Date of Award

6-2013

Degree Name

MS in Electrical Engineering

Department

Electrical Engineering

Advisor

Xiao-Hua (Helen) Yu

Abstract

Traffic signal control with swam intelligence ant colony optimization

Pang-shi Shih

Ant colony optimization (ACO) is a meta-heuristic based on the indirect communication of a colony of artificial ants mediated by pheromone trails with collaboration and knowledge-sharing mechanism during their food-seeking process. ACO has been successfully applied to solve many NP-hard combinational optimization problems such as travel salesman problem, quadratic problem, just to name a few. In this research, we apply the ACO algorithm to the traffic signal control in order to minimize the user delay at a traffic intersection. Simulation results from our computational experiments indicate that ACO provides better performance during high traffic demand, compared to the conventional Fully Actuated Control (FAC).

Keywords: Ant colony optimization (ACO), meta-heuristic, the traffic signal control, user delay

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