CITIES focuses on the interactions between different types of networks: Physical, Digital, and Social Networks, within an urban context.
How has CITIES’ focus evolved?
At the intersection of those three networks, we now focus on three research themes: Mobility, Uncertainty, and Fairness.
Mobility:
Urban mobility is a complex and multifaceted problem that can significantly impact the quality of life, economic competitiveness, and environmental sustainability of urban areas. We aim to develop innovative solutions for seamless end-to-end transport in multi-modal urban systems, leverage big data to develop real-time decision support for highly connected urban mobility systems, and investigate the operational aspects of autonomous mobility and other new technologies.
Within the Mobility theme, research spans several innovative areas, including the development of autonomous modular vehicles (AMVs) to enhance public transport by minimizing travel costs, enabling transfer-less service, and integrating on-demand systems with existing routes—exemplified by a proposed prototype in Abu Dhabi. Another focus is on analyzing urban mobility patterns and traffic congestion by studying network behavior, driver dynamics, and congestion thresholds using large-scale traffic data to inform smarter traffic control. Additionally, research on the security of connected and autonomous vehicles (CAVs) investigates potential cyberattacks and aims to create certification systems to safeguard autonomous driving technologies.
Uncertainty
Decision-making with severe uncertainty, missing or inaccurate data is a challenge that current decision-support tools are ill equipped to handle. CITIES integrates diverse schools of thought and cutting-edge technologies, to build innovative models and techniques that will enable decision-makers to effectively address a wide range of urban problems, from public health resource planning to misinformation mitigation and mobility routing.
The Uncertainty theme focuses on enhancing decision-making under conditions of limited, inaccurate, or misleading information. One project designs robust decision-support systems using scalable tools for conditional value at risk (CVaR) optimization to manage risks in extreme scenarios like financial crises. Another initiative tackles misinformation by developing auditing tools and case databases to help platforms fairly assess and mitigate the spread of false information. Additionally, researchers are creating algorithmic tools to analyze large, noisy datasets from mobile sensors, such as those in connected and autonomous vehicles, ensuring reliable performance despite data incompleteness.
Fairness
Where people live and how they use the city shapes a multitude of life outcomes from health through education to work. However, the benefits and perils of urban living are not equally shared on either the local or global scale. We aim to focus on the determinants of inequality in outcomes to be able to promote economic growth, as well as social and environmental sustainability, so that cities can create a more cohesive and prosperous community for everyone.
The Fairness theme explores how the benefits and burdens of urban development are distributed, focusing on social equity and inclusion. One project investigates neighborhood effects by analyzing how location and mobility impact outcomes like employment and health, using registry and housing data alongside spatial annotation tools. Another initiative studies the equitable deployment of green infrastructure by building a global dataset with satellite imagery and machine learning, and adapting a cooperative educational game to explore community decision-making in the U.A.E. Additionally, the theme addresses fairness in algorithmic systems, such as ensuring equitable distribution of green time in traffic light management, highlighting the importance of fairness in both policy and technological interventions.