arXiv Machine Learning By Qishen Zhou, Yifan Zhang, Michail A. Makridis, Anastasios Kouvelas, Yibing Wang, Simon Hu

Metropolis-Scale Resilient and Trustworthy Traffic Flow Inference Using Multi-Source Data

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arXiv AI
Aug 24

RiskTraf: Risk-Extrapolated Residual Learning for Multi-Variate Traffic Flow Prediction

RiskTraf introduces a risk-extrapolated residual learning approach for multi-variate traffic flow prediction, leveraging raw flow, speed, and occupancy data from the new PEMSB-3V benchmark. The method freezes a trained spatio-temporal backbone and adds a lightweight residual head that learns from historical speed and occupancy to correct flow predictions across different traffic regimes. Experiments show consistent improvements over various backbones and outperform existing debiasing and distribution-shift adaptation techniques.

By Guangyu Wang, Zhidan Liu