Abstract -Pune, one of India’s fastest-growing metropolitan cities, faces severe traffic congestion due to rapid urbanization, increasing vehicular density, and inadequate transport infrastructure. This research paper explores the challenges associated with traffic management in Pune and evaluates existing solutions implemented by local authorities. Through case studies of critical traffic zones such as Katraj, Nal Stop, Warje, and Hadapsar Road, we identify key congestion factors, including poor road design, improper parking, and ineffective signal coordination. Several traffic management strategies have been adopted to mitigate these issues, such as road widening, signal optimization, and strict enforcement against encroachments. However, despite these measures, congestion persists due to inconsistent implementation and a lack of integrated solutions. This paper proposes the deployment of Intelligent Traffic Management Systems (ITMS) to enhance real-time traffic monitoring and regulation. ITMS leverages Artificial Intelligence (AI), Internet of Things (IoT), and Big Data Analytics to optimize traffic flow, detect violations, and predict congestion trends. A case study of the Mumbai-Pune Expressway’s Zero Fatality Corridor demonstrates how AI-driven interventions led to a 52% reduction in accident fatalities over four years .The study highlights that a multi-pronged approach, integrating ITMS with improved infrastructure planning and public transportation enhancements, is essential for sustainable urban mobility. Results suggest that Pune can significantly reduce traffic congestion and road accidents by adopting technology-driven traffic management solutions. The paper concludes by emphasizing the need for continued research into autonomous traffic control systems, dynamic traffic light coordination, and policy reforms to ensure long-term efficiency.

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1. Pune Traffic Congestion: Reality, Cause and Regulation – A Case Studyhttps://papers.ssrn.com/sol3/papers.cfm?abstract_id=3573469
2. Pune Traffic Congestion: Reality, Cause and Regulation—A Case Study Authors: S. Apte, R. R. Deshpande
3. Apte, S.S. & Deshpande, R.R. (2020). Pune Traffic Congestion: Reality, Cause and Regulation. SSRN.
4. Singh, A. et al. (2019). Urban Traffic Management in India. Indian Journal of Transportation.
5. Apte, S. S., & Deshpande, R. R. (2020). Pune Traffic Congestion: Reality, Cause and Regulation – A Case Study. SSRN. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3573469
6. Singh, A., Sharma, P., & Mehta, R. (2019). Urban Traffic Management in India. Indian Journal of Transportation, 45(3), 112–125.
7. Greenshields, B. D. (1935). A Study of Traffic Capacity. Highway Research Board Proceedings, 14, 448–477.
8. Bertalanffy, L. von (1968). General System Theory: Foundations, Development, Applications. George Braziller.
9. Caragliu, A., Del Bo, C., & Nijkamp, P. (2011). Smart Cities in Europe. Journal of Urban Technology, 18(2), 65–82.
10. Fuller, R. (2005). Towards a General Theory of Driver Behaviour. Elsevier.
11. Sivaraman, V., & Kumar, N. (2021). AI-Based Traffic Signal Control Systems: A Review. International Journal of Advanced Research in Computer Science and Software Engineering, 11(7), 45–52.
12. Tan, J., Wong, K., & Lee, S. (2018). Predictive Traffic Flow Analytics Using Big Data Techniques. Transportation Research Part C, 95, 560–573.
13. Lee, H., & Park, S. (2017). IoT-Enabled Smart Parking Solutions for Urban Environments. Journal of Transportation Technologies, 7(3), 123–134.
14. World Economic Forum. (2020). Shaping the Future of Mobility: AI and Connected Infrastructure for Smart Cities. WEF Reports.

Abstract -Pune, one of India’s fastest-growing metropolitan cities, faces severe traffic congestion due to rapid urbanization, increasing vehicular density, and inadequate transport infrastructure. This research paper explores the challenges associated with traffic management in Pune and evaluates existing solutions implemented by local authorities. Through case studies of critical traffic zones such as Katraj, Nal Stop, Warje, and Hadapsar Road, we identify key congestion factors, including poor road design, improper parking, and ineffective signal coordination. Several traffic management strategies have been adopted to mitigate these issues, such as road widening, signal optimization, and strict enforcement against encroachments. However, despite these measures, congestion persists due to inconsistent implementation and a lack of integrated solutions. This paper proposes the deployment of Intelligent Traffic Management Systems (ITMS) to enhance real-time traffic monitoring and regulation. ITMS leverages Artificial Intelligence (AI), Internet of Things (IoT), and Big Data Analytics to optimize traffic flow, detect violations, and predict congestion trends. A case study of the Mumbai-Pune Expressway’s Zero Fatality Corridor demonstrates how AI-driven interventions led to a 52% reduction in accident fatalities over four years .The study highlights that a multi-pronged approach, integrating ITMS with improved infrastructure planning and public transportation enhancements, is essential for sustainable urban mobility. Results suggest that Pune can significantly reduce traffic congestion and road accidents by adopting technology-driven traffic management solutions. The paper concludes by emphasizing the need for continued research into autonomous traffic control systems, dynamic traffic light coordination, and policy reforms to ensure long-term efficiency.

🔒 This is a subscription article

Full text is available to subscribers and institutional members. Please choose an option below to access it.

1. Pune Traffic Congestion: Reality, Cause and Regulation – A Case Studyhttps://papers.ssrn.com/sol3/papers.cfm?abstract_id=3573469
2. Pune Traffic Congestion: Reality, Cause and Regulation—A Case Study Authors: S. Apte, R. R. Deshpande
3. Apte, S.S. & Deshpande, R.R. (2020). Pune Traffic Congestion: Reality, Cause and Regulation. SSRN.
4. Singh, A. et al. (2019). Urban Traffic Management in India. Indian Journal of Transportation.
5. Apte, S. S., & Deshpande, R. R. (2020). Pune Traffic Congestion: Reality, Cause and Regulation – A Case Study. SSRN. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3573469
6. Singh, A., Sharma, P., & Mehta, R. (2019). Urban Traffic Management in India. Indian Journal of Transportation, 45(3), 112–125.
7. Greenshields, B. D. (1935). A Study of Traffic Capacity. Highway Research Board Proceedings, 14, 448–477.
8. Bertalanffy, L. von (1968). General System Theory: Foundations, Development, Applications. George Braziller.
9. Caragliu, A., Del Bo, C., & Nijkamp, P. (2011). Smart Cities in Europe. Journal of Urban Technology, 18(2), 65–82.
10. Fuller, R. (2005). Towards a General Theory of Driver Behaviour. Elsevier.
11. Sivaraman, V., & Kumar, N. (2021). AI-Based Traffic Signal Control Systems: A Review. International Journal of Advanced Research in Computer Science and Software Engineering, 11(7), 45–52.
12. Tan, J., Wong, K., & Lee, S. (2018). Predictive Traffic Flow Analytics Using Big Data Techniques. Transportation Research Part C, 95, 560–573.
13. Lee, H., & Park, S. (2017). IoT-Enabled Smart Parking Solutions for Urban Environments. Journal of Transportation Technologies, 7(3), 123–134.
14. World Economic Forum. (2020). Shaping the Future of Mobility: AI and Connected Infrastructure for Smart Cities. WEF Reports.