Details

Autor(en) / Beteiligte

• Seong Ho Han
• Yun Sub Byen
• Jong Hyen Baek
• Tae Ki An
• Su Gil Lee
• Hyun Jun Park

Titel

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

Ist Teil von

• Proceedings of IEEE. IEEE Region 10 Conference. TENCON 99. 'Multimedia Technology for Asia-Pacific Information Infrastructure' (Cat. No.99CH37030), 1999, Vol.1, p.360-362 vol.1

Ort / Verlag

IEEE

Erscheinungsjahr

1999

Quelle

IEEE Electronic Library (IEL)

Beschreibungen/Notizen

• 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.