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考虑出行者行为的多重网络拥堵风险传播模型
引用本文:黄建华,孙梦歌. 考虑出行者行为的多重网络拥堵风险传播模型[J]. 交通运输系统工程与信息, 2021, 21(1): 8-15. DOI: 10.16097/j.cnki.1009-6744.2021.01.002
作者姓名:黄建华  孙梦歌
作者单位:福州大学,经济与管理学院,福州 350116
基金项目:国家社科基金一般项目/General Projects of National Social Science Foundation of China(20BGL003)
摘    要:城市道路交通拥堵风险传播过程受拥堵预警信息、出行者行为特性及居民出行流量分布等诸多因素影响.本文提出包括道路子网、信息子网和出行子网的多重网络模型,应用改进的UAU-SIR(Unaware-Aware-Unaware-Susceptible-Infective-Recovered)模型,探讨多重网络预警信息下的城市道路...

关 键 词:城市交通  拥堵传播分析  微观马尔科夫链  道路  预警信息  出行者路线选择
收稿时间:2020-11-02

Multi-network Congestion Risk Propagation Model Considering Driver Behavior
HUANG Jian-hua,SUN Meng-ge. Multi-network Congestion Risk Propagation Model Considering Driver Behavior[J]. Journal of Transportation Systems Engineering and Information Technology, 2021, 21(1): 8-15. DOI: 10.16097/j.cnki.1009-6744.2021.01.002
Authors:HUANG Jian-hua  SUN Meng-ge
Affiliation:School of Economics and Management, Fuzhou University, Fuzhou 350116, China
Abstract:The risk propagation process of urban road traffic congestion is affected by many factors, such as congestion warning information, traveler behavior characteristics and resident traffic flow distribution. In this paper, a multinetwork model is proposed including road network, information network and travel network. The propagation mechanism of urban road congestion risk under multi- network warning information is discussed using the improved UAU- SIR model. With the analysis of road network characteristics of typical cities in China, a network generation model is developed to reflect the real road conditions. The congestion risk propagation is analyzed through the influence of road network topology and travelers' behavior characteristics. The results of numerical simulation show that traffic warning information significantly affect the propagation of road congestion in case of serious congestions. The propagation threshold of congestion risk is related to the topology of road network, warning information, the behavior characteristics of travelers respond to warning information and the information transmission rate. Compared with the simulation road network, the ER random network has lower burst threshold and wider propagation area. It suggests that when making the information strategies, traveler's risk attitude and perception to congestions should be considered. Improving information communication intensity is helpful to maintain the stability of traffic flow.
Keywords:urban traffic  congestion propagation analysis  micro Markov chain  roadway  warning information  drivers' route choice behavior  
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