In much of the human world, cars are a part of everyday life. While many researchers study people in cars to understand driving performance, or, more recently, trust or supervisory control of automation, the car can also be a way for better understanding a wider array of human-machine interaction issues. Cars are relatively easy to come by, easy to instrument, and enable relatively simple collection of longitudinal data across a diverse population of participants.

In my research group, we use the car to better understand human interaction at scale. For example, we address interruption, error recognition and recovery and multi-party interaction by using the car as a on-road laboratory to develop generalizable understandings of task, communication and social context. Additionally, we use driving simulation as a way to explore contingent interaction between multiple parties, and to explore how those interaction patterns differ across different geographical contexts. Most recently, during the COVID-19 pandemic, we have been using the car to gather large datasets of public activity, to better understand differences and patterns for example in social-distancing behavior. In this talk, I will survey my lab's research activity and detail novel methods we are developing to tackle the challenge of understanding interaction at large.

Wendy Ju is an Associate Professor at the Jacobs Technion-Cornell Institute at Cornell Tech and the Technion and in the Information Science field at Cornell University. Her work in the areas of human-robot interaction and automated vehicle interfaces highlights the ways that interactive devices can be designed to be safer, more predictable, and more socially appropriate. Professor Ju has innovated numerous methods for early-stage prototyping of automated systems to understand how people will respond to systems before the systems are built. She has a PhD in Mechanical Engineering from Stanford, and a Master's in Media Arts and Sciences from MIT.