The ability to measure drivers’ physiological responses is important for understanding their state and behaviour under different driving conditions. Driver’s physiological responses can be used in the development and evaluation of novel user interfaces, driver profiling or advanced driver assistance systems. This paper presents a research study exploring the use of wearable devices for assessment of different cardiovascular and electrodermal activity in the driving environment. Driver’s heart rate, heart-rate variability, galvanic skin response, skin temperature and ECG signals were observed in different levels of driving demand. The results showed that most of the collected signals are motion sensitive, revealing the need to take into consideration the motion artifact when analyzing the data. With the raw signals, it is possible to differentiate between no-driving and driving with all of the observed signals, whereas with the ECG signals also different levels of demand could be detected.
COBISS.SI-ID: 12780884
The aim of the present study was to investigate the role of driving demands, neuroticism, and their interaction when predicting driving behaviour. More precisely, we strived to examine how driving behaviour (i.e., speeding, winding, tailgating and jerky driving) unfold across low and high driving demands and whether they are contingent on a personality factor that has previously been linked to stress reactivity. We found that driving behaviour became safer in scenarios that were highly demanding in terms of information processing, while this pattern did not emerge with vehicle handling demands. Moreover, tentative support was found for the notion that individuals high in neuroticism are less able to adapt their behaviour to higher information processing demands.
COBISS.SI-ID: 25088008
Driving characteristics of neurological patients recognized as fit-, unfit- and conditionally-fit-to-drive based on a standard multidisciplinary assessment were compared in three simulated driving environments (rural, highway, and urban). The analysis revealed that compared to the fit group, the unfit group had longer reaction times, more difficulties with lateral control, exceeded the speed limit more, made more signalling errors, and had more collisions. Results show that simulated driving reflects the differences between fit and unfit drivers, but not the conditional ones, who require a more personalized approach.
COBISS.SI-ID: 15945987
Autonomous vehicles are expected to take complete control of the driving process, enabling the former drivers to act as passengers only. This could lead to increased sickness as they can be engaged in tasks other than driving. Adopting different sickness mitigation techniques gives us unique types of motion sickness in autonomous vehicles to be studied. In this paper, we report on a study where we explored the possibilities of assessing motion sickness with electrogastrography (EGG), a non-invasive method used to measure the myoelectric activity of the stomach, and its potential usage in autonomous vehicles (AVs). The EGG results showed a significant increase of the dominant frequency (DF) and the percentage of the high power spectrum density (FSD) as well as a significant decrease of the power spectrum density Crest factor (CF) during the AV simulation. Based on the results, we conclude that EGG could be used for assessment of motion sickness in autonomous vehicles. DF, CF and FSD can be used as overall sickness indicators, while the relative increase in amplitude of EGG signal and duration of that increase can be used as short-term sickness indicators where the driving environment may affect the driver.
COBISS.SI-ID: 47242243
This paper presents an evaluation of the low-cost Eye Tribe eye tracker for assessment of changes in pupil size as a measure for cognitive load of drivers. It further explores blink rates and fixation times as potential assessment metrics for cognitive and attention load parameters. The Detection Response Task (DRT) was used a reference method to validate the results. The results showed that the eye tracker precisely recognizes an increasing pupil diameter with increasing secondary task difficulty. Increase in blink rates, decreasing fixation time and narrowing of the attention field was also detected in trials with increased cognitive load, indicating these pupil factors could be used as an alternative method for assessment of driver’s cognitive load.
COBISS.SI-ID: 11875668