Automation Preferences by Traffic Climate and Driver Skills in Two Samples From Countries with Different Levels of Traffic Safety

Abstract

Automated systems present great capabilities with a wide range of options. In this respect, vehicle preferences and factors affecting these preferences are important for the future of automated systems. While automated systems offer varied features and improvements for drivers and general traffic safety, the relationship between drivers’ perceptions of traffic systems and driver skills have not been studied. The present study, therefore, focuses on country differences and the relationships between traffic climate and driver skills and their impact on the preferred level of vehicle automation for drivers in Turkey and Sweden. The study was conducted with 318 drivers (age: mean [M] = 22.41, standard deviation [SD] = 2.77) from Turkey and 312 drivers (age: M = 28.80, SD = 8.53) from Sweden in 2020. A questionnaire package asking for demographic information and preferred levels of vehicle automation—Traffic Climate Scale (TCS) and the Driver Skill Inventory (DSI)—was completed. A series of analyses of covariance (ANCOVA), hierarchical regression, and moderated moderation analyses were conducted. Drivers from Turkey preferred higher automation levels than drivers from Sweden. Drivers with higher perceived safety skills, with lower perceived perceptual-motor skills or perceiving the traffic system as more externally demanding preferred higher automation levels. Drivers’ automation preferences were affected by various individual and country-level factors. For the first time, drivers’ automation preferences were elaborated in relation to traffic climate and driver skills in two countries with different levels of traffic safety. Theoretical and practical implications of the findings are discussed in the light of the literature.

Keywords

human factors automation preference traffic climate driver skills hierarchical regression

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