This course examines the behavioral foundation for transportation systems and policies, including:

• sensing travel behavior with new technology and measurement instruments
• understanding travel by incorporating behavioral science
• nudging travel behavior through preference shaping and demand management
• designing mobility systems that integrate autonomous vehicles, shared mobility, and public transit
• regulating travel by developing behavior-sensitive transport policies

We introduce multiple frameworks of explaining and changing behavior, contrasting the perspectives of classic economic theory with behavioral economics and social psychology. We present a spectrum of instruments for positively influencing behavior and improving welfare: from manipulating information and changing perceptions of time and space, to pricing and framing, to inducing emotions of pride and shame, and exploiting peer pressure or enhancing self-control and motivation. The course combines behavioral science, transportation technology, and data analytics to shape travel behavior, design mobility systems and reform transportation policies. The 2019 offering uses new mobility services such as autonomous vehicles (AVs), shared mobility systems, and personal mobility devices as the primary examples.

Most importantly the course challenges students to critique, design, implement and interpret experiments that nudge travel behavior; and to bring behavioral insights to the creative design of transportation systems and policies—making them not only efficient and equitable but also simpler, transparent, acceptable, and adaptive to behavioral changes. 

Links: syllabus; reading; DUSP subject listing; MIT subject listing; project examples, project guideline