Abstract: Nowadays, the capabilities of roads and transportation systems have not evolved in a way that is efficiently copes with the increasing number of vehicles and growth of population. Traffic congestion is becoming the issues of the entire globe. The traffic congestion issues have some other indirect overseen issues such as noise, pollution and increase travelling time. This project aims to explore and review the data mining and machine learning technologies adopted in research and industry to attempt to overcome the direct and indirect traffic issues on humanity and societies. The study is focusing on the traffic management approaches that were depended on data mining and machine learning technologies to detect and predict the traffic only. Using data mining technology in traffic management provides a powerful analysis and processing function of mass traffic data and directs drivers and systems to make better decisions. Knowledge mining and discovery is an emerging area in traffic management systems focuses on using and analyzing large amount of traffic data to be used for traffic control, route guidance, or route programming. This study is important to the traffic research communities, traffic software companies, and traffic government officials. Additionally, this study will draw general attention to a new traffic management proposition approach.

Keywords: Data Mining, machine learning, Decision TreeTraffic management, KNN.

PDF | DOI: 10.17148/IJARCCE.2021.10227

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