The influence of driver stress, partial-vehicle automation, and subjective state on driver performance

The present study addressed the effects of stress, partial-vehicle automation, and subjective state on simulated vehicle driving. 168 college students participated. Participants in the stress-induction condition completed a ‘winter’ drive which included periodic loss-of-control episodes. Participants in the no-stressinduction condition were not exposed to loss of control. Participants then completed a test phase, during which they drove in one of three conditions varying in level of automation. Manipulation checks demonstrated that both the stress manipulation and level of automation influenced subjective state. Driver performance data were analyzed by means of hierarchical multiple regressions. Vehicle automation but not the stress induction influenced performance. In addition, individual differences in subjective task engagement and worry were associated with performance. Resource theory provides a framework that partially but not completely explains the impact of stress factors on performance. Data further show that analysis of individual differences is essential for predicting the effects of stress factors.

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Use of High-Fidelity Simulation to Evaluate Driver Performance with Vehicle Automation Systems

Engineering Psychology and Cognitive Ergonomics - Lecture Notes in Computer Science ◽

10.1007/978-3-642-02728-4_36 ◽

2009 ◽

pp. 339-348

Author(s):

Timothy Brown ◽

Jane Moeckli ◽

Dawn Marshall

Keyword(s):

High Fidelity ◽

High Fidelity Simulation ◽

Driver Performance ◽

Automation Systems ◽

Vehicle Automation

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Attention and Threat Detection: Warnings and How They Affect Takeover Performance

Proceedings of the Human Factors and Ergonomics Society Annual Meeting ◽

10.1177/1071181320641446 ◽

2020 ◽

Vol 64 (1) ◽

pp. 1856-1860

Author(s):

Emily Brunsen ◽

Anne C. McLaughlin ◽

Jing Feng

Keyword(s):

Blind Spot ◽

Threat Detection ◽

Warning Signals ◽

Braking System ◽

Spot Detection ◽

Driver Performance ◽

Vehicle Automation ◽

The Relationship

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.

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