摘要
大量研究表明,模糊交通信号控制算法在性能上明显优于传统方法,但现有研究大多采用单策略控制,在复杂多变的城市交通流条件下,难以充分发挥交叉口的通行能力.为此,在深入分析交通需求的基础上,提出了基于模糊理论的多策略模糊控制算法.同时,为克服用经验法确定多套模糊策略的困难与不足,还设计了基于遗传算法的模糊规则和隶属度函数优化方法.仿真结果表明,多策略模型优于单策略模型,更优于传统交通控制方法.
Plenty of researches indicate that fuzzy traffic signal control algorithms obviously outperform the conventional methods. Nevertheless, most of the available researches adopt single-strategy control method, so it is difficult to fully exert the capacity of intersection under the condition of complex and time-varying urban traffic flow. For this reason, based on the deep analysis of traffic demand, a fuzzy theory based multi-strategy fuzzy control algorithm is proposed. At the same time, in order to overcome the difficulty and limitation of determining the multiple fuzzy strategies by using experiential method, a genetic algorithm based optimization method is designed for optimizing fuzzy rules and membership functions. Simulation result proves that multi-strategy model outperforms single-strategy model, and its perforrnance is better than that of the conventional method.
出处
《系统工程学报》
CSCD
北大核心
2007年第1期46-52,共7页
Journal of Systems Engineering
关键词
模糊控制
遗传算法
单交叉口
多策略
优化
fuzzy control
genetic algorithm
isolated intersection
multi-strategy
optimization
