Design and Implementation of a Novel Architecture Based on Digital Twin and GIS for Intelligent Traffic Monitoring
Subject Areas :
zahra rezaee
1
,
hossein aghamohammadi
2
*
,
محمد حسن وحیدنیا
3
,
زهرا عزیزی
4
,
Saeed Behzadi
5
1 -
2 - Assistant Professor, Department of Remote Sensing and GIS, Science and Research Branch, Islamic Azad University, Tehran, Iran
3 - -3Assistant Professor, Center for Remote Sensing and GIS Research, Faculty of Earth Sciences, Shahid Beheshti University, Tehran, Iran
4 - Assistant Professor, Department of Remote Sensing and GIS, Science and Research Branch, Islamic Azad University, Tehran, Iran
5 - Associated Professor, Department of Surveying Engineering, Faculty of Civil, Water and Environmental Engineering, Shahid Beheshti University, Tehran, Iran
Keywords: Smart City, Digital Twin, Urban Traffic Management, GIS, Traffic Prediction,
Abstract :
The rapid growth of urbanization and the increasing number of motor vehicles have created significant challenges in urban traffic management. Heavy traffic not only leads to time wastage and increased air pollution but can also hinder quick and effective responses to emergencies such as accidents and natural disasters. In this context, advanced technologies such as Digital Twin and Geographic Information Systems (GIS) have gained attention as powerful tools for intelligent traffic management and improving emergency responses. This research aims to develop a location-based simulation model using Digital Twin and GIS to predict traffic and enhance urban traffic management. In this study, a digital twin system was designed and implemented using real-time data, such as traffic information and weather conditions, leveraging online services. The results demonstrate that this system can accurately monitor and predict traffic conditions, and its capabilities can subsequently be utilized in applications such as optimal routing and traffic reduction. Additionally, the online dashboard developed in this research provides real-time access to traffic and environmental data, significantly aiding decision-making and urban traffic management. This innovative approach represents a significant step toward smart traffic management and lays the groundwork for creating smart cities and improving urban quality of life.
1) Manfred Boltze, Vu Anh Tuan, Approaches to Achieve Sustainability in Traffic Management, Procedia Engineering, Volume 142, 2016, Pages 205-212, ISSN 1877-7058, https://doi.org/10.1016/j.proeng.2016.02.033.
2) R. Abdellah, O. A. K. Mahmood, A. Paramonov and A. Koucheryavy, "IoT traffic prediction using multi-step ahead prediction with neural network," 2019 11th International Congress on Ultra Modern Telecommunications and Control Systems and Workshops (ICUMT), 2019, pp. 1-4, doi: 10.1109/ICUMT48472.2019.8970675.
3) Nie L, Wang X, Zhao Q, Shang Z, Feng L, Li G. DT for transportation big data: a reinforcement learning-based network traffic prediction approach. IEEE Transactions on Intelligent Transportation Systems. 2023 Jan 18;25(1):896-906.
4) Zhang Y, Zhang H. Urban digital twins: decision-making models for transportation network simulation. In Proceedings of the 2022 International Conference on Computational Infrastructure and Urban Planning 2022 Jun 18 (pp. 18-21).
5) Rezaei Z, Vahidnia MH, Aghamohammadi H, Azizi Z, Behzadi S. Digital twins and 3D information modeling in a smart city for traffic controlling: A review. Journal of Geography and Cartography. 2023 Jun 27;6(1):1865.
6) Muthuramalingam S, Bharathi A, Rakesh Kumar S, Gayathri N, Sathiyaraj R, Balamurugan B. IoT based intelligent transportation system (IoT-ITS) for global perspective: A case study. Internet of things and big data analytics for smart generation. 2019:279-300.
7) Vaidya RB, Kulkarni S, Didore V. Intelligent transportation system using IOT: A Review. Int. J. Res. Trends Innov. 2021;6:80-7.
8) Schleich B, Anwer N, Mathieu L, Wartzack S. Shaping the digital twin for design and production engineering. CIRP Annals 2017; 66(1): 141–144. doi: 10.1016/j.cirp.2017.04.040
9) Korth B, Schwede C, Zajac M. Simulation-ready digital twin for realtime management of logistics systems. In2018 IEEE international conference on big data (big data) 2018 Dec 10 (pp. 4194-4201). IEEE.
10) Grieves M, Vickers J, Twin D. Mitigating unpredictable, undesirable emergent behavior in complex systems. Transdisciplinary Perspectives on Complex Systems. 2016:85-113.
11) Liu M, Fang S, Dong H, Xu C. Review of digital twin about concepts, technologies, and industrial applications. Journal of Manufacturing Systems 2021; 58(Part B): 346–361. doi: 10.1016/j.jm¬sy.2020.06.017.
12) Del Giudice M, Osello A (editors). Handbook of research on developing smart cities based on digital twins. Hershey: IGI Global; 2021.
13) Tao F, Cheng J, Qi Q, et al. Digital twin-driven product design, manufacturing and service with big data. The International Journal of Advanced Man¬ufacturing Technology 2018; 94: 3563–3576. doi: 10.1007/s00170-017-0233-1.
14) Wladimir Hofmann, Fredrik Branding, Implementation of an IoT- and Cloud-based Digital Twin for Real-Time Decision Support in Port Operations, IFAC-PapersOnLine, Volume 52, Issue 13, 2019, Pages 2104-2109, ISSN 2405-8963, https://doi.org/10.1016/j.ifacol.2019.11.516.
15) Kumar SAP, Madhumathi R, Chelliah PR, et al. A novel digital twin-centric approach for driver in¬tention prediction and traffic congestion avoidance. Journal of Reliable Intelligent Environments 2018;
16) T. Ambra and C. Macharis, "Agent-Based Digital Twins (ABM-Dt) In Synchromodal Transport and Logistics: the Fusion of Virtual and Pysical Spaces," 2020 Winter Simulation Conference (WSC), 2020, pp. 159-169, doi: 10.1109/WSC48552.2020.9383955.
17) Jiang W, Luo J. Graph neural network for traffic forecasting: A survey. Expert systems with applications. 2022 Nov 30;207:117921.
18) Kadar Muhammad Masum, M. Kalim Amzad Chy, I. Rahman, M. Nazim Uddin and K. Islam Azam, "An Internet of Things (IoT) based Smart Traffic Management System: A Context of Bangladesh," 2018 International Conference on Innovations in Science, Engineering and Technology (ICISET), 2018, pp. 418-422, doi: 10.1109/ICISET.2018.8745611.
19) Mohammed Sarrab, Supriya Pulparambil, Medhat Awadalla, Development of an IoT based real-time traffic monitoring system for city governance, Global Transitions, Volume 2 2020, Pages 230-245, ISSN 2589-7918, https://doi.org/10.1016/j.glt.2020.09.004.
20) https://www.google.com/maps