Traffic signal timing optimization method based on minimum spanning tree clustering genetic algorithm

Abstract

The invention discloses a traffic signal timing optimization method based a minimum spanning tree clustering genetic algorithm. The optimization method comprises the following steps: performing individual coding, initializing data, and setting parameters; conducting population initialization; calculating the individual fitness value in the populations; performing the minimum spanning tree clustering on the populations; selecting individuals in the populations to participate in the genetic operation; carrying out the crossover and mutation operation on the selected individuals; repeatedly iterating until the optimal timing in corresponding periods is obtained. By performing the minimum spanning tree clustering on the populations, individuals in the populations have high similarity, the similarity among the populations is relatively low, the population diversity can be maintained through the intersection of the populations, and the premature convergence phenomenon is inhibited; the optimization method is used for optimizing the single timing of a single intersection, effective timing time can be obtained, and the queuing vehicles in front of the intersection is reduced.

Description

technical field [0001] The invention belongs to the optimization problem of urban traffic control signal timing, and specifically adopts a genetic algorithm based on clustering to optimize it. method of timing control. Background technique [0002] Urban transportation is the lifeblood of urban economic life, a symbol of a city's civilization and progress, and plays a very important role in the development of urban economy and the improvement of people's living standards. In my country, with the continuous development of the economy, the urbanization process is accelerating, the number of motor vehicles is increasing rapidly, the traffic volume is increasing, the urban traffic supply is seriously insufficient, and the contradiction between supply and demand is intensifying. Take Beijing as an example. At present, the number of motor vehicles in Beijing has exceeded 2 million. The annual growth rate of urban roads is 3%, while the growth rate of vehicles is 15%, and the annu...

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Problems solved by technology

Traffic congestion in cities, mostly caused by insufficient or underutilized intersections, resulting in disrupted traffic, increased accidents, and severe delays

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