Journal of South China University of Technology (Natural Science Edition) ›› 2015, Vol. 43 ›› Issue (8): 126-134,143.doi: 10.3969/j.issn.1000-565X.2015.08.019

• Traffic & Transportation Engineering • Previous Articles     Next Articles

Passenger Flow Assignment Model of Subway Networks Under Train Capacity Constraint#br#

Zhou Wei-teng Han Bao-ming1,2   

  1. 1. School of Traffic and Transportation,Beijing Jiaotong University,Beijing 100044,China; 2. State Key Laboratory of Rail Traffic Control and Safety,Beijing Jiaotong University,Beijing 100044,China
  • Received:2015-01-06 Revised:2015-03-17 Online:2015-08-25 Published:2015-07-01
  • Contact: 韩宝明(1963-),男,教授,博士生导师,主要从事运输组织现代化研究. E-mail: bmhan@bjtu.edu.cn
  • About author:周玮腾(1988-),男,博士,主要从事城市轨道交通运输规划与管理研究. E-mail: zwt_bjtu@126.com
  • Supported by:
     Supported by the Beijing Municipal Natural Science Foundation(9132015)

Abstract: The passenger flow assignment of subway networks plays an important role in the operation and management of urban rail transit networks. As the influence of the train capacity constraint on the passenger flow assignment in a schedule-based network is seldom taken into account in relevant literature,this paper constructs a dynamic assignment model of passenger flows under the condition of the stochastic user equilibrium,and designs a solution algorithm by establishing a schedule-expanded network and by designing corresponding k-shortest path search algorithm. Moreover,the congestion and overload delay under the train capacity constraint are also taken into account. Then,the proposed model is verified by a numerical example in Beijing subway networks,and the parameter sensitivity is analyzed. The results show that the proposed model is of a rapid convergence and a higher degree of accuracy with a relative error of 9. 5% ~11. 2%,which can meet the requirements of analyzing and estimating the passenger flow distribution in a large-scalesubway network.

Key words: subways, passenger flow assignment, schedule, traincapacity, overload delay

CLC Number: