Attention and Threat Detection: Warnings and How They Affect Takeover Performance. (December 2020)

• Record Type: Journal Article
• Authors: Brunsen, Emily; McLaughlin, Anne C.; Feng, Jing
• Is Part Of: Proceedings of the Human Factors and Ergonomics Society ... Annual Meeting. Volume 64:Part 1(2020)
• Page Start: 1856
• Page End: 1860
• Publication Date: 2020-12
• Subjects: Human engineering -- Congresses; 620.8205
• DOI: 10.1177/1071181320641446
• Languages: English
• ISSNs: 1541-9312

Abstract

Vehicle automation is becoming more advanced in helping drivers understand and react to the environment around them. Many newer vehicle models come standard with backup cameras, blind spot detection, and warning signals. It's important to identify if such features significantly improve driver performance. The current study investigated the relationship between the presentation of a warning indicating a threat and whether or not that signal helped the participants detect the threat. Findings suggested that participants asked to detect when an automated braking system engaged were significantly more accurate at noticing the system engaged than those asked to manually take-over the vehicle when a threat emerged. In both groups, those given visual warnings that a threat was about to occur were faster in taking over the vehicle when needed than those who did not receive a warning. However, accuracy was low across all conditions groups.