A New Multiobjective Signal Optimization for Oversaturated Networks

This paper presents a new methodology for optimizing the signal timing controls of oversaturated networks based on the cell transmission model and a goal programming technique with multiple objectives. The proposed model accounts for intersection spillovers, equity in delays, and system throughputs. This new formulation is solved by genetic algorithms to obtain signal timing plans. A case study with a nine-intersection network and a comparison between the proposed model and the throughput-maximizing strategy are examined. It is found that the new method can efficiently minimize spillovers, balance delay equity, and provide reasonable system throughputs in their respective order for oversaturated networks. The result also indicates that the throughput-maximizing strategy does not always yield minimum spillovers for oversaturated networks and occasionally provides a larger difference in average link delay at a spillover intersection than the proposed model does.

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