Driving in traffic-filled roads can be a hassle. Apps such as Google’s Waze have stepped in to allow us to dynamically re-plan our driving routes as we go to avoid traffic and other slowdowns. Using game theory to model drivers and graph theory to model routes previous work has shown that cases exist in which providing information to certain drivers decreases net traffic time, but in all other cases some information can be given that increases net traffic time. Unfortunately, the former cases are extremely narrow and do not provide an accurate model of the real world. In this SuperUROP project, I will examine the latter cases and classify the optimal information to provide drivers to optimize net traffic time among all drivers.

“I strive to be at the forefront of technology. SuperUROP allows me to do that by designing a project with Professor Asu Ozdaglar, a leader in the field of optimal control both on the academic and industrial sides. I’m excited to apply the knowledge I’ve learned in many of my classes and UROPS, as well as learning how the industry evaluates research and adapts it to improve our everyday lives.”