Simulation Analysis of Self-driving Travelling Routes

doi:10.16182/j.issn1004731x.joss.17WJP-018

Abstract

Abstract: 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 5A 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.

Key words: travel route planning, Matlab simulation, travel plans, time value

CLC Number:

U116.2

Sun Ling, Dong Ya, Liu Wei, Yang Guanyun. Simulation Analysis of Self-driving Travelling Routes[J]. Journal of System Simulation, 2019, 31(3): 429-437.

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