Decision-making at Unsignalized Intersection for Autonomous Vehicles: Left-turn Maneuver with Deep Reinforcement Learning

• URL: http://arxiv.org/abs/2008.06595v2
• Date: Sat, 13 Nov 2021 03:30:27 GMT
• Title: Decision-making at Unsignalized Intersection for Autonomous Vehicles: Left-turn Maneuver with Deep Reinforcement Learning
• Authors: Teng Liu, Xingyu Mu, Bing Huang, Xiaolin Tang, Fuqing Zhao, Xiao Wang, Dongpu Cao
• Abstract summary: This work proposes a deep reinforcement learning based left-turn decision-making framework at unsignalized intersection for autonomous vehicles. The presented decision-making strategy could efficaciously reduce the collision rate and improve transport efficiency. This work also reveals that the constructed left-turn control structure has a great potential to be applied in real-time.
• Score: 17.715274169051494
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Decision-making module enables autonomous vehicles to reach appropriate maneuvers in the complex urban environments, especially the intersection situations. This work proposes a deep reinforcement learning (DRL) based left-turn decision-making framework at unsignalized intersection for autonomous vehicles. The objective of the studied automated vehicle is to make an efficient and safe left-turn maneuver at a four-way unsignalized intersection. The exploited DRL methods include deep Q-learning (DQL) and double DQL. Simulation results indicate that the presented decision-making strategy could efficaciously reduce the collision rate and improve transport efficiency. This work also reveals that the constructed left-turn control structure has a great potential to be applied in real-time.

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