arXiv AI July 28, 2026 By L\'eo Hein, Giovanni De Nunzio, Aur\'elie Pirayre, Laurent Najman

Capacity-Aware Deep Learning for Generalizable Traffic Volume Estimation Across Links and Cities

arXiv:2607. 24056v1 Announce Type: cross Abstract: Network-wide traffic volume estimation typically relies on propagating measurements from fixed sensors, making performance highly dependent on sensor density and limiting deployment in sparsely instrumented networks.

Summary generated by The Flow from the publisher's feed. The full article lives at arXiv AI.

arXiv AI

2d ago

Simulation-Driven Vehicular Traffic Data Augmentation: Extending Sensor Coverage Through Virtual Sensing

arXiv:2608. 13993v1 Announce Type: new Abstract: Urban traffic management relies on sensor networks whose spatial coverage is limited by deployment costs and privacy regulations.

By Davide Andrea Guastella, Eladio Montero Porras, Evangelos Pournaras, Gianluca Bontempi

safety

arXiv AI

Jun 10

MoE Enhanced Federated Learning for Spatiotemporal Prediction

arXiv:2606. 10499v1 Announce Type: cross Abstract: Traffic prediction is fundamental to intelligent transportation systems and urban computing, yet many cities continue to suffer from traffic data scarcity due to limited sensor deployment and uneven urban development.

By Zhehao Dai, Xiao Han, Zhaolin Deng, Zijian Zhang, Xiangyu Zhao, Guojiang Shen, Xiangjie Kong

benchmarks safety

arXiv AI

Jun 18

Large-Scale OD Matrix Estimation with A Deep Learning Method

arXiv:2310. 05753v2 Announce Type: replace Abstract: The estimation of origin-destination (OD) matrices is a crucial aspect of Intelligent Transport Systems (ITS).

By Zheli Xiong, Defu Lian, Enhong Chen, Gang Chen, Xiaomin Cheng

arXiv AI

Aug 3

SqLinear: Balanced Square Partitioning Makes Linear Interaction Sufficient for Large-Scale Traffic Forecasting

arXiv:2606. 21072v2 Announce Type: replace-cross Abstract: Traffic prediction is a core task in intelligent transportation systems and urban-scale decision making.

By Yongfeng Su, Hongwen Li, Zijian Zhang, Ziquan Fang, Lu Chen, Christian S. Jensen, Hong Gao, Yinjun Han

llms

arXiv Machine Learning

Jul 30

Neural Architecture Search for Traffic Prediction: A Survey of Methods, Challenges, and Future Directions

arXiv:2607. 26467v1 Announce Type: new Abstract: Traffic prediction is a core task in intelligent transportation systems, supporting applications such as adaptive signal control, route guidance, and ride-hailing dispatch.

By Truong Giang Vu, Li Yang, Richard W. Pazzi

llms benchmarks

arXiv Machine Learning

Jul 7

Deep Learning Network-Temporal Models For Traffic Prediction

arXiv:2603. 11475v2 Announce Type: replace Abstract: Accurate prediction of multivariate time series is essential for emerging network intelligent control, observability, and management functions.

By Yufeng Xin, Ethan Fan

llms fine-tuning

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Simulation-Driven Vehicular Traffic Data Augmentation: Extending Sensor Coverage Through Virtual Sensing

MoE Enhanced Federated Learning for Spatiotemporal Prediction

Large-Scale OD Matrix Estimation with A Deep Learning Method

SqLinear: Balanced Square Partitioning Makes Linear Interaction Sufficient for Large-Scale Traffic Forecasting

Neural Architecture Search for Traffic Prediction: A Survey of Methods, Challenges, and Future Directions

Deep Learning Network-Temporal Models For Traffic Prediction