Abstract | ||
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Trajectory planning is commonly used as part of a local planner in autonomous driving. This paper considers the problem of planning a continuous-curvature-rate trajectory between fixed start and goal states that minimizes a tunable trade-off between passenger comfort and travel time. The problem is an instance of infinite dimensional optimization over two continuous functions: a path and a velocity profile. We propose a simplification of this problem that facilitates the discretization of both functions. This paper also proposes a method to quickly generate minimal-length paths between start and goal states based on a single tuning parameter: the second derivative of curvature. Further, we discretize the set of velocity profiles along a given path into a selection of longitudinal jerk way-points along the path. Finally, we repeatedly solve the path and velocity profiles in an iterative fashion. Numerical examples are provided to illustrate the benefits of the proposed methods. |
Year | DOI | Venue |
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2022 | 10.1109/TIV.2022.3141881 | IEEE Transactions on Intelligent Vehicles |
Keywords | DocType | Volume |
Motion planning,path planning,trajectory optimization | Journal | 7 |
Issue | ISSN | Citations |
2 | 2379-8858 | 0 |
PageRank | References | Authors |
0.34 | 9 | 2 |
Name | Order | Citations | PageRank |
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Alexander Botros | 1 | 0 | 0.68 |
Stephen L Smith | 2 | 1163 | 83.01 |