Abstract
This paper presents an approach for generate train driving plans using continuous Case-Based Planning (CBP). Each plan P is formed by a set of actions elaborated without human intervention which, when applied, can move a train in a stretch of railroad. The actions are planned due the reuse and sharing of past experiences, a complex due to the variations in the (i) weight, number of locomotives and railroad cars of the train, (ii) profiles of stretches travelled and (iii) environmental conditions. To overcome these difficulties, a driver a support system is provided to help in the conduction. Here, we distributed the main steps of the CBP among specialized agents with different roles: Planner, Executor and Case-Manager. Our approach was evaluated by different metrics: (i) accuracy of the case recovery task, (ii) efficiency of task adaptation and application of such cases in realistic scenarios and (iii) fuel consumption. We show that the inclusion of new experiences reduces the efforts of both the Planner and the Executor and the fuel consumption and allow the reuse of the obtained experiences in similar scenarios with low effort.
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Our thanks to Brazilian Federal Agency for the Support and Evaluation of Graduate Education (CAPES) and Brazilian Innovation Agency (FINEP) to support this research.
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Borges, A.P., Dordal, O.B., Ribeiro, R., Ávila, B.C., Scalabrin, E.E. (2015). Generation of Economical Driving Plans Using Continuous Case-Based Planning. In: Hammoudi, S., Maciaszek, L., Teniente, E., Camp, O., Cordeiro, J. (eds) Enterprise Information Systems. ICEIS 2015. Lecture Notes in Business Information Processing, vol 241. Springer, Cham. https://doi.org/10.1007/978-3-319-29133-8_10
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DOI: https://doi.org/10.1007/978-3-319-29133-8_10
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