state lattice framework pioneered for planetary rover navigation to the structured environment of public roadways. The main contribution of this paper is a search space representation that allows the search algorithm to systematically and efficiently explore both spatial and temporal dimensions in real time. This allows the low-level trajectory planner to assume greater responsibility in planning to follow a leading vehicle, perform lane changes, and swerve around obstacles in the presence of other vehicles. We show that our algorithm can readily be accelerated on a GPU, and demonstrate it on an autonomous passenger vehicle.

Keywords

autonomous driving, motion planning, lattice planner

Notes

Associated Project(s): Autonomous Driving Motion Planning

Number of pages: 7

Text Reference

Matthew McNaughton, Christopher Urmson, John M. Dolan, and Jin-Woo Lee, "Motion Planning for Autonomous Driving with a Conformal Spatiotemporal Lattice," Proceedings of the International Conference on Robotics and Automation, May, 2011, pp. 4889-4895.

BibTeX Reference

@inproceedings{McNaughton_2011_6933,
   author = "Matthew McNaughton and Christopher Urmson and John M Dolan and Jin-Woo Lee",
   title = "Motion Planning for Autonomous Driving with a Conformal Spatiotemporal Lattice",
   booktitle = "Proceedings of the International Conference on Robotics and Automation",
   pages = "4889-4895",
   month = "May",
   year = "2011",
}

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