Smart City Gnosys

Smart city article details

Title Efficient Traffic Routing With Temporal Fusion Transformers: Addressing Urban Congestion Challenges
ID_Doc 22428
Authors Sreelekha M.; Janarthanan M.
Year 2024
Published SSRG International Journal of Electronics and Communication Engineering, 11, 11
DOI http://dx.doi.org/10.14445/23488549/IJECE-V11I11P117
Abstract The exponential increase in urban population necessitates the emergence of transportation systems that are both effective and sustainable, using the potential modern technology. The issue of dynamic traffic flow significantly impedes the movement of vehicles. Traffic congestion is a critical issue affecting urban mobility and efficiency in cities worldwide, with Bangalore no exception. This study addresses the challenge of leveraging advanced predictive analytics and intelligent transport systems to manage traffic congestion. The proposed research aims to address the limitations of traditional traffic management strategies by integrating the Temporal Fusion Transformer (TFT) model into an Intelligent Transport System (ITS) framework. The research employs rigorous data preprocessing techniques to leverage extensive data from multiple online map service providers and traffic monitoring platforms, spanning from January 1, 2019, to December 31, 2023. The TFT model forecasts traffic congestion with notable precision, achieving a Mean Absolute Error (MAE) of 0.39, Mean Squared Error (MSE) of 0.30, Root Mean Squared Error (RMSE) of 0.55, Mean Absolute Percentage Error (MAPE) of 7.2%, and an R-squared (R²) value of 0.87. The outcomes obtained clearly illustrate the model’s superior accuracy and efficacy. Integrating TFT predictions into the ITS framework enhances real-time traffic control by improving the timings of traffic signals, recommending alternative routes, and improving incident management. This proactive approach significantly reduces traffic congestion and enhances travel efficiency, substantially advancing urban traffic management solutions. © 2024 Seventh Sense Research Group®.
Author Keywords Intelligent Transport System; Smart city; Temporal Fusion Transformer; Traffic congestion; Traffic volume


Similar Articles


Id Similarity Authors Title Published
27462 View0.897Ait Ouallane A.; Bakali A.; Bahnasse A.; Broumi S.; Talea M.Fusion Of Engineering Insights And Emerging Trends: Intelligent Urban Traffic Management SystemInformation Fusion, 88 (2022)
32238 View0.892Jain V.; Mitra A.Integrative Hybrid Information Systems For Enhanced Traffic Maintenance And Control In Bangalore: A Synchronized ApproachHybrid Information Systems: Non-Linear Optimization Strategies with Artificial Intelligence (2024)
32025 View0.883Fatorachian H.; Kazemi H.Integrating Learning-Based Solutions In Intelligent Transportation Systems: A Conceptual Framework And Case Studies ValidationCogent Engineering, 11, 1 (2024)
29107 View0.882Silva P.; Smolková P.; Michailidu S.; Beránek J.; Macháček R.; Slaninová K.; Martinovič J.; Cmar R.High-Performance Computing For Distributed Route Computation In Traffic Flow ModelsProcedia Computer Science, 255 (2025)
44733 View0.88Karthick Raghunath K.M.; Rohith Bhat C.; Vinoth Kumar V.; Athiyoor Kannan V.; Mahesh T.R.; Manikandan K.; Krishnamoorthy N.Redefining Urban Traffic Dynamics With Tcn-Fl Driven Traffic Prediction And Control StrategiesIEEE Access, 12 (2024)
38883 View0.88Kumar A.; Batra N.; Mudgal A.; Yadav A.L.Navigating Urban Mobility: A Review Of Ai-Driven Traffic Flow Management In Smart Cities2024 11th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions), ICRITO 2024 (2024)
38283 View0.879Dhanasekaran S.; Gopal D.; Logeshwaran J.; Ramya N.; Salau A.O.Multi-Model Traffic Forecasting In Smart Cities Using Graph Neural Networks And Transformer-Based Multi-Source Visual Fusion For Intelligent Transportation ManagementInternational Journal of Intelligent Transportation Systems Research, 22, 3 (2024)
735 View0.879Djahel, S; Doolan, R; Muntean, GM; Murphy, JA Communications-Oriented Perspective On Traffic Management Systems For Smart Cities: Challenges And Innovative ApproachesIEEE COMMUNICATIONS SURVEYS AND TUTORIALS, 17, 1 (2015)
20250 View0.877Pawar 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 ManagementInternational Journal of Advanced Computer Science and Applications, 16, 5 (2025)
6459 View0.877Aroba O.J.; Mabuza P.; Mabaso A.; Sibisi P.Adoption Of Smart Traffic System To Reduce Traffic Congestion In A Smart CityLecture Notes in Networks and Systems, 668 LNNS (2023)