Providing dynamic route advice for urban goods vehicles: the learning process enhanced by the emerging technologies

This paper investigates the contribution of emerging technologies (i.e., internet of things and big data) for providing route advice to goods vehicles driving within cities. More precisely, the implementation and application issues related to the introduction of opportunities offered by emerging technologies in gathering real-time data, in obtaining knowledge and support for providing route suggestions will be pointed out. The main results concern the formalization of the trade-off that it is necessary to activate between the different emerging technologies (starting from internet of things and big data) to improve the learning process of path utility. This process is formalized within the general theory of dynamic transport systems. Thus, the possibility of using multiple technologies in an integrated way is pointed out, identifying the road ahead for researchers and technicians both for specializing the general technologies related to the transport systems, and for improving the current systems that provide the user with real-time and personalized information on the route.