Abstract

International audience; In the latest few years, lot of efforts have been done to pave the way to sustainable mobility, in order to solve pollution problems and fuel shortage. The use of electric vehicles (EV) is considered as one of the best ecologic and economic solution. However, autonomy barriers and limitations slow the progress and the deployment of this technology. In this paper, we propose an advanced electric vehicles' fleet management architecture. This architecture considers the most important factors that can affect the traveling mode of electric vehicles, in order to offer different services to fleet management companies for an efficient monitoring and management of their fleets. One of the most important service, considered in this paper, consists on providing economic itineraries planning for electric vehicles. Best routes, in term of electric power consumption, are computed based on the collected information about road topology (elevation variations, source, destination, etc.), weather conditions, vehicle characteristics, driver profile, traffic conditions and electric charging stations positions. In case of battery drop, new routes passing through the nearest available charging stations are recalculated and provided to the driver. To prove the concept, we implemented a lightweight traffic management server that provides this itinerary planning service to an EV fleet company. The server provides a web application to book an EV and plan the trip. All possible itineraries are displayed on a map with electric power consumption, traveled distance and duration details. Then, the server uploads the chosen itinerary into the vehicle's GPS or into the driver's smartphone.

Abstract

Effective itinerary planning attracts more and more attention of both researchers and practitioners with a view to reduce costs, ensure quality of service as well as to meet the ever-growing needs of the population for public transport services enabling selection of specific travel modes while avoiding the negative impacts of traffic congestion. In this context the objective of this paper is to develop and test a generic fractal-like model of multimodal transport networks. Its purpose is to identify potentials and limitations of using the fractal organization perspective in compiling multimodal transport networks and public transport services in the course of selecting multi-modal routes that have the shortest paths through the network. Results of computational experiments assessing the scalability of the proposed method are presented as well.