关键词: 城市交通, 级联失效模型, 风险扰动机理, 交通拥塞风险, 控制特性

Abstract: This paper applies the information physics system to analyze the cascading failure process of urban traffic congestion risk field and proposes the quantitative method for toughness risk size assessment. A CPS(Cyber Physical Systems) control model is developed with mutual coupling of real traffic road network, traffic congestion prevention, and control type zoning of urban traffic congestion risk field in consideration of the multidimensional coupling characteristics of urban traffic congestion risk. The structural characteristics of the traffic domain is examined through the complex network theory. The CPS characteristic parameters are redefined, the four processes of CPS cascade failure are defined, and the CPS cascade failure model is developed with urban traffic congestion risk field. The risk factor is defined as the intervention point and the risk perturbation mechanism is elaborated through the network topology theory. The CPS connectivity is examined through the normalized quantitative node connectivity, delay time, average operating speed, average congestion length and other toughness indexes. The CPS damage perturbation and toughness are evaluated by different failure-recovery strategies, the indicators of the robustness, damage/recovery rate, and recovery capability. The results from case studies show that: (1) Guiyang city urban traffic congestion risk field CPS real traffic network consists of 170 intersections and 231 edges, and the traffic congestion prevention and control type zoning network consist of 21 traffic command areas and 41 edges. (2) The maximum and minimum degree value of the CPS model is respectively 22 and 1. The degree value obeys the power rate distribution function, has characteristic scale-free network features, and the mediator shows the exponential distribution. The degree value perturbation has the greatest influence on the real traffic network of Guiyang city, and the mediator perturbation has the greatest influence on the type of sub-districts of Guiyang city's traffic congestion prevention and control. (3) When t=2 , the network performance starts to decline under both meso and degree perturbation, and the meso perturbation affects the performance more than the degree perturbation, and both reach the lowest at t=7 . (4) The median recovery effect is better than the degree value recovery, under the median perturbation, the degree value recovery and median recovery effect of Guiyang city's real traffic network is poor, the toughness value is respectively 0.01123 and 0.01252, which is significantly lower than that of the toughness value of the traffic congestion prevention and control type of partitioning (0.1355). The proposed model provides reference for the quantitative evaluation and initiation of the traffic congestion control strategy at different stages.

Key words: urban traffic, cascading failure model, risk perturbation mechanism, traffic congestion risk, control characteristics