Evaluating the dynamic resilience of the multi-mode public transit network for sustainable transport

Improving multi-mode public transit resilience becomes crucial as urban traffic infrastructure gradually completes. This paper aims to build a dynamic resilience evaluation method and explore the resilience evolution process for multi-mode public transit. For establishing the resilience evaluation method, we considered both structural and functional indicators of the network. Then, we built a nonlinear load-capacity model and a cascading failure model to reflect the dynamic feature of resilience. Next, attack scenarios were designed according to the actual characteristics of the multi-mode public transit. Using the passenger flow data from Xi'an, we tested the impact of station capacity on the dynamic resilience results and analyzed the resilience evolution process. The results indicate that the network's resilience performance was the worst when the subway station was destroyed. Through adjusting the capacity control parameters, we found the best station capacity control parameter is alpha = 0.5, beta = 0.4. Moreover, the sharply reducing intervals found in the results could help traffic managers improve transport efficiency while controlling costs.

Automated summary

This study aims to establish a dynamic resilience evaluation method and explore the resilience evolution process for multi-mode public transit. The research found that the network's resilience performance was the worst when the subway station was destroyed. By adjusting the capacity control parameters, transport efficiency can be improved.