Innovative approaches to traffic management based on digital twins of road networks

Introduction. The article considers the development of the theoretical model for the implementation of digital twins of highways and assesses their effectiveness within the traffic management system, adapting their construction principles to the specifics of Russia’s transport infrastructure.

Materials and Methods. The integration of digital twins into traffic management demonstrates its effectiveness through a close relationship with intelligent transport systems. The research is based on modern method and system analysis to the creation and application of digital twins. The authors propose a mathematical model for formalizing and evaluating the effectiveness, which integrates key factors such as: road maintenance costs, reduc­tion of vehicle idle time, fuel savings, and improved safety. Digital twins generate economic benefits through more accurate forecasting of repair and preventive maintenance work, diminishing operational expenses, and decreased need for constant personnel presence at sites. Furthermore, they also serve as a key tool for long-term planning, providing the capability to model future scenarios for the development of the transport network with minimal finan­cial investment.

Results. The study encompassed methods of predictive analytics, data from pilot projects, and approaches to creating digital twins that utilize data collected by sensor networks, video cameras, and drones. Processing and integrating this information into the unified digital platform enables real-time monitoring of changes on the roads, forecasting situation development, and making informed management decisions using tools of predictive analytics. A theoretical and economic model has been developed and formalized to assess the effectiveness of digital twins, providing quantitative justification for investment decisions. Several specific problems related to scaling these tech­nologies in the Russian Federation were identified, including an insufficient regulatory framework, the need to develop unified data standards, and a shortage of skilled personnel. A structured table outlining the development of digital twins and their key directions is presented.

Discussion and Conclusion. The research has showed that combining digital twins with intelligent transport sys­tems opens sufficient opportunities for optimizing traffic flow management, improving road safety, and increasing transport capacity. Comprehensive traffic optimization is impossible without demonstrating the practical significance of digital twins. The proposed model can serve as a basis for planning and justifying investments in the digitalization of transport infrastructure at various state and municipal levels. However, successful implementation depends on many factors and requires a complex approach, including serious personnel training at all levels, development of the regulatory framework, and creation of the unified digital ecosystem.

1. Thonhofer E., et al. (2023). “Infrastructure-based Digital Twins for Cooperative, Connected, Automated Driving and Smart Road Services.” IEEE Open Journal of Intelligent Transportation Systems, 4: 311-324. DOI: 10.1109/OJITS.2023.3266800

2. Svistelnikov A. A., et al. Demand for Testing and Research of Intelligent Transport Systems and Their Individual Components, Including Those Aimed at Ensuring the Movement of Highly Automated Vehicles. Transport Business of Russia 2024; 4: 188–191. (In Russ.). EDN QNPAKW.

3. Didenko D.N. Digital Transformation of Russia’s Transport and Road Sector. Bulletin of Science. 2024; 2(12)(81): 973-982. (In Russ.).

4. Kravchenko P.A., Plotnikov A.M., Oleshchenko E.M. On Digital Technologies for Ensuring Road Safety in the Russian Federation. Transport of the Russian Federation: Journal on Science, Practice, Economics. 2018; 4(77): 12-16. (In Russ.).

5. Rizaeva Yu.N. State Policy in the Development of Unmanned Systems. Intelligence. Innovations. Investments, 2023; 5: 11-19 (In Russ.).

6. Komarova A. A., Akulov A. O. Road Passportization Using Digital Technologies and Digital Twins. Moscow Economic Journal. 2024; 9 (6): 55–73. (In Russ.). DOI: 10.55186/2413046X_2024_9_6_279 EDN SZRPLJ

7. Wu D., et al. Digital Twin Technology in Transportation Infrastructure: A Comprehensive Survey of Current Applications, Challenges, and Future Directions. Applied Sciences, 2025; 15(4): 1911. DOI: 10.3390/app15041911

8. Akimov A.E., et al. On the Creation of a Digital Twin for Road Construction. System Technologies. 2023; 4(49): 25-34. (In Russ.).

9. Chekina E.V. Building Digital Twins of Highways in an Intelligent Transport GIS Environment. IT & Transport: Collection of Scientific Articles. 2021; 88. (In Russ.).

10. Kušić K., Schumann, R., Ivanjko, E. A Digital Twin in Transportation: Real-time Synergy of Traffic Data Streams and Simulation for Virtualizing Motorway Dynamics. Advanced Engineering Informatics. 2023; 55: Article ID 101858. DOI: 10.1016/j.aei.2022.101858

11. Evstigneev I.A., Shmytinsky, V.V. Issues of Interaction Between Autonomous Vehicles and Road Infrastructure. Transport of the Russian Federation: Journal on Science, Practice, Economics. 2019; 6(85): 17-21. (In Russ.).

12. Argota Sánchez-Vaquerizo, J. Getting Real: The Challenge of Building and Validating a Large-scale Digital Twin of Barcelona’s Traffic with Empirical Data. ISPRS International Journal of Geo-Information. 2022; 11(1): 24. DOI: 10.3390/ijgi11010024

13. Ivanov S.A., et al. Concept for Building a City’s Digital Twin. Bulletin of the South Ural State University. Series: Computational Mathematics and Informatics. 2020; 9(4): 5-23. (In Russ.).

14. Hilmani A., Maizate, A., Hassouni, L. Automated Real-time Intelligent Traffic Control System for Smart Cities Using Wireless Sensor Networks. Wireless Communications and Mobile Computing. 2020; Article ID 8841893. DOI: 10.1155/2020/8841893

15. Biryukov T.A., Inevatkina, A.P. Smart Roads: The Impact of V2X Innovative Technologies on Safety and Efficiency. Bulletin of Science. 2025; 4,1(82): 963-967. (In Russ.).