A Multi-agent Traffic Simulation Framework for Evaluating the Impact of Traffic Lights.

Abstract

The growing of the number of vehicles cause serious strains on road infrastructures. Traffic jams inevitably occur, wasting time and money for both cities and their drivers. To mitigate this problem, traffic simulation tools based on multiagent techniques can be used to quickly prototype potentially problematic scenarios to better understand their inherent causes. This work centers around the effects of traffic light configuration on the flow of vehicles in a road network. To do so, a Multi-Agent Traffic Simulation Framework based on Particle Swarm Optimization techniques has been designed and implemented. Experimental results from this framework show an improvement in the average speed obtained by traffic controlled by adaptive over static traffic lights.

Antonio Gonzalez-Pardo

Associate Professor

Lecturer at the Computer Science Department. Main research interests are related to Computational Intelligence and Metaheuristics applied to Social Networks Analysis, and the optimization of graph-based problems.