Title: Path selection method of intelligent vehicle based on fuzzy big data game

Authors: Zhiwu Huang

Addresses: School of Computer and Information Science, Hubei Engineering University, Xiaogan, Hubei 432000, China

Abstract: In view of the traditional intelligent vehicle routing method, the problems of inaccurate selection, long time and low efficiency have always existed. We proposed a path selection method for intelligent vehicle based on fuzzy big data game. Through analysis of the modelling principle of intelligent transportation vehicle routing and the relevant principle of the least squares algorithm, we calculated the function of risk factors in the path selection of intelligent transportation vehicles and established the conditional constraint model for vehicle routing. By using the depth neural network method, the path congestion state was identified, and the intelligent vehicle routing database was established. The simulation results show that the extraction time and accuracy of the method are better than those of the traditional path selection method in the improved method.

Keywords: intelligent transportation; path selection; improvement strategy; fuzzy control; big data game.

DOI: 10.1504/IJVAS.2018.093118

International Journal of Vehicle Autonomous Systems, 2018 Vol.14 No.1, pp.62 - 81

Received: 09 Sep 2017
Accepted: 24 Apr 2018
Published online: 09 Jul 2018 *

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