Empirical Analysis of Traveling Backwards and Passenger Flows Reassignment on a Metro Network with Automatic Fare Collection (AFC) Data and Train Diagram-Reference-Cited by-同舟云学术

Empirical Analysis of Traveling Backwards and Passenger Flows Reassignment on a Metro Network with Automatic Fare Collection (AFC) Data and Train Diagram

Published:2018-07-24 Issue:8 Volume:2672 Page:230-242
ISSN:0361-1981
Container-title:Transportation Research Record: Journal of the Transportation Research Board
language:en
Short-container-title:Transportation Research Record

Author:

Xu Ruihua¹,Li Yanan¹,Zhu Wei¹,Li Sijie¹

Affiliation:

1. The Key Laboratory of Road and Traffic Engineering, Ministry of Education, Tongji University, Shanghai, P.R. China

Publisher

SAGE Publications

Subject

Mechanical Engineering,Civil and Structural Engineering

Link

http://journals.sagepub.com/doi/pdf/10.1177/0361198118781395

Reference23 articles.

1. Zhu W., Li Y. N., Zhou Y. L. Calibration and Evaluation of Rail Transit Assignment Models with Passenger Flow Investigation and Big Data Analysis. Tongji University and Beijing Metro Co., Ltd, China, 2017, pp. 28–30.

2. Modelling Transport

3. Passenger Choice Models for Analysis of Impacts of Real-Time Bus Information on Crowdedness

4. Crowding in public transport systems: Effects on users, operation and implications for the estimation of demand

5. Use of Mixed Stated and Revealed Preference Data for Crowding Valuation on Public Transport in Santiago, Chile

Cited by 6 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. A new approach on passenger flow assignment with multi-connected agents;Physica A: Statistical Mechanics and its Applications;2023-10

2. Robust Optimization of Train Timetables with Short-Length and Full-Length Services and Uncertain Passenger Volumes and Vehicle Choice Behavior;2023

3. A Deep Learning Model with Conv-LSTM Networks for Subway Passenger Congestion Delay Prediction;Journal of Advanced Transportation;2021-05-15

4. Estimating left behind patterns in congested metro systems: a Bayesian model;Smart and Resilient Transport;2021-05-10

5. A specific perspective: Subway driver behaviour recognition using CNN and time‐series diagram;IET Intelligent Transport Systems;2021-01-28