Open AccessPerceived safety and trust in SAE Level 2 partially automated cars: Results from an online questionnaire
Author(s) -
Siordhoff,
Jork Stapel,
Xiaolin He,
Alexandre Gentner,
Riender Happee
Publication year - 2021
Publication title -
plos one
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.99
H-Index - 332
ISSN - 1932-6203
DOI - 10.1371/journal.pone.0260953
Subject(s) - automation , expectancy theory , distracted driving , phone , applied psychology , structural equation modeling , driving simulator , human factors and ergonomics , poison control , computer science , psychology , engineering , social psychology , medicine , simulation , medical emergency , mechanical engineering , linguistics , philosophy , machine learning
The present online study surveyed drivers of SAE Level 2 partially automated cars on automation use and attitudes towards automation. Respondents reported high levels of trust in their partially automated cars to maintain speed and distance to the car ahead ( M = 4.41), and to feel safe most of the time ( M = 4.22) on a scale from 1 to 5. Respondents indicated to always know when the car is in partially automated driving mode ( M = 4.42), and to monitor the performance of their car most of the time ( M = 4.34). A low rating was obtained for engaging in other activities while driving the partially automated car ( M = 2.27). Partial automation did, however, increase reported engagement in secondary tasks that are already performed during manual driving (i.e., the proportion of respondents reporting to observe the landscape, use the phone for texting, navigation, music selection and calls, and eat during partially automated driving was higher in comparison to manual driving). Unsafe behaviour was rare with 1% of respondents indicating to rarely monitor the road, and another 1% to sleep during partially automated driving. Structural equation modeling revealed a strong, positive relationship between perceived safety and trust ( β = 0.69, p = 0.001). Performance expectancy had the strongest effects on automation use, followed by driver engagement, trust, and non-driving related task engagement. Perceived safety interacted with automation use through trust. We recommend future research to evaluate the development of perceived safety and trust in time, and revisit the influence of driver engagement and non-driving related task engagement, which emerged as new constructs related to trust in partial automation.