SMART TRANSPORTATION SYSTEMS FOR URBAN MOBILITY AND CONGESTION REDUCTION

Abstract

The city jams and commuting in cities worldwide have become a nightmare due to rapid urbanization and the increased number of cars. This paper will analyse how smart transportation systems can be effective in improving the movement and reducing congestion within a city by implementing intelligent technologies. The paper evaluates the impacts of adaptive traffic control, real-time traffic monitoring, smart parking, and smart public transit management on the basis of traffic performance indicators, system efficiency metrics, and environmental results. The findings indicate that intelligent transport systems contribute greatly to efficiency and reduce travel time on the average and congestion indices along the urban routes. The increase in the effectiveness of the public transport and the ability to predict the schedule had made people start using it more and a definite shift toward not driving their own vehicles. The findings also indicate that the decrease in the use of fuel and greenhouse gases is a consequence of a smoother flow of traffic and the choice of routes. The IoT sensors and analytics platforms which allow you to make decisions based on the data mattered a lot as far as proactive congestion control and long-term planning of the transportation in the cities are concerned. The research establishes that system integration issues, data protection as well as costs of implementation have challenges, although the gains are enormous. In general, the findings demonstrate that intelligent transport systems are a potent and durable solution to the challenges of contemporary city mobility. They embrace efficient, environment-friendly, and service-oriented transportation systems.