Multi-network Congestion Risk Propagation Model Considering Driver Behavior

Abstract

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.

Key words: urban traffic, congestion propagation analysis, micro Markov chain, roadway, warning information, drivers' route choice behavior

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拥堵风险传播机制；以国内典型城市道路网络特征分析为基础，构建符合真实道路状况的网络生成模型，并探讨道路网络拓扑结构和出行者面对预警信息时的行为特征对拥堵风险传播的影响。数值模拟结果表明：交通预警信息在发生严重拥堵时可以显著抑制道路拥堵传播，拥堵风险传播阈值与道路网络拓扑结构、预警信息、出行者面对预警信息时的行为特征及信息传输速率相关；ER随机网络与模拟路网相比具有爆发阈值更低，传播范围更广的特征。说明信息策略制定应更加重视出行者的风险态度和对拥堵的感知，提升信息通信强度有助于维持交通流的稳定。

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

CLC Number:

U121

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.

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.

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URL: http://www.tseit.org.cn/EN/abstract/abstract20177.shtml

http://www.tseit.org.cn/EN/Y2021/V21/I1/8

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