A methodology based on floating car data for the analysis of the potential rail-road freight demand

A fundamental task in freight transportation planning is to estimate and forecast freight vehicle demand between origin-destination (O-D) pairs, including the prediction of the use of different transport modes and services. Therefore, the purpose of this paper is to investigate road freight transport through floating car data (FCD) to identify the potential demand that can be shifted from road to rail-road intermodal transport. The developed methodology is parametric, and thus it can be easily transferred in other regional contexts, taking the compatibility of the network infrastructures with respect to road transport structure into due consideration. In fact, given that the possibility to move road demand to rail-road intermodal one is mainly conditioned to length of the whole journey and, for effective service to implement, to the magnitude of the shifted flows, the core of the proposed methodology consists in inferring truck/lorry O-D flows by FCD. A real test case application shows the goodness of the proposed approach. The case study focuses on the freight village of Padua (northern Italy), for which 60 working-day observations within six months (January - June 2018) were available. The out-of-sample validation study shows a close reproduction of observed traffic counts in some important sections along regional freeways and motorways, and the potential O-D relationships that could be interested by shifting were identified.