Accident; analysis and prevention
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Observational Study
Adolescent driving behavior before and during restrictions related to COVID-19.
Understanding who heeds the driving-related COVID-19 restrictions is critical for assisting public health professionals improve response to this and future pandemic events. The purpose of the current study was to characterize driving behavior changes among adolescents as a function of COVID-19 restrictions. It was hypothesized that adolescent driving would be reduced by COVID-19 restrictions, especially for younger teens, non-minorities, females, non-working teens, and those with higher prosocial tendencies. ⋯ Findings provide early evidence of COVID-19 restriction-related adolescent driving changes suggesting older, employed, minority teens and teens with lower prosocial tendencies are less likely to reduce driving behavior. These observations provide a foundation for more extensive studies of adolescent drivers during various driving and contact restrictions and inform future public health campaigns for social distancing.
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Emergency response drivers (ERDs) are often required to engage in high-risk driving manoeuvres on their way to a reported incident. Such risk requires that these drivers receive a high-level of training and continued development. The aim of this paper was to investigate an innovative format for a new potential tool that could support the training and assessment of these drivers: a single-clip Holistic Hazard Test, containing multiple hazards in a single route. ⋯ ERDs once again responded to MCQs more accurately, and also scored more hazard points on the basis of faster responses to hazards compared to control participants. These results suggest such tests can successfully tap into ERD-specific skills with regard to spotting, predicting and responding to hazards on the road. We recommend refinement of this tool for assessment of emergency response drivers, and further development to extend the materials to create a training tool.
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Traffic accidents are becoming a significant cause for unnatural deaths around the world, with more than 1.25 million fatalities in road accidents each year, and over 20 million people severely injured. A large portion of accidents that result in fatalities involve interaction between vehicles and pedestrians. In the literature, researchers speculate on a wide range of reasons for these figures. ⋯ A series of experiments conclude the paper and support the claim that this phenomenon is frequent among crossing pedestrians. The experimental results suggest that in some common scenarios, more cautious pedestrians may lower the initial risk for an accident at the expense of a total higher risk for an accident during the entire road crossing process, compared with a pedestrian who takes an initial higher level of risk that results in, overall, a decreased probability for an accident. A statistical analysis implies that there are significant differences in this occurrence between adults and children.
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Overtaking cyclists is challenging for drivers because it requires a well-timed, safe interaction between the driver, the cyclist, and the oncoming traffic. Previous research has investigated this manoeuvre in different experimental environments, including naturalistic driving, naturalistic cycling, and simulator studies. These studies highlight the significance of oncoming traffic-but did not extensively examine the influence of the cyclist's position within the lane. ⋯ The results showed that, both when the cyclist rode closer to the centre of the lane and when the time gap to the oncoming vehicle was shorter, safety margins for all potential collisions decreased. Under these conditions, drivers-particularly female drivers-preferred accelerative over flying manoeuvres. Bayesian statistics modelled these results to inform the development of active safety systems that can support drivers in safely overtaking cyclists.
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Forward collision warning (FCW) and autonomous emergency braking (AEB) systems are increasingly available and prevent or mitigate collisions by alerting the driver or autonomously braking the vehicle. Threat-assessment and decision-making algorithms for FCW and AEB aim to find the best compromise for safety by intervening at the "right" time: neither too early, potentially upsetting the driver, nor too late, possibly missing opportunities to avoid the collision. Today, the extent to which activation times for FCW and AEB should depend on factors such as pedestrian speed and lane width is unknown. ⋯ Fractional factorial design effectively compared the influence of seven factors on driver behaviour within a single experiment; however, this design did not allow in-depth data analysis. In the future, OpenDS might become a standard platform, enabling crowdsourcing and favouring repeatability across studies in traffic safety. Finally, this study advises future design and evaluation procedures (e.g. new car assessment programs) for FCW and AEB by highlighting which factors deserve further investigation and which ones do not.