A Novel Application of Non-linear Dynamics Investigating Cognitive Workload and Situational Trust in Highly Automated Vehicles

Abstract

Vehicles with driving automation are becoming increasingly present despite the reported apprehension of potential consumers. The potential benefits, such as fewer crashes, lighter traffic, and increased transportation access, give merit in researching how to engender appropriate human- automation interaction that will ensure a smoother adoption of the technology. One method involves investigating how users receive information about the vehicle. Using a simulated highly automated vehicle, researchers examined how content temporality and modality affected the situational trust and cognitive workload of 36 participants using subjective measures and 15 participants using non-linear dynamics. Researchers found only one significant main effect of temporality on workload; however, post-hoc comparisons between groups were insignificant. Nevertheless, applying non-linear dynamics to driving research is a novel and underutilized approach. Researchers, designers, and users may benefit from using real-time measures rather than aggregate scores to understand how driver behavior changes based on the environment.