TA-ANP is a task-aware attentive neural process that performs global traffic state inference by fusing multi-source data, jointly solving three sub-tasks, and providing calibrated uncertainty estimates with resilience to changing sensor configurations.
Ayuntamiento de Madrid, 2026a
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Mathematical analysis based on the Macroscopic Fundamental Diagram proves road transportation networks are fragile, with a skewness indicator for cross-network comparison and simulations showing stochastic reinforcement.
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Metropolis-Scale Resilient and Trustworthy Traffic Flow Inference Using Multi-Source Data
TA-ANP is a task-aware attentive neural process that performs global traffic state inference by fusing multi-source data, jointly solving three sub-tasks, and providing calibrated uncertainty estimates with resilience to changing sensor configurations.
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The fragile nature of road transportation networks
Mathematical analysis based on the Macroscopic Fundamental Diagram proves road transportation networks are fragile, with a skewness indicator for cross-network comparison and simulations showing stochastic reinforcement.