【作者】 杜娟；

【导师】 马文阁；

【作者基本信息】 辽宁工学院 ， 控制理论与控制工程， 2007， 硕士

【摘要】 智能交通系统(ITS)是解决现代社会交通需求与供给矛盾的重要途径之一,是解决交通基础设施建设增长缓慢与机动车数量逐年迅速增长之间矛盾的最为有效的途径。造成交通拥挤往往突出表现在道路的交叉口处,交叉口是城市道路的交汇点,在道路网和交通流中起着十分重要的作用。采用了模糊控制技术,不需要建立精确的数学模型。本文的研究工作主要是对单交叉及干线交叉口设计新的建模及控制方法。对多相位单交叉口提出一种基于可变相序的模糊控制方法,以车辆平均车辆延误作为控制目标,综合考虑各相位车道上的车队长度以及各相位的延误次数,得到最优的相序安排和各通行相位的绿灯延长。运用了MATLAB对其控制效果进行仿真分析,结果表明该算法可有效降低通行车辆在交叉口的平均延误时间,使交叉口的通行能力提高。并且,本文对干线交叉口采取递阶模糊协调控制的算法,第一级为控制级,计算路口的各控制参数,第二级是协调级,综合主干方向的车流状况及各个路口的情况,对各个路口的周期、相序及主干方向的绿信比进行调整,仿真结果表明,该算法优于定时模糊控制算法。同时为满足智能交通系统高性能模糊控制器设计的需要,解决城市交通信号智能控制模糊规则提取的瓶颈问题,本文利用蚁群算法进行控制规则的优化,用尽量少的规则得到尽可能好的控制效果,在已有的完备的规则中优选出若干条规则嵌入模糊控制器。对优化过的模糊控制器在不同的交通条件下进行了仿真,并与未经过优化的模糊控制器在相同的交通环境下对车辆的控制进行比较。仿真结果表明蚁群算法与模糊控制相结合的智能控制技术,更有效地降低通行车辆在交叉口的平均延误时间,更能适应复杂多变的交通环境。更多还原

【Abstract】 Intelligent transportation system (ITS) is one of the important ways to solve the important approach of traffic demand and supply in the modem society and the best way to solve the contradiction between the slow-increasing basic traffic establishment and the fast-increasing number of vehicles. More and more phenomenon indicates that the city traffic jam is usually manifested in the intersections, which are the converge points and play important role in road net and traffic flow.This thesis is mainly focused on designing new models and control arithmetic to single intersection and trunk road traffic. In this paper, fuzzy control method in multi-phase intersections based on variable phase sequence is put forward. The average delay time are used to determine the overtime of green light and the numbers of delay on all next time for green light phase. MATLAB is exploited to simulate the multiphase fuzzy control system. The result showed that which can reduce the average delay time and to improve he traffic power of the traffic vehicle in grade intersection effectively. And, this paper use hierarchy fuzzy coordinated control method to solve the problem of traffic control for the trunk roads. The first level is manipulative level that calculates the parameter .The second level is coordinated level that correct the cyclical, phase and split of intersections by consider the traffic of trunk roads and intersections. Simulation result shows that hierarchical control fuzzily algorithms is better than the fixed coordination control algorithms in the traffic junction coordination control. To meet the needs of designing fuzzy controllers with high performance in intelligent transportation systems, in this paper, ant colony algorithm is used, in order to get better control results with less control rules and select several good fuzzy rules from a completed fuzzy rule base which is used to construct the Fuzzy controller. MATLAB is used to simulate the optimized fuzzy controller under the different traffic environments, and comparing with the out optimized fuzzy controller which worked under the same traffic environment. The results indicates that the intelligent control technology which combined fuzzy control with Ant colony algorithm could lower the average delay time inthe flat surface for the vehicle which was going through the single intersection than the time controlling and it is easier to adapt to the complicated and versatile transportation environment.更多还原