Abstract

Purpose: The main target of this paper was to examine the significance of Artificial Intelligence and Machine Learning and their effect on the transportation business.
 Methodology: This hypothesis was a survey of the significant machine learning calculations and their applications in the field of big data. This paper try to attempt to exhibit the need to remove significant data from the huge measure of enormous information as traffic data available in this day and age and recorded diverse machine learning strategies that can be utilized to separate this information needed to encourage better dynamic for transportation applications.
 Findings: This paper present an investigation of the different Artificial Intelligence (AI) methods that have been actualized to improve Intelligent Transportation Systems (ITS). Specifically, this paper assembled them into three main territories relying upon the main field where they were applied: Vehicle control, Traffic control and prediction, and Road security and accident prediction. The aftereffects of this examination uncover that the mix of various AI methodologies is by all accounts promising, particularly to oversee and investigate the huge measure of data created in transportation

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