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Title:

Provable Traffic Rule Compliance in Safe Reinforcement Learning on the Open Sea

Document type:
Zeitschriftenaufsatz
Author(s):
Hanna Krasowski; Matthias Althoff
Abstract:
For safe operation, autonomous vehicles have to obey traffic rules that are set forth in legal documents formulated in natural language. Temporal logic is a suitable concept to formalize such traffic rules. Still, temporal logic rules often result in constraints that are hard to solve using optimization-based motion planners. Reinforcement learning (RL) is a promising method to find motion plans for autonomous vehicles. However, vanilla RL algorithms are based on random exploration and do not au...     »
Journal title:
IEEE Transactions on Intelligent Vehicles
Year:
2024
Pages contribution:
1-18
Fulltext / DOI:
doi:10.1109/TIV.2024.3400597
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