Subway-Emergency Bridging Strategy for Bus Scheduling Considering Passenger Travel Behavior

Abstract

Subway disruptions change the travel modes of stranded passengers, which mode they choose to continue traveling intuitively reflects passenger demand and influences the bridging strategy. Previous studies used statistical methods and passenger simulation models to capture passenger travel behaviors. However, very few studies explored the passengers’ behavioral decision-making mechanism and revealed the influence factors conclusively. To this end, we used the cumulative prospect theory and random utility theory to develop a passenger travel behavior decision-making model, which determines the affected passenger flow Origin-Destination (OD) under disruption and designs an emergency bus bridging (EBB) strategy considering passenger demands. A simulated annealing-improved genetic algorithm was further used to enhance the solution efficiency of the EBB strategy. Finally, a case study was conducted for Fuzhou Metro Line 1 in China, which includes a sensitivity analysis of the number of emergency buses and passenger flow OD. The results show that, compared with the baseline strategy, the EBB strategy reduces passenger costs which improves passenger evacuation efficiency.

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