Abstract
There are more than one objective in the traffic signal control, so the multi-objective optimization is necessary. The purpose of this paper is to establish Multi-Objective Cycle Length Optimization (MOCLO) model and solve it by ant colony optimization algorithms. Three optimization objectives are selected by fuzzy clustering method, considering the time benefit of vehicles and pedestrians and environmental benefit. The optimization objectives of MOCLO model are minimum vehicle delay, minimum pedestrian delay, and minimum stops. The input of the model are vehicle volumes and pedestrian volumes. Ant colony optimization algorithms are used to solve the MOCLO model, which can uniformly approximate every part of Pareto-optimal front. A case study demonstrates that multi-objective optimization is effective in cycle length optimization.
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