User expectations of partial driving automation capabilities and their effect on information design preferences in the vehicle

Appl Ergon. 2020 Jan:82:102969. doi: 10.1016/j.apergo.2019.102969. Epub 2019 Oct 7.

Abstract

Partially automated vehicles present interface design challenges in ensuring the driver remains alert should the vehicle need to hand back control at short notice, but without exposing the driver to cognitive overload. To date, little is known about driver expectations of partial driving automation and whether this affects the information they require inside the vehicle. Twenty-five participants were presented with five partially automated driving events in a driving simulator. After each event, a semi-structured interview was conducted. The interview data was coded and analysed using grounded theory. From the results, two groupings of driver expectations were identified: High Information Preference (HIP) and Low Information Preference (LIP) drivers; between these two groups the information preferences differed. LIP drivers did not want detailed information about the vehicle presented to them, but the definition of partial automation means that this kind of information is required for safe use. Hence, the results suggest careful thought as to how information is presented to them is required in order for LIP drivers to safely using partial driving automation. Conversely, HIP drivers wanted detailed information about the system's status and driving and were found to be more willing to work with the partial automation and its current limitations. It was evident that the drivers' expectations of the partial automation capability differed, and this affected their information preferences. Hence this study suggests that HMI designers must account for these differing expectations and preferences to create a safe, usable system that works for everyone.

Keywords: Autonomous vehicle; Driving simulator; HMI; Information preferences; Partial automation; Qualitative; SAE level 2.

MeSH terms

  • Adolescent
  • Adult
  • Attention
  • Automation*
  • Automobile Driving / psychology*
  • Automobiles*
  • Computer Simulation
  • Equipment Design
  • Female
  • Humans
  • Male
  • Reaction Time
  • Spatial Navigation*