IEEJ Transactions on Electronics, Information and Systems
Online ISSN : 1348-8155
Print ISSN : 0385-4221
ISSN-L : 0385-4221
<Information Processing, Software>
Markov Decision Process-based Run Curve Optimization for Energy Saving and Ride Comfort
Sae KimuraKoki YoshimotoKenji UedaSatoru TakahashiDaniel Nikovski
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2014 Volume 134 Issue 10 Pages 1577-1583

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Abstract

This paper addresses train run curve optimization problem considering both energy saving and ride comfort. Based on our previous work, we present MDP-RCO, a method to solve minimum-energy run curves by Dynamic programming. The method achieves a fast computation by modeling the problem with a Markov decision process (MDP). Also, we propose two extended methods of MDP-RCO, which we call MDP-RCO-JERK and MDP-RCO-COUNT in order to reduce run mode fluctuation for ride comfort improvement. MDP-RCO-JERK uses an evaluation function defined by the weighted sum of time, energy consumption and jerk, and MDP-RCO-COUNT prohibits the state transition more than some times in a small section. We have confirmed that MDP-RCO would solve optimal run curves fast enough, and that MDP-RCO-COUNT would reduce the mode fluctuation almost without losing energy optimality.

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© 2014 by the Institute of Electrical Engineers of Japan
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