Chapter
Jan 13, 2020
Sixth International Conference on Transportation Engineering

Passenger Flow Assignment of Urban Rail Transit under Networking Conditions

Publication: ICTE 2019

ABSTRACT

Under the background of network operation of urban rail transit, the mode of "seamless transfer" has brought new challenges to the operation and management of urban rail transit while bringing convenience to passengers. Establishing a reasonable model to truly reflect the passenger flow assignment of the rail transit network, which is of great significance for solving the problem of balanced operation and ticket income distribution of existing network and predicting the impact on the current passenger flow with new metro lines accessing. The crowding effect of passenger travel, transfer times, and other influence factors are fully considered in this paper based on the characteristics of urban rail transit system. The definition method of feasible path is proposed, and the equilibrium assignment model of passenger flow based on feasible paths is established, which is solved by Frank-Wolfe algorithm. This model embodies the choice psychology of minimizing passenger travel impedance, and reflects the actual situation of route diversification. The effectiveness of the model and algorithm is verified by an example of the partial rail transit network in Beijing.

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ACKNOWLEDGEMENT

This research was supported by the National Natural Science Foundation (Project No.:U1734204), the People’s Republic of China.

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Published In

Go to ICTE 2019
ICTE 2019
Pages: 523 - 531
Editors: Xiaobo Liu, Ph.D., Southwest Jiaotong University, Qiyuan Peng, Ph.D., Southwest Jiaotong University, and Kelvin C. P. Wang, Ph.D., Oklahoma State University
ISBN (Online): 978-0-7844-8274-2

History

Published online: Jan 13, 2020

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Authors

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School of Traffic and Transportation, Beijing Jiaotong Univ., Beijing 100044, P.R. China. E-mail: [email protected]
Xingchen Zhang [email protected]
School of Traffic and Transportation, Beijing Jiaotong Univ., Beijing 100044, P.R. China (corresponding author). E-mail: [email protected]

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