A Model for Traffic Accidents Prediction Based on Driver Personality Traits Assessment

Promet (Zagreb)

Boris Antić¹  Svetlana Čičević¹  Krsto Lipovac¹  Marjana Čubranić-Dobrodolac¹ 

[1] University of Belgrade, Faculty of Transport and Traffic Engineering;

关键词: risk perception;    aggressiveness;    impulsiveness;    self-perception;    traffic accidents;    traffic safety;   

DOI  :  10.7307/ptt.v29i6.2495

来源: DOAJ

【 摘 要 】

The model proposed in this paper uses four psychological instruments for assessing driver behaviour and personality traits aiming to find a relationship between the considered constructs and the occurrence of traffic accidents. A Barratt Impulsiveness Scale (BIS-11) was used for the assessment of impulsivity, Aggressive Driving Behaviour Questionnaire (ADBQ) for assessing the aggressiveness while driving, Manchester Driver Attitude Questionnaire (DAQ) and the Questionnaire for self-assessment of driving ability. Besides these instruments, the participants filled out an extensive demographic survey. Within the statistical analysis, in addition to the descriptive indicators, correlation coefficients were calculated and four hierarchical regression analyses were performed to determine the predictive power of personality traits on the occurrence of traffic accidents. Further, to confirm the results and to obtain additional information about the relationship between the considered variables, the structural equation modelling and binary logistic regression have been implemented. A sample of this research covered 305 drivers, of which there were 100 bus drivers and 102 truck drivers, as well as 103 drivers of privately owned vehicles. The results indicate that BIS-11 and ADBQ questionnaires show the best predictive power which means that impulsivity and aggressiveness as personality traits have the greatest influence on the occurrence of traffic accidents. This research could be useful in many fields, such as the design of selection procedures for professional drivers, development of programs for the prevention of traffic accidents and violations of law, rehabilitation of drivers who have been deprived of the driving license, etc.

【 授权许可】

Unknown