Merging in Congested Freeway Traffic Using Multipolicy Decision Making and Passive Actor-Critic Learning

Tomoki Nishi

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Prashant Doshi

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Danil V. Prokhorov

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IEEE Transactions on Intelligent Vehicles, pp. 287-297, 2019.

Cited by: 0|Bibtex|Views14|DOI:https://doi.org/10.1109/TIV.2019.2904417

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Other Links: dblp.uni-trier.de|arxiv.org|academic.microsoft.com

Keywords:

MergingPicture archiving and communication systemsTraffic controlReinforcement learningVehicle dynamicsMore(2+)

Abstract:

Merging in congested freeway traffic is a significant challenge toward realizing fully automated (level 4) driving. Merging vehicles need to decide not only how to merge safely into a spot, but also where to merge. We present a method for freeway merge based on multipolicy decision making coupled with a reinforcement learning technique ca...More

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