Michael Holland from NYU's Center for Urban Science & Progress (CUSP) presented a keynote lecture at KAUST's Winter Enrichment Program (WEP) 2015 on the importance of urban science. CUSP, launched in 2012, aims to make New York City a world capital of science and technology through multi-sector research and education. Holland emphasized how analyzing urban data can improve city government, planning, policy, and citizen engagement. Why it matters: As urbanization increases, the development of urban science and the effective use of urban data become crucial for sustainable and efficient city management in the GCC region and globally.
Researchers developed a data-driven toolkit for short-term traffic forecasting using high-resolution traffic data from urban road sensors. The method models forecasting as a matrix completion problem, mapping inputs to a higher-dimensional space using kernels and adaptive boosting. Validated using real-world data from Abu Dhabi, UAE, the method outperforms state-of-the-art algorithms.
This article discusses the application of uncertain time series (UTS) approach to manage and analyze big traffic data for high-resolution vehicular transportation services. The study addresses challenges such as data sparseness, decision-making among multiple UTSs, and future forecasting with spatio-temporal correlations. Jilin Hui, previously a Research Associate at the Inception Institute of Artificial Intelligence (UAE), is applying this approach to solve problems related to increased congestion, greenhouse gas emissions, and reduced air quality in urban environments. Why it matters: The application of AI techniques to traffic management could significantly improve urban mobility and environmental sustainability in the GCC region and beyond.
This article discusses the evolution of mobile extended reality (MEX) and its potential to revolutionize urban interaction. It highlights the convergence of augmented and virtual reality technologies for mobile usage. A novel approach to 3D models, characterized as urban situated models or “3D-plus-time” (4D.City), is introduced. Why it matters: The development of MEX and 4D.City could significantly enhance user experience and analog-digital convergence in urban environments, offering new possibilities for human-computer interaction.
Dr. Tarek Ali Fadaak, a Shura Council member, discussed the importance of environmental balance and improved resource management in Saudi urban planning during a 2018 KAUST lecture. He highlighted challenges like insufficient and poorly utilized open spaces in Saudi cities, emphasizing the need for aesthetic improvements and more public spaces. Fadaak stressed the importance of investing in the education of Saudi youth to drive future development and address these urban planning challenges. Why it matters: This underscores the ongoing focus on sustainable urban development and the role of Saudi talent in shaping future cities within the Kingdom, aligning with Vision 2030 goals.
The paper introduces a novel method for short-term, high-resolution traffic prediction, modeling it as a matrix completion problem solved via block-coordinate descent. An ensemble learning approach is used to capture periodic patterns and reduce training error. The method is validated using both simulated and real-world traffic data from Abu Dhabi, demonstrating superior performance compared to other algorithms.