On Smart Traffic Management
DOI:
https://doi.org/10.15662/IJEETR.2026.0802027Keywords:
Bug Triaging, Machine Learning, Open-Source Software, Issue Classification, Software MaintenanceAbstract
Efficient traffic management systems are required due to the rising traffic congestion caused by the rapid rise of urbanization. The goal of this project, "On Smart Traffic Management," is to use cutting-edge machine learning algorithms to forecast traffic situations (Low, Normal, High, and Heavy). Although effective, the current system's use of Long Short-Term Memory (LSTM) and Logistic Regression may not adequately account for the intricacies of traffic dynamics. On the other hand, the suggested system combines the Random Forest, XGBoost, and Decision Tree algorithms to improve the accuracy and dependability of predictions. This research aims to create a reliable model for forecasting traffic patterns by utilizing historical traffic data, environmental variables, and real-time inputs
While the back-end is created in Python to provide smooth data processing and analysis, the front-end is created with HTML, CSS, and JavaScript to create an intuitive user experience. An intelligent traffic management system that offers real-time traffic forecasts is the expected result, which will help reduce traffic and enhance urban mobility in general
References
1. KHALIL M. YOUSEF, JAMAL N. AL-KARAKI and ALI M. SHATNAWI, "Intelligent Traffic Light Flow Control System Using Wireless Sensors Networks", Journal Of Information Science And Engineering, vol. 26, pp. 753-768, 2010.
2. S. Coleri, S. Y. Cheung and P. Varaiya, "Sensor networks for monitoring traffic", Proceedings of the 42nd Annual Allerton Conference on Communication Control and Computing, pp. 32-40, 2004.
3. Greater Amman Municipality, “Traffic report study 2007,” http://www.ammancity. gov.jo/arabic/docs/GAM4-2007.pdf.
4. The Vehicle Detector Clearinghouse, “A summary of vehicle detection and surveillance technologies used in intelligent transportation systems,” Southwest Technology Development Institute, 2000.
5. C.Nagarajan and M.Madheswaran - ‘Stability Analysis of Series Parallel Resonant Converter with Fuzzy Logic Controller Using State Space Techniques’- Taylor &Francis, Electric Power Components and Systems, Vol.39 (8), pp.780-793, May 2011. DOI: 10.1080/15325008.2010.541746
6. C.Nagarajan and M.Madheswaran - ‘Experimental verification and stability state space analysis of CLL-T Series Parallel Resonant Converter’ - Journal of Electrical Engineering, Vol.63 (6), pp.365-372, Dec.2012. DOI: 10.2478/v10187-012-0054-2
7. C.Nagarajan and M.Madheswaran - ‘Performance Analysis of LCL-T Resonant Converter with Fuzzy/PID Using State Space Analysis’- Springer, Electrical Engineering, Vol.93 (3), pp.167-178, September 2011. DOI 10.1007/s00202-011-0203-9
8. S.Tamilselvi, R.Prakash, C.Nagarajan,“Solar System Integrated Smart Grid Utilizing Hybrid Coot-Genetic Algorithm Optimized ANN Controller” Iranian Journal Of Science And Technology-Transactions Of Electrical Engineering, DOI10.1007/s40998-025-00917-z,2025
9. S.Tamilselvi, R.Prakash, C.Nagarajan,“ Adaptive sliding mode control of multilevel grid-connected inverters using reinforcement learning for enhanced LVRT performance” Electric Power Systems Research 253 (2026) 112428, doi.org/10.1016/j.epsr.2025.112428
10. S.Thirunavukkarasu, C. Nagarajan, 2024, “Performance Investigation on OCF and SCF study in BLDC machine using FTANN Controller," Journal of Electrical Engineering And Technology, Volume 20, pages 2675–2688, (2025), doi.org/10.1007/s42835-024-02126-w
11. C. Nagarajan, M.Madheswaran and D.Ramasubramanian- ‘Development of DSP based Robust Control Method for General Resonant Converter Topologies using Transfer Function Model’- Acta Electrotechnica et Informatica Journal , Vol.13 (2), pp.18-31,April-June.2013, DOI: 10.2478/aeei-2013-0025.
12. C.Nagarajan and M.Madheswaran - ‘DSP Based Fuzzy Controller for Series Parallel Resonant converter’- Springer, Frontiers of Electrical and Electronic Engineering, Vol. 7(4), pp. 438-446, Dec.12. DOI 10.1007/s11460-012-0212-0.
13. C.Nagarajan and M.Madheswaran - ‘Experimental Study and steady state stability analysis of CLL-T Series Parallel Resonant Converter with Fuzzy controller using State Space Analysis’- Iranian Journal of Electrical & Electronic Engineering, Vol.8 (3), pp.259-267, September 2012.
14. C.Nagarajan and M.Madheswaran, “Analysis and Simulation of LCL Series Resonant Full Bridge Converter Using PWM Technique with Load Independent Operation” has been presented in ICTES’08, a IEEE / IET International Conference organized by M.G.R.University, Chennai.Vol.no.1, pp.190-195, Dec.2007
15. Suganthi Mullainathan, Ramesh Natarajan, “An SPSS and CNN modelling based quality assessment using ceramic materials and membrane filtration techniques”, Revista Materia (Rio J.) Vol. 30, 2025, DOI: https://doi.org/10.1590/1517-7076-RMAT-2024-0721
16. M Suganthi, N Ramesh, “Treatment of water using natural zeolite as membrane filter”, Journal of Environmental Protection and Ecology, Volume 23, Issue 2, pp: 520-530,2022
17. M. Tubaishat, Q. Qi, Y. Shang and H. Shi, “Wireless sensor-based traffic light control,” IEEE CCNC, LasVegas, NV, USA, (2008), pp. 702-706.
18. J. Yousef and Ali, “Intelligent Traffic Light Flow Control System Using Wireless Sensors Networks,” Journal of Information Science and Engineering, vol. 26, no. 3, (2010), pp. 753-768.
19. C. Cai, C. K. Wong and B. G. Heydecker, “Adaptive traffic signal control using approximate dynamic programming,” Elsevier Transportation Research Part C, vol. 17, (2009), pp. 456-474.
20. Ashish, M. Manisha, V. Harish and R. Amrita, "Traffic Density Measurement based On-road Traffic Control using Ultrasonic Sensors and GSM Technology", proc. AEEE 4th International Conference on Emerging Trends in Engineering and Technology Kurushetra, pp. 778-786, 2013, October 25-27.
21. Tamás Tettamanti, "Wireless Traffic Signal Controller with Distributed Control System Architecture", PeriodicaPolytechnica Civil Engineering, vol. 63, no. 3, pp. 918-925, 2019.
22. Younes MB and A Boukerche, "Traffic efficiency applications over downtown roads: a new challenge for intelligent connected vehicles", ACM Computing Surveys (CSUR), vol. 53, no. 5, pp. 1-30, Sep 2020.
