Introducing a multivariate model for predicting driving performance: The role of driving anger and personal characteristics

dc.contributor.authorRoidl, Ernst
dc.contributor.authorSiebert, Felix Wilhelm
dc.contributor.authorOehl, Michael
dc.contributor.authorHöger, Rainer
dc.date.accessioned2019-08-14T13:05:17Z
dc.date.available2019-08-14T13:05:17Z
dc.date.issued2013-08-15
dc.description.abstractIntroduction: Maladaptive driving is an important source of self-inflicted accidents and this driving style could include high speeds, speeding violations, and poor lateral control of the vehicle. The literature suggests that certain groups of drivers, such as novice drivers, males, highly motivated drivers, and those who frequently experience anger in traffic, tend to exhibit more maladaptive driving patterns compared to other drivers. Remarkably, no coherent framework is currently available to describe the relationships and distinct influences of these factors. Method: We conducted two studies with the aim of creating a multivariate model that combines the aforementioned factors, describes their relationships, and predicts driving performance more precisely. The studies employed different techniques to elicit emotion and different tracks designed to explore the driving behaviors of participants in potentially anger-provoking situations. Study 1 induced emotions with short film clips. Study 2 confronted the participants with potentially anger-inducing traffic situations during the simulated drive. Results: In both studies, participants who experienced high levels of anger drove faster and exhibited greater longitudinal and lateral acceleration. Furthermore, multiple linear regressions and path-models revealed that highly motivated male drivers displayed the same behavior independent of their emotional state. The results indicate that anger and specific risk characteristics lead to maladaptive changes in important driving parameters and that drivers with these specific risk factors are prone to experience more anger while driving, which further worsens their driving performance. Driver trainings and anger management courses will profit from these findings because they help to improve the validity of assessments of anger related driving behavior.en
dc.identifier.eissn1879-1247
dc.identifier.issn0022-4375
dc.identifier.urihttps://depositonce.tu-berlin.de/handle/11303/9754
dc.identifier.urihttp://dx.doi.org/10.14279/depositonce-8787
dc.language.isoenen
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/en
dc.subject.ddc150 Psychologiede
dc.subject.ddc380 Handel, Kommunikation, Verkehrde
dc.subject.otheremotionsen
dc.subject.otherdriving angeren
dc.subject.otherdriving motivationen
dc.subject.otherdriving performanceen
dc.subject.otherrisky drivingen
dc.titleIntroducing a multivariate model for predicting driving performance: The role of driving anger and personal characteristicsen
dc.typeArticleen
dc.type.versionacceptedVersionen
dcterms.bibliographicCitation.doi10.1016/j.jsr.2013.08.002en
dcterms.bibliographicCitation.journaltitleJournal of Safety Researchen
dcterms.bibliographicCitation.originalpublishernameElsevieren
dcterms.bibliographicCitation.originalpublisherplaceAmsterdamen
dcterms.bibliographicCitation.pageend56en
dcterms.bibliographicCitation.pagestart47en
dcterms.bibliographicCitation.volume47en
tub.accessrights.dnbfreeen
tub.affiliationFak. 5 Verkehrs- und Maschinensysteme::Inst. Psychologie und Arbeitswissenschaft::FG Arbeits-, Ingenieur- und Organisationspsychologiede
tub.affiliation.facultyFak. 5 Verkehrs- und Maschinensystemede
tub.affiliation.groupFG Arbeits-, Ingenieur- und Organisationspsychologiede
tub.affiliation.instituteInst. Psychologie und Arbeitswissenschaftde
tub.publisher.universityorinstitutionTechnische Universität Berlinen

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