Citation

Louw T, Kuo J, Romano R, Radhakrishnan V, Lenné MG, Merat N. Transp. Res. F Traffic Psychol. Behav. 2019; 62: 870-882.

Copyright

(Copyright © 2019, Elsevier Publishing)

DOI

10.1016/j.trf.2019.03.020

PMID

unavailable

Abstract

The aim of this study was to understand driver responses to "silent" failures in automated driving, where automation failed during a simulator drive, without a take-over warning. The effect of a visual non-driving related task (NDRT) and a road-based vigilance task presented drivers' take-over response and visual attention was also investigated. Currently, automated driving systems face a number of limitations that require control to be handed back to the driver. Much of the research to date has focused on explicit take-over requests (ToRs) and shows that drivers struggle to resume control safely, exacerbated by disengagement from the driving task, for instance, due to the presence of NDRTs. However, little is known about whether, and how, drivers will respond to more subtle automation failures that come without a warning, and how this is affected by NDRT engagement. Thirty participants drove a simulated automated drive in two conditions, which had 6 silent automation failures each (3 on a Curve, 3 in a Straight), with no ToRs. In one condition, drivers were required to constantly monitor the road, which was enforced by a road-based vigilance task (VMS Only). In the other, drivers performed an additional visual NDRT, requiring them to divide their attention (VMS + Arrows).

RESULTS showed that, in both conditions, all drivers eventually detected and responded to all silent automation failures. However, engaging in an additional NDRT during automation resulted in significantly more lane excursions and longer take-over times. Adding a visual NDRT not only changed the distribution of drivers' visual attention before and after the failure but also how they divided their attention between information on the road environment and the human-machine interface, which provided information on automation status. These results provide support for how driver monitoring systems may be used to detect drivers' visual attention to the driving task and surroundings, and used as a tool for encouraging driver intervention, when required.

Language: en

Keywords

Automated driving; Automation failure; Distraction; Driver behaviour; Eye-tracking; Take-over