Sharing the Roads: Robot Drivers (Vs. Human Drivers) Might Provoke Greater Driving Anger When They Perform Identical Annoying Driving Behaviors

Author(s):  
Tingting Li ◽  
Lin Wang ◽  
Jinting Liu ◽  
Jiangshu Yuan ◽  
Peng Liu
Author(s):  
Tingru Zhang ◽  
Alan H.S. Chan ◽  
Hongjun Xue ◽  
Xiaoyan Zhang ◽  
Da Tao

With the dramatic increase in motorization, road traffic crashes have become the leading cause of death in China. To reduce the losses associated with road safety problems, it is important to understand the risk factors contributing to the high crash rate among Chinese drivers. This study investigated how driving anger and aberrant driving behaviors are related to crash risk by proposing and testing one mediated model. In this model, the effects of driving anger on road crash risk were mediated by aberrant driving behaviors. However, unlike previous studies, instead of using the overall scale scores, the subscales of driving anger and aberrant driving behaviors were used to establish the mediated model in this study. To test the validity of this model, an Internet-based questionnaire, which included various measures of driving anger, aberrant driving, and road crash history, was completed by a sample of 1974 Chinese drivers. The results showed that the model fitted the data very well and aberrant driving behaviors fully mediated the effects of driving anger on road crash risk. Findings from the present study are useful for the development of countermeasures to reduce road traffic crashes in China.


2015 ◽  
Vol 37 (1) ◽  
pp. 42-46 ◽  
Author(s):  
Jessye Almeida Cantini ◽  
George Oliveira Santos ◽  
Eduardo de Carvalho Machado ◽  
Antonio Egídio Nardi ◽  
Adriana Cardoso Silva

Introduction: Driving anger has attracted the attention of researchers in recent years because it may induce individuals to drive aggressively or adopt risk behaviors. The Driving Anger Scale (DAS) was designed to evaluate the propensity of drivers to become angry or aggressive while driving. This study describes the cross-cultural adaptation of a Brazilian version of the short form and the long form of the DAS.Methods: Translation and adaptation were made in four steps: two translations and two back-translations carried out by independent evaluators; the development of a brief version by four bilingual experts in mental health and driving behaviors; a subsequent experimental application; and, finally, an investigation of operational equivalence.Results: Final Brazilian versions of the short form and of the long form of the DAS were made and are presented. Conclusions: This important instrument, which assesses driving anger and aggressive behaviors, is now available to evaluate the driving behaviors of the Brazilian population, which facilitates research in this field.


2010 ◽  
Vol 69 (4) ◽  
pp. 233-238 ◽  
Author(s):  
Nolwenn Morisset ◽  
Florence Terrade ◽  
Alain Somat

Les recherches dans le domaine de la santé, et notamment en matière de conduite automobile, attestent que le jugement subjectif du risque (comparatif et absolu) et l’auto-efficacité perçue sont impliqués dans les comportements à risque. Cette étude avait pour objectif d’étudier l’influence de l’auto-efficacité perçue sur le jugement subjectif du risque, évalué au moyen d’une mesure indirecte, et de tester le rôle médiateur de ce facteur entre l’auto-efficacité perçue et les comportements auto-déclarés. Les participants, 90 hommes, lisaient deux scénarii décrivant les deux comportements les plus impliqués dans l’accidentologie: la vitesse et l’alcool au volant. Les résultats ne montrent pas de lien significatif entre l’auto-efficacité perçue et le score de jugement comparatif mais une relation significative avec les deux évaluations absolues du risque (autrui et soi). De plus, le jugement absolu du risque pour soi médiatise partiellement la relation entre auto-efficacité perçue et comportements auto-déclarés relatifs aux deux risques routiers étudiés.


2008 ◽  
Author(s):  
Valerie D. Weisser ◽  
Kevin Manning ◽  
Allison Blasco ◽  
Nicole Sesitito ◽  
Jocelyn Ang ◽  
...  

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