单交叉口多策略模糊控制算法与优化

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.

Multi-strategy based fuzzy control algorithm and its optimization for isolated intersection

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 performance is better than that of the conventional method.