Assessing vulnerability of road networks based on traffic flow betweenness centrality: A case study in Wuxi
DU Jiaxin1,2, ZHANG Feng1,2, DU Zhenhong1,2, LIU Renyi1,2
1.Zhejiang Provincial Key Lab of GIS, Zhejiang University, Hangzhou 310028, China 2.Department of Geographic Information Science, Zhejiang University, Hangzhou 310027, China
Abstract：Road networks are vulnerable to many events. Thus protecting the essential part of roads is important in rescue and emergency cases. Traffic Flow Betweenness Centrality (TFBC) was introduced to the study of network vulnerability considering both static network structure and dynamic demands of traffic. Taking Wuxi city as a case, using road information from the open street map and taxi trajectory data, the vulnerability of city road network was estimated. Vulnerability maps and statistics are presented to compare with the results by other vulnerability compute methods for validation and verification. The results show that:（1) Both TFBC and static network structure analysis gave high scores of vulnerability to streets that are near metropolitan areas. Those streets are the main vessels connecting different parts of the city. （2) TFBC identified important city center hubs, such as train stations, hospitals, flyovers as vulnerable. However, the vulnerability of these essential parts was underestimated by the static network structure analysis. （3) Nodes were assigned to low vulnerability in rural areas by TFBC. In contrast, static network structure analysis assigned high value to roads in villages, especially those which were connected to the metropolitan area. It seemed not reasonable since few people are using those road. The method of TFBC in road network research can effectively reveal the level of vulnerability by considering both static network structure and dynamic demands of traffic, which is of great significance to understanding the runtime pattern of road networks. The data source of TFBC is not limited to taxi trajectories, but can also use trajectory data generated by cell phones, bicycles and other motor vehicles. With more trajectory data provided in future studies, the results calculated by TFBC will be more accurate. Our research results are of great value to the related policy-making in urban transportation planning and management.
杜佳昕, 张丰, 杜震洪, 刘仁义. 基于加权流量介数中心性的路网脆弱性分析——以无锡市为例[J]. 浙江大学学报（理学版）, 2020, 47(2): 223-230.
DU Jiaxin, ZHANG Feng, DU Zhenhong, LIU Renyi. Assessing vulnerability of road networks based on traffic flow betweenness centrality: A case study in Wuxi. Journal of ZheJIang University(Science Edition), 2020, 47(2): 223-230.
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2020, Vol. 47 
