Section I. Behavioral Foundation of Urban Mobility


Section II. Mobility System: Design with Behavioral Perspective





Section IV: Machine Learning for Transportation

Public Transit: Driving the future of mass transport.


The JTL Urban Mobility Lab at MIT brings behavioral science and transportation technology together to shape travel behavior, design mobility systems, and improve transportation policies. We apply this framework to managing automobile ownership and usage, optimizing public transit planning and operation, promoting active modes of walking and cycling, governing autonomous vehicles and shared mobility services, and designing multimodal urban transportation systems.

We organize our research into three themes: Behavior, System and Policy: Theme I examines the behavioral foundation of urban mobility, including the emotionality and sociality of travel, as well as perceptions of travel time; Theme II focuses on the design of mobility systems with a behavioral perspective, including mobility sensing and prediction systems, mobility information systems, integrated autonomous vehicle and public transportation systems, and behavioral nudging systems; and Theme III investigates the formulation, implementation and evaluation of behavior-sensitive transportation policies, including policy equity, acceptance and compliance, accessibility and agglomeration, and, more specifically, China’s urbanization and motorization policies. Finally we see transportation as a language: to describe a person, to characterize a city, and to understand an institution. 

JTL is directed by Prof. Jinhua Zhao, the Edward H. and Joyce Linde Associate Professor of City and Transportation Planning at MIT, working with an enthusiastic group of transportation researchers. Our inter-disciplinary lab includes social scientists, data wranglers, designers, computer scientists, transport engineers, and planners of all stripes.