基于改进免疫遗传算法的交通信号优化控制

The Optimization for Traffic Signal Based on Improved Immunogenetic Algorithm

阐述免疫遗传学的基本原理,对传统免疫遗传算法做了改进.模拟抗体两次应答抗原的机理,引入信息熵计算抗原间的亲和力,选择亲和力高且相似度低的抗体遗传到后代,运用细胞记忆机制保存优良抗体,并令记忆细胞参与进化。避免算法陷入局部最优值.在此基础上,提出一种更新的相位配时优化算法对交通信号控制问题进行探讨,并设计相应的仿真实验.对一个四相位单交叉路口的交通流进行建模和分析,实验结果验证该算法处理交通配时优化问题的可行性和有效性.

In this paper the basic principle of immunogenetics is described , and the traditional immunogenetics algorithm is improved. The mechanism that the antibody twice responds to the antigen is simulated. Information entropy is utilized to compute the affinity between antigens and the antibodies that have high affinity and low similarity are inherited to next generation . Best antibodies are kept in memory set then participate in evolution , which can make the algorithm avoid losing in the local optimal solution. A new phase timing optimization algorithm is proposed to discuss the problem of traffic signal control. An experiment for the traffic model at a four-phase single intersection is designed with this algorithm, and the simulation results show its feasibility and effectiveness.