智能车辆导航系统中路径选择算法的研究与实现
发布时间：2018-12-13 01:12
【摘要】：当今社会科技高速发展，人们的生活水平不断提高，越来越多的人拥有私家车，，人们越来越离不开车辆导航系统，而智能车辆导航系统中最核心的部分就是路径选择算法,所以本文是解决人们生活中的实际问题。 论文第一章介绍了我国目前交通道路上存在的一些问题，解决这些问题最好的办法是交通智能化，利用车辆导航系统使车辆能够在道路上井井有条的行驶。本章概述了智能车辆导航系统，研究了它的背景和意义，对其发展现状作了简单的介绍了，构思了本章论文的研究内容。第二章主要研究了智能车辆导航系统的基本框图及其主要功能，此外，智能车辆导航系统技术用到了多个学科里面的各种技术方法，但是用到的关键技术有六种。第三章介绍了图论中图的相关知识，确定了实际的交通路网可以抽象为一个赋权有向图，研究了路网的两种连通性表达和三种存储结构。 第四章是本文的重点，本章讨论了智能车辆导航系统中路径选择算法，研究了目前应用最广泛的Dijkstra算法、Floyd算法和基本蚁群算法；研究了这三种算法的主要思想，这些算法实现步骤和流程，针对初始的时候基本蚁群算法容易陷入局部最优的缺陷已做了一点改进，把蚁群算法数学模型中转移概率公式做了一些简化，并将其加入一个放大因子，通过蚁群算法实验仿真可知，改进蚁群算法提高了搜索效率。 最后，以Windows7系统为开发平台，以MatlabR2008a为开发工具，搭建了智能导航最短路径规划系统，完成了对四种算法的集成，实现了四种方法的路径规划，本文还利用实际数据完成了对系统的测试。
[Abstract]:Nowadays, with the rapid development of social science and technology, people's living standard is improving, more and more people own private cars, and people are more and more inseparable from vehicle navigation system, and the most important part of intelligent vehicle navigation system is path selection algorithm. So this paper is to solve the actual problems in people's lives. The first chapter introduces some problems existing in the traffic road in our country. The best way to solve these problems is to use the vehicle navigation system to make the vehicle run orderly on the road. This chapter summarizes the intelligent vehicle navigation system, studies its background and significance, makes a brief introduction to its development status, and conceive the research content of this chapter. The second chapter mainly studies the basic block diagram of intelligent vehicle navigation system and its main functions. In addition, intelligent vehicle navigation system technology uses a variety of technical methods in many disciplines, but there are six key technologies used. The third chapter introduces the related knowledge of graph in graph theory, determines that the actual traffic network can be abstracted as a weighted directed graph, and studies two kinds of connectivity representation and three storage structures of road network. The fourth chapter is the focus of this paper, this chapter discusses the intelligent vehicle navigation system path selection algorithm, the most widely used Dijkstra algorithm, Floyd algorithm and basic ant colony algorithm; The main ideas of these three algorithms are studied. The steps and flow of these algorithms are discussed. The basic ant colony algorithm is easy to fall into local optimum at the beginning. The formula of transfer probability in the mathematical model of ant colony algorithm is simplified, and an amplification factor is added to it. Through the simulation of ant colony algorithm experiment, the improved ant colony algorithm improves the search efficiency. Finally, using Windows7 system as the development platform and MatlabR2008a as the development tool, the intelligent navigation shortest path planning system is built, the integration of four algorithms is completed, and the path planning of the four methods is realized. The test of the system is completed by using the actual data.
【学位授予单位】：中原工学院
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：TP301.6;U495
[Abstract]:Nowadays, with the rapid development of social science and technology, people's living standard is improving, more and more people own private cars, and people are more and more inseparable from vehicle navigation system, and the most important part of intelligent vehicle navigation system is path selection algorithm. So this paper is to solve the actual problems in people's lives. The first chapter introduces some problems existing in the traffic road in our country. The best way to solve these problems is to use the vehicle navigation system to make the vehicle run orderly on the road. This chapter summarizes the intelligent vehicle navigation system, studies its background and significance, makes a brief introduction to its development status, and conceive the research content of this chapter. The second chapter mainly studies the basic block diagram of intelligent vehicle navigation system and its main functions. In addition, intelligent vehicle navigation system technology uses a variety of technical methods in many disciplines, but there are six key technologies used. The third chapter introduces the related knowledge of graph in graph theory, determines that the actual traffic network can be abstracted as a weighted directed graph, and studies two kinds of connectivity representation and three storage structures of road network. The fourth chapter is the focus of this paper, this chapter discusses the intelligent vehicle navigation system path selection algorithm, the most widely used Dijkstra algorithm, Floyd algorithm and basic ant colony algorithm; The main ideas of these three algorithms are studied. The steps and flow of these algorithms are discussed. The basic ant colony algorithm is easy to fall into local optimum at the beginning. The formula of transfer probability in the mathematical model of ant colony algorithm is simplified, and an amplification factor is added to it. Through the simulation of ant colony algorithm experiment, the improved ant colony algorithm improves the search efficiency. Finally, using Windows7 system as the development platform and MatlabR2008a as the development tool, the intelligent navigation shortest path planning system is built, the integration of four algorithms is completed, and the path planning of the four methods is realized. The test of the system is completed by using the actual data.
【学位授予单位】：中原工学院
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：TP301.6;U495
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