DOI: https://doi.org/10.15368/theses.2009.158
Available at: https://digitalcommons.calpoly.edu/theses/190
Date of Award
11-2009
Degree Name
MS in Electrical Engineering
Department/Program
Electrical Engineering
Advisor
Xiao-Hua (Helen) Yu
Abstract
Traffic signal control is an effective way to improve the efficiency of traffic networks and reduce users’ delays. Ant Colony Optimization (ACO) is a metaheuristic based on the behavior of ant colonies searching for food. ACO has successfully been used to solve many NP-hard combinatorial optimization problems and its stochastic and decentralized nature fits well with traffic flow networks. This thesis investigates the application of ACO to minimize user delay at traffic intersections. Computer simulation results show that this new approach outperforms conventional fully actuated control under the condition of high traffic demand.