Development of a V2X Platform for Predictive Driving Functions Validation

Automotive technologies are advancing significantly in the last years enhancing vehicle automation more and more. On the other side new communications technologies are going to change the way humans and machines interact each other. Vehicles will be soon autonomous and will be able to cooperate and communicate each other. This can be achieved gradually by enabling step by step a certain level of intelligence onto the vehicle which would bring to satisfy the needs of the society of today and of the next future, such as the reduction of pollutant emissions and enhancement of traffic efficiency. This thesis work aim at developing a prototype vehicle that can be connected to the external world. This allows to retrieve the right information to predict the driver behaviour and the external situation to that the use of the powertrain can be optimized automatically in order to reduce the production of pollutant emission. The project has been developed in several steps starting from the project requirements analysis. Soon after the requirements have been established, software and hardware component have been used to build a platform capable to communicate and to establish multiple connections. This platform has been developed for electrified vehicles. The development of the project has been executed at FEV Italia s.r.l, which is an internationally recognized leader in design and development of advanced gasoline, diesel and hybrid powertrains and vehicle systems. The work has been performed in the Green Mobility Research Laboratory born by the collaboration between FEV Italia s.r.l and the university of Bologna.