Smart City Gnosys

Smart city article details

Title	Intelligent Traffic Systems: A Graph Analytics Approach For Sustainable Transportation Networks Using Bengaluru Traffic
ID_Doc	32624
Authors	Rakshika S.; Shravya U.; Roy Dey S.
Year	2023
Published	2023 International Conference on Network, Multimedia and Information Technology, NMITCON 2023
DOI	http://dx.doi.org/10.1109/NMITCON58196.2023.10275919
Abstract	Millions of people's daily commutes are impacted by serious problems with urban transportation networks, such as congestion, delays, and accidents. Rapid urbanization, poor infrastructure, and insufficient traffic management systems are frequently blamed for these problems. An intelligent Traffic system is essential to solve these issues and improve the effectiveness, and sustainability of transportation systems. This investigation aims to perform an in-depth network analysis using the case of Bengaluru, an urban city of India, utilizing graph analytics techniques. Centrality measures are used to identify critical nodes and road segments that critically contribute to traffic congestion. Further, Community detection algorithms uncover clusters of areas with similar traffic patterns and congestion hotspots. Lastly, link prediction methods forecast future traffic flows and indicate potential bottlenecks. The research findings provide data-driven insights and recommendations for improving the efficiency and sustainability of transportation in Bengaluru. The findings of this study can go beyond Bengaluru, serving as a valuable resource for those making decisions, transportation organizations, and urban planners in quickly expanding urban areas with comparable transportation difficulties. © 2023 IEEE.
Author Keywords	Centrality Measures; Community detection; Graph Analytics; Intelligent Traffic systems; Link Prediction; Traffic analysis

Similar Articles

Id	Similarity	Authors	Title	Published
28277	0.924	Mohanty A.; Mohapatra A.G.; Mohanty S.K.	Graph-Based Analysis For Optimizing Traffic Flow In Urban Networks	Neural Networks and Graph Models for Traffic and Energy Systems (2025)
32238	0.908	Jain V.; Mitra A.	Integrative Hybrid Information Systems For Enhanced Traffic Maintenance And Control In Bangalore: A Synchronized Approach	Hybrid Information Systems: Non-Linear Optimization Strategies with Artificial Intelligence (2024)
14795	0.886	Dogo E.M.; Makaba T.; Afolabi O.J.; Ajibo A.C.	Combating Road Traffic Congestion With Big Data: A Bibliometric Review And Analysis Of Scientific Research	EAI/Springer Innovations in Communication and Computing (2021)
5752	0.88	Gupta K.; Lee C.-N.	A Vehicle Congestion Prediction Approach For Smart City Traffic Management	Procedia Computer Science, 260 (2025)
46591	0.88	Deveshwar P.; Singh T.; Sharma Y.; Bidwe R.V.; Hiremani V.; Devadas R.; Shah K.	Revolutionizing Smart Cities: A Data-Driven Traffic Monitoring System For Real-Time Traffic Density Estimation And Visualization	Lecture Notes in Networks and Systems, 1075 LNNS (2025)
38883	0.879	Kumar A.; Batra N.; Mudgal A.; Yadav A.L.	Navigating Urban Mobility: A Review Of Ai-Driven Traffic Flow Management In Smart Cities	2024 11th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions), ICRITO 2024 (2024)
58162	0.878	Tao X.; Cheng L.; Zhang R.; Chan W.K.; Chao H.; Qin J.	Towards Green Innovation In Smart Cities: Leveraging Traffic Flow Prediction With Machine Learning Algorithms For Sustainable Transportation Systems	Sustainability (Switzerland), 16, 1 (2024)
50555	0.876	Zubairi J.A.; Idwan S.; Haider S.A.; Hurtgen D.	Smart City Traffic Management For Reducing Congestion	IEEE 19th International Conference on Smart Communities: Improving Quality of Life Using ICT, IoT and AI, HONET 2022 (2022)
22428	0.875	Sreelekha M.; Janarthanan M.	Efficient Traffic Routing With Temporal Fusion Transformers: Addressing Urban Congestion Challenges	SSRG International Journal of Electronics and Communication Engineering, 11, 11 (2024)
38283	0.875	Dhanasekaran 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 Management	International Journal of Intelligent Transportation Systems Research, 22, 3 (2024)