The global optimization of signal settings and traffic assignment combined problem: a comparison between algorithms

The increasing vehicular traffic on urban road in network demands effective measure of traffic control on road network, especially at the intersection, where turning movement of vehicle and mixed traffic creates congestion. In congested parts of the cities, traffic control at road intersection is the most efficient method. The Traffic Signal Synchronization is a traffic engineering technique of matching the green light times for a series of intersections to enable the maximum number of vehicles to pass through, thereby reducing stops and delays experienced by motorists. The principal objective of Traffic Signal Synchronization at intersection is to clear maximum number of vehicles through the intersection in a given length and time with least number of accidents, at maximum safe speed and with minimum delay. Synchronizing traffic signals ensures a better flow of traffic and minimizes gas consumption and pollutant emissions. In this paper, we apply different approaches to minimize the total travel time on the network. The Surrogate Method (SM), the Projected Gradient Algorithm (PGA), the Particle Swarm Optimization (PSO) and the Genetic Algorithm (GA) are developed for the Global Optimization of Signal Settings and Traffic Assignment combined problem. Numerical experiments on real test network are reported.