Car drivers coping with hazardous events in real versus simulated situations: Declarative, behavioral and physiological data used to assess drivers' feeling of presence

A simulator study assessing the effectiveness of training and warning systems on drivers' response performance to vehicle cyberattacks

Modern vehicles are vulnerable to cyberattacks and the consequences can be severe. While technological efforts have attempted to address the problem, the role of human drivers is understudied. This study aims to assess the effectiveness of training and warning systems on drivers' response behavior to vehicle cyberattacks. Thirty-two participants completed a driving simulator study to assess the effectiveness of training and warning system according to their velocity, deceleration events, and count of cautionary behaviors. Participants, who held a valid United States driving license and had a mean age of 20.4 years old, were equally assigned to one of four groups: control (n = 8), training-only (n = 8), warning-only (n = 8), training and warning groups (n = 8). For each drive, mixed ANOVAs were implemented on the velocity variables and Poisson regression was conducted on the normalized time with large deceleration events and cautionary behavior variables. Overall, the results suggest that drivers' response behaviors were moderately affected by the training programs and the warning messages. Most drivers who received training or warning messages responded safely and appropriately to cyberattacks, e.g., by slowing down, pulling over, or performing cautionary behaviors, but only in specific cyberattack events. Training programs show promise in improving drivers' responses toward vehicle cyberattacks, and warning messages show rather moderate improvement but can be further refined to yield consistent behavior.

Effects of simulated presence therapy on agitated behavior, cognition, and use of protective constraint among patients with senile dementia

The research was conducted to investigate the improvement of agitated behaviors, cognitive functions, and negative emotions among patients with senile dementia and the burden of caregivers after simulated presence therapy (SPT) intervention. 85 Patients with senile dementia were included as the research subjects and divided into control group (40 cases performed with routine nursing) and observation group (45 cases undergoing routine nursing combined with SPT) via a random number table method. Cohen-Mansfield agitation inventory (CAMI) and protective constraint were used to assess the improvement of agitated behaviors among patients. Besides, apathy evaluation scale-informant (AES-I), functional independence measure (FIM), self-rating depression scale (SDS), self-rating anxiety scale (SAS), clock drawing test, and caregiver burden inventory (CBI) were adopted to evaluate the differences in apathy, daily living and sociability, depression, anxiety, cognitive functions, and caregiver burden between the two groups. It was demonstrated that CAMI score, the duration of protective constraint use, AES-I score, SDS score, SAS score, and CBI score among patients in observation group all apparently decreased compared with those in control group after the intervention. In contrast, FIM and clock drawing test scores both notably increased (p < 0.05). The above findings suggested that SPT could obviously reduce the incidence of agitated behaviors, improve the level of apathy, daily living and sociability, depression, anxiety, and cognitive functions, and relieve caregiver burden among patients with senile dementia during SPT intervention for patients with senile dementia.

Stress influence on real-world driving identified by monitoring heart rate variability and morphologic variability of electrocardiogram signals: the case of intercity roads

Objectives. This study examines which of the heart rate variability (HRV) and morphologic variability (MV) metrics may have the highest accuracy in different stress detection during real-world driving. Methods. The cross-sectional study was carried out among 93 intercity mini-bus male drivers aged 22-67 years. The Trillium 5000 Holter Recorder and GARMIN Virb Elite camera were used to determine heart rate and vehicle speed measurements along the path, respectively. We considered the HRV and MV metrics of electrocardiogram (ECG) signals including the mean RR interval (mRR), mean heart rate (mHR), normalized low-frequency spectrum (nLF), normalized high-frequency spectrum (nHF), normalized very low-frequency spectrum (nVLF), difference of normalized low-frequency spectrum and normalized high-frequency spectrum (dLFHF), and sympathovagal balance index (SVI). Results. The analysis showed that the HRV metrics mHR, mRR, nVLF, nLF, nHF, dLFHF and SVI are effective in mental stress detection while driving as compared to rest time. We obtained a high accuracy of stress detection for MV metrics as compared to the traditional HRV analysis, of approximately 92%. Conclusions. Our findings indicate that driver stress could be detected with an accuracy of 92% using MV metrics as an accurate physiological index of the driver's state.

Back on the Road: Comparing Cognitive Assessments to Driving Simulators in Moderate to Severe Traumatic Brain Injuries

Objective: To compare established clinical outcome assessments for predicting behind the wheel driving readiness and driving simulator results across age groups and in traumatic brain injury. Methods: Participants included adults who had a traumatic brain injury ranging in age from 31 to 57 years and a non-impaired adult population ranging in age from 18 to 80 years. Physical and cognitive outcomes measures were collected included range of motion and coordination, a “Rules of the Road Test” a “Sign Identification Test,” Trails A and B, and the clock drawing test. Visual measures included the Dynavision D2 system and motor-free visual perceptual test-3 (MVPT-3). Finally, the driving simulators (STIÒ version M300) metro drive assessment was used, which consisted of negotiating several obstacles in a metropolitan area including vehicles abruptly changing lanes, pedestrians crossing streets, and negotiating construction zones. Results: Our findings suggest that the standard paper-pencil cognitive assessments and sign identification test significantly differentiate TBI from a non-impaired population (Trails A, B and Clock drawing test p < 0.001). While the driving simulator did not show as many robust differences with age, the TBI population did have a significantly greater number of road collisions (F3, 78 = 3.5, p = 0.02). We also observed a significant correlation between the cognitive assessments and the simulator variables. Conclusions: Paper-pencil cognitive assessments and the sign identification test highlight greater differences than the STI Driving Simulator between non-impaired and TBI populations. However, the driving simulator may be useful in assessing cognitive ability and training for on the road driving.

Detecting driver stress and hazard anticipation using real-time cardiac measurement: A simulator study

OBJECTIVES

In the context of growing interest in real-time driver stress detection systems, we question the value of using heart rate change over short time periods to detect driver stress and hazard anticipation.

METHODS

To this end, we explored changes in heart rate and speed as well as perceived stress in 27 drivers in a driving simulator. Driver stress was triggered by using hazardous road events, while hazard anticipation was manipulated using three levels of hazard predictability: unpredictable (U), predictable (P), and predictable and familiar (PF).

RESULTS

The main results indicate that using heart rate change (1) is a good indicator for detecting driver stress in real time, (2) provides a cardiac signature of hazard anticipation, and (3) was affected by perceived stress groups. Further investigation is needed to validate the lack of relationship between increased anticipation/predictability and strengthened cardiac signature.

CONCLUSIONS

These results support the use of heart rate change as an indicator of real-time driver stress and hazard anticipation.

Sensitivity of Physiological Measures of Acute Driver Stress: A Meta-Analytic Review

Background: The link between driving performance impairment and driver stress is well-established. Identifying and understanding driver stress is therefore of major interest in terms of safety. Although many studies have examined various physiological measures to identify driver stress, none of these has as yet been definitively confirmed as offering definitive all-round validity in practice. Aims: Based on the data available in the literature, our main goal was to provide a quantitative assessment of the sensitivity of the physiological measures used to identify driver stress. The secondary goal was to assess the influence of individual factors (i.e., characteristics of the driver) and ambient factors (i.e., characteristics of the context) on driver stress. Age and gender were investigated as individual factors. Ambient factors were considered through the experimental apparatus (real-road vs. driving simulator), automation driving (manual driving vs. fully autonomous driving) and stressor exposure duration (short vs. long-term). Method: Nine meta-analyses were conducted to quantify the changes in each physiological measure during high-stress vs. low-stress driving. Meta-regressions and subgroup analyses were performed to assess the moderating effect of individual and ambient factors on driver stress. Results: Changes in stress responses suggest that several measures are sensitive to levels of driver stress, including heart rate, R-R intervals (RRI) and pupil diameter. No influence of individual and ambient factors was observed for heart rate. Applications and Perspective: These results provide an initial guide to researchers and practitioners when selecting physiological measures for quantifying driver stress. Based on the results, it is recommended that future research and practice use (i) multiple physiological measures, (ii) a triangulation-based methodology (combination of measurement modalities), and (iii) a multifactorial approach (analysis of the interaction of stressors and moderators).