Descripció del projecte
The SGR Research Group IMP – Information Modeling and Processing has addressed in recent years the research on key aspects of City Logistics systems, namely all those concerning topics related with real-time fleet dispatching, dynamic routing and others dealing with time dependencies in routing models. The the experience gained through the analysis of these systems lead the group to focus the research on the special cases of urban mobility and in particular to emerging phenomena like multiple passenger ridesharing which will likely reshape the future mobility. Preliminary results of this research can be found in “M. P. Linares, J. Barceló, C. Carmona and L. Montero (2016), Challenges of Dynamic Ride Sharing Demand Responsive Transportation Models,2016 International Symposium of Transport Simulation (ISTS’16 Conference), Transportation Research Procedia, available online at www.sciencedirect.com”. The research project that will be object of this thesis, will be based on these preliminary results and on the appraisal of the current evolution of mobility systems as a consequence of the combined effects of societal and technological changes.
Social and technological changes are prompting paradigm changes reshaping the future of mobility. A social shifting from car ownership to vehicle usage, combined with the evolution of the ICT applications, is making possible a seamless journey door-to-door, providing mobility feelings of freedom similar to those usually associated with the property of a private car, without the need of owning a car. Mobility as a Service (MaaS) is perhaps the main and more challenging response to this new situation as probe the growing trend of companies offering multiple variants of these services as car-sharing, car-pooling, ridesharing, or the alternatives of Demand Responsive transport Systems. MaaS involves components like advanced service selection and provision mechanisms usually supported fleet dispatching modules performing two main functions in real-time: identification of the most suitable vehicle to provide the requested service, in terms of quality of the service for the customer, and of profitability for the operator, depending on the traffic conditions in the road network, and the dynamic rerouting of vehicles to the most convenient routes
Dispatching and dynamically rerouting raise a rich variety of combinatorial optimization problems offering a fertile research domain but, further from the theoretical challenge, real life applications also pose another challenging problem: how efficiently evaluate and test the dispatching and routing policies for large metropolitan networks, fleet sizes and realistic demand. Therefore the research will have to develop, implement and test a quick and computationally cheap ad hoc simulation approach for testing and conducting approximate feasibility studies of MaaS operational proposals.
