Spatiotemporal state lattices for fast trajectory planning in dynamic on-road driving scenarios

We present a method for motion planning in the presence of moving obstacles that is aimed at dynamic on-road driving scenarios. Planning is performed within a geometric graph that is established by sampling deterministically from a manifold that is obtained by combining configuration space and time....

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Bibliographic Details
Published in2009 IEEE/RSJ International Conference on Intelligent Robots and Systems pp. 1879 - 1884
Main Authors Ziegler, J., Stiller, C.
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.10.2009
Subjects
Intelligent vehicles
Lattices
Motion planning
Road vehicles
Runtime
Sampling methods
Space vehicles
Spatiotemporal phenomena
Trajectory
Vehicle dynamics
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Summary:We present a method for motion planning in the presence of moving obstacles that is aimed at dynamic on-road driving scenarios. Planning is performed within a geometric graph that is established by sampling deterministically from a manifold that is obtained by combining configuration space and time. We show that these graphs are acyclic and shortest path algorithms with linear runtime can be employed. By reparametrising the configuration space to match the course of the road, it can be sampled very economically with few vertices, and this reduces absolute runtime further. The trajectories generated are quintic splines. They are second order continuous, obey nonholonomic constraints and are optimised for minimum square of jerk. Planning time remains below 20 ms on general purpose hardware.
ISBN:9781424438037
1424438039
ISSN:2153-0858
DOI:10.1109/IROS.2009.5354448