AI-enhanced traffic management
V. Pream Sudha, Rangasamy Suganthi, Malathy Sathyamoorthy, V. Malathy, Krishnan Ravichandran Dhanya · 2026
Urban traffic congestion remains a pressing challenge, affecting travel efficiency, fuel consumption, and environmental sustainability. AI-driven traffic management systems are transforming urban mobility by harnessing the power of predictive analytics, deep learning models, and adaptive traffic control mechanisms. These advanced solutions enable the optimization of traffic flow, the reduction of congestion, and the improvement of overall transportation efficiency. Leveraging Internet of Things (IoT) connectivity and real-time data processing dynamically adjust traffic signals, continuously monitor vehicle movement, and refine route planning to ensure smoother and more responsive urban transportation networks. Furthermore, Vehicle Cloud Computing (VCC) plays a crucial role in modern traffic management by enabling seamless connectivity between vehicles, infrastructure, and cloud-based services. VCC leverages cloud computing to process vast amounts of traffic data, support autonomous vehicle operations, and enhance real-time decision-making. By utilizing cloud-based platforms, vehicles can access live traffic updates, hazard warnings, and optimal route recommendations. Additionally, pay-as-you-go service models in VCC provide scalable solutions for navigation assistance, fleet management, and emergency response, reducing road-related inefficiencies. Despite its promising potential, AI-driven traffic management and VCC face challenges such as data privacy concerns, infrastructure limitations, and the scalability of AI models across diverse urban environments. Overcoming these obstacles requires collaborative efforts among researchers, city planners, and technology providers to establish secure and adaptable AI frameworks. In conclusion, integrating AI-based predictive traffic management with cloud-enabled VCC presents a transformative approach to urban mobility. Continued advancements in AI technologies, coupled with strategic investments in smart infrastructure and cloud-based traffic solutions, will be instrumental in shaping the future of intelligent transportation systems. The integration of AI, IoT, and VCC provides solutions to critical societal challenges, particularly in transportation and urban mobility. By creating a more efficient, sustainable, and intelligent urban infrastructure, these technologies help reduce traffic congestion, enhance road safety, lower environmental impact, and ultimately improve the quality of life for communities worldwide