智能交通最短路径Dijkstra模糊动态方法分析

提高道路网络上的动态路由选择效率是当前路网建设中的难题,现有解决路由问题的方法都是基于静态方向的研究。提出一种基于模糊的Dijkstra最短路径动态算法,以被量化的限定用户参量为语言变量,用模糊集理论提供模糊数输出在网络上的最短路径预测。通过处理模糊参数,提出用模糊数表示不同路径与边长间距离的两种比较方法。采用梯级平均综合表示法改进Dijkstra算法,并以数值的道路网络实例来说明该方法的有效性。

The Shortest Path of Fuzzy Dynamic Approach Based on Dijkstra Arithmetic in Intelligent Transportation

Improving the efficiency of dynamic routing problem on road network is a diffcult. I here is numerous works proposed for this problem and they try to solve this in different aspects. Most of the existing routing problem based on static approach. In this paper, we propose a fuzzy Dijkstra＇s shortest path algorithm based on dynamic approach. The linguistic variables that qualify user parameters are quantified using fuzzy set theory that provides fuzzy numbers outputs to predict the shortest route on network. By handling the fuzzy parameter, it gives issue to compare the distance between two different paths with their edge lengths represented by fuzzy numbers. The addition of fuzzy numbers using graded mean integration representation is used to improve Dijkstra＇s algorithm. A numerical example of a road network is used to illustrate the efficiency of the proposed method.