Function of Traffic Prediction in Alleviating Traffic Congestion

被引:0
作者
Zhao, Zheng [1 ]
Han, Zhenxing [2 ]
Zhao, Changchen [1 ]
Zhang, Yixin [3 ]
机构
[1] Beihang Univ, Hangzhou Innovat Institue, Hangzhou 310051, Peoples R China
[2] Enjoyor Technol Co Ltd, Zhejiang Intelligent Transportat Engn Technol Res, Hangzhou 311400, Peoples R China
[3] Beihang Univ, Sch Automat Sci & Elect Engn, Beijing 100191, Peoples R China
来源
2022 INTERNATIONAL CONFERENCE ON FRONTIERS OF ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING, FAIML | 2022年
基金
中国国家自然科学基金;
关键词
traffic prediction; traffic congestion; cyclic causal model; travel decision model; simulation;
D O I
10.1109/FAIML57028.2022.00035
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Traffic prediction technique can be used to guide people's travel, and there are many researches have been conducted to achieve a higher prediction accuracy. If the traffic prediction result can be timely conveyed to all travelers, personal travel plan may also change accordingly, thus to influence the traffic state of the road network. This paper considers decision-making model, cyclic causal model, and game process, and analyzes the function of traffic prediction in alleviating traffic congestion. Simulation results prove that the sharing mechanism of traffic forecast results is very important, meanwhile, a limited effect can be also found when using traffic prediction to alleviate traffic congestion.
引用
收藏
页码:141 / 145
页数:5
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