Abstract
Digital twin technology ought to be employed to ascertain the efficacy and safety of this novel road infrastructure management paradigm. This paper delves into supplementary aspects beyond the conventional methods applied to road transportation systems. We introduce a simulation model for the optimal control of traffic signals in a mixed environment comprised of both autonomous and traditional vehicles, a mathematical framework for approximating unavailable data, and a method of automated simulation model generation to mitigate the time and effort expended on model generation. Our study designates a pilot autonomous driving district as the target area and appoints the operational route of the public autonomous shuttle bus as a driving route of the autonomous vehicles.
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References
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Acknowledgment
This paper is supported by the National Research Foundation of Korea, funded by the Ministry of Science and Information and Communications Technology of Korea. (Grants: 2022R1A4A1019071).
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Lim, H., Go, M., Lim, T., Kim, D.Y. (2023). Adaptive Traffic Signal Control for a Mixed Autonomous and Traditional Vehicles by Agent-Based Digital Twin Simulation. In: Alfnes, E., Romsdal, A., Strandhagen, J.O., von Cieminski, G., Romero, D. (eds) Advances in Production Management Systems. Production Management Systems for Responsible Manufacturing, Service, and Logistics Futures. APMS 2023. IFIP Advances in Information and Communication Technology, vol 691. Springer, Cham. https://doi.org/10.1007/978-3-031-43670-3_42
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DOI: https://doi.org/10.1007/978-3-031-43670-3_42
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