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Driver distraction
(2017)
This report for the Institute of Advanced Motorists (IAM) summarises recent research and knowledge from scientific studies about distracted driving. The report defines what it means to be "distracted" when driving, discusses the impact of distraction on driver behaviour and safety, and what can be done to reduce distracted driving. The focus of distraction discussed here relates to how drivers engage with technology when driving. The report begins with a background to driver distraction, followed by discussion about what is actually meant by driver distraction. It is then considered why humans cannot successfully do two things at the same time, particularly within the context of driving. The subsequent section summarises the scientific research findings to date with regard to driver distraction and technology, and how this affects different types of road user. Recommendations for how driver distraction can be mitigated in the real world and a summary conclude the report. Responses to common questions raised by drivers are presented in Appendix A.
Many safety-relevant tasks in control or diagnostics require binary choices such as "conflict versus separation" in air traffic control, "normal versus pathological" when interpreting x-ray pictures, or "permitted versus forbidden" when inspecting airport security scans. Deciders often are uncertain, but nevertheless required to decide between two alternatives, that is, they have not only to decide upon an action, but also about the admissible level of uncertainty. If the accepted level of judgment certainty is not taken into account, the sequence of decisions does not capture the full picture of the underlying decision process. Differences in judgment certainty are relevant, because they reflect not only the adequacy of the human-machine interface that is evaluated, but also the differences in expertise of the decider and the requirements of the actual situation or task. Therefore, capturing both judgment certainty and discrimination performance is essential. A comparison of different human-machine-interfaces (for air traffic control) is used to illustrate a methodological approach, which allows for integrated analyses of decision processes based on receiver-operator-characteristics and practical guidelines for the evaluation of human-machine-interfaces for safety-relevant operation procedures are provided.
The strong prevalence of human error as a crash causation factor in motorcycle accidents calls for countermeasures that help tackling this issue. Advanced rider assistance systems pursue this goal, providing the riders with support and thus contributing to the prevention of crashes. However, the systems can only enhance riding safety if the riders use them. For this reason, acceptance is a decisive aspect to be considered in the development process of such systems. In order to be able to improve behavioural acceptance, the factors that influence the intention to use the system need to be identified. This paper examines the particularities of motorcycle riding and the characteristics of this user group that should be considered when predicting the acceptance of advanced rider assistance systems. Founded on theories predicting behavioural intention, the acceptance of technologies and the acceptance of driver support systems, a model on the acceptance of advanced rider assistance systems is proposed, including the perceived safety when riding without support, the interface design and the social norm as determinants of the usage intention. Since actual usage cannot be measured in the development stage of the systems, the willingness to have the system installed on the own motorcycle and the willingness to pay for the system are analyzed, constituting relevant conditions that allow for actual usage at a later stage. Its validation with the results from user tests on four advanced rider assistance systems allows confirming the social norm and the interface design as powerful predictors of the acceptance of ARAS, while the extent of perceived safety when riding without support did not have any predictive value in the present study.
Immediate user self-evacuation is crucial in case of fire in road tunnels. This study investigated the effects of information with or without additional virtual reality (VR) behavioural training on self-evacuation during a simulated emergency situation in a road tunnel. Forty-three participants were randomly assigned to three groups with accumulating preventive training: The control group only filled in questionnaires, the informed group additionally read an information brochure on tunnel safety, and the VR training group received an additional behavioural training in a VR tunnel scenario. One week later, during the test session, all participants conducted a drive through a real road tunnel in which they were confronted with a collision of two vehicles and intense smoke. The informed and the behaviourally trained participants evacuated themselves more reliably from the tunnel than participants of the control group. Trained participants showed better and faster behavioural responses than informed only participants. Interestingly, the few participants in the control group who reacted adequately to the scenario were all female. A 1 year follow-up online questionnaire showed a decrease of safety knowledge, but still the trained group had somewhat more safety relevant knowledge than the two other groups. Information and especially VR behavioural training both seem promising to foster adequate self-evacuation during crisis situations in tunnels, although long term beneficial behavioural effects have to be demonstrated. Measures aiming to improve users/ behaviour should take individual difference such as gender into account.