Macrolevel Classification Yard Capacity Modeling
Classification yards play a significant role in railroad freight transportation and are often considered bottlenecks for railroad networks. Based on a generic yard simulation model, the model in the presented study fits the Bureau of Public Roads function, which is widely used in highway capacity to represent the volume–dwell time relationship. The proposed analytical model incorporates major features of rail yards, such as the number and capacity of tracks in each area, the number of engines and humps, the humping speed, and the assemble rate. The model is validated by historical data from 16 classification yards of Class I railroads in the United States. The results show that the proposed model can generate precise capacity data of rail yard, as well as the dwell time of rail cars in yards. The dwell time increases sharply when the volume is greater than the capacity of a rail yard. The identified relationship may help a railroad analyze its network at the macro level and therefore improve the systemwide capacity and efficiency.
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Availability:
- Find a library where document is available. Order URL: http://worldcat.org/isbn/9780309442084
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Authors:
- Zhang, Licheng
- Jin, Mingzhou
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0000-0002-2387-8129
- Ye, Zhirui
- Li, Haodong
- Clarke, David B
- Wang, Yanyan
- Publication Date: 2017
Language
- English
Media Info
- Media Type: Digital/other
- Features: Figures; References; Tables;
- Pagination: pp 125–133
- Monograph Title: Railroads, Volume 2
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Serial:
- Transportation Research Record: Journal of the Transportation Research Board
- Issue Number: 2608
- Publisher: Transportation Research Board
- ISSN: 0361-1981
Subject/Index Terms
- TRT Terms: Classification yards; Dwell time; Freight traffic; Macroscopic traffic flow; Railroad traffic; Railroads; Simulation; Traffic volume; Validation; Yard operations
- Geographic Terms: United States
- Subject Areas: Freight Transportation; Operations and Traffic Management; Planning and Forecasting; Railroads; Terminals and Facilities;
Filing Info
- Accession Number: 01631422
- Record Type: Publication
- ISBN: 9780309442084
- Report/Paper Numbers: 17-04438
- Files: TRIS, TRB, ATRI
- Created Date: Mar 30 2017 2:27PM