Proceedings of the 2018 International Conference on Mechanical, Electronic, Control and Automation Engineering (MECAE 2018)

Capacity Evaluation and Optimization of Heavy Haul Railway Station Based on the Simulation of Operation of Station

Authors
Mengqi Ma, Xingchen Zhang, Zhimei Wang
Corresponding Author
Mengqi Ma
Available Online March 2018.
DOI
https://doi.org/10.2991/mecae-18.2018.108How to use a DOI?
Keywords
Rely on the fixed and flexible application principles of track.
Abstract
Heavy haul railway mainly transport bulk cargo such as coal and steel. Its characteristics includes large volume of freight, complicated operation of station, obvious heavy cargo direction etc. The bulk cargo's timeliness standard is low, the occupied time between different operations of station is distinct different. Therefore, the heavy haul railway train has great optimization space in the transportation organization of the station. The purpose of this paper is to strengthen the capacity of heavy haul railway stations. Based on the analysis of operations of the heavy load railway station, the simulation system is established. Rely on the fixed and flexible application principles of track, the shortest path selection method of route and the train insertion method to strengthen the train station capacity. The simulation is carried out with CiYaowan station in Baoshen Railway as an example, the feasibility of the method and simulation system is verified.
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Proceedings
2018 International Conference on Mechanical, Electronic, Control and Automation Engineering (MECAE 2018)
Publication Date
March 2018
ISBN
978-94-6252-493-4
DOI
https://doi.org/10.2991/mecae-18.2018.108How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

TY  - CONF
AU  - Mengqi Ma
AU  - Xingchen Zhang
AU  - Zhimei Wang
PY  - 2018/03
DA  - 2018/03
TI  - Capacity Evaluation and Optimization of Heavy Haul Railway Station Based on the Simulation of Operation of Station
BT  - 2018 International Conference on Mechanical, Electronic, Control and Automation Engineering (MECAE 2018)
PB  - Atlantis Press
UR  - https://doi.org/10.2991/mecae-18.2018.108
DO  - https://doi.org/10.2991/mecae-18.2018.108
ID  - Ma2018/03
ER  -