Get Ready for Take-Overs: Using Head-Up Display for Drivers to Engage in Non-Driving-Related Tasks in Automated Vehicles.

Objective: The study aims to investigate the potential of using HUD (head-up display) as an approach for drivers to engage in non-driving-related tasks (NDRTs) during automated driving, and examine the impacts on driver state and take-over performance in comparison to the traditional mobile phone.

Background: Advances in automated vehicle technology have the potential to relieve drivers from driving tasks so that they can engage in NDRTs freely. However, drivers will still need to take-over control under certain circumstances.

Can't simply roll it out: Evaluating a real-world virtual reality intervention to reduce driving under the influence.

Driving under the influence (DUI) increases the risk of crashes. Emerging technologies, such as virtual reality (VR), represent potentially powerful and attractive tools for the prevention of risky behaviours, such as DUI. Therefore, they are embraced in prevention efforts with VR interventions primed to grow in popularity in near future.

Driving under the influence of drugs or alcohol: Predicting the intentions of young drivers.

Driving under the influence (DUI) of drugs or alcohol impairs driving performance and, as a result, increases the risk of crashes. The risk of DUI is five-fold higher for young drivers (aged 18-25 years), but little is known about what determines their DUI intentions. This study applied an extended model of the Theory of Planned Behavior (TPB) to address the research question of what factors might influence young drivers' future intentions to DUI.

Understanding the predictors of young drivers' speeding intention and behaviour in a three-month longitudinal study.

This study aimed to examine to what extent an Adolescent Speeding Specific Model (ASSM), extending the theory of planned behaviour (TPB), predicts young drivers' (aged 18-25) future and past speeding (n = 126). The ASSM tested the contribution of demographics, split TPB, additional predictors and past behaviour to young drivers' speeding at two moments of time, over three months. Hierarchical multiple regression revealed that participants most likely to speed in the future were those who have done so in the past (independent predictor (ip): past compliance with the speed limit), and who were not certain in their ability to control their speeding (ip: self-efficacy).