Assessing the vulnerability of urban rail transit network under heavy air pollution: A dynamic vehicle restriction perspective
place - asia, place - urban, mode - rail, policy - congestion, policy - environment, operations - performance
Dynamic vehicle restriction, Rail transit network, Vulnerability, Complex network
With the sharp increase of vehicle emissions in urban areas, some cities in China have launched dynamic vehicle restriction policies to reduce carbon emissions by limiting the use of private cars. The dynamic vehicle restriction policies include One-Day-Per-Week (ODPW) and Odd-And-Even (OAE). The implementation of these policies can cause private car users to switch to public transport. This adds tremendous pressure on urban public transportation systems, especially the rail transport network (RTN). In this study, we examine the impact of dynamic restriction policies on RTN’s vulnerability. An evaluation indicator system for RTN’s vulnerability is first constructed using the average shortest path, congestion degree, and average passenger flow intensity. Thereafter, we simulate the cascading failure process of the RTN using a load capacity model. The simulation results show that implementing dynamic vehicle restriction policies will lead to cascading failure of the RTN and increase its vulnerability. According to the simulation results, it was found that when the restriction policy changes from ODPW to OAE, the RTN is more likely to cause cascading failure and its vulnerability increases sharply. Consequently, transport operators should adopt various measures to prevent the cascading failures of RTN and reduce its vulnerability according to different restriction policies.
Permission to publish the abstract has been given by Elsevier, copyright remains with them.
Ma, F., Liang, Y., Yuen, K.F., Sun, Q., Zhu, Y., Wang, Y., & Shi, W. (2020). Assessing the vulnerability of urban rail transit network under heavy air pollution: A dynamic vehicle restriction perspective. Sustainable Cities and Society, Vol. 52.