Objective: A driving simulator study was conducted in order to assess the relative utility of unimodal auditory, unimodal vibrotactile, and combined audiotactile (i.e., multisensory) in-car warning signals to alert and inform drivers of likely front-to-rear-end collision events in a situation modeled on real-world driving. Background: The implementation of nonvisual in-car warning signals may have important safety implications in lessening any visual overload during driving. Multisensory integration can provide synergistic facilitation effects. Method: The participants drove along a rural road in a car-following scenario in either the presence or absence of a radio program in the background. The brake light signals of the lead vehicle were also unpredictably either enabled or disabled on a trial-by-trial basis. Results: The results showed that the participants initiated their braking responses significantly more rapidly following the presentation of audiotactile warning signals than following the presentation of either unimodal auditory or unimodal vibrotactile warning signals. Conclusion: Multisensory warning signals offer a particularly effective means of capturing driver attention in demanding situations such as driving. Application: The potential value of such multisensory in-car warning signals is explained with reference to recent cognitive neuroscience research.

Automated driving can fundamentally change road transportation and improve quality of life. However, at present, the role of humans in automated vehicles (AVs) is not clearly established. Interviews were conducted in April and May 2015 with twelve expert researchers in the field of Human Factors (HF) of automated driving to identify commonalities and distinctive perspectives regarding HF challenges in the development of AVs. The experts indicated that an AV up to SAE Level 4 should inform its driver about the AV's capabilities and operational status, and ensure safety while changing between automated and manual modes. HF research should particularly address interactions between AVs, human drivers, and vulnerable road users. Additionally, driver training programs may have to be modified to ensure that humans are capable of using AVs. Finally, a reflection on the interviews is provided, showing discordance between the interviewees' statements-which appear to be in line with a long history of work on human factors research, and the rapid development of automation technology. We expect our perspective to be instrumental for stakeholders involved in AV development and instructive to other parties.

Alcohol-induced hangover, defined by a series of symptoms, is the most commonly reported consequence of excessive alcohol consumption. Alcohol hangovers contribute to workplace absenteeism, impaired job performance, reduced productivity, poor academic achievement, and may compromise potentially dangerous daily activities such as driving a car or operating heavy machinery. These socioeconomic consequences and health risks of alcohol hangover are much higher when compared to various common diseases and other health risk factors. Nevertheless, unlike alcohol intoxication the hangover has received very little scientific attention and studies have often yielded inconclusive results. Systematic research is important to increase our knowledge on alcohol hangover and its consequences. This consensus paper of the Alcohol Hangover Research Group discusses methodological issues that should be taken into account when performing future alcohol hangover research. Future research should aim to (1) further determine the pathology of alcohol hangover, (2) examine the role of genetics, (3) determine the economic costs of alcohol hangover, (4) examine sex and age differences, (5) develop common research tools and methodologies to study hangover effects, (6) focus on factor that aggravate hangover severity (e.g., congeners), and (7) develop effective hangover remedies.

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The generalized optic acceleration cancellation (GOAC) theory of catching proposes that the path of a fielder running to catch a ball is determined by the attempt to satisfy 2 independent constraints. The 1st is to keep the angle of elevation of gaze to the ball increasing at a decreasing rate. The 2nd is to control the rate of horizontal rotation necessary to maintain fixation on the ball. Depending on the lateral velocity of the ball relative to the fielder, this rate may be zero or constant at a negative or positive value. The authors show that a simulated fielder implementing the GOAC strategy follows a path indistinguishable from that of real fielders running to catch balls thrown on the same trajectories.