Socio-economic and driving experience factors affecting drivers' perceptions of traffic crash risk. (February 2016)

• Record Type: Journal Article
• Authors: Machado-León, José Luis; de Oña, Juan; de Oña, Rocío; Eboli, Laura; Mazzulla, Gabriella
• Is Part Of: Transportation research. Volume 37(2016)
• Page Start: 41
• Page End: 51
• Publication Date: 2016-02
• Subjects: Road crashes risk -- Rank-ordered logit model -- Gender -- Driving experience -- Income -- Number of people in household; Automobile drivers -- Psychology -- Periodicals; Automobile driving -- Psychological aspects -- Periodicals; Transportation -- Psychological aspects -- Periodicals; 629.283019
• DOI: 10.1016/j.trf.2015.11.010
• Languages: English
• ISSNs: 1369-8478

Abstract

Highlights: A Stated Preference survey is used to measure drivers' perceptions of crash risk. The Stated Preference approach considers that subjective risk is context dependent. Effects of five risky driving behaviours on perceptions of risk are identified. Socio-economic variables & driving experience have a significant effect on perception. Abstract: Drivers are estimated to contribute an overwhelming proportion to the burden of traffic crashes, as factors that increase crash risk are frequently due to unsafe driving behaviours. The relationship between risk perceptions and people's risky driving behaviours is still not well understood. This paper aims to further analyse the potential effect of risky driving behaviours on drivers' perceptions of crash risk and differences in perceptions among drivers. Crash risk perceptions in an inter-city, two-way road context of 492 drivers were measured by using a Stated Preference (SP) ranking survey. Rank-ordered logit models were used to evaluate the impact on risk perception of five unsafe driving behaviours and to identify differences in drivers' risk perceptions. The five unsafe driving behaviours considered in the analysis were respectively related to whether or not the driver follows the speed limits, the rules of passing another car and the safe distance, whether or not the driver is distracted, and whether or not she/he is driving under optimal personal conditions. All risky driving behaviours showed a significant potential effect ( p < 0.001) on crash risk perceptions, and model's results allowed to differentiate more important from less important unsafe driving behaviours based on their weight on perceived crash risk. Additionally, this paper further analyses the potential differences in risk perception of these traffic violations between drivers of different characteristics, such as driving experience, household size, income and gender. The SP technique could be applied to further analyse differences in perceptions of risky driving behaviours among drivers. Future research should consider the potential effect of driving skill on perceptions of risky driving behaviours.