Research on Emergency Bus Scheduling Under Urban Rail Transit Service Interruptions

To address the limitations of conventional emergency scheduling models characterized by singular modes and low evacuation efficiency, this study proposes the concept of collaborative bridging. Firstly, an emergency bus scheduling model was formulated with dual objectives of minimizing total operation time and average passenger delay, incorporating constraints on transportation capacity and passenger evacuation demands. Secondly, the ideal point method was employed to integrate the multi-objective functions, followed by an improved artificial bee colony (IABC) algorithm for model resolution. A case study of sudden service interruption on Jinan Metro Line 1 validated the proposed methodology. Results demonstrate that compared with traditional emergency bridging strategies under identical vehicle deployment conditions, the improved scheduling model reduces total operation time by 291 min and decreases average passenger delay by 3.3 min. Furthermore, the IABC algorithm achieves a 32.24% improvement in computational efficiency and reduces the total objective function value by 0.23 compared to the conventional ABC algorithm. The proposed approach significantly enhances the utilization efficiency of emergency buses for rapid passenger evacuation, effectively mitigates impacts of rail transit service interruptions, fulfills urgent travel demands, and ensures orderly public transportation operations during emergencies.