Isolated Intersection Control Based on Improved Genetic Algorithm

Single intersection control is an efficient tool to release traffic congestion. We proposed intelligent algorithms which can be used in single-intersection control optimization. In the algorithm, the competition law for the selection operator of genetic algorithms was improved with the Hill sorting strategy, and the basic genetic algorithm was changed into an improved new binary genetic algorithm. Simulation results from a 4-phase interaction control strategy show that genetic algorithm is applicable to traffic control. Genetic algorithm improved in the paper reduced delay and queuing length significantly within short time under high traffic demand. This new method of signal control gives a new idea for the signal control and provides more theoretical basis in the area of the optimization of signal control for the future.