Transportation Network

Transportation network research focuses on optimizing the efficiency, resilience, and fairness of transportation systems through data-driven modeling and algorithmic approaches. Current research emphasizes developing and applying advanced machine learning techniques, including graph neural networks, reinforcement learning, and optimal transport methods, to address challenges such as real-time traffic routing, predicting traffic flow and modal split, and mitigating the impact of attacks or uncertainties. These advancements have significant implications for improving urban planning, traffic management, and the overall user experience, leading to more efficient and sustainable transportation networks.