Author

Filipe Rodrigues

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#machine learning Jun 2026

Hierarchical Forecast Reconciliation for Urban Rail Transit Demand Prediction under Operational Disruptions

Under train delays and cancellations, reconciliation continues to improve OD accuracy, with FCR achieving larger reductions than MinT-Sample in disruption-affected subsets, highlighting the value of hierarchical reconciliation under both regular and disrupted operations.

Dang Viet Anh Nguyen, Alma Fazlagic, Kristín Loft et al. · arXiv.org · 0 citations

#reinforcement learning Open access Sep 2026

A framework for benchmarking traffic signal control robustness under incidents: comparative study of reinforcement learning-based methods

T-REX is introduced, an open-source, SUMO-based simulation framework for training and evaluating RL-TSC methods under dynamic, incident scenarios, and shows that while independent value-based and decentralized pressure-based methods offer fast convergence and generalization in stable traffic conditions and homogeneous...

Dang Viet Anh Nguyen, Carlos Lima Azevedo, Tomer Toledo et al. · European Transport Research... · 0 citations