A Time-Space Network Model Based on a Train Diagram for Predicting and Controlling the Traffic Congestion in a Station Caused by an Emergency
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 t...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2019-06-01
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| Series: | Symmetry |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2073-8994/11/6/780 |
| _version_ | 1811305422264467456 |
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| author | Zihan Qu Shiwei He |
| author_facet | Zihan Qu Shiwei He |
| author_sort | Zihan Qu |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-04-13T08:26:00Z |
| format | Article |
| id | doaj.art-ee2626da58c9457c9b2aece9dc30af8a |
| institution | Directory Open Access Journal |
| issn | 2073-8994 |
| language | English |
| last_indexed | 2024-04-13T08:26:00Z |
| publishDate | 2019-06-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Symmetry |
| spelling | doaj.art-ee2626da58c9457c9b2aece9dc30af8a2022-12-22T02:54:30ZengMDPI AGSymmetry2073-89942019-06-0111678010.3390/sym11060780sym11060780A Time-Space Network Model Based on a Train Diagram for Predicting and Controlling the Traffic Congestion in a Station Caused by an EmergencyZihan Qu0Shiwei He1Key Laboratory of Transport Industry of Big Data Application Technologies for Comprehensive Transport, Ministry of Transport, Beijing Jiaotong University, Beijing 100044, ChinaSchool of Transportation, Beijing Jiaotong University, Beijing 100044, ChinaTimely 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.https://www.mdpi.com/2073-8994/11/6/780railway transportationtime-space networkA* algorithmtraffic congestiontraffic forecastingtraffic controlrailcar flow distribution |
| spellingShingle | Zihan Qu Shiwei He 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 railway transportation time-space network A* algorithm traffic congestion traffic forecasting traffic control railcar flow distribution |
| title | A Time-Space Network Model Based on a Train Diagram for Predicting and Controlling the Traffic Congestion in a Station Caused by an Emergency |
| title_full | A Time-Space Network Model Based on a Train Diagram for Predicting and Controlling the Traffic Congestion in a Station Caused by an Emergency |
| title_fullStr | A Time-Space Network Model Based on a Train Diagram for Predicting and Controlling the Traffic Congestion in a Station Caused by an Emergency |
| title_full_unstemmed | A Time-Space Network Model Based on a Train Diagram for Predicting and Controlling the Traffic Congestion in a Station Caused by an Emergency |
| title_short | A Time-Space Network Model Based on a Train Diagram for Predicting and Controlling the Traffic Congestion in a Station Caused by an Emergency |
| title_sort | time space network model based on a train diagram for predicting and controlling the traffic congestion in a station caused by an emergency |
| topic | railway transportation time-space network A* algorithm traffic congestion traffic forecasting traffic control railcar flow distribution |
| url | https://www.mdpi.com/2073-8994/11/6/780 |
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