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arXiv · 1808.02550

Collaborative Planning for Mixed-Autonomy Lane Merging

Shray Bansal·Akansel Cosgun·Alireza Nakhaei·Kikuo Fujimura
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Abstract

Driving is a social activity: drivers often indicate their intent to change lanes via motion cues. We consider mixed-autonomy traffic where a Human-driven Vehicle (HV) and an Autonomous Vehicle (AV) drive together. We propose a planning framework where the degree to which the AV considers the other agent's reward is controlled by a selfishness factor. We test our approach on a simulated two-lane highway where the AV and HV merge into each other's lanes. In a user study with 21 subjects and 6 different selfishness factors, we found that our planning approach was sound and that both agents had less merging times when a factor that balances the rewards for the two agents was chosen. Our results on double lane merging suggest it to be a non-zero-sum game and encourage further investigation on collaborative decision making algorithms for mixed-autonomy traffic.

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Shray Bansal, Akansel Cosgun, Alireza Nakhaei, Kikuo Fujimura. 2018-08-07. Collaborative Planning for Mixed-Autonomy Lane Merging. https://arxiv.org/abs/1808.02550

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