4 papers
Metropolis-Scale Resilient and Trustworthy Traffic Flow Inference Using Multi-Source Data
Qishen Zhou, Yifan Zhang, Michail A. Makridis +3
Inferring network-wide traffic states from sparse observations with high accuracy and trustworthy uncertainty quantification is essential for intelligent transportation systems, ye…
ORThought: Benchmarking and Automating Logistics Optimization Modeling
Beinuo Yang, Qishen Zhou, Junyi Li +3
Optimization modeling stands as the engine of scientific decision-making in logistics and transportation, yet its adoption is hindered by a steep expertise threshold and the latenc…
Network-wide Freeway Traffic Estimation Using Sparse Sensor Data: A Dirichlet Graph Auto-Encoder Approach
Qishen Zhou, Yifan Zhang, Michail A. Makridis +3
Network-wide Traffic State Estimation (TSE), which aims to infer a complete image of network traffic states with sparsely deployed sensors, plays a vital role in intelligent transp…
MoGERNN: An Inductive Traffic Predictor for Unobserved Locations
Qishen Zhou, Yifan Zhang, Michail A. Makridis +3
Given a partially observed road network, how can we predict the traffic state of interested unobserved locations? Traffic prediction is crucial for advanced traffic management syst…