How drowsiness and distraction can interfere with take-over performance: A systematic and meta-analysis review.

Drowsiness and distraction are major factors of road crashes and responsible of>35% of road fatalities. Automated driving could solve or minimize their impact, yet it is also in itself a way to promote them. Previous literature reviews and meta-analysis regarding take-overs during automated driving primarily focused on distraction rather than drowsiness. We thus present a systematic and meta-analysis literature review focused on the effect of distraction and drowsiness on take-over performance. From an initial selection of 1896 articles from databases, we obtained by applying systematic review methodology a total of 58 articles with 42 articles dedicated to distraction and 17 articles related to drowsiness. According to our analysis, we demonstrated that distraction and drowsiness increased the take-over request reaction time (TOR-RT), which could also lead to a reduction of the quality of take-overs. In addition, this longer reaction time was even more important in the case of handheld non-driving related tasks, which is important to consider as phone use is among the most frequent tasks done during automated driving. On a more methodological aspect, we also demonstrated that take-over time budget had a significant effect on TOR-RT. However, it is difficult to estimate to what extend distraction and drowsiness could impact the take-over quality, even if several elements supported safety issues. We underpinned several limits of the current methodologies applied in the study of distraction and drowsiness such as (i) the lack of additional measures related to the take-over quality (e.g., accelerations, collision rate), (ii) the many different methodologies applied to the determination of the TOR-RT (e.g., deactivation by the steering wheel, pedals, button), (iii) the high frequency of take-over requests which can lead to habituation effects, (iv) the lack of control conditions, (v) the fact that the level of drowsiness was relatively low in most studies. We thus highlighted recommendations for a better estimation of the effect of distraction and drowsiness on take-over performance. Further studies should adopt more standardized measures of TOR-RT and additional take-over quality measures, try minimizing the number of take-over requests, and carefully consider the time budget available for the use case since it influences the TOR-RT. Regarding distraction, researchers should consider the impact of tasks requiring handholding items. Concerning drowsiness, further protocols should consider the non-linearity of drowsiness and presence of micro sleeps and favor take-over requests based on drowsiness level protocols rather than on fixed duration protocols.

Young and older adult pedestrians' behavior when crossing a street in front of conventional and self-driving cars.

Self-driving vehicles are gradually becoming a reality. But the consequences of introducing such automated vehicles (AVs) into current road traffic cannot be clearly foreseen yet, especially for pedestrian safety. The present study used virtual reality to examine the pedestrians' crossing behavior in front of AVs as compared to conventional cars (CVs). Thirty young (ages 21-39) and 30 older (ages 68-81) adults participated in a simulated street-crossing experiment allowing for a real walk across an experimental two-way street. Participants had to cross (or not cross) in mixed traffic conditions where highly perceptible AVs always stopped to let them cross, while CVs did not brake to give them the right of way. Available time gap (from 1 to 5 s), approach speed (30 or 50 km/h), and the lane in which the cars were approaching (near and/or far lane of the two-way street) were varied. The results revealed a significantly higher propensity to cross the street, at shorter gaps, when AVs gave way to participants in the near lane while CVs were approaching in the far lane, leading to more collisions in this condition than in the others. These risky decisions were observed for both young and older participants, but much more so for the older ones. The results also indicated hesitation to cross in front of an AV in both lanes of the two-way street, with later initiations and longer crossing times, especially for the young participants and when the AVs were approaching at a short distance and braked suddenly. This study highlights the potential risks for pedestrians of introducing AVs into current road traffic, complicating the street-crossing task for young and older people alike. Future studies should look further into the role of repeated practice and trust in AVs. The design of these vehicles must also be addressed. Some practical recommendations are provided.

Introduction and validation of the Natural Disasters Picture System (NDPS).

Given the growing demand for studies dealing with natural disasters, the research fields of emotion and social cognition require validated picture stimuli of natural hazards. Such material is essential for studying perceptual processes and behaviors of exposed individuals, and it could find practical applications, such as the improvement of communication strategies during crises. We present the Natural Disasters Picture System (NDPS), a database of pictures of natural hazards, with an emphasis on volcanic threats, and their impact on the environment and humans. We first describe in detail the picture selection and database creation. We then report the validation procedure. One hundred twenty participants rated the pictures on the basis of four dimensions: valence, arousal, dominance and certainty. For each picture, we ultimately determined the best-fitting emotion on the basis of its dimensional pattern. The Hierarchical Ascendant Classification, which yielded 4 clusters subdivided into 9 classes, indicated a highly consistent and distinctive classification of the pictures. Overall, 90% of the pictures elicited negative emotions (fear or sadness), and the other 10% induced neutral to positive emotions (e.g., aesthetic emotions). The NDPS offers a new tool for studying natural events and disasters in the field of affective and cognitive sciences, which will benefit from scientific research and its practical applications. The NDPS is unrestrictedly accessible for researchers.

Influence of uncertainty on framed decision-making with moral dilemma.

In cases of impending natural disasters, most events are uncertain and emotionally relevant, both critical factors for decision-making. Moreover, for exposed individuals, the sensitivity to the framing of the consequences (gain or loss) and the moral judgments they have to perform (e.g., evacuate or help an injured person) constitute two central effects that have never been examined in the same context of decision-making. In a framed decision-making task with moral dilemma, we investigated whether uncertainty (i.e., unpredictably of events) and a threatening context would influence the framing effect (actions framed in loss are avoided in comparison to the ones framed in gain) and the personal intention effect (unintentional actions are more morally acceptable in comparison to intentional actions) on the perceived moral acceptability of taking action. Considering the impact of uncertainty and fear on the processes underlying these effects, we assumed that these emotions would lead to the negation of the two effects. Our results indicate that the exposure to uncertain events leads to the negation of the framing effect, but does not influence the moral acceptability and the effect of personal intention. We discuss our results in the light of dual-process models (i.e. systematic vs. heuristic), appraisal theories, and neurocognitive aspects. These elements highlight the importance of providing solutions to cope with uncertainty, both for scientists and local populations exposed to natural hazards.