自驾游交通路线仿真分析

Simulation Analysis of Self-driving Travelling Routes

我国自驾游发展迅速,建立自驾游出行规划模型,运用Matlab进行仿真,采用遍历求解优化算法和随机求解优化算法得到各区域最优旅行计划。若某区域旅游时间过长,则运用K-mean聚类算法将该区域分为两类再进行仿真求解。以我国5A景区为例,建立全国自驾游出行方案规划模型。提出时间价值概念,通过比较飞机、火车、汽车的出行方式,进行时间价值的敏感性分析,得出不同时间价值人群的最优出行方式,为全国各地的不同人群推荐相应出行方式和路线安排。

China’s tourism industry develops rapidly. By building self-driving traveling plan model and using traversal algorithm and stochastic optimization algorithm, the area optimal travel plans with Matlab simulation are obtained. If traveling time is too long in one area, the K-mean clustering algorithm can be used to divide it into two parts for simulation. A case study of 5 A attractions in China is used for establishing a national self-driving traveling plan model. The concept of the Time Value is proposed. By comparing the travel modes of plane, train and car, the common model is established. The sensitivity analysis of Time Value is carried out, and the best traveling way for different Value Time crowd is obtained.The appropriate travel modes and routes for different groups all over the country are recommended.