Dynamic Optimization for Multi-Phase Intersection Timing Using Stratified Genetic Algorithm

Abstract:

Based on the study on traffic flow characteristics of the intersection, and current signal timing model of intersection, this paper selected the stop delay, the number of stops and parking traffic capacity as the indexes, and translated them into a single nonlinear objective function which is the fitness of genetic algorithm. In order to meet the changes of intersection traffic flow, this paper improved the basic genetic algorithm. The improved algorithm with two genetic layers carried on signal timing optimization for middle traffic flow and peak traffic flow situation. Experiments show that the model is reasonable, and the effect caused by timing parameters optimization is obvious.

• Periodical: Applied Mechanics and Materials (Volumes 135-136)
• Pages: 470-476
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.135-136.470
• Online since: October 2011
• Authors: Hong Ke Xu, Jian Wu Fang, Wei Song Yang, Shang Gao, Mao De Yan
• Keywords: Intelligent Transportation, Intersection, Multi-Phase Intersection Timing, Stratified Genetic Algorithm

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