Algorithmes d’éco conduite coopérative de véhicules électriques légers et leur validation expérimentale à échelle réduite « Downscaling ».

The intelligent vehicle is already a reality, but it is necessary to know what will be its evolution in the following years. In addition, its global deployment not only passes through the vehicle itself but also extends to the infrastructure, so the public and private sectors should plan for the arrival of autonomous and cooperative vehicles, in their most developed state in a time horizon not excessively far away. In this connected mobility, the deliberate exchange of intentions between vehicles and infrastructure reduces the need to "guess" about surrounding traffic and allows for better coordination. Vehicles can thus cooperate rather than compete in urban and highway areas, contributing harmoniously to improved mobility and overall efficiency. This co-operation is about exchanging information and co-ordinating movements for a "common" goal. Even with the best intentions of human drivers, cooperation between conventional vehicles remains rather problematic due to missing information and the difficulty of coordinating while driving. It is clear, therefore, that the key roles in this program are played by efficient connectivity, by centralized or distributed algorithms capable of calculating the best movement instructions for all coordinated vehicles, and by delegated or autonomous driving vehicles that are programmed to follow these instructions. As for the common objective to be achieved, in addition to traffic fluidity and road safety, an important role must be assigned to energy efficiency and environmental quality. This requires that the energy consumption and pollutant emission characteristics of the cooperating vehicles be taken into account by the centralized control algorithms, and that the said algorithms be capable of calculating the optimal laws of motion with respect to these criteria, all within the constraints imposed by the real-time nature of this control. This is known as cooperative eco-driving. Automated eco-driving of a single vehicle has already shown convincing results in the past, both in terms of reducing CO2 emissions and pollutant emissions, not to mention the benefits for safety and driving comfort. Cooperative eco-driving of vehicles has been studied mainly for specific scenarios such as platooning, lane changing and intersection crossing. Proofs of concept mainly through simulation have shown interesting potential gains. While further research is needed to refine and improve these algorithms, The main research question addressed in this thesis is the validation of these concepts on a reduced scale “Downscaling” and to what extent the potential energy gains can be translated into reality.