Training Methods to Support Drivers’ Ability to Use AV Systems
Associate Professor of Industrial and Manufacturing Systems Engineering, College of Engineering and Computer Science, the University of Michigan-Dearborn, Associate Research Scientist, Human Factors, University of Michigan Transportation Research Institute and Intermittent Lecturer in Industrial and Operations Engineering, College of Engineering
This study aimed to examine the efficacy of multiple knowledge- and skill-based training strategies on drivers’ safe operation and trust calibration when interacting with in-vehicle systems of varying degrees of automation. Both knowledge- and skill-based training strategies regarding different levels of automation controls were developed and evaluated by using both the University of Michigan Transportation Research Institute automated simulator and the Mcity Test Facility. Both objective performance and subjective rating data from a total of 20 driver participants were collected and compared. The analytic design of the experiment employed a mixed-model design.
Developed and tested training materials on improving users’ understanding of automated vehicle (AV) systems.