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Vehicles are becoming connected entities. As a result, a likely scenario isthat such entities might be literally bombarded with information from amultitude of devices. In this context, a key challenging requirement for bothconnected and autonomous vehicles is that they will need to become cognitivebodies, able to parse information and use only the pieces of information thatare relevant to the vehicle in the context of a given journey. In order toaddress this fundamental requirement, a decision engine is presented in thispaper. The engine makes it possible for the vehicle to understand which piecesof information are really relevant, and subsequently to process only thosepieces of information. In order to illustrate the key features of our system,we show that it is possible to build upon the engine to develop a distributedtraffic management system, and then we validate such a system via bothconventional (numerical and SUMO-based) simulations and a Hardware-in-the-Loop(HIL) platform. Both the conventional simulations and the HIL validation showedthat the engine can be effectively used to design a distributed trafficmanagement system.

On the design of a decision engine for connected vehicles with an application to congestion management