Insights into the psychophysiological state of car drivers

Driving a vehicle is a complex and dynamic activity performed daily by millions of individuals, requiring an optimal psychophysiological state to ensure safe operation. Due to the high number of traffic accidents, road safety has become an international concern and an investigation into the factors that influence driving behaviour may facilitate the development of technologies designed to monitor drivers and enhance human well-being. Peripheral and non-invasive physiological measures can reveal affective and cognitive states and could provide insights into a driver’s mental state and workload while driving. The main goal of this thesis was to explore and monitor the driver’s physiological state in both real and simulated driving contexts and to examine the effects of various factors, both environmental and human, that can potentially cause changes in driving behaviour and alter the driver’s psychophysiological state. This work includes three studies, each of which sought to contribute to the existing body of knowledge on the extent to which and the manner in which these factors can influence the driver’s psycho-physiological state. In the first study, we aimed to monitor the driver’s cardiac autonomic activity during real road driving, assuming psychophysiological variations based on driving context and psychosocial stress induced in urban environments. We considered psychological factors, sex and driving experience as potential modulatory components for cardiac autonomic responses during driving. Heart rate (HR) and heart rate variability (HRV) were measured during actual driving tasks in a sample of male and female drivers, with psychometric characteristics collected using questionnaires. HRV analysis revealed a significant overall autonomic activation while driving, independent from the exposure to external stressors. Neither sex nor driving experience seemed to affect cardiac autonomic response to driving. A significant positive correlation emerged between anxiety/stress symptoms and aberrant driving behaviour. The second study explored the effects of mental workload due to distracted driving on the driver’s physiological state. The goal was pursued by monitoring cardiac autonomic activity during a simulated low-traffic highway scenario, in which the participant was subjected to various distraction tasks. We expected variations according to the amount of mental workload derived from distractive stimuli during the primary driving task and we considered sex as potential explanatory factor for psychophysiological modulation during driving. HRV analysis revealed significant overall autonomic activation during driving, independent of exposure to additional secondary distractive tasks and sex. In summary, the results of both studies suggest that driving has a significant impact on cardiac autonomic neural modulation, also demonstrating that peripheral biomarkers such as HRV are useful for providing information on ecological and everyday situations such as driving activity. The third and final study in this thesis investigated a mental and physical risk condition during driving, typically characterised by low physiological activation: fatigue. We sought to assess validity of physiological indices, such as nasal skin temperature and heart rate, in detecting changes in arousal levels during 3-h monotonous driving, a common scenario for inducing fatigue while driving. Driving mode conditions (autonomous and manual driving) were included in the experimental protocol as a possible modulation factor of the driver’s physiological response to fatigue due to prolonged driving. Our results showed no evidence of physiological deactivation due to fatigue from driving time. The use of autonomous driving or changing driving mode mid-activity may have contributed to mitigating the effects of fatigue on physiological parameters classically observed in paradigms with prolonged monotonous driving. In conclusion, this thesis adds to the current literature by examining psychophysiological activity while driving in both real and simulated driving environments. It emphasises the importance of considering the psychophysiological approach as a valid method in the field of driving safety, with the potential to add useful knowledge for the development of biometric sensors that can be applied to monitor the driver’s state and, through artificial intelligence, manage risk situations related to distraction, fatigue or emotional states while driving.