A Framework to Support Experts in the Study of Energy Efficiency in Urban Trains

Abstract

In the context of Smart Cities, there are concerns regarding Urban Mobility, which consists of identifying alternatives for the reduction of traffic of individual vehicles, better occupation of urban space, among other aspects. An alternative is the adoption of electric trains. However, a problem concerning energy consumption arises. Thus, this work aims to propose a framework based on Genetic Algorithms (GAs), called SmartSubway, to assist specialists with insertion of domain information in the problem of energy efficiency in electric trains in order to identify energy efficient driving profiles. As proof of concept, a system inspired in GAs was implemented. To validate the system, the domain information of a real scenario was inserted, where it was possible to carry out six experiments and identify the ones that obtained the best results.