A Genetic Algorithm Based Train Speed
Regulation Optimization
Author(s)
C. Rongwu, Y. Tao & B. R. Bisrat
Abstract
The intelligent train speed regulation algorithm plays a very important role in the
automatic train control system. A genetic algorithm based time precision train
speed regulation for the energy consumption optimization algorithm of a
Communication Based Train Control System (CBTC) is studied in this paper.
Compared to traditional performance level commands, which were generated by
the Automatic Train Supervision (ATS) subsystem, the enhanced genetic
algorithm based train speed regulation algorithm can be used to save energy
consumption and improve passenger travel comfort at each defined inter-section
of travel time. In this algorithm, each travel time target speed will be reflected by
its particular speed profile, which has been optimized by the genetic algorithm
with the object of energy saving. In the CBTC system, with the adoption of the
bandwidth network of the train-wayside communication, this optimization
process can be carried out offline or online in the ATS subsystem and transmit to
the onboard Automatic Train Operation (ATO) subsystem to guide train
operation control.
Keywords: genetic algorithm, time precision, energy saving, CBTC, train speed
regulation, performance level.
Keywords
genetic algorithm, time precision, energy saving, CBTC, train speed
regulation, performance level.
Related Book
Other papers in this volume
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