Citation

Rukonić L, Mwange MAP, Kieffer S. SN Comput. Sci. 2023; 4(1): e56.

Copyright

(Copyright © 2023, Holtzbrinck Springer Nature Publishing Group)

DOI

10.1007/s42979-022-01455-9

PMID

36405007

PMCID

PMC9668227

Abstract

The automotive industry is working toward driving automation and driver-assistance technology is becoming a norm in modern cars. Warning alert systems support the driver-car interaction and inform drivers about automation system status, upcoming obstacles, or dangers ahead. However, older drivers' needs are not always addressed in research studies, although they make up a large segment of drivers. Therefore, we conducted a qualitative three-round formative evaluation of a warning alert system using video prototypes in lab and remote settings. The goal was to evaluate visual-, sound-, and speech-based alerts based on: (a) their efficiency in informing drivers about the road situation ahead, and (b) participants' subjective opinions. We evaluated the system's efficiency using self-reported data measuring participants' cognitive load, usability, UX, and ease of use. Also, we conducted interviews to collect subjective feedback about proposed prototypes. In this article, we describe the design of warning alerts and report on their evaluation results. Our results show that speech-based warnings, especially when coupled with visual warnings, are efficient and accepted well by the participants. This article illustrates older drivers' attitude toward the use of different warning modalities in the driving context.

Language: en

Keywords

Older drivers; Formative evaluation; Modalities; Video prototypes; Warning alerts