Smart City Gnosys

Smart city article details

Title	Deep Reinforcement Learning (Drl) For Real-Time Traffic Management In Smart Cities
ID_Doc	18032
Authors	Singh D.
Year	2023
Published	2023 International Conference on Communication, Security and Artificial Intelligence, ICCSAI 2023
DOI	http://dx.doi.org/10.1109/ICCSAI59793.2023.10421359
Abstract	With the advent of smart urban spaces, efficient and flexible traffic management has become a necessity. The changing nature of urban traffic makes traditional traffic management systems - which rely on pre-established systems - inefficient. This study presents a deep reinforcement learning (DRL) model for real-time traffic management in smart cities. To optimize traffic flow and reduce congestion, the model uses deep-rooted reinforcement learning to automatically adapt to changing traffic conditions Urbanized several simulated systems representing a range of vehicle scenarios were used to evaluate our technology. According to the results, the traffic volume increased significantly and the typical waiting time decreased compared to the traditional traffic management system. The program can also successfully accommodate unexpected traffic incidents such as accidents or roadblocks. This study demonstrates the potential of DRL to transform urban traffic management and create a more sustainable, efficient and effective smart city. © 2023 IEEE.
Author Keywords	Deep Reinforcement Learning; Real-time Adaptation; Smart Cities; Traffic Control; Urban Traffic Management

Similar Articles

Id	Similarity	Authors	Title	Published
18053	0.945	Kansal V.; Shnain A.H.; Deepak A.; Rana A.; Manjunatha; Dixit K.K.; Rajkumar K.V.	Deep Reinforcement Learning For Iot-Based Smart Traffic Management Systems	Proceedings of International Conference on Contemporary Computing and Informatics, IC3I 2024 (2024)
23735	0.944	Sattarzadeh A.R.; Pathirana P.N.	Enhancing Adaptive Traffic Control Systems With Deep Reinforcement Learning And Graphical Models	Proceedings - 2024 IEEE International Conference on Future Machine Learning and Data Science, FMLDS 2024 (2024)
18057	0.942	Mittal M.; Sehgal A.; Varshney N.; Kumar S.P.; Boob N.S.; Reddy R.A.	Deep Reinforcement Learning For Optimizing Route Planning In Urban Traffic	IEEE International Conference on "Computational, Communication and Information Technology", ICCCIT 2025 (2025)
38098	0.924	Fereidooni Z.; Palesi L.A.I.; Nesi P.	Multi-Agent Optimizing Traffic Light Signals Using Deep Reinforcement Learning	IEEE Access, 13 (2025)
11516	0.917	Giannini F.; Franze G.; Pupo F.; Fortino G.	Autonomous Vehicles In Smart Cities: A Deep Reinforcement Learning Solution	Proceedings of the 2022 IEEE International Conference on Dependable, Autonomic and Secure Computing, International Conference on Pervasive Intelligence and Computing, International Conference on Cloud and Big Data Computing, International Conference on Cyber Science and Technology Congress, DASC/PiCom/CBDCom/CyberSciTech 2022 (2022)
43250	0.913	Sattarzadeh A.R.; Pathirana P.N.	Probabilistic Graph Models: A Key To Boosting Deep Reinforcement Learning In Urban Traffic Networks	2025 17th International Conference on Computer and Automation Engineering, ICCAE 2025 (2025)
6359	0.905	Rao P.S.V.S.; Bhadula S.; Balasubramani R.; Suryawanshi P.B.; Yadav A.K.; Vekariya D.	Adaptive Traffic Management In Smart Cities Using Deep Reinforcement Learning For Iot Mobile Ad Hoc Networks	2nd International Conference on Intelligent Cyber Physical Systems and Internet of Things, ICoICI 2024 - Proceedings (2024)
18026	0.905	Faqir N.; En-Nahnahi N.; Boumhidi J.	Deep Q-Learning Approach For Congestion Problem In Smart Cities	4th International Conference on Intelligent Computing in Data Sciences, ICDS 2020 (2020)
1392	0.902	Yiğit Y.; Karabatak M.	A Deep Reinforcement Learning-Based Speed Optimization System To Reduce Fuel Consumption And Emissions For Smart Cities	Applied Sciences (Switzerland), 15, 3 (2025)
6356	0.899	Kumar R.; Sharma N.V.K.; Chaurasiya V.K.	Adaptive Traffic Light Control Using Deep Reinforcement Learning Technique	Multimedia Tools and Applications, 83, 5 (2024)