The VIPAFLEET project consists in developing models and algorithms for managing the fleet of Individual Public Autonomous Vehicles (VIPA). Hereby, we consider a fleet of cars distributed at specified stations in an industrial area to supply internal transportation, where the cars can be used in different modes of circulation (tram mode, elevator mode, taxi mode). One goal is to develop and implement suitable algorithms for each mode in order to satisfy all the requests and to reduce the waiting time of a customer. The innovative idea and challenge of the project is to develop and install a dynamic fleet management system that allows the operator to switch between the different modes within the different periods of the day according to the dynamic transportation demands of the users. For that, we currently study the best case and worst case behavior of several online algorithms. So far, we carefully modeled the underlying online transportation system and implemented an according fleet management framework, to handle modes, demands and commands as well as to integrate different online algorithms.
Mots clés : Online transportation problem, fleet management, autonomous vehicles