Traffic light optimization for Bus Rapid Transit using a parallel evolutionary algorithm: The case of Garzon Avenue in Montevideo, Uruguay

Abstract

This article proposes the design and implementation of a parallel evolutionary algorithm for public transport optimization on Garzon Avenue, Montevideo, Uruguay. This is an interesting complex urban scenario, due to the number of crossings, streets, and traffic lights in the zone. We introduce an evolutionary algorithm to efficiently synchronize traffic lights and improve the average speed of buses and other vehicles. The experimental analysis compares the numerical results of the evolutionary algorithm against a baseline scenario that models the current reality. The results show that the proposed evolutionary algorithm achieves better quality of service improving up to 15.3% average bus speed and 24.8% the average speed of other vehicles.