Passenger-Flow-Status Assessment Method of Urban Rail Network Based on GA-WNN

Abstract

Along with the rapid development of urban transportation in recent years, the urban rail network has gradually formed. In the context of networked operations, mass passenger flow brings challenges to security management. This paper presents a passenger flow index system for urban rail network to assess passenger-flow-status, from three aspects of the passenger flow in urban rail network, including the capacity, the connection state and the transferability. Based on the index system, wavelet neural network with the genetic algorithm (GA-WNN) is used to form the assessment method of passenger-flow-status in urban rail network. The advantages of the assessment method are verified by a case study.