Research And Realization Of Path Selection Algorithm In Intelligent Vehicle Navigation System

Nowadays, The rapid development of science and technology, people’s living standardsimprove, more and more people own the cars, it is increasingly inseparable from the carnavigation system, and intelligent navigation system is the core part of the path selectionalgorithm, so this people solve real problems in real life.The first chapter describes some of the problems of existing traffic on the road now, thebest way to solve these problems is the intelligent transportation, vehicle navigation systemmakes use of a vehicle capable of traveling on the road in perfect order. This chapter providesan overview of the intelligent vehicle navigation system to study its background andsignificance, gave a brief introduction to its current development, the idea of a research thesisof this chapter. The second chapter studies the basic block diagram of the intelligent vehiclenavigation system and its main function, in addition, the intelligent vehicle navigation systemtechnology have used in the various technical disciplines inside the methods, but there are sixkey technologies used. The third chapter describes the knowledge graph theory to determinethe actual road network can be abstracted as a directed graph empowered to study theexpression connectivity of two methods and three storage structures of the road network.The fourth chapter is the focus of this article, this chapter discusses the intelligent vehiclenavigation system path selection algorithm, the most widely studied Dijkstra algorithm, Floydalgorithm and the basic ant colony algorithm; studied the main idea of these three algorithms,these algorithms implementation steps and processes for the initial time basic ant colonyalgorithm easy to fall into local optimum has done little to improve, the ant colony algorithmis a mathematical model of the transition probability formula did some simplification, andadded an amplification factor, by the simulation shows that the ant colony algorithm,improved ant colony algorithm improves search efficiency.Finally, ToWindows7system development platform, To MatlabR2008a development tools to build a shortest path planning of intelligent transportation systems, completed theintegration of four algorithms to achieve a path planning four methods, the paper also usesactual data completed test system.