A review of the application of machine learning technologies in vehicle navigation and positioning

Abstract

In recent years, the accuracy requirement of vehicle navigation and positioning is higher and higher. Since some obvious disadvantages emerge in the integration of various traditional technologies, many studies have begun to apply machine learning to vehicle navigation and positioning, which utilize the powerful self-learning ability of machine learning algorithms. The main advantages of machine learning methods include solving the problem of narrow application scope of traditional information fusion algorithms. Solve the problems of low navigation and positioning accuracy and poor anti-interference ability. In this paper, the applications of machine learning related algorithms in vehicle navigation and localization are overviewed in detail, including support vector machines, neural networks and random forests. Meanwhile, the application research status of machine learning technology in vehicle navigation and positioning is summarized, and the future research directions are prospected.