The Smart Cities Research Center is a collaboration between UC Berkeley and Lawrence Berkeley National Laboratory to improve energy-efficient mobility systems. The availability of data opens new perspectives on activity-based modeling of urban mobility and traffic microsimulations. The new center, currently preparing to launch, will study mathematical models and data analytics with approaches ranging from behavioral studies to control theory, working with industry and public agencies to collect and model data and use it to develop more efficient transportation networks. The research focuses on novel approaches to modeling interdependent energy and transportation systems. The work will leverage analytics capabilities of rich geospatial data and develop novel approaches to studying multiple aspects of urban dynamics in the nexus of cyber, physical, and social systems. A unifying approach will be developed that uses machine learning along with a variety of optimization algorithms, infrastructure control methods, and policy analysis to produce transportation development scenarios and recommendations to practitioners and decision makers. Research areas are grounded in the disciplines covered by master’s and doctorate programs in civil, systems, and transportation engineering.
MISSION: Improve mobility in a sustainable and energy-efficient way by advancing quantitative modeling of urban systems. Foster interdisciplinary training to solve real-world challenges posed by modern cities.
• Urban data analytics
• Distributed control systems
• Smarter transportation
• Computation social science
• Location-based social networks
"Cities have grown into complex ‘systems of systems’ saturated by aging infrastructures of increasing maintenance costs, fading control over private data, and a growing pool of interlinked socioeconomic problems. The scaling laws observed in the evolution of today’s cities fundamentally contradicts sustainability. At the same time, technology and connectivity have brought to life unprecedented opportunities to approach these challenges in a data-driven way. The work of our new center lies at this tension point.” — Alexei Pozdnukhov, Center Co-Director