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Title:

Learning to Obey Traffic Rules using Constrained Policy Optimization

Document type:
Konferenzbeitrag
Author(s):
Xiao Wang; Christoph Pillmayer; Matthias Althoff
Abstract:
When planning motions for autonomous vehicles, traffic rules must be obeyed to ensure safety and reject liability claims. However, present solutions do not scale well with the complexity of traffic rules or even consider them. To solve this problem, we propose a scalable approach based on constrained policy optimization to improve traffic rule compliance of motion planners for autonomous vehicles. Our approach encodes traffic rules as constraints of the optimization problem and does not require...     »
Keywords:
Reinforcement Learning; Automated Vehicle Operation, Motion Planning, Navigation; Advanced Vehicle Safety Systems
Book / Congress title:
IEEE International Conference on Intelligent Transportation Systems (ITSC)
Year:
2022
Fulltext / DOI:
doi:10.1109/ITSC55140.2022.9921880
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