Ant colony algorithm for traffic signal timing optimization

In order to separate the conflict of the traffic flow effectively, time delay, number of stops and traffic capacity are chosen as performance indexes, and the objective function related to the cycle time and the saturation of an intersection is established by using the weighting coefficients. Then, based on the uncertainty and convergence analysis of ant colony algorithm (ACA), computational experiments are conducted and numerical comparisons are made for the values of performance indexes achieved by the signal timing optimization problem with Webster algorithm, genetic algorithm (GA) and ACA. Numerical results show that ACA is a simple and feasible method for signal timing optimization problems.

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