Algorithm and Application of Multi-modal Evacuation Strategy for Intercity Railway Disruption in a Metropolitan Area

Abstract

When an emergency situation befalls the intercity high-speed railway system, response contingency always focuses on mitigating the interruption to the original operation. This study addresses an evacuation problem for stranded passengers by coordination of multi-modal transit, with the immediate recovery of transport corridors and the redesign of transit routes. A multi-modal transit-based evacuation strategy is proposed through a bi-level optimization model. The model simultaneously formulates the selection of lines, vehicle scheduling, and passenger assignment that trades off passenger delay versus operating cost. The upper level uses an integer program to determine the transit lines and fleet size, and the lower level assigns passengers onto multi-modal routes considering their perceptions of transfer and vehicle congestion. A hybrid heuristic algorithm is proposed to solve the complexity from back-up conditions and nonlinear on-route utility. The case study is based on a disruption to the Beijing-Hebei metropolitan transit system, which is composed of five transit modes, to analyze the conflicting objectives under different mode combinations and network topologies. The adaptation for demand distribution with regard to trip distance is studied to recommend the vehicle composition in a realistic situation. The application and analysis procedure aim to enhance the decision-support system. Results show that mode combinations could provide time and cost saving solutions and extend the Pareto frontier. Effectiveness of mode combination is not equivalent to different demand distributions. Multi-modal collaboration would effectively accelerate the evacuation and save costs. These findings may be of interest to decision makers developing efficient response strategies to improve post-disruption resilience.