The shortest path algorithm for urban rail transit based on spatio-temporal accessibility

Abstract

Rail transit systems are an important part of public transportation in large cities. However, unforeseen emergencies such as floods, equipment failures, or large events can cause serious consequences such as traffic congestion and stranded passengers, thus affecting the normal operation of rail transit. To cope with these emergencies, this paper proposes a new algorithm that can query the latest reachable time under time constraints. A rail network model is developed to optimize Dijkstra's algorithm in emergency situations by using a new data structure. The study emphasizes the temporal complexity and spatio-temporal accessibility of the algorithm. Finally, the model and algorithm are validated using data from the Beijing Metro. The proposed shortest path planning emergency strategy for rail transit and the application of the algorithm are mainly aimed at the command center level of rail transit and solved practical problems.