Jack Labriola, assistant professor of technical communication, explores the need for human drivers to still be paying attention.
The professional mission of Jack Labriola, Ph.D., is to design and create better experiences for users in their day-to-day use of technology. He has over six years of experience working in university usability labs, performing research, and re-designing apps and websites for a variety of small businesses and non-profits. He has participated in several design challenges to develop prototype applications for student education and the FDA. His research interests include usability, user experience (UX), design thinking, and autonomous vehicles. Currently, he is helping to create and build up the Technical Communication and Interactive Design Department’s usability research lab, where he hopes to encourage students and faculty to collaborate with the surrounding community in testing, designing and creating better product experiences.
Taking Control of Autonomous Vehicles
Whether we realize it or not, autonomous vehicles, or “AVs” – also called self-driving vehicles – are already on the roads around us. However, as we might expect, they are not perfect just yet. And while they may not comprise the majority of the cars on the road, we understand that the future of driving depends on the successful and safe implementation of AVs on our roads.
With the technology available right now, human drivers are still responsible for monitoring their AV and stepping in to take control over that vehicle when necessary, such as when a malfunction occurs. Yet, many drivers are unfamiliar with driving an AV and may have difficulty anticipating when they need to step in and what’s the best way to take control.
Dr. Kyung Jung, a colleague and associate professor of psychology, and I are testing what it takes for the human driver to successfully and safely take back control of a malfunctioning AV and also, what undesirable responses could occur. Using a driving simulator, we are focusing on understanding how human drivers react during various malfunctions. For example, can they respond appropriately and quickly enough if their AV doesn’t sense the traffic signal? Or how should they react if rain or snow starts to obscure the road lines and the car can no longer sense the lanes?
Ultimately, we will use our data to develop a driver-training program to teach human drivers about AVs, improve the monitoring and handling abilities of drivers of autonomous vehicles and enhance the safety of our roads in the future.