Abstract
Road transport undeniably constitutes the predominant mechanism for facilitating the transportation of both goods and individuals on a global scale, serving as an essential backbone for economic and social interactions across diverse regions and cultures. The noticeable decrease in the flow of vehicles, which can be attributed to a plethora of internal and external factors, with a particular emphasis on the phenomenon of congestion, has profound implications that significantly influence fuel consumption rates, contribute to pollution associated with emissions, adversely affect the health and well-being of bystanders, and culminate in a considerable loss of time for individuals navigating these congested environments. In light of their elevated population densities coupled with their classification as emerging economies, South Asian countries find themselves necessitated to implement automated systems for the critical processes of predicting, identifying, and effectively addressing the challenges posed by road traffic congestion in order to enhance urban mobility and overall transport efficiency. This thorough research carefully explores the various techniques that have been utilized to recognize traffic congestion, presenting an extensive assessment of their individual strengths and weaknesses, thus offering insightful observations about the existing situation in this field of study. The examination of the diverse approaches and advanced technologies that have been utilized for the operation of lane-less roadways have been conducted, revealing substantial potential for further innovations that could greatly assist future researchers in their endeavors to enhance traffic management and improve roadway safety and efficiency.