MBZUAI graduate Maryam Mohamed Buty Alghfeli's master's research focused on using the metaverse to enhance intelligent transportation systems and vehicular networks. Her work proposed a framework for sensing, communication, and task offloading in the vehicular metaverse, addressing challenges related to computing and communication resource constraints. The research also considered self-sustainability and proactive learning approaches to improve network operation and serve autonomous vehicles. Why it matters: This research contributes to the development of more efficient and resilient autonomous vehicle networks, which are crucial for the future of smart cities and transportation in the UAE and beyond.
Dirk Ahlborn discussed the future of transport in his WEP keynote address at KAUST on January 11. He specifically addressed the Hyperloop concept. Why it matters: Such discussions at leading institutions signal growing interest in innovative transport solutions within the region.
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.
Munther Dahleh, director at the MIT Institute for Data, Systems, and Society (IDSS), discussed his group's research on network systems at the KAUST 2018 Winter Enrichment Program. The research focuses on the fragility of large networked systems, like highway systems, in response to disruptions that may lead to catastrophic failures. Dahleh's team studies transportation networks, electrical grids, and financial markets to understand system interconnection in causing systemic risk. Why it matters: Understanding networked systems is crucial for building resilient infrastructure and mitigating risks in critical sectors across the GCC region.
KAUST has launched self-driving shuttles on its campus, making it the first adopter of autonomous vehicles in Saudi Arabia. The pilot project utilizes vehicle technology from Local Motors and EasyMile. SAPTCO will operate the autonomous shuttles and manage operations with Saudi staff. Why it matters: This initiative advances Saudi Arabia's 2030 Vision and positions KAUST as a regional leader in smart city development and AI research.
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.
KAUST's Fuel Lubricants Efficient Engine Technology (FLEET) Consortium, established with OSP last year, added Luberef and Ferrari as new members. FLEET has completed six projects in its first year, including studying liquid spray and combustion, developing fuel cells, and capturing energy from ship engines. Eight new projects have been announced, including lubricant exploration for electric and hydrogen vehicles and improving hydrogen engine performance. Why it matters: The expansion of FLEET and its new projects underscore Saudi Arabia's commitment to carbon neutrality through collaborative research and development in sustainable transportation technologies.