An Agent-Based Traffic Recommendation System: Revisiting and Revising Urban Traffic Management Strategies
文献类型:期刊论文
作者 | Jin, Junchen6,7; Rong, Dingding7; Pang, Yuqi5; Ye, Peijun4; Ji, Qingyuan2,3; Wang, Xiao4; Wang, Ge1; Wang, Fei-Yue4 |
刊名 | IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS |
出版日期 | 2022-06-03 |
页码 | 13 |
ISSN号 | 2168-2216 |
关键词 | Switches Control systems Timing Task analysis Behavioral sciences Analytical models Research and development Agent-based recommendation system deep recommendation human-in-the-loop operation on-demand traffic management strategies |
DOI | 10.1109/TSMC.2022.3177027 |
通讯作者 | Ji, Qingyuan(qingyuan.ji@zju.edu.cn) |
英文摘要 | Strategic traffic management is crucial for combating traffic congestion at the macroscopic level. However, such a field is still relatively unexplored, particularly for microscopic control objects, such as intersections and coordinated intersection groups. This article proposes a human-in-the-loop recommendation system for strategic urban traffic management, which follows an agent-based structure. A regional agent dispatcher is defined to assign agents for operation whenever ``operation on-demand'' is required. Such a requirement is identified by a daily-dependent operational mode on strategic traffic operations at a control object level. The strategic management scheme for each control object is guided by a strategic agent (customized), which is essentially a deep recommender model with a specific architecture. By featuring the multiagent design, a customized operational scheme can be generated at the intersection level, which instructs the corresponding controller to take specific operations. The utility of the recommendation system is demonstrated via a case study using real-world traffic data. In both offline and online evaluations, the system performs consistently at traffic operational recommendations in different scenarios and has the potential to provide more reasonable traffic operational strategies than a human-operated system. |
WOS关键词 | SIGNAL CONTROL ; FRAMEWORK ; INTELLIGENCE ; ARCHITECTURE ; INTERNET ; LIGHTS |
资助项目 | National Natural Science Foundation of China[62173329] ; National Key Research and Development Program of China[2018AAA0101502] |
WOS研究方向 | Automation & Control Systems ; Computer Science |
语种 | 英语 |
出版者 | IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC |
WOS记录号 | WOS:000809367300001 |
资助机构 | National Natural Science Foundation of China ; National Key Research and Development Program of China |
源URL | [http://ir.ia.ac.cn/handle/173211/49596] |
专题 | 自动化研究所_复杂系统管理与控制国家重点实验室_先进控制与自动化团队 |
通讯作者 | Ji, Qingyuan |
作者单位 | 1.Univ Chinese Acad Sci, Coll Econ & Management, Beijing 100190, Peoples R China 2.Zhejiang Univ, Coll Comp Sci & Technol, Hangzhou 310027, Peoples R China 3.Enjoyor Co Ltd, Smart Transport Res Inst, Hangzhou 310030, Peoples R China 4.Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China 5.Zhejiang Lab, Intelligent Transport Res Ctr, Hangzhou 311121, Peoples R China 6.Zhejiang Univ, Coll Elect Engn, Hangzhou 310027, Peoples R China 7.Zhejiang Supcon Informat Co Ltd, Traff Res & Dev Dept, Hangzhou 310052, Peoples R China |
推荐引用方式 GB/T 7714 | Jin, Junchen,Rong, Dingding,Pang, Yuqi,et al. An Agent-Based Traffic Recommendation System: Revisiting and Revising Urban Traffic Management Strategies[J]. IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS,2022:13. |
APA | Jin, Junchen.,Rong, Dingding.,Pang, Yuqi.,Ye, Peijun.,Ji, Qingyuan.,...&Wang, Fei-Yue.(2022).An Agent-Based Traffic Recommendation System: Revisiting and Revising Urban Traffic Management Strategies.IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS,13. |
MLA | Jin, Junchen,et al."An Agent-Based Traffic Recommendation System: Revisiting and Revising Urban Traffic Management Strategies".IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS (2022):13. |
入库方式: OAI收割
来源:自动化研究所
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