Abstract
Purpose: Urban rail transit is a complex and dynamic system, which is difficult to be described in a global mathematical model for its scale and interaction. In order to analyze the spatial and temporal characteristics of passenger flow distribution and evaluate the effectiveness of transportation strategies, a new and comprehensive method depicted such dynamic system should be given. This study therefore aims at using simulation approach to solve this problem for subway network. Design/methodology/approach: In this thesis a simulation model based on multi-agent approach has been proposed, which is a well suited method to design complex systems. The model includes the specificities of passengers’ travelling behaviors and takes into account of interactions between travelers and trains. Findings: Research limitations/implications: We developed an urban rail transit simulation tool for verification of the validity and accuracy of this model, using real passenger flow data of Beijing subway network to take a case study, results show that our simulation tool can be used to analyze the characteristic of passenger flow distribution and evaluate operation strategies well. Practical implications: The main implications of this work are to provide decision support for traffic management, making train operation plan and dispatching measures in emergency. Originality/value: A new and comprehensive method to analyze and evaluate subway network is presented, accuracy and computational efficiency of the model has been confirmed and meet with the actual needs for large-scale network.
Highlights
Urban rail transit has played a key role to people mobility
As the foundation and core for transportation operations, spatial and temporal characteristics of passenger flow distribution are significant for making operation plans, collaborative organizations, and adjustment in emergency and improvement of network bottlenecks
Based on schedules and under train capacity constraints, Agostino, Umberto and Luca (2012) present a schedulebased dynamic assignment model for transit networks, which takes into account congestion through explicit vehicle capacity constraints
Summary
Urban rail transit has played a key role to people mobility. With expansion of network, it is more important for providing a convenient, secure and economical transport by collaborative organization. As the foundation and core for transportation operations, spatial and temporal characteristics of passenger flow distribution are significant for making operation plans, collaborative organizations, and adjustment in emergency and improvement of network bottlenecks It is very difficult or even impossible to adopt a global mathematical model to make new transportation solutions for such system due to its scale and complexity. Poon, Wong and Tong (2004) adopts a model for crowded network based on timetable, use simulation method for solving the problem As these static transit assignment models could not reveal the bottleneck induced congestion problem and are not able to properly evaluate the transit network under dramatically changing network conditions (e.g. passenger arrival rate and loading of transit services) during the period of analysis (Schmoecker, Bell & Kurauchi, 2008). They are commonly adopted for the strategic and long-term planning and evaluation
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