Abstract
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.
Highlights
Since the early 19th century, we trust cars driving at high speeds in complex traffic
The second-highest mean rating was obtained for always knowing when the car is in partially automated driving mode (M = 4.42, SD = 0.87), and the third-highest was obtained for trusting the partially automated car to maintain the speed and distance to the car ahead (M = 4.41, SD = 0.73)
The analysis revealed that performance expectancy had the strongest effect on automation use (β = 0.31, p = 0.001), followed by driver engagement (β = 0.30, p = 0.001), and non-driving related task engagement (β = 0.14, p = 0.01)
Summary
Since the early 19th century, we trust cars driving at high speeds in complex traffic. Cruise Control (ACC) and Lane Keeping Assistance (LKA). These SAE Level 2 systems require the permanent supervision of human drivers to ensure the reliable and safe operation of the automated driving system. Driver monitoring systems have already been implemented in passenger cars since the early 2000s. Daimler equipped their Mercedes Benz model series with drowsiness detection algorithms using the steering wheel behavior of drivers. Further monitoring technologies include infrared eye-tracking systems and heart rate activity monitors [1,2,3] These technologies monitor driver’s readiness to take over control from the automated car on highways, allowing drivers to perform non-driving related tasks for a few seconds
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