From global open multi-source data to network-wide traffic flow: A large-scale case study across multiple cities
Peer-Reviewed Publication
Updates every hour. Last Updated: 27-Jan-2026 02:11 ET (27-Jan-2026 07:11 GMT/UTC)
To address the trade-off between accuracy and cross-city generalization in traffic flow estimation, a research team from The Hong Kong Polytechnic University and New York University proposes a novel framework based on global open multi-source (GOMS) data, including urban structures and population density. By developing an advanced graph neural network model that effectively fuses these static urban features with dynamic traffic data, the study achieves stable and accurate network-wide traffic estimation, as validated across 15 diverse cities in Europe and North America.
Researchers at National University of Singapore used multiple interpretable machine learning methods to predict traffic congestion in in Alameda County in the San Francisco Bay Area, USA, during the pre-lockdown, lockdown, and post-lockdown periods.
Permafrost degradation on the Qinghai-Tibet Plateau is accelerating under climate warming, causing roadbed settlement, waterlogging, thawing interlayers, and long-term instability in high-altitude highways. The study reviews global and Chinese permafrost engineering practices, identifies the mechanisms behind pervasive subgrade deformation, and highlights challenges in current “permafrost-protection” design approaches. It proposes a third design principle — proactively improving foundation conditions — advancing from passive protection to active treatment. The work further summarizes shallow and deep foundation treatment techniques, evaluates engineering applications, and outlines development trends such as improved hydrological investigation, long-term monitoring, and novel construction materials.
The Universitat Jaume I in Castelló will develop six research and innovation projects in areas such as environmental sustainability and risk detection to improve disaster response through funding obtained in the competitive call for proposals from the Valencian Innovation Agency (AVI) (IVACE+e innovación) 2025, which seeks to promote innovation, R&D transfer and collaboration between universities, technology centres and companies.
The UJI has obtained funding in three lines of the call financed by the European Union within the framework of the European Regional Development Fund (ERDF) Programme for the Valencian Community 2021-2027 – IVACE+ for an amount of nearly one million euros, with which it will promote six projects with direct technological and social impact to respond to real challenges.
The various initiatives led by UJI research staff will provide innovative solutions in the field of environmental sustainability through advanced technologies to improve water quality and management, strengthen the circular carbon economy, promote cleaner and safer production systems aligned with green technology, and strengthen the innovation ecosystem through materials with a lower environmental impact. They also seek to anticipate responses to situations of risk due to natural disasters resulting from climate change.