Use of ML to Predict Traffic for an Intelligent Transportation System

Liu Chang

Abstract


The purpose of this study is to create a technology that can forecast traffic flow accurately and quickly. Everything that can impact the flow of traffic on the road is included in the Traffic Environment, including traffic lights, accidents, rallies, and even road repairs that produce congestion. A motorist or passenger can make an educated decision if they have previous knowledge that is close to accurate about all of the aforementioned everyday life events that might impact traffic. Additionally, it aids in the development of self-driving cars in the future. As traffic data has grown rapidly in recent decades, we've shifted to big data concepts for transportation.

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