A Decision-Making Model for Autonomous Vehicles at Intersections Based on Hierarchical Reinforcement Learning

Xue Mei Chen; Shu Yuan Xu; Zi Jia Wang; Xue Long Zheng; Xin Tong Han; En Hao Liu

doi:10.1142/S2301385024500122

A Decision-Making Model for Autonomous Vehicles at Intersections Based on Hierarchical Reinforcement Learning

Xue Mei Chen, Shu Yuan Xu, Zi Jia Wang, Xue Long Zheng, Xin Tong Han, En Hao Liu

Advanced Research Institute of Multidisciplinary Science

Beijing Institute of Technology

Research output: Contribution to journal › Article › peer-review

2 Citations (Scopus)

Abstract

By aiming at addressing the left-turning problem of an autonomous vehicle considering the oncoming vehicles at an urban unsignallized intersection, a hierarchical reinforcement learning is proposed and a two-layer model is established to study behaviors of left-turning driving. Compared with the conventional decision-making models with a fixed path, the proposed multi-paths decision-making algorithm with horizontal and vertical strategies can improve the efficiency of autonomous vehicles crossing intersections while ensuring safety.

Original language	English
Pages (from-to)	641-652
Number of pages	12
Journal	Unmanned Systems
Volume	12
Issue number	4
DOIs	https://doi.org/10.1142/S2301385024500122
Publication status	Published - 1 Jul 2024

Keywords

Autonomous vehicles
decision-making model
deep deterministic policy gradient
hierarchical reinforcement learning
urban intersections

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10.1142/S2301385024500122

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abstract = "By aiming at addressing the left-turning problem of an autonomous vehicle considering the oncoming vehicles at an urban unsignallized intersection, a hierarchical reinforcement learning is proposed and a two-layer model is established to study behaviors of left-turning driving. Compared with the conventional decision-making models with a fixed path, the proposed multi-paths decision-making algorithm with horizontal and vertical strategies can improve the efficiency of autonomous vehicles crossing intersections while ensuring safety.",

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author = "Chen, {Xue Mei} and Xu, {Shu Yuan} and Wang, {Zi Jia} and Zheng, {Xue Long} and Han, {Xin Tong} and Liu, {En Hao}",

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AU - Wang, Zi Jia

AU - Zheng, Xue Long

AU - Han, Xin Tong

AU - Liu, En Hao

N1 - Publisher Copyright: #c World Scientific Publishing Company.

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N2 - By aiming at addressing the left-turning problem of an autonomous vehicle considering the oncoming vehicles at an urban unsignallized intersection, a hierarchical reinforcement learning is proposed and a two-layer model is established to study behaviors of left-turning driving. Compared with the conventional decision-making models with a fixed path, the proposed multi-paths decision-making algorithm with horizontal and vertical strategies can improve the efficiency of autonomous vehicles crossing intersections while ensuring safety.

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KW - decision-making model

KW - deep deterministic policy gradient

KW - hierarchical reinforcement learning

KW - urban intersections

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A Decision-Making Model for Autonomous Vehicles at Intersections Based on Hierarchical Reinforcement Learning

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Keywords

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