Optimizing road intersection traffic flow using stochastic and heuristic algorithms

Vehicular Ad-hoc Network, VANET, offers new opportunities for better road traffic management. Using vehicle to vehicle (V2V) and vehicle to infrastructure (V2I) communications, several research works were published on road traffic improvement in general and at road intersection in particular. One of the challenging problems is to minimize vehicles' waiting time at the intersection as well optimize traffic flow by adjusting the traffic signals timing. In this area, several methods have been proposed in the literature which can be classified as adaptive, heuristic, pre-timed and others. In these methods traffic density and statistical data are generally used to determine the traffic signals timing. However, these methods either don't offer an optimal solution or are not cost effective in terms of computational time. In this paper, we propose the use of Simultaneous Perturbation Stochastic Algorithm (SPSA) to compute in real time the best traffic signals timing that minimizes the vehicles' travel time at the road intersection. A specific intersection in the city of Moncton with real traffic data was studied. Simulation results show a substantial improvement in term of vehicles' travel time in comparison with the pre-timed setting currently used by the city of Moncton. We also propose a heuristic algorithm which performs well too.