This event is designed for U-M IOE PhD students and faculty and is also open to all U-M students, faculty and staff.

Title:
Investigating and Predicting Driver Takeover Performance and Designing Alert Displays in Conditionally Automated Driving

Abstract:
Automated vehicles have the potential to provide our society with safer, more comfortable and fuel-efficient driving. In conditionally automated vehicles, drivers serve as a fallback for the vehicle and need to take over control of the vehicle when the automation fails. This raises safety concerns because the automated driving puts drivers out-of-the-loop and increases the difficulty of takeovers when requested. To address this problem, I systematically investigate how drivers’ emotions, cognitive load, vehicle capability and driving environments influence their behavioral and physiological responses to takeover requests using human-subject experiments. Next, I develop computational models to predict drivers’ takeover performance using their physiological data and environment data. Furthermore, I propose in-vehicle alert displays based on the framework of situational awareness to help drivers improve takeover performance in conditionally automated driving. I will conclude my talk with an overview of other on-going projects and a discussion of future work opportunities that apply human factors, predictive modeling, and human-centered design to human-automation teaming.

Bio:
Na Du is currently a Ph.D. candidate in the Industrial & Operations Engineering at the University of Michigan. Her research aims to improve human performance and safety by applying human factors and data analytical techniques to the analysis, design, and evaluation of the autonomous technologies. Her research interests include transportation human factors, human-automation interaction, and computational modeling of human behaviors. She received her bachelor’s degree in psychology from Zhejiang University. She is a recipient of several awards and fellowships, including HFE Women Rising Star Award, HFES Student Member with Honors Award, HFES Aging Technical Group Scholarship, and Rackham Predoctoral
Fellowship.