• Naveen Thakur
• Nitesh Bhalerao
• Poonam Bhadouriya
• Pradeep Sawant
• H. R. Kulkarni,Madhuri Pise

Rapid urbanization and the unprecedented rise in vehicle ownership have led to chronic traffic congestion in major Indian cities, with Pune emerging as a critical hotspot. Traditional traffic management techniques—such as static signal timers, manual control, and non-adaptive routing—are insufficient to cope with the dynamic nature of today’s traffic demands. This review provides an in-depth examination of Artificial Intelligence (AI) applications in traffic management, including adaptive traffic signals, machine learning-based congestion forecasting, computer vision-driven vehicle detection, and IoT-enabled real-time monitoring. Evidence from global deployments, Indian pilot projects, and Pune’s recent smart traffic initiatives demonstrates the transformative potential of AI in reducing delays, improving travel efficiency, enhancing road safety, and lowering emissions. Despite the promise, challenges such as infrastructure readiness, data accuracy, privacy concerns, and high implementation cost persist. This paper synthesizes existing research, evaluates AI’s applicability to Pune, and offers policy recommendations to support sustainable, smart urban mobility.

Review on AI for Traffic Management

"Review on AI for Traffic Management", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.13, Issue 1, page no.126-134, January-2026, Available :http://www.jetir.org/papers/JETIRHG06013.pdf

"Review on AI for Traffic Management", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.13, Issue 1, page no. pp126-134, January-2026, Available at : http://www.jetir.org/papers/JETIRHG06013.pdf