The emotional spectrum in traffic situations: Results of two online-studies

Roidl, Ernst; Frehse, Berit; Oehl, Michael; Höger, Rainer

doi:10.1016/j.trf.2012.12.009

Cited by 42 publications

(13 citation statements)

References 39 publications

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“…sudden braking of the front vehicle) or general survival goal (e.g. obscene gestures from other drivers) (Deffenbacher et al, 1994;Mesken et al, 2007;Roidl et al, 2013). The general aggression model (GAM, Anderson and Bushman, 2002) further contends that the relationship between emotional experience and behavioural expression is moderated by cognitive appraisals.…”

Section: Driving Anger and Violationsmentioning

confidence: 99%

Dimensions of driving anger and their relationships with aberrant driving

Zhang

Chan

Zhang

2015

Accident Analysis & Prevention

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Section: Driving Anger and Violationsmentioning

confidence: 99%

Dimensions of driving anger and their relationships with aberrant driving

Zhang

Chan

Zhang

2015

Accident Analysis & Prevention

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“…One of the most commonly studied causes of traffic accidents is risky driving behaviour (Di Stasi et al 2010;Hu et al 2013;Roidl et al 2013;Trógolo et al 2014). Researchers agree that psychological factors are related to risky driving and thus contribute, or detract, from traffic safety.…”

Section: Introductionmentioning

confidence: 99%

Difficulties in emotion regulation and risky driving among Lithuanian drivers

Šeibokaitė

Endriulaitienė

Sullman

et al. 2017

Traffic Injury Prevention

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“…A revised version of Geneva Emotion Wheel was selected as classification basis of driving emotion. 45,46 Sixteen kinds of driving emotions were included in the Emotion Wheel. 47 For the convenience of study, eight typical driving emotions, namely, anger, surprise, fear, anxiety, helplessness, contempt, relief, and pleasure were selected.…”

Section: Data Acquisitionmentioning

confidence: 99%

Feature extraction and dynamic identification of driving intention adapting to multi-mode emotions

Wang

Liu

et al. 2019

Advances in Mechanical Engineering

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Accurate identification of driving intention and reasonable control of driver's behavior is seen as an important mean to reduce man-made traffic accidents for the intelligent vehicle. However, the intention identification processes associated with driving emotion-related impact have received very little attention. With the aim of uncovering the emotional impact on driving intention identification, the car-following condition was taken as an example, and multi-source and dynamic data of human-vehicle-environment under different driving emotional states were obtained through the experiments of emotions induction, actual driving, and virtual driving in this study. The feature extraction and dynamic identification models based on rough set theory and back-propagation artificial neural network were built to recognize driving intentions. The results showed that there were some differences in driving intention identification under different emotional modes. The differences were mainly manifested in the complexity and accuracy of intention feature vectors. The rationality and validity of the intentions feature extraction and identification models were verified by the actual driving experiments, virtual driving experiments, and interactive simulation experiments. The research results can provide theoretic basis for the emotional intelligence research of advanced vehicle, driving assist systems, and unmanned vehicles.

show abstract

The emotional spectrum in traffic situations: Results of two online-studies

Cited by 42 publications

References 39 publications

Dimensions of driving anger and their relationships with aberrant driving

Dimensions of driving anger and their relationships with aberrant driving

Difficulties in emotion regulation and risky driving among Lithuanian drivers

Feature extraction and dynamic identification of driving intention adapting to multi-mode emotions

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