The driver state monitoring in semi-automated vehicles- the influence of the circadian phase

Abstract

Background: automation offers the potential to mitigate or reduce the risks related to driving. However, there are also some new challenges for drivers related to semi‐automated driving. Two phases of semi-automated driving that raised concerns of the researchers were a period of automation that requires a monitoring activity from the driver and the take-over of manual control following the automated mode. Topic: the aim of this doctoral thesis was to propose models of the driver state monitoring in semi-automated vehicles and present data on the psychophysiological changes occurring during semi-automated driving, as well as the circadian effect on semi-automated driving and driver state monitoring. Methods: fifty-two participants were recruited to the experiment on semi-automated driving. They participated in two experimental sessions day-time session (9 a.m.- 1 p.m.) and a night-time session (10 p.m.- 2 a.m.). They went through theexperimental scenario simulating semi-automated driving with phases of manual driving, automated phase, take-over and manual driving. During the experiment their psychophysiological functions were recorded with the following measures: electrooculography, electromyography, electrocardiography, respiration belt, electrodermal activity device, oximetry for the pulse and blood oxygenation, their voice was recorded for the acoustic voice analysis, saliva was collected for the hormonal analysis, and four questionnaires were collected at different stages of the experiment. Additionally, electroencephalography was recorded; however, its analysis was not included in this thesis. Results: two predictive models were proposed to predict performance after take-over and attention during automation. Analysis of the time-course of the semi-automated driving
suggested a decrease of the driving performance after automation associated with increased sleepiness, increased fatigue, decreased readiness to take-over and decreased mental workload. Some physiological changes suggested mental underload. Comparison of the circadian phases resulted in multiple physiological, behavioural and cognitive changes. Conclusions: physiology can be used to predict the driver’s performance in semi-automated vehicles; however, the proposed models are not ready to be implemented in the cars. Automation creates a risk for driving safety due to mental underload. Sleepiness and fatigue present the largest risk for automation monitoring, while suboptimal mental workload and arousal for the safety of the take-over. The circadian phase affects the psychophysiology and performance of the driver; however, the direction of the effects requires further investigation.

More information

Identifiers

ORCID for Jonathan Preston: orcid.org/0000-0002-6866-049X

Catalogue record

Export record