THE ROLE OF MACHINE LEARNING IN ANALYZING TRAFFIC PATTERNS FOR IMPROVED ROAD DESIGN

Abstract

Traffic blocking is becoming as a global concern. This study seeks to examine and evaluate the data mining and machine learning technologies utilized in studies and enterprises to address both direct and indirect traffic challenges affecting mankind and society. The data gathered is significant for traffic research groups, traffic software enterprises, and governmental traffic officials. It directly influences the formulation of explicit strategies for new traffic control proposals. The current study is among the greatest in terms of the work of examined literature pertaining to data mining and machine learning. This review will also highlight a novel method to traffic management.