Presented by Angus McKerral from the University of Newcastle
Highly automated vehicles (AVs) offer an enormous potential benefit to the road safety environment. However, their impact is conditional on efficient human-system interactions, and factors such as driver anxiety have the potential to affect transitions of control when vehicle system boundaries are reached (takeover scenarios).
We aimed to demonstrate the relationship between driver anxiety and key cognitions underpinning takeover performance. Situation awareness and anxiety were assessed during takeover scenarios pre- and post an extended fatiguing automated drive while either passively monitoring the vehicle or engaging in non-driving related tasks.
Drivers required to monitor the AV during the fatiguing drive were shown to have significantly lower driving-specific post-drive anxiety. Drivers' state-anxiety was found to predict changes in situation awareness.
The results demonstrate the impairing effect of anxiety in critical takeover capacity and emphasise the importance of tailoring human-machine interactions to individuals. Finally, exposure to AV driving scenarios may reduce driving anxiety, but only in specific contexts.
About the speaker
Angus McKerral is a PhD candidate at the University of Newcastle, Australia, investigating factors affecting driver takeover capacity in highly automated vehicles.
As part of the Applied Psychology Lab, his research makes use of simulated driving environments to assess driver reconstruction of situation awareness during critical takeover, using a range of psychometric and physiological methods.
Date | Tuesday, 27 September 2022 |
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Time | 12:30pm - 1:00pm |
Audience | Staff,Postgraduate students,Undergraduate students,Public |
Event Type |
Seminar |
Campus | Dunedin |
Department | Psychology |
Location | William James Building, Seminar Room 1.03, Dunedin |
Cost | Free |
Contact Name | Narun Pat |
Contact Phone | +64 3 479 4629 |
Contact Email | narun.pat@otago.ac.nz |
Website | https://www.otago.ac.nz/psychology/index.html |