NDLI: An optimal automatic train operation (ATO) control using genetic algorithms (GA)

Content Provider	IEEE Xplore Digital Library
Author	Seong Ho Han Yun Sub Byen Jong Hyen Baek Tae Ki An Su Gil Lee Hyun Jun Park
Copyright Year	1999
Description	Author affiliation: Korea Railway Res. Inst., South Korea (Seong Ho Han)
Abstract	This paper shows the form of the optimal solution and how to minimize energy of the train driving control that can be included into automatic train operation (ATO) systems. We consider the case where a train is to be driven by automatic operation mode along a nonconstant gradient curve and with speed limits. Using the genetic algorithms (GA), we constructed an optimal train driving strategy. The results are compared with P. Howlett's optimization method using the constrained optimal technique (Lagrange function and Kuhn-Tucker equations) in view of energy cost benefit. For the case studies, we used a railway track of Seoul City MRT system. As a result of the test, we verified that the proposed algorithm could be of effective energy cost benefit.
Starting Page	360
Ending Page	362
File Size	253380
Page Count	3
File Format	PDF
ISBN	0780357396
DOI	10.1109/TENCON.1999.818425
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	1999-09-15
Publisher Place	South Korea
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Optimal control Automatic control Control systems Genetic algorithms Optimization methods Equations Cost function Rail transportation Cities and towns Testing
Content Type	Text
Resource Type	Article

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