2 citations · 2 across the 4 of their papers we have counts for
6 papers
FedeRICo: Federated Region-Influenced Coupling for Traffic Flow Prediction
Fermin Orozco, Man Luo, Johan Wahlström
Urban traffic forecasting often relies on information distributed across stakeholders who may be unable to share raw data due to privacy or commercial constraints, motivating feder…
TRACE: Trajectory Recovery with State Propagation Diffusion for Urban Mobility
Jinming Wang, Hai Wang, Hongkai Wen +2
High-quality GPS trajectories are essential for location-based web services and smart city applications, including navigation, ride-sharing and delivery. However, due to low sampli…
CityVerse: A Unified Data Platform for Multi-Task Urban Computing with Large Language Models
Yaqiao Zhu, Hongkai Wen, Mark Birkin +1
Large Language Models (LLMs) show remarkable potential for urban computing, from spatial reasoning to predictive analytics. However, evaluating LLMs across diverse urban tasks face…
HALO: Hierarchical Reinforcement Learning for Large-Scale Adaptive Traffic Signal Control
Yaqiao Zhu, Hongkai Wen, Geyong Min +1
Adaptive traffic signal control (ATSC) is essential for mitigating urban congestion in modern smart cities, where traffic infrastructure is evolving into interconnected Web-of-Thin…
Federated Learning for Traffic Flow Prediction with Synthetic Data Augmentation
Fermin Orozco, Pedro Porto Buarque de Gusmão, Hongkai Wen +2
Deep-learning based traffic prediction models require vast amounts of data to learn embedded spatial and temporal dependencies. The inherent privacy and commercial sensitivity of s…
TrajWeaver: Trajectory Recovery with State Propagation Diffusion Model
Jinming Wang, Hai Wang, Hongkai Wen +2
With the proliferation of location-aware devices, large amount of trajectories have been generated when agents such as people, vehicles and goods flow around the urban environment.…