Traffic signal timing optimization method based on principal component analysis and local search improved orthogonal genetic algorithm

Abstract

Provided is a traffic signal timing optimization method based on principal component analysis and a local search improvement orthogonality genetic algorithm. The algorithm is provided by analyzing internal relation among the genetic algorithm, image processing and mode recognition and can be used for solving various function optimization problems. By means of the algorithm, an improvement orthogonality cross operator based on principal component analysis is provided. The operator first conducts PCA projection on the population before cross, individual length is reduced during cross, orthogonal cross operation is implemented on the projection area, the projection is projected to the original space after cross, redundant individual number and calculation expenses caused by redundancy are reduced, algorithm convergence speed is further improved, and the local search strategy is further introduced. The algorithm is applied to single-crossing signal timing optimization. By means of testing comparison with the existing algorithm, the method improves algorithm generality and efficiency, effective timing time is acquired, and the number of the queuing vehicles in front of a crossing is reduced.

Description

technical field [0001] The invention belongs to the optimization problem of urban traffic control signal timing. Using orthogonal genetic algorithm and algorithms in the cross field of biometric identification technology (specifically involving orthogonal genetic algorithm, principal component analysis PCA and local search strategy) to realize the signal timing control of urban single intersections. Background technique [0002] With the rapid development of my country's economy and the continuous acceleration of the urbanization process, the number of motor vehicles has also increased rapidly, the traffic volume has increased greatly, the transportation supply is seriously insufficient, and the contradiction between supply and demand is prominent. 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 annual growth rate of traffic v...

AI Technical Summary

Problems solved by technology

Song Xuehua and others invented a single intersection signal timing optimization method based on genetic algorithm. The genetic algorithm used in this invention is a standard genetic algorithm, in which the optimal retention strategy is added to the selection strategy, but the local search ability of the standard genetic algorithm is not strong. prone to premature convergence

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