Accident-Oriented Delay Propagation in High-Speed Railway Network

Abstract

This paper presents an approach to estimate the delay propagation in a high-speed railway (HSR) network under accident conditions. Considering the complexity and dynamics of HSR accidents, different levels of delay are discussed using clustering analysis, and the delay propagation is analyzed both forward and backward using different mathematical formulations. The forward delay propagation is described by a fitting distribution between arrival delay and forward resistance of accidents at different levels. The backward-delay-propagating mechanism is exploited by a combined model of horizontal propagation and vertical propagation under corresponding constraints of minimum headway and emergency measures. To integrate the forward- and the backward-propagating models, a global algorithmic framework is then designed with special consideration of routes separation. Finally, an applied case analysis of regional rail network in the Yangtze River Delta verifies the feasibility of the delay propagation algorithm. Through a validation test to accidents with detailed records, results suggest that the proposed algorithm can conservatively estimate the delay distribution with an accuracy greater than 75%.