Study of Intelligent Traffic Management System for North India

Abstract

In recent years, the urbanization in North Indian cities has been accelerated at such a rate and existing road infrastructure has been suffocated to such an extent, the traffic congestion has been made too thick, the travel time is too long, the vehicular emissions and the amount of fuel consumption are too high. The traditional traffic control mechanisms are now obsolete in cities like Delhi, Chandigarh, Lucknow, Jaipur which have experienced exponential growth in the population and entries of the vehicles. However, these legacy systems are built on fixed time signal control, as well as manual surveillance, they are not flexible nor scalable enough to cope with the demand of the modern dynamic urban mobility problems. This research presents that there is the feasibility and the effectiveness of implementing an Intelligent Traffic Management System (ITMS) designed specifically for these urban centers. The study takes a systematic review on the current traffic patterns and infrastructure limitations leveraging machine learning algorithms, real time traffic data and Internet of Things (IoT) technologies. Data driven diagnostics find key congestion points, and a modelled integration of adaptive traffic signals, ANPR and smart surveillance is used to evaluate operational enhancement. Advanced traffic engineering tools are used to simulate traffic flow efficiency, commuter safety, and environmental sustainability potential improvements. The findings point to the need to accelerate towards intelligent, data-centric solutions for urban mobility of North India.