Min, D., Choi, S., & Kim, D.-K. (2026). Deep Reinforcement Learning for Dynamic Origin-Destination Matrix Estimation in Microscopic Traffic Simulations Considering Credit Assignment. Transportation Research Part C: Emerging Technologies, In press. (https://authors.elsevier.com/c/1nlEo,M0mRcoSg)

Min, D., Yun, H., Kim, D.-K. & Ham, S. W. (2026). Dynamic Origin-Destination Matrix Estimation Using Metamodel-based Model Predictive Control for Real-Time Application. Transportation Research Record, 2680(5), 418-440. https://doi.org/10.1177/03611981251378484

Min, D., Yun, H., Ham, S. W. & Kim, D.-K. (2025). Real-time Estimation of Origin-Destination Matrices Using a Deep Neural Network for Digital Twins. Transportation Research Record, 2679(2), 1309-1328. https://doi.org/10.1177/03611981241266837

Min, D. & Kim, D.-K. (2026). Online Estimation of Dynamic Origin-Destination Matrices Using Reinforcement Learning with Link-Flow Propagation Guidance.  Under review at IEEE Transactions on Intelligent Transportation Systems. (Preprint: https://doi.org/10.48550/arXiv.2608.30317)

Min, D. & Kim, D.-K. (2026). Dynamic Origin–Destination Matrix Estimation from Planning to Operations: A Review.  Manuscript ready for submission .

Kim, J. , Lee, S.-H., Min, D., & Kim, D.-K. (2026) Ensemble-based Model Predictive Control for Variable Speed Limit and Ramp Metering in Freeway Merging under Mixed Traffic Environment. Under review at Journal of Intelligent Transportation Systems.

Min, D., & Kim, D.-K. (2025). Developing a Risk Recognition System Based on a Large Language Model for Autonomous Driving. Engineering Proceedings, 102(1), 7.

Min, D., Yun, H., & Kim, D.-K. (2024). Developing Lane-changing Strategy of Autonomous Vehicles Based on Deep Reinforcement Learning Using Long-range Information for Mitigating Traffic Congestion. Journal of the Eastern Asia Society for Transportation Studies, 15, 2788-2803.