Towards Comprehensive Maneuver Decisions for Lane Change Using Reinforcement Learning

Chen Chen
Chen Chen
Jun Qian
Jun Qian
Jun Luo
Jun Luo
Hongbo Zhang
Hongbo Zhang

NeurIPS workshop on MLITS, 2018.

Cited by: 1|Bibtex|Views9|Links

Abstract:

In this paper, we consider the problem of autonomous lane changing for self driving vehicles in a multi-lane, multi-agent setting. We use reinforcement learning solely to obtain a high-level policy for decision making, while the lower level action is executed by a pre-defined controller. To obtain a comprehensive model adaptive to as wide...More

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