交通路径诱导系统中最优路径选取研究与仿真

摘要

Study the optimization problems of traffic route guidance system. The paper put forward a distribution traffic route guidance system based on adaptive mutation artificial fish algorithm. Introducing a distribution mutation operator which combines gaussian variation and cauchy variants, traffic congestion parameters were extracted and fed back to control terminals. AFSA way iterative process was used and the distribution of the iteration time was taken as freedom parameters to improve the efficiency of the induced traffic. Experiments show that the algorithm can enhance the performance of the transportation route guidance and satisfactory results have been obtained.%研究交通路径诱导系统优化问题.复杂路况高峰时多条道路车辆同时汇聚造成交通拥塞,但是拥塞信息的实时变化存在高度的非线性和突变性.传统的交通路径诱导系统,仅仅是针对最短距离进行路径选取,非线性和突变性拥堵信息不能在模型中得到反应,一旦拥堵发生,会降低交通路径诱导的效率.提出了一种基于自适应t分布变异人工鱼群算法的交通路径诱导系统.引入t分布变异算子将高斯变异和柯西变异的优点结合起来,提取交通路径拥塞参数,并将其反馈到控制端,使用AFSA方式进行迭代处理,将迭代次数作为t分布的自由度参数,从而提高了交通诱导的效率.实验证明,鱼群算法提高了交通路径诱导的性能,避免了交通拥塞的缺陷.