Modeling Passenger Flow Distribution Based on Disaggregate Model for Urban Rail Transit

  • Da-lei Wang
  • En-jian Yao
  • Yang Yang
  • Yong-sheng Zhang
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 215)

Abstract

It is widely recognized that one of the most effective ways to solve urban traffic problems is developing public transport system, especially urban rail transit system. The estimation of passenger flow distribution, as an important part of travel demand analysis of urban rail transit, is the prerequisite of the operation organization and management of urban rail transit system, especially when a new line is put into operation. This paper proposes a new passenger flow distribution model, which is based on disaggregate model approach and conforms the aggregated historical passenger flow data to disaggregate data through representative individual method. Influencing factors including travel time, attracted traffic flow, land-use type, intensity around station, and so on are considered. Using the historical passenger flow data of urban railway system in Beijing before and after Line 4 is put into operation, the model is built and the estimation accuracy evaluated. The result shows that the disaggregate model is more accurate than the conventional aggregate single restraint gravitational model.

Keywords

Urban transit system Estimation of passenger flow distribution Disaggregate model Representative individual method 

Notes

Acknowledgments

This research is supported by the State Key Laboratory of Rail Traffic Control and Safety (Contract No. RCS2011ZT012), 973 Program (No. 2012CB725403) and National Key Technology R&D Program (No. 2011BAG01B01).

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Copyright information

© Springer-Verlag Berlin Heidelberg 2014

Authors and Affiliations

  • Da-lei Wang
    • 1
  • En-jian Yao
    • 1
    • 2
  • Yang Yang
    • 1
  • Yong-sheng Zhang
    • 1
  1. 1.School of Traffic and TransportationBeijing Jiaotong UniversityBeijingChina
  2. 2.State Key Laboratory of Rail Traffic Control and SafetyBeijing Jiaotong UniversityBeijingChina

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