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Self-Organized Routing for Autonomous Vehicles via Deep Reinforcement Learning

文献类型：期刊论文

作者Pei, Huaxin1; Zhang, Jiawei1; Zhang, Yi2,3; Xu, Huile4; Li, Li2
刊名IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
出版日期2024
卷号73期号:1页码:426-437
关键词Routing Autonomous vehicles Vehicle-to-everything Vehicle dynamics Estimation Automation Traffic congestion self-organized deep reinforcement learning autonomous vehicle
ISSN号0018-9545
DOI10.1109/TVT.2023.3311198
通讯作者Li, Li(li-li@tsinghua.edu.cn)
英文摘要Routing for autonomous vehicles with global traffic information and sufficient direct cooperation among vehicles has been widely studied to relieve traffic congestion in recent years. However, the assembly rate of Vehicle-to-Everything (V2X) equipment in practical traffic systems is currently and could be at a low level in near future. Accordingly, autonomous vehicles can only access localized traffic information, and direct cooperation among them cannot always be guaranteed. Thus, how to optimize the routing choices in such scenarios is worthy of particular attention. In this article, we propose a self-organized routing strategy based on deep reinforcement learning (DRL). Under the condition of limited traffic information, the proposed self-organized mechanism well organizes localized traffic conditions through vehicle-level routing decisions, which are able to achieve network-wide benefits gains. In the specified DRL, we propose a novel reward mechanism to harmonize indirect interactions among vehicles by jointly learning individual and overall efficiency, even if each vehicle is modified to make individual decisions independently, rather than only focusing on individual interests as in the greedy strategy. Numerical experiments demonstrate that the proposed self-organized strategy is promising to resolve the routing problem from the perspective of individual decision-making with limited traffic information.
WOS关键词TRAFFIC ASSIGNMENT ; NETWORK ; SCHEME ; MODEL
资助项目National Key Research and Development Program of China
WOS研究方向Engineering ; Telecommunications ; Transportation
语种英语
WOS记录号WOS:001166813500113
出版者IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
资助机构National Key Research and Development Program of China
源URL[http://ir.ia.ac.cn/handle/173211/58117]  
专题模式识别国家重点实验室_三维可视计算
通讯作者Li, Li
作者单位1.Tsinghua Univ, Dept Automat, Beijing 100084, Peoples R China
2.Tsinghua Univ, Dept Automat, BNRist, Beijing 518055, Peoples R China
3.Tsinghua Berkeley Shenzhen Inst, Shenzhen 518055, Guangdong, Peoples R China
4.Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing 100190, Peoples R China
推荐引用方式
GB/T 7714		 Pei, Huaxin,Zhang, Jiawei,Zhang, Yi,et al. Self-Organized Routing for Autonomous Vehicles via Deep Reinforcement Learning[J]. IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY,2024,73(1):426-437.
APA Pei, Huaxin,Zhang, Jiawei,Zhang, Yi,Xu, Huile,&Li, Li.(2024).Self-Organized Routing for Autonomous Vehicles via Deep Reinforcement Learning.IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY,73(1),426-437.
MLA Pei, Huaxin,et al."Self-Organized Routing for Autonomous Vehicles via Deep Reinforcement Learning".IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY 73.1(2024):426-437.

入库方式： OAI收割

来源：自动化研究所

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