Smart City Gnosys

Smart city article details

Title	Enhancing Urban Mobility: Machine Learning-Powered Fusion Approach For Intelligent Traffic Congestion Control In Smart Cities
ID_Doc	24066
Authors	Chaudhary A.; Meenakshi M.; Sharma S.; Rahman M.; Srinivasan S.
Year	2025
Published	International Journal of System Assurance Engineering and Management
DOI	http://dx.doi.org/10.1007/s13198-024-02672-6
Abstract	Urban areas encounter a substantial issue of traffic congestion, particularly in smart cities where traffic control techniques must adapt to fluctuating circumstances. The efficacy of the approach can be impacted by variables such as the grade and accessibility of up-to-the-minute traffic data, computer resources and the intricacy of metropolitan road networks. This paper introduces a new method called Dynamic Tabu Search-based Gated Recurrent Units (DTS-GRU) for managing traffic congestion in smart cities. The dataset contains real-time comprising of collected traffic video from Pune city, India, as well as captured footage from highway closed-circuit television (CCTV) cameras which are used to train and assess the DTS-GRU model. The experimental findings validate the efficacy of the DTS-GRU strategy in enhancing traffic flow and mitigating congestion. The simulation was performed using Python software. Our experimental findings show that the suggested strategy is effective in terms of accuracy (93.10%), precision (94.05%), recall (94.60%) and F1-score (92.90%). The findings indicate that the suggested method has the potential to make a substantial impact on alleviating congestion, optimizing traffic movement and promoting urban mobility as a group.
Author Keywords	Dynamic Tabu Search-based Gated Recurrent Units (DTS-GRU); Smart cities; Traffic congestion

Similar Articles

Id	Similarity	Authors	Title	Published
40920	0.906	Abdullah S.M.; Periyasamy M.; Kamaludeen N.A.; Towfek S.K.; Marappan R.; Kidambi Raju S.; Alharbi A.H.; Khafaga D.S.	Optimizing Traffic Flow In Smart Cities: Soft Gru-Based Recurrent Neural Networks For Enhanced Congestion Prediction Using Deep Learning	Sustainability (Switzerland), 15, 7 (2023)
58544	0.904	Sravani B.; Shreyas A.V.; Abbas H.M.; Chanti Y.; Punitha S.	Traffic Congestion Prediction In Smart Cities Using Multilevel-Gated Recurrent Unit	International Conference on Intelligent Algorithms for Computational Intelligence Systems, IACIS 2024 (2024)
49871	0.895	Saleem M.; Abbas S.; Ghazal T.M.; Adnan Khan M.; Sahawneh N.; Ahmad M.	Smart Cities: Fusion-Based Intelligent Traffic Congestion Control System For Vehicular Networks Using Machine Learning Techniques	Egyptian Informatics Journal, 23, 3 (2022)
7046	0.894	Rathore S.P.S.; Farhaoui Y.; Aniebonam E.E.; Nagpal T.; Thanuja M.; Kaushik P.	Ai-Driven Traffic Congestion Management: A Predictive Analytics Approach For Smart Cities	2025 IEEE International Conference on Interdisciplinary Approaches in Technology and Management for Social Innovation, IATMSI 2025 (2025)
58653	0.889	Zafar N.; Haq I.U.; Sohail H.; Chughtai J.-U.-R.; Muneeb M.	Traffic Prediction In Smart Cities Based On Hybrid Feature Space	IEEE Access, 10 (2022)
20250	0.888	Pawar A.B.; Khan S.A.; Baker El-Ebiary Y.A.; Burugari V.K.; Abdufattokhov S.; Saravanan A.; Ghodhbani R.	Digital Twin-Based Predictive Analytics For Urban Traffic Optimization And Smart Infrastructure Management	International Journal of Advanced Computer Science and Applications, 16, 5 (2025)
7669	0.887	Jawad-Ur-Rehman C.; Ul Haq I.; Muneeb M.	An Attention-Based Recurrent Learning Model For Short-Term Travel Time Prediction	PLoS ONE, 17, 12 December (2022)
7345	0.879	Sawah M.S.; Taie S.A.; Ibrahim M.H.; Hussein S.A.	An Accurate Traffic Flow Prediction Using Long-Short Term Memory And Gated Recurrent Unit Networks	Bulletin of Electrical Engineering and Informatics, 12, 3 (2023)
8489	0.879	Sheeba G.; Selvaganesan J.	An Intelligent And Resolute Traffic Management System Using Grcnet-Stmo Model For Smart Vehicular Networks	International Journal of Information Technology (Singapore), 16, 8 (2024)
58620	0.878	Almukhalfi H.; Noor A.; Noor T.H.	Traffic Management Approaches Using Machine Learning And Deep Learning Techniques: A Survey	Engineering Applications of Artificial Intelligence, 133 (2024)