Evaluation of Carrying Capacity Reliability for Regional Rail Transit System

Abstract

In contrast to previous studies that equated the network capacity of transportation systems with their carrying capacity, this study redefines the carrying capacity of regional rail transit systems as the maximum volume of passengers that can be transported within a specified timeframe. This novel definition accounts for the effective integration of sub-networks based on structural configurations and passenger flow dynamics, while ensuring that the service levels satisfy established travel demands. The study categorizes passenger flow into three distinct groups—unaffected, delayed, and lost—and examines the varying travel behaviors during service disruptions. It introduces a methodology to compute the carrying capacity, which includes the effective carrying capacity that reflects service quality and the residual carrying capacity that addresses the interaction between supply and demand. Additionally, this research proposes three indices to measure the reliability of carrying capacity: loss of carrying capacity, occupancy of residual carrying capacity, and redundancy of travel delays. These indices evaluate system performance with regard to satisfaction, safety, and delay. Employing the space vector method, these indices were integrated into a comprehensive evaluation framework and applied to the Chongqing regional rail transit system in China. The results show that during section failure, the reliability of the carrying capacity tends to improve as the volume of lost passenger flow increases during peak hours. Notably, the comprehensive evaluation score of carrying capacity reliability during the evening peak is nearly half of that during the morning peak, attributed to the more varied travel purposes in the evening. Moreover, the system exhibits higher reliability during off-peak hours because of significantly lower occupancy levels of residual carrying capacity under similar conditions of disruption. The evaluation of carrying capacity reliability for regional rail transit system can provide decision support in different time periods for the transportation resources allocation, operation cost, and service quality.