摘要
通过对到达车辆数目的模糊分类,将交通信号控制方案以不同规则集的形式实施,根据实际控制效果利用遗传算法对规则集进行改进,形成了一种具有机器学习能力的单路口交通信号新控制方法.经过仿真实验,对该方法的控制效果与定时控制和感应控制进行了比较,仿真实验的结果说明该方法的控制效果明显优于传统控制方式.
The traffic signal control schemes are put in the form of rule-sets into use through fuzzy classifying the arrived cars in this paper. Genetic algorithm is applied to improve the rule-sets according to the effect of actual controlling. These procedures form a new machining-learning traffic signal control approach for isolated intersection. After simulating, the control effect of this new approach with fixed-time control method and actuated control method are compared. The result of simulating illustrates that the effect of the new approach is obviously better than the traditional ones.
出处
《系统工程理论与实践》
EI
CSCD
北大核心
2004年第8期130-135,共6页
Systems Engineering-Theory & Practice
关键词
机器学习
交通信号控制
遗传算法
交通仿真
machining-learning
traffic signal control
genetic algorithms
traffic simulation
