Autonomous Vehicle Trajectory Planning under Uncertainty Using Stochastic Collocation
Hong Fu Liu, Yu Zhang, Shao Fei Chen, Jing Chen · Advanced materials research · 2012
We propose a framework based on stochastic collocation to solve autonomous vehicle optimal trajectory planning problems with probabilistic uncertainty. We model uncertainty from the location and size of obstacles. We develop stochastic pseudospectral methods to solve the minimum expectation cost of differential equation, which meets path, control, and boundary constraints. Results are shown on two examples of autonomous vehicle trajectory planning under uncertainty, which illustrated the feasibility and applicability of our method.