Publications by authors named "Mikael Ljung Aust"

Frustration is a complex emotional phenomenon subject to various triggers and manifested through multifaceted behavioral and affective responses. This study investigates the relationship between distinct frustration-inducing situations encountered during driving and the corresponding affective responses, focusing on the mediating role of behavioral dimensions. A total of 2244 participants answered a questionnaire on driving behavior, the likelihood of experiencing frustration in various driving situations, and affective responses in frustrating situations.

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Driver fatigue is a contributing factor in about 10-30% of all fatal crashes. Prevention of fatigue-related crashes relies on robust detection of driver fatigue and application of effective countermeasures. A potential countermeasure is fragrance administration since odors can have alerting effects on humans.

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Article Synopsis
  • - The research highlights the unclear impacts of cognitive load on driving behavior and the need for better methods to measure it for traffic safety studies, advocating for more comprehensive driver monitoring systems.
  • - Current approaches often oversimplify cognitive load as a single factor, ignoring its complex nature that involves various mental responses influenced by specific driving tasks and environments.
  • - A driving simulator study utilized multiple physiological measures (like heart rate and EEG) to analyze cognitive load during a testing task, suggesting that examining a range of responses can enhance the understanding and measurement of cognitive load in driving contexts.
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Objective: The aim of this study was to understand how to secure driver supervision engagement and conflict intervention performance while using highly reliable (but not perfect) automation.

Background: Securing driver engagement-by mitigating irony of automation (i.e.

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To develop relevant road safety countermeasures, it is necessary to first obtain an in-depth understanding of how and why safety-critical situations such as incidents, near-crashes, and crashes occur. Video-recordings from naturalistic driving studies provide detailed information on events and circumstances prior to such situations that is difficult to obtain from traditional crash investigations, at least when it comes to the observable driver behavior. This study analyzed causation in 90 video-recordings of car-to-pedestrian incidents captured by onboard cameras in a naturalistic driving study in Japan.

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Fatal motor vehicle intersection crashes occurring in Norway in the years 2005-2007 were analyzed to identify causation patterns among their underlying contributing factors, and also to assess if the data collection and documentation procedures used by the Norwegian in-depth investigation teams produces the information necessary to do causation pattern analysis. 28 fatal accidents were analyzed. Causation charts of contributing factors were first coded for each driver in each crash using the Driving Reliability and Error Analysis Method (DREAM).

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Objective: The objective of the present study was to examine the effect of working memory load on drivers' responses to a suddenly braking lead vehicle and whether this effect (if any) is moderated by repeated scenario exposure.

Background: Several experimental studies have found delayed braking responses to lead vehicle braking events during concurrent performance of nonvisual, working memory-loading tasks, such as hands-free phone conversation. However, the common use of repeated, and hence somewhat expected, braking events may undermine the generalizability of these results to naturalistic, unexpected, emergency braking scenarios.

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To define pre-crash scenarios for evaluation of active safety functions, data from crash investigations is often used. Typical data sources include official databases with police reported crashes (macroscopic data) and in-depth case studies (microscopic data). Macroscopic data is often representative but has little detail on causation, while the opposite is true of microscopic data.

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