Dwell-time and run-time control for DC mass rapid transit railways
Data(s) |
2007
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Resumo |
Dwell times at stations and inter-station run times are the two major operational parameters to maintain train schedule in railway service. Current practices on dwell-time and run-time control are that they are only optimal with respect to certain nominal traffic conditions, but not necessarily the current service demand. The advantages of dwell-time and run-time control on trains are therefore not fully considered. The application of a dynamic programming approach, with the aid of an event-based model, to devise an optimal set of dwell times and run times for trains under given operational constraints over a regional level is presented. Since train operation is interactive and of multi-attributes, dwell-time and run-time coordination among trains is a multi-dimensional problem. The computational demand on devising trains' instructions, a prime concern in real-time applications, is excessively high. To properly reduce the computational demand in the provision of appropriate dwell times and run times for trains, a DC railway line is divided into a number of regions and each region is controlled by a dwell- time and run-time controller. The performance and feasibility of the controller in formulating the dwell-time and run-time solutions for real-time applications are demonstrated through simulations. |
Formato |
application/pdf |
Identificador | |
Publicador |
The Institution of Engineering and Technology |
Relação |
http://eprints.qut.edu.au/37950/5/37950.pdf DOI:10.1049/iet-epa:20060132 Wong, K. K. & Ho, T. K. (2007) Dwell-time and run-time control for DC mass rapid transit railways. IET Electric Power Applications, 1(6), pp. 956-966. |
Direitos |
Copyright 2007 The Institution of Engineering and Technology |
Fonte |
Faculty of Built Environment and Engineering; School of Engineering Systems |
Palavras-Chave | #010206 Operations Research #090507 Transport Engineering #Rapid Transit Railways #Train Control #Dynamic Programming #Event-based Model |
Tipo |
Journal Article |