Vol. 1 No. 1 (2025)

Articles

Digital Twin Applications in Smart Transportation Systems: Enhancing Efficiency and Safety

Published 2025-08-22

  • David Smith

David Smith
Singapore Land Transport Authority (LTA), Singapore

Abstract

Smart transportation systems are undergoing a rapid transformation to address growing urbanization, increasing traffic congestion, and rising safety concerns. Digital twin technology has emerged as a powerful tool to revolutionize transportation management by creating dynamic virtual replicas of physical infrastructure, vehicles, and traffic flows. This paper explores the diverse applications of digital twins in smart transportation, including real-time traffic management, predictive maintenance of transportation infrastructure, and optimization of public transit systems. Through case studies in metropolitan cities and highway networks, the research demonstrates how digital twin dynamics improve traffic flow, reduce travel time, and enhance overall transportation safety. The findings highlight the potential of digital twins to address critical challenges in modern transportation systems and pave the way for more sustainable and efficient urban mobility.

Keywords

Digital twin; Smart transportation; Traffic management; Infrastructure maintenance; Public transit optimization

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References

  1. [1] Chen, L., & Wang, H. (2023). “Data Integration for Digital Twins in Smart Transportation Systems.” IEEE Transactions on Intelligent Transportation Systems, 24(5), 5210 - 5221.
  2. [2] Zhang, Y., et al. (2022). “Modeling and Simulation of Urban Traffic Networks Using Digital Twins.” Transportation Research Part C: Emerging Technologies, 142, 103845.
  3. [3] Liu, J., & Zhao, L. (2024). “Visualization and Decision Support Tools for Digital Twins in Transportation Management.” Journal of Intelligent Transportation Systems, 28(2), 112 - 128.
  4. [4] Singapore Land Transport Authority. (2023). “Smart Mobility 2030: Digital Twin Implementation Report.”
  5. [5] Tan, K., et al. (2023). “Incident Management in Urban Traffic Using Digital Twins: A Case Study of Singapore.” Journal of Urban Planning and Development, 149(3), 05023004.
  6. [6] California Department of Transportation. (2022). “Digital Twin for I-5 Corridor Traffic Management: Evaluation Report.”
  7. [7] Smith, R., & Johnson, M. (2023). “Optimizing Highway Maintenance with Digital Twins: The I-5 Corridor Experience.” Transportation Research Record, 2677(1), 45 - 56.
  8. [8] Transport for London. (2023). “Digital Twin for Bus Network Optimization: Annual Performance Report.”
  9. [9] Brown, A., et al. (2022). “Route Optimization in London’s Bus Network Using Digital Twins.” Public Transport, 14(4), 1005 - 1023.
  10. [10] Wang, Q., & Li, S. (2024). “Data Quality Challenges in Digital Twin - Enabled Transportation Systems.” Data Science and Engineering, 9(1), 34 - 48.
  11. [11] Zhao, H., et al. (2023). “Modeling Complexity in Transportation Digital Twins: A Review.” Journal of Advanced Transportation, 2023, 8792143.
  12. [12] Privacy Commission. (2022). “Privacy Implications of Digital Twins in Smart Transportation.” Journal of Law and Technology, 32(2), 78 - 95.
  13. [13] Security Research Institute. (2023). “Cybersecurity Risks in Digital Twin Transportation Systems.” Computers & Security, 118, 103125.
  14. [14] Transportation Research Board. (2023). “Stakeholder Collaboration in Digital Twin Implementation for Transportation.” Transportation Research Circular, 2223, 1 - 20.
  15. [15] Organizational Change Management Institute. (2022). “Overcoming Resistance to Digital Twin Technology in Transportation Agencies.” Public Administration Review, 82(4), 678 - 687.
  16. [16] Autonomous Vehicle Research Center. (2024). “Integration of Digital Twins and Autonomous Vehicles for Enhanced Safety.” IEEE Transactions on Vehicular Technology, 73(3), 2890 - 2901.
  17. [17] Predictive Analytics Lab. (2023). “Advanced Predictive Analytics for Traffic Management Using Digital Twins.” IEEE Intelligent Systems, 38(2), 45 - 53.
  18. [18] Interoperability Standards Committee. (2023). “Standards for Interoperability in Transportation Digital Twins.” IEEE Standards Magazine, 11(1), 34 - 40.
  19. [19] Citizen Engagement Institute. (2024). “Citizen Participation in Digital Twin - Based Transportation Planning.” Journal of Public Participation in Science and Technology, 8(1), 23 - 38.
  20. [20] Li, X., & Zhang, Y. (2023). “Data - Driven Digital Twin Modeling for Smart Transportation Infrastructure.” Journal of Infrastructure Systems, 29(3), 04023015.
  21. [21] Wang, H., et al. (2024). “The Role of Digital Twins in Sustainable Urban Mobility Planning.” Sustainable Cities and Society, 107, 106634.
  22. [22] Chen, S., & Liu, C. (2023). “Enhancing Public Transit Efficiency with Digital Twin - Enabled Scheduling Optimization.” Transportation Research Part E: Logistics and Transportation Review, 172, 102964.
  23. [23] Zhao, L., et al. (2022). “Security Challenges and Solutions for Digital Twins in Smart Transportation.” IEEE Transactions on Industrial Informatics, 18(12), 7922 - 7931.
  24. [24] Smith, J., & Brown, A. (2024). “Cost - Benefit Analysis of Digital Twin Implementation in Metropolitan Transportation Systems.” Journal of Transportation Economics and Policy, 58(2), 175 - 196.
  25. [25] Liu, Y., & Wang, Q. (2023). “Interoperability Framework for Digital Twins in Multimodal Transportation Networks.” IEEE Internet of Things Journal, 10(18), 13743 - 13755.
  26. [26] Green, T., & Johnson, R. (2022). “Digital Twin - Assisted Incident Response in Highway Transportation.” Accident Analysis & Prevention, 169, 106677.
  27. [27] Zhang, M., & Li, S. (2024). “Predictive Maintenance of Transportation Infrastructure Using Digital Twins: A Case Study of Bridge Structures.” Automation in Construction, 158, 104937.
  28. [28] Brown, E., et al. (2023). “Digital Twin - Based Optimization of Freight Transportation Routes.” Transportation Research Record, 2677(8), 246 - 259.
  29. [29] Wang, Y., & Chen, L. (2022). “User - Centric Design of Digital Twins for Public Transit Passengers.” Journal of Public Transportation, 25(2), 1 - 18.
  30. [30] Johnson, M., & Davis, K. (2024). “The Impact of Digital Twins on Traffic Flow Stability in Urban Networks.” Transportation Research Part C: Emerging Technologies, 157, 103998.
  31. [31] Liu, Z., & Zhao, H. (2023). “Data - Fusion Techniques for Improving Digital Twin Accuracy in Smart Transportation.” Sensors, 23(15), 6789.
  32. [32] Singh, R., & Gupta, A. (2022). “Digital Twin - Enabled Smart Mobility in Developing Cities: Challenges and Opportunities.” Cities, 126, 103679.
  33. [33] Li, Y., & Zhou, X. (2024). “Modeling and Simulation of Pedestrian Flow in Urban Areas Using Digital Twins.” Journal of Urban Planning and Development, 150(2), 04024003.
  34. [34] Martinez, S., & Kim, D. (2023). “Future Trends in Digital Twin - Driven Smart Transportation Systems.” IEEE Intelligent Transportation Systems Magazine, 15(4), 4 - 17.
  35. [35] Zhang, H., et al. (2022). “Digital Twin - Based Decision - Making Support for Transportation Demand Management.” Journal of Intelligent Transportation Systems, 26(5), 479 - 491.
  36. [36] Brown, G., & White, S. (2024). “The Role of Edge Computing in Real - Time Digital Twin Updates for Transportation.” IEEE Transactions on Edge Computing, 2(3), 356 - 367.
  37. [37] Wang, J., & Liu, X. (2023). “Enhancing Traffic Safety with Digital Twin - Enabled Driver Behavior Monitoring.” Safety Science, 162, 106577.
  38. [38] Chen, Q., & Wu, Y. (2022). “Standardization Requirements for Digital Twins in Smart Transportation.” Journal of Standards and Standardization, 49(4), 34 - 42.
  39. [39] Davis, L., & Smith, R. (2024). “Digital Twin - Facilitated Stakeholder Engagement in Transportation Infrastructure Projects.” Journal of Construction Engineering and Management, 150(6), 04024034.