Paper Title:
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.

  Info
Periodical
Chapter
Chapter 4: Image Processing & Modeling of Materials
Edited by
Robin G. Qiu and Yongfeng Ju
Pages
470-476
DOI
10.4028/www.scientific.net/AMM.135-136.470
Citation
H. K. Xu, J. W. Fang, W. S. Yang, S. Gao, M. D. Yan, "Dynamic Optimization for Multi-Phase Intersection Timing Using Stratified Genetic Algorithm", Applied Mechanics and Materials, Vols. 135-136, pp. 470-476, 2012
Online since
October 2011
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