Usability testing of three visual HMIs for assisted driving: How design impacts driver distraction and mental models

Abstract

There is a variety of visual human-machine interfaces (HMI) designed across vehicle manufacturers that support drivers while supervising driving automation features, such as adaptive cruise control (ACC). These various designs communicate the same limited amount of information to drivers about their ACC system and it is unclear which HMI designs impact driver distraction the least or how their design could be modified to help drivers develop more accurate mental models of their ACC system. Using a user-centred design (UCD) approach, we designed a speedometer to inform drivers about some of the system’s capabilities and then invited 23 drivers to use ACC in a low-fidelity driving simulator to compare the usability of three HMIs using eye-tracking, response times, and qualitative data. Our attempt at designing an intuitive and more informative speedometer received mixed results, but design recommendations are given regarding the indication of the set target speed, set time gap between vehicles (headway distance), and system mode (conventional or adaptive cruise).

Practitioner summary: Manufacturers’ heterogeneous designs of their visual HMIs for the ACC systems may impact driver distraction in different ways. We used usability testing to compare three HMIs in a driving simulator and make several design recommendations to indicate speed, time gap, and system mode in a more efficient way.

Abbreviations: ACC: adaptive cruise control; ADAS: advanced driving assistance system; HMI: human-machine interface; ISO: international organisation for standardization; OEM: original equipment manufacturer; RSME: rating scale of mental effort; RT: response time; R-TLX: raw task load index; SUS: system usability scale; TGT: total glance time; UCD: user-centred design; UX: user experience; xTGT: extended total glance time

Keywords:

• Adaptive cruise control
• human-machine interface
• User-centred design
• Eye-tracking
• Visual attention

Acknowledgements

The authors would like to thank Michael Daly for his contribution to implementing our HMI with the University of Leeds Driving Simulator.

Ethics approval

This research was approved by the Social Sciences, Environment and LUBS (AREA) Faculty Research Ethics Committee of the University of Leeds under the reference LTTRAN-122.

Consent to participate

Respondents gave consent to participate.

Consent for publication

Respondents gave consent for publication.

Authors’ contributions

Mickaël Perrier, the doctoral student, designed the study, developed the HMI and iPad application, analysed the data, and wrote the article.

Tyron Louw and Oliver Carsten, the doctoral supervisors, assisted throughout the conduction of this study and the writing of this article.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Availability of data, material, and code

The datasets, custom codes, and materials generated and analysed during the current study are available in the Open Framework repository: https://osf.io/9wnq8/?view_only=5b47cd7cf6434dc6bcc7fda13dea5f0a.

Notes

1 Interface: any physical means of translating and transmitting a signal intelligible by one party into a signal intelligible by another party, in either direction.

2 Adaptive cruise control (ACC) accelerates the vehicle up to a chosen target speed and decelerates to slower lead vehicles to maintain a set headway time.

Additional information

Funding

The researchers are supported by funding from Bosch UK, EPSRC, and the University of Leeds.