A Novel EEG-Based Assessment of Distraction in Simulated Driving under Different Road and Traffic Conditions.

The drivers' distraction plays a crucial role in road safety as it is one of the main impacting causes of road accidents. The phenomenon of distraction encompasses both psychological and environmental factors and, therefore, addressing the complex interplay contributing to human distraction in automotive is crucial for developing technologies and interventions for improving road safety. In scientific literature, different works were proposed for the distraction characterization in automotive, but there is still the lack of a univocal measure to assess the degree of distraction, nor a gold-standard tool that allows to "detect" eventual events, road traffic, and additional driving tasks that might contribute to the drivers' distraction. Therefore, the present study aimed at developing an EEG-based "Distraction index" obtained by the combination of the driver's mental workload and attention neurometrics and investigating and validating its reliability by analyzing together subjective and behavioral measures. A total of 25 licensed drivers were involved in this study, where they had to drive in two different scenarios, i.e., City and Highway, while different secondary tasks were alternatively proposed in addition to the main one to modulate the driver's attentional demand. The statistical analysis demonstrated the reliability of the proposed EEG-based distraction index in identifying the drivers' distraction when driving along different roads and traffic conditions (all p < 0.001). More importantly, the proposed index was demonstrated to be reliable in identifying which are the most impacting additional driving tasks on the drivers' distraction (all p < 0.01).

Gender disparities in observed motorcycle helmet use in Madagascar: female motorcyclists behave safer but have lower overall protection.

BACKGROUND: Although motorcycle helmets can save lives in case of a crash, no helmet use data are available for many countries. When data is available, it is often only analysed as a global average, preventing targeted road safety education and legislative action. In this study, we conducted a detailed analysis of motorcycle helmet use in the capital of Madagascar. METHODS: Using a cross-sectional observational field survey framework, we observed 17 230 individual motorcycles. We systematically recorded motorcycle riders' helmet use, position on the motorcycle, rider numbers and gender. RESULTS: We found a general helmet use of 76.1%. Observed drivers had a significantly higher helmet use (84.6%) than passengers (47.7%), and subsequently helmet use per motorcycle decreased significantly when the number of riders per motorcycle increased. Female drivers had significantly higher helmet use than male drivers, and female passengers had significantly higher helmet use than male passengers. That is, on the same position of the motorcycle, female riders behaved safer than male riders. However, since female riders were more often passengers than drivers, their average helmet use was lower than that of male riders overall. Contrary to findings from other countries, motorcycle helmet use did not differ significantly throughout the day but was relatively constant. CONCLUSION: Our results show the potential for injury and fatality prevention in Madagascar through increased passenger helmet use. This increase would also proportionally benefit female riders more than male riders. Findings regarding road safety legislation's applied impact, education, enforcement and future research needs are discussed.

Predicting acceptance and adoption of renewable energy community solutions: the prosumer psychology.

Background: This paper, in the frame of social acceptance of renewable energies and innovative community-based production and consumption models, aims at supporting a data-driven approach able to deal with climate change and identify and quantify the psycho-sociological dimensions and factors that could support the transition from a technology-driven approach to a consumer-driven approach throughout the emerging " prosumer business models". In addition to the already existing Social Acceptance dimensions, this paper tries to identify a purely individual psychological fourth dimension to understand the processes and factors that underlie individual acceptance and adoption of new renewable energy business models, with the realization of a Prosumer Acceptance Index. Methods: Questionnaire data collection has been performed throughout an online survey platform, combining standardized and ad-hoc questions adapted for the research purposes, based on the developed theoretical model. To identify the main factors (individual/social) influencing the relation with renewable energy technology adoption, a Factorial Analysis has been conducted to identify the latent variables that are related to each other. Linear regression has been conducted to identify and quantify the factors that could better predict behavioural intention to become a prosumer. Results: Five latent psychological factors were revealed: concern about environmental issues, interest in energy sharing, concern on climate change, social influence and impact on bill cost. Three variables were found to significantly measure and predict the scores of the "Acceptance in becoming a prosumer" ad hoc scale: attitude, economic incentive and age. Conclusions: This research can facilitate policymakers and stakeholders to better understand which relevant psycho-sociological factors are intervening in the renewable energy technology acceptance processes and what and how specifically target when proposing change towards sustainable energy production and consumption.