摘要
在传统的交叉口信号模糊控制基础上,提出了基于相序优化的模糊控制算法,并用改进的遗传算法优化模糊控制规则。对相序的优化考虑了驾驶员的心理,执行了专家的决策;对控制规则进行优化,减少了因专家主观性而导致控制器的不完备性。以典型的十字交叉口和四相位交通信号控制为例,选择不同时段的交通流数据进行仿真。结果表明:采用该控制算法设计的信号控制器能有效避免交通流不平衡引起的拥挤堵塞,具有更好的实时性和控制效果。
Fuzzy control algorithm based on optimization of phases＇ order was presented and improved genetic algorithm was used to optimize fuzzy control rules on the basis of traditional signal fuzzy control at intersection. In the optimization of phases＇ order, drivers＇ psychology was considered and experts＇ decisions were performed. The optimization of control rules reduced the inadequacy of controller caused by experts＇ subjectivity. Taking typical intersection and fourphase traffic signal controlling as example, traffic flow datum in different periods were chosen for simulation. The results indicate that controllers using the control algorithm in this paper can avoid congestion caused by unbalanced traffic flow effectively and it has better real-time characteristics and control effects.
出处
《中国公路学报》
EI
CAS
CSCD
北大核心
2006年第6期97-101,共5页
China Journal of Highway and Transport
基金
国家自然科学基金项目(60674062)
关键词
交通工程
交叉口信号
遗传算法
智能控制
仿真
模糊控制
traffic engineering
intersection signal
genetic algorithm
intelligent control
simulation
fuzzy control
