摘要
为了克服传统的交通路口信号控制算法不能适应环境变化的缺陷,本文引入了基于遗传学习分类的数据挖掘方法,通过对历史交通数据和控制参数进行规则编码、以及适应度函数的构造,从大量历史交通数据中挖掘出适应交通环境变化的信号控制规则。最后,构造了单路口交通控制仿真平台,实验表明能有效提高路口控制效率并适应环境变化。
n order to overcome the defect that traditional intersection traffic signal control algorithm cannot adapt to the changing environment. This paper introduces the genetic learning and classifier method for the traffic signal control, by means of coding the traffic data and constructing the fitness function, to excavate the traffic signal control rules which can adapt to the changing environment Finally, the traffic signal control simulation platform is built to verify it. The experiment shows it can effectively improve the control efficiency ofintersection and quickly adapt to environment changes.
出处
《微计算机信息》
2011年第2期233-234,237,共3页
Control & Automation
关键词
数据挖掘
分类
遗传学习
交通信号
Data mining
classifiers
Genetic learning
Traffic signal.
