Author

Donggyu Min

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#machine learning Nov 2025

Deep Reinforcement Learning for Dynamic Origin-Destination Matrix Estimation in Microscopic Traffic Simulations Considering Credit Assignment

By reframing DODE as a sequential decision-making problem, this approach addresses the credit assignment challenge through a learned policy and provides a novel framework for calibration of microscopic traffic simulations.

Donggyu Min, Seongjin Choi, Dong-Kyu Kim · Transportation Research Part... · 0 citations

#artificial intelligence Preprint Aug 2026

Online Estimation of Dynamic Origin-Destination Matrices Using Reinforcement Learning with Link-Flow Propagation Guidance

LFPG-RL is developed and evaluated, which integrates link-flow propagation guidance (LFPG) into proximal policy optimization (PPO), and results support the contention that the method is a more efficient and accurate online OD demand calibration method compared to existing ones.

Donggyu Min, Dong-Kyu Kim · 0 citations