Abstract
The vulnerability of an urban road network is affected by many factors, such as internal road network layout, network structure strength, and external destructive events, which have great uncertainty and complexity. Thus, there is still no unified and definite vulnerability analysis scheme available to cities. This paper proposes an integrative vulnerability identification method for urban road networks, which mainly relates to the vulnerability connotation and characteristics analysis of urban road networks during emergency, and vulnerability comprehensive evaluation indices design based on urban road network connectivity, traffic efficiency and performance, and an empirical study on a vulnerability identification method of an urban road network. In the empirical case, a real road network and traffic operation data were used from Science and Technology Park of Shenzhen City, China. In the context of one certain emergency scenario, the stated preference survey method and maximum likelihood method are used to solve the road users’ random travel choice behavior parameters; subsequently, based on the traffic equilibrium distribution prediction, the traffic vulnerability identification methods of the road network in this region were verified before and after the emergency. The method presented here not only considers the impact of network topology changes on road network traffic function during emergency but also considers the impact of dynamic changes in road network traffic demand on vulnerability; therefore, it is closer to the actual distribution of urban road network traffic vulnerability.
Highlights
E VURN’s main research purpose is to obtain a method that can quickly, accurately, and reliably identify those vulnerable links in the road network, to provide assistance to reduce the losses caused by various emergencies on vulnerable roads [7, 8], and fundamentally provide decision support for improving the risk resistance ability of urban road networks
Based on the analysis of the connotation and characteristics of the VURN, this paper proposes an integrative identification index which can comprehensively reflect the changes of urban road network vulnerability and designs the corresponding identification model and algorithm. e main contributions are as follows: (1) A three-dimensional model for vulnerability analysis of an urban road network under emergency is established. e model can better explain the concept of the VURN, which mainly involves three variables, namely, the process variable of emergency, the traffic loss variable of the road network caused by the emergency, and the probability variable of the emergency
(2) An integrative vulnerability identification index system of an urban road network is established. e VURN is affected by many factors, in the connectivity and stability of the network topology, and in the effectiveness and reliability of the network service function, which are related to the process of emergency. erefore, based on the comprehensive identification index system of the emergency occurrence process, the city can more accurately identify the VURN
Summary
Studies of vulnerability emerged in the field of engineering and were extended to the social economic and political institutional level by social scientists. (3) In examining the impact of emergency, if the loss degree of the road traffic network is more serious, it indicates that the inherent vulnerability is greater and that the road network is more vulnerable to external interference factors. (4) Once the emergency and losses are under control, if the service level of the road traffic network is conducive to effective restoration under external repair, the impact of the vulnerability is considered low; the impact is categorized as high. Erefore, we define the vulnerability of a road traffic network as follows: the vulnerability of a road traffic network refers to the comprehensive embodiment of the probability of a road traffic network being affected, the severity of loss consequences, and the difficulty of recovery in an emergency encounter Pmax is the maximum probability of an emergency, and lmax is the maximum loss caused by an emergency. erefore, we define the vulnerability of a road traffic network as follows: the vulnerability of a road traffic network refers to the comprehensive embodiment of the probability of a road traffic network being affected, the severity of loss consequences, and the difficulty of recovery in an emergency encounter
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