A fuel economic model predictive control strategy for a group of connected vehicles in urban roads

The advancements in communication, sensing, and computing has enabled the development of connected vehicle systems where improved decision and control strategies are enabled with the aid of information exchange within the vehicular system. In this paper, we consider a connected vehicle system and develop fuel economic control strategies for a group of vehicles in congested urban road conditions. We exploit the Signal Phase and Timing (SPAT) information from the traffic lights and utilize model predictive control with a modified cost to reduce stopping at red lights and improve the fuel economy for a group of vehicles. The simulation results indicate the improvement in group performance for our proposed method.