Abstract
In this paper, we propose a constrained optimal control approach as a reference trajectory generator for a driving scenario with uncertainty. With a given scenario, this generator can produce a reference trajectory in order to make validations for autonomous vehicle’s decision-making problems. The constrained optimal control problem guarantees obtaining a collision-free trajectory with safety and comfort based on the design of the objective function and the constraints of the vehicle. The uncertainty of environmental information provided by sensors is taken into account, and a stochastic optimization problem is proposed to limit the risk of violating safety requirements. Numerical experiments show that the stochastic model can better ensure the robustness of the obtained solutions.
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Acknowledgement
This work was supported by the French government under the “France 2030” program, as part of the SystemX Technological Research Institute.
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© 2023 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
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Zhang, S., Hadji, M., Lisser, A. (2023). Optimal Control Based Trajectory Planning Under Uncertainty. In: Martins, A.L., Ferreira, J.C., Kocian, A., Tokkozhina, U. (eds) Intelligent Transport Systems. INTSYS 2022. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 486. Springer, Cham. https://doi.org/10.1007/978-3-031-30855-0_5
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DOI: https://doi.org/10.1007/978-3-031-30855-0_5
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