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

Wei Zhang, Duanqiang Zhai () and Ziqi Wang
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Wei Zhang: School of Architecture, Tianjin University, Tianjin 300072, China
Duanqiang Zhai: Tongji University, Shanghai 200092, China
Ziqi Wang: School of Civil Engineering and Transportation, Northeast Forestry University, Harbin 150040, China

Sustainability, 2024, vol. 16, issue 14, 1-16

Abstract: 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.

Keywords: resident travel characteristics; urban road networks; vulnerability; cascade failure (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2024
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