Traffic Traps: An Investigation into Road Congestion Management

Abstract

Abstract: Urban traffic congestion presents a significant global challenge, necessitating effective traffic management for seamless transportation system operations. This study emphasizes the implementation of an Intelligent Traffic Management System (ITMS) capable of real-time monitoring and control. Focusing on Mattoor Junction in Ernakulam, Kerala, this research applies distinct algorithms in Python and MATLAB, introducing three key equations: Average Traffic Flow (ATF), Traffic Variability Index (TVI), and Time-of-Day Congestion Index (CI). The methodology involves a detailed survey of the route, traffic volume counts, spot speed studies, and roadside interviews to gather data. The ATF, TVI, and CI equations are used to analyze traffic patterns, variability, and congestion levels. The findings reveal significant congestion on critical routes intersecting at Mattoor Junction, particularly during peak hours. To address this, the study proposes the implementation of an automated traffic signal system, optimizing signal timings. This intervention aims to enhance traffic flow and reduce congestion. The research underscores the potential of ITMS for real-time traffic management, offering a data-driven approach to urban traffic challenges. The integration of theoretical models with empirical data provides a comprehensive framework for future ITMS strategies, contributing to more efficient and adaptive urban traffic management