面向智能交通系统的最优路线规划设计方法

交通拥堵已经成为城市化进程中必须要解决的问题之一。随着智能交通系统的逐渐普及,基于车辆导航和定位系统的路径规划成为解决交通拥堵、提高通行效率的关键技术。该文首先介绍现阶段常用的几种路径规划算法,随后分别概述车辆最优行驶路径的静态规划和动态规划方法。通过搭建车辆路径规划仿真平台,利用静态路径规划数学模型,可以使用最短路径查询算法和详略层快速查询算法,为驾驶员规划一条最优路径。创建动态规划数学模型,则能帮助车辆主动避开有交通管制的路径,进一步提升通行效率。实验表明,使用基于车辆协调算法的动态路径规划,能够减少智能交通网络中拥堵道路数,从而提高整个智能交通系统的通行效率。

Traffic congestion has become one of the problems that must be solved in the process of urbanization.With the popularization of intelligent transportation system,route planning based on vehicle navigation and positioning system has become a key technology to solve traffic congestion and improve traffic efficiency.This paper first introduces several algorithms for common path planning at present,and then summarizes the static planning and dynamic planning methods of optimal vehicle path respectively.By building the simulation platform of vehicle path planning and using the mathematical model of static path planning,the shortest path query algorithm and detail layer fast query algorithm can be used to plan an optimal path for drivers.The mathematical model of dynamic programming can help vehicles actively avoid the path with traffic control and further improve traffic efficiency.Experiments show that dynamic path planning based on vehicle coordination algorithm can reduce the number of congested roads in the intelligent transportation network,thus improving the traffic efficiency of the entire intelligent transportation system.