Travel Characteristics and Vulnerability Analysis of Road Resource Utilization Based on Taxi GPS Data

被引:0
|
作者
Zhang, Wei [1 ,2 ]
Zhai, Duanqiang [3 ]
Wang, Ziqi [4 ]
机构
[1] Tianjin Univ, Sch Architecture, Tianjin 300072, Peoples R China
[2] Zhejiang Univ, ZJU STEC Urban Dev & Planning Innovat Joint Res Ct, Hangzhou 310058, Peoples R China
[3] Tongji Univ, Shanghai 200092, Peoples R China
[4] Northeast Forestry Univ, Sch Civil Engn & Transportat, Harbin 150040, Peoples R China
关键词
resident travel characteristics; urban road networks; vulnerability; cascade failure; TRAFFIC FLOW; NETWORKS; ROBUSTNESS; EMERGENCE; LINKS;
D O I
10.3390/su16145979
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Residents' travel and logistics are greatly affected by urban transportation networks, which are one of the most important supports for urban socio-economic activities. Urban transportation systems tend to cripple when faced with challenges such as natural hazards and social unrest. This paper proposes a framework for a vulnerability analysis of urban road networks (URNs) based on real traffic flows with GPS data. An improved K-shell critical node identification method is proposed based on structural and traffic characteristics. Then, a cascade failure model is proposed to analyze the structural and functional vulnerability of the URN by combining the load capacity model and the vulnerability model. This paper takes the Harbin main city URN as an example and first analyzes the passenger travel distribution and the relationship between travel orders, population and POI. Four deliberate attack methods are proposed to analyze the vulnerability of the URN under deliberate attack on commute days and rest days. The experimental results show that URNs exhibit intense vulnerability, with the fastest cascading failure occurring based on improved K-shell node failure. Furthermore, URNs are more vulnerable on rest days compared to commuter days. These findings could be used to inform a vulnerability-based spatiotemporal design of UBNs and provide theoretical support for managing traffic congestion on different days.
引用
收藏
页数:16
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