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Open AccessArticle

A Time-Space Network Model Based on a Train Diagram for Predicting and Controlling the Traffic Congestion in a Station Caused by an Emergency

by 1 and 2,*
1
Key Laboratory of Transport Industry of Big Data Application Technologies for Comprehensive Transport, Ministry of Transport, Beijing Jiaotong University, Beijing 100044, China
2
School of Transportation, Beijing Jiaotong University, Beijing 100044, China
*
Author to whom correspondence should be addressed.
Symmetry 2019, 11(6), 780; https://doi.org/10.3390/sym11060780
Received: 23 May 2019 / Revised: 6 June 2019 / Accepted: 10 June 2019 / Published: 12 June 2019
(This article belongs to the Special Issue Symmetry in Engineering Sciences)
Timely predicting and controlling the traffic congestion in a station caused by an emergency is an important task in railway emergency management. However, traffic forecasting in an emergency is subject to a dynamic service network, with uncertainty surrounding elements such as the capacity of the transport network, schedules, and plans. Accurate traffic forecasting is difficult. This paper proposes a practical time-space network model based on a train diagram for predicting and controlling the traffic congestion in a station caused by an emergency. Based on the train diagram, we constructed a symmetric time-space network for the first time by considering the transition of the railcar state. On this basis, an improved A* algorithm based on the railcar flow route was proposed to generate feasible path sets and a dynamic railcar flow distribution model was built to simulate the railcar flow distribution process in an emergency. In our numerical studies, these output results of our proposed model can be used to control traffic congestion. View Full-Text
Keywords: railway transportation; time-space network; A* algorithm; traffic congestion; traffic forecasting; traffic control; railcar flow distribution railway transportation; time-space network; A* algorithm; traffic congestion; traffic forecasting; traffic control; railcar flow distribution
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MDPI and ACS Style

Qu, Z.; He, S. A Time-Space Network Model Based on a Train Diagram for Predicting and Controlling the Traffic Congestion in a Station Caused by an Emergency. Symmetry 2019, 11, 780. https://doi.org/10.3390/sym11060780

AMA Style

Qu Z, He S. A Time-Space Network Model Based on a Train Diagram for Predicting and Controlling the Traffic Congestion in a Station Caused by an Emergency. Symmetry. 2019; 11(6):780. https://doi.org/10.3390/sym11060780

Chicago/Turabian Style

Qu, Zihan; He, Shiwei. 2019. "A Time-Space Network Model Based on a Train Diagram for Predicting and Controlling the Traffic Congestion in a Station Caused by an Emergency" Symmetry 11, no. 6: 780. https://doi.org/10.3390/sym11060780

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