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

Metropolis-Scale Resilient and Trustworthy Traffic Flow Inference Using Multi-Source Data arXiv:2605.25004v1 Announce Type: cross Abstract: Inferring network-wide traffic states from sparse observations with high accuracy and trustworthy uncertainty quantification is essential for intelligent transportation systems, yet it remains challenging due to the underdetermined nature of the problem, multifaceted disturbances in sensing networks, and the inherent conflicts among multiple inference sub-t