An Energy-Driven Road-to-Driver Assistance System for Intersections

Several municipalities are investigating smart road infrastructures to help reducing pollution and traffic congestion. In this paper, a road to vehicle assistance system is presented. The system continuously suggests the optimal velocity the driver should adopt in order to minimize fuel consumption in a long urban road with frequent intersection controlled by traffic lights. Fuel saving is enabled by the apriori knowledge of the signal timing and phasing. The advantage of the algorithm is that it is minimally invasive as it does not require complex communication protocols. The method is based on an offline velocity profile optimization. In the paper, the optimization algorithm is detailed and the potential for fuel saving evaluated in simulation. The method is entirely focused on fuel efficiency. It is shown that average fuel savings up to 55% are to be expected with an average reduction of the traveling time of 28%.