Min, D., & Kim, D.-K. (2026). Reframing Dynamic Origin-Destination Matrix Estimation as a Sequential Decision-Making Problem for Microscopic Traffic Simulation. The 32nd Gangneung ITS World Congress, Gangneung, Republic of Korea. (Scheduled)

Min, D., & Kim, D.-K. (2026). Balancing Metamodel Accuracy and Optimization Tractability in OD Matrix Estimation: A Kolmogorov-Arnold Networks Approach. The 32nd Gangneung ITS World Congress, Gangneung, Republic of Korea. (Scheduled)

Min, D., & Kim, D.-K. (2026). Smoothing the Objective Landscape in Bi-level OD Matrix Estimation with Kolmogorov–Arnold Networks. The 15th Asia-Pacific Conference on Transportation and the Environment(APTE 2026), Jeju, Republic of Korea.

Min, D., Choi, S., & Kim, D.-K. (2026). Deep Reinforcement Learning for Dynamic Origin-Destination Matrix Estimation in Microscopic Traffic Simulations Considering Credit Assignment. TRB 105th Annual Meeting, Washington, D.C.

Min, D., & Kim, D.-K. (2025). Developing a Rist Recognition System based on a Large Language Model for Autonomous Driving. ITS Asia Pacific Forum 2025, Suwon, Republic of Korea.

Yun, H., Kim, D.-K., Min, D., & Lee, S.-H. (2025). Partitioning Large-Scale Urban Networks for Multi-Region Macroscopic Fundamental Diagram Analysis. The 10th Civil Engineering Conference in the Asian Region(CECAR10), Jeju, Republic of Korea.

Min, D., Yun, H., Ham, S. W. & Kim, D.-K. (2025). Real-time Dynamic Origin-Destination Matrix Estimation Using Metamodel-based Model Predictive Control. TRB 104th Annual Meeting, Washington, D.C.

Lee, E.-J., Min, D., Ham, S. W. & Kim, D.-K. (2025). Enhancing Accuracy and Reliability of Origin-Destination Matrix Estimation Using Ensemble Empirical Mode Decomposition. TRB 104th Annual Meeting, Washington, D.C.

Min, D., Yun, H., Ham, S. W. & Kim, D.-K. (2024). Real-time Estimation of Origin-Destination Matrices Using a Deep Neural Network for Digital Twins. TRB 103rd Annual Meeting, Washington, D.C.

Min, D., Yun, H., & Kim, D.-K. (2023). Developing Lane-changing Strategy of Autonomous Vehicles Based on Deep Reinforcement Learning Using Long-range Information for Mitigating Traffic Congestion. EASTS 2023, Malaysia.

Min, D., & Kim, D.-K. (2026). Deep Reinforcement Learning-Based Method for Estimating Dynamic Origin-Destination Matrices in Dynamic Traffic Assignment Environments. The 2026 Korean Society of ITS Spring Conference, Jeju, Republic of Korea.

Min, D. & Kim, D.-K. (2026). Metamodel-based Origin-Destination Matrix Estimation Using Kolmogorov-Arnold Networks. The 94th Conference of Korean Society of Transportation, Republic of Korea.

Min, D., & Kim, D.-K. (2025). Cross-Attention based Spatio-Temporal Graph Convolutional Network for Speed Prediction with Origin-Destination Demand Context. The 2025 Korean Society of ITS Fall Conference, Jeju, Republic of Korea.

Min, D. & Kim, D.-K. (2025). Deep Reinforcement Learning Approach for Dynamic Origin-Destination Matrix Estimation in Microscopic Traffic Simulations. The 93rd Conference of Korean Society of Transportation, Republic of Korea.

Kim, J. Lee, S.-H., Min, D. & Kim, D.-K. (2025). Ensemble-based Model Predictive Control for Freeway Merging Area under Mixed Traffic Environment. The 93rd Conference of Korean Society of Transportation, Republic of Korea.

Min, D., & Kim, D.-K. (2025). Off-line Dynamic Origin-Destination Matrix Estimation Using Reinforcement Learning. The 2025 Korean Society of ITS Spring Conference, Jeju, Republic of Korea.

Min, D. & Kim, D.-K. (2024). Fine-tuning O-D matrices of Microscopic Traffic Simulation Using Guided Reinforcement Learning. The 2024 Korean Society of ITS Fall Conference, Republic of Korea.

Lee, E.-J., Min, D. & Kim, D.-K. (2024). Enhancing Short-Term Origin-Destination Matrix Estimation Using Savitzky-Golay Filtering. The 2024 Korean Society of ITS Fall Conference, Republic of Korea.

Min, D. & Kim, D.-K. (2024). Metamodel-based Real-time Dynamic Origin-Destination Matrix Estimation Using Optimal Control Problem Formulation. The 91st Conference of Korean Society of Transportation, Republic of Korea.

Min, D. & Kim, D.-K. (2024). Developing an Autonomous Driving Hazard Perception System Based on Large Language Model and Surrogate Safety Indicator. The 2024 Korean Society of ITS Spring Conference, Republic of Korea.

Min, D., Ham, S. W. & Kim, D.-K. (2023). Dynamic Origin-Destination Matrices Estimation Using Deep Recurrent Q-Learning. The 2023 Korean Society of ITS Fall Conference, Republic of Korea.

Min, D. & Kim, D.-K. (2023). Developing Dynamic O/D Estimation Method using Microscopic Traffic Simulation and Deep Neural Network. The 89th Conference of Korean Society of Transportation, Republic of Korea.

Min, D., Ham, S. W. & Kim, D.-K. (2023). Generating OD Matrix Using Multi-modal Observational Data for High-resolution Microscopic Traffic Simulation. The 2023 Korean Society of ITS Spring Conference, Republic of Korea.

Min, D. & Kim, D.-K. (2022). Analysis on Input Data Attributions Using Saliency Maps of Autonomous Lane-changing Model Based on Deep Reinforcement Learning. The 2022 Korean Society of ITS Fall Conference, Republic of Korea.

Min, D., Yun, H. & Kim, D.-K.  (2022). Developing Lane Changing Strategy of Autonomous Vehicles Based on Reinforcement Learning Using Information of Short-Range V2V Driving Information. The 2022 Korean Society of ITS Spring Conference, Republic of Korea.