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Mobility Analytics
Explosive growth in urban populations across the world is imposing severe strain on available mobility and transportation resources. Rapidly changing cyberinfrastructure capabilities, environmental policy, and increasing social connectivity further emphasize the need to innovate significantly to utilize transportation resources efficiently. iLab Mobility Analytics focuses on using tools from the fields of operations research, information systems, machine learning and economics to develop management strategies for efficient, robust, equitable and green mobility systems.
Our research is motivated by the following current trends:
- vast amounts of data generated being by physical infrastructure via low cost sensing
- increasing participation by users via cell phones, GPS traces and social networking applications
- increasing awareness, from governments and individuals, towards developing energy-efficient systems.
The combination of physical and social data sources provide a foundation for informed data-driven service operations management; and facilitate problem-driven inter-disciplinary research.
Specific applications that iLab faculty are currently involved in include bike-sharing, car-sharing, next-generation aviation systems and emergency management systems.
Closely related to the mobility analytics thrust is Traffic 21, an initiative of Heinz College. Traffic 21 leverages the strengths of faculty across CMU to address design and deployment in transportation.
Robert C. Hampshire
Lavanya Marla