An Enhanced Dynamic User Optimal Passenger Flow Assignment Model for Metro Networks

Abstract

By considering the difference between a car driver's route choice behavior on the road and a passenger's route choice behavior in urban rail transit (URT), this paper proposes an enhanced Dynamic User Optimal (DUO) passenger flow assignment model for metro networks. To capture realistic URT phenomena, the model has integrated the train operation disturbance constraint. Real passenger and train data are used to verify the proposed model and algorithm. The results indicate that the DUO-based model is more suitable for describing passenger route choice behavior under uncertain conditions compared to a static model. Moreover, this paper found that passengers under oversaturated conditions are more sensitive to train operation disturbances compared to undersaturated passengers.

A Method for Safety Evaluation and Enhancement of Urban Rail Transit Network Based on Passenger Flow Assignment

“…Most researches on passenger flow assignment emphasize passenger routing behavior analysis. Pan [4] presented an enhanced model for metro networks to dynamically assign passenger flow, which depicted passengers' route choice behavior. Sun [5] made use of Bayesian inference framework to model network cost and passenger route choice.…”