An Approach to Design Variables for Analysis of Conditionally Automated Driving Transitions

Abstract

In conditionally automated vehicles, drivers can occasionally activate the autopilot
to perform driving tasks such as steering and braking. During this time, the driver
may participate in secondary tasks such as reading and monitoring the
surrounding. However, the driver must stay alert to a potential request to resume
driving in situations that cannot be managed by the autopilot. The situation
awareness of drivers in such driving situations that cannot be managed by the
autopilot is required to avoid accidents during the transition. Previous studies
indicate that various variables such as complexity of surrounding traffic
conditions, secondary tasks, speed of subject vehicle, and previous takeover
transition experience affect takeover performance. However, the approach to
utilize these variables to enable efficient takeover transitions have not been
determined. This contribution discusses a systematic design of these variables. It
utilizes known dimensions of complex dynamical systems and fundamentals of
human cognitive processes to design driving scenarios and secondary tasks. The
characteristics of the variables are systemically varied to generate different driving
situations to better understand how they determine takeover transitions and
interaction.