Age-related declines in car following performance under simulated fog conditions

Driving Behaviour in Depression Based on Subjective Evaluation and Data from a Driving Simulator

Road traffic collisions are a major issue for public health. Depression is characterized by mental, emotional and executive dysfunction, which may have an impact on driving behaviour. Patients with depression (N = 39) and healthy controls (N = 30) were asked to complete questionnaires and to drive on a driving simulator in different scenarios. Driving simulator data included speed, safety distance from the preceding vehicle and lateral position. Demographic and medical information, insomnia (Athens Insomnia Scale, AIS), sleepiness (Epworth Sleepiness Scale, ESS), fatigue (Fatigue Severity Scale, FSS), symptoms of sleep apnoea (StopBang Questionnaire) and driving (Driver Stress Inventory, DSI and Driver Behaviour Questionnaire, DBQ) were assessed. Gender and age influenced almost all variables. The group of patients with depression did not differ from controls regarding driving behaviour as assessed through questionnaires; on the driving simulator, patients kept a longer safety distance. Subjective fatigue was positively associated with aggression, dislike of driving, hazard monitoring and violations as assessed by questionnaires. ESS and AIS scores were positively associated with keeping a longer safety distance and with Lateral Position Standard Deviation (LPSD), denoting lower ability to keep a stable position. It seems that, although certain symptoms of depression (insomnia, fatigue and somnolence) may affect driving performance, patients drive more carefully eliminating, thus, their impact.

The architecture of functional brain network modulated by driving during adverse weather conditions

Traffic accidents caused by adverse weather conditions have attracted the attention of many countries. Previous studies have focused on the driver's response in a particular situation under foggy conditions, but little is known about the functional brain network (FBN) topology that is modulated by driving in foggy weather, especially when the vehicle encounters cars in the opposite lane. An experiment consisting of two driving tasks is designed and conducted using sixteen participants. Functional connectivity between all pairs of channels for multiple frequency bands is assessed using the phase-locking value (PLV). Based on this, a PLV-weighted network is subsequently generated. The clustering coefficient (C) and the characteristic path length (L) are adopted as measures for the graph analysis. Statistical analyses are performed on graph-derived metrics. The major finding is that the PLV is significantly increased in the delta, theta and beta frequency bands while driving in foggy weather. Additionally, for the brain network topology metric, compared with driving in clear weather, significant increases are observed (driving in foggy weather) in the clustering coefficient for alpha and beta frequency bands and the characteristic path length for all frequency bands considered in this work. Driving in foggy weather would regulate FBN reorganization in different frequency bands. Our findings also suggest that the effects of adverse weather conditions on functional brain networks with a trend toward a more economic but less efficient architecture. Graph theory analysis may be a beneficial tool to further understand the neural mechanisms of driving in adverse weather conditions, which in turn may help to reduce the occurrence of road traffic accidents to some extent.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11571-022-09825-y.

Louis EK. Cognition and driving ability in isolated and symptomatic REM sleep behavior disorder

STUDY OBJECTIVES

To analyze cognitive deficits leading to unsafe driving in patients with REM Sleep Behavior Disorder (RBD), strongly associated with cognitive impairment and synucleinopathy-related neurodegeneration.

METHODS

Twenty isolated RBD (iRBD), 10 symptomatic RBD (sRBD), and 20 age- and education-matched controls participated in a prospective case-control driving simulation study. Group mean differences were compared with correlations between cognitive and driving safety measures.

RESULTS

iRBD and sRBD patients were more cognitively impaired than controls in global neurocognitive functioning, processing speeds, visuospatial attention, and distractibility (p < .05). sRBD patients drove slower with more collisions than iRBD patients and controls (p < .05), required more warnings, and had greater difficulty following and matching speed of a lead car during simulated car-following tasks (p < .05). Driving safety measures were similar between iRBD patients and controls. Slower psychomotor speed correlated with more off-road accidents (r = 0.65) while processing speed (-0.88), executive function (-0.90), and visuospatial impairment (0.74) correlated with safety warnings in sRBD patients. Slower stimulus recognition was associated with more signal-light (0.64) and stop-sign (0.56) infractions in iRBD patients.

CONCLUSIONS

iRBD and sRBD patients have greater selective cognitive impairments than controls, particularly visuospatial abilities and processing speed. sRBD patients exhibited unsafe driving behaviors, associated with processing speed, visuospatial awareness, and attentional impairments. Our results suggest that iRBD patients have similar driving-simulator performance as healthy controls but that driving capabilities regress as RBD progresses to symptomatic RBD with overt signs of cognitive, autonomic, and motor impairment. Longitudinal studies with serial driving simulator evaluations and objective on-road driving performance are needed.

The effects of age and physical exercise on multimodal signal responses: Implications for semi-autonomous vehicle takeover requests

The present study examined whether the non-chronological age factor, engagement in physical exercise, affected responses to multimodal (combinations of visual, auditory, and/or tactile) signals differently between younger and older adults in complex environments. Forty-eight younger and older adults were divided into exercise and non-exercise groups, and rode in a simulated Level 3 autonomous vehicle under four different task conditions (baseline, video watching, headway estimation, and video-headway combination), while being asked to respond to various multimodal warning signals. Overall, bi- and trimodal warnings had faster response times for both age groups across driving conditions, but was more pronounced for older adults. Engagement in physical exercise was associated with smaller maximum braking force for younger participants only, and also corresponded to longer average fixation durations, compared to the non-exercise group. Findings from this research can help to guide decisions about the design of warning and information systems for semi-autonomous vehicles.

Estimating time-to-contact when vision is impaired

Often, we have to rely on limited information when judging time-to-contact (TTC), as for example, when driving in foul weather, or in situations where we would need reading glasses but do not have them handy. However, most existing studies on the ability to judge TTC have worked with optimal visual stimuli. In a prediction motion task, we explored to what extent TTC estimation is affected by visual stimulus degradation. A simple computer-simulated object approached the observer at constant speed either with clear or impaired vision. It was occluded after 1 or 1.5 s. The observers extrapolated the object’s motion and pressed a button when they thought the object would have collided with them. We found that dioptric blur and simulated snowfall shortened TTC-estimates. Contrast reduction produced by a virtual semi-transparent mask lengthened TTC estimates, which could be the result of distance overestimation or speed underestimation induced by the lower contrast or the increased luminance of the mask. We additionally explored the potential influence of arousal and valence, although they played a minor role for basic TTC estimation. Our findings suggest that vision impairments have adverse effects on TTC estimation, depending on the specific type of degradation and the changes of the visual environmental cues which they cause.

Analyzing the effect of fog weather conditions on driver lane-keeping performance using the SHRP2 naturalistic driving study data

INTRODUCTION

Driving in foggy weather conditions has been recognized as a major safety concern for many years. Driver behavior and performance can be negatively affected by foggy weather conditions due to the low visibility in fog. A number of previous studies focused on driver performance and behavior in simulated environments. However, very few studies have examined the impact of foggy weather conditions on specific driver behavior in naturalistic settings.

METHOD

This study utilized the second Strategic Highway Research Program (SHRP2) Naturalistic Driving Study (NDS) dataset to evaluate driver lane-keeping behavior in clear and foggy weather conditions. Preliminary descriptive analysis was conducted and a lane-keeping model was developed using the ordered logistic regression approach to achieve the study goals.

RESULTS

This study found that individual variables such as visibility, traffic conditions, lane change, driver marital status, and geometric characteristics, as well as some interaction terms (i.e., weather and gender, surface condition and driving experience, speed limit and mileage last year) significantly affect lane-keeping ability. An important finding of this study illustrated that affected visibility caused by foggy weather conditions decreases lane-keeping ability significantly. More specifically, drivers in affected visibility conditions showed 1.37 times higher Standard Deviation of Lane Position (SDLP) in comparison with drivers who were driving in unaffected visibility conditions.

CONCLUSIONS

These results provide a better understanding of driver lane-keeping behavior and driver perception of foggy weather conditions. Moreover, the results might be used to improve Lane Departure Warning (LDW) systems algorithm by allowing them to account for the effects of fog on visibility. Practical Applications: These results provide a better understanding of driver lane-keeping behavior and driver perception of foggy weather conditions. Moreover, the results might be used to improve Lane Departure Warning (LDW) systems algorithm by allowing them to account for the effects of fog on visibility.

Traffic Simulation and Visual Verification in Smog

Smog causes low visibility on the road and it can impact the safety of traffic. Modeling traffic in smog will have a significant impact on realistic traffic simulations. Most existing traffic models assume that drivers have optimal vision in the simulations, making these simulations are not suitable for modeling smog weather conditions. In this article, we introduce the Smog Full Velocity Difference Model (SMOG-FVDM) for a realistic simulation of traffic in smog weather conditions. In this model, we present a stadia model for drivers in smog conditions. We introduce it into a car-following traffic model using both psychological force and body force concepts, and then we introduce the SMOG-FVDM. Considering that there are lots of parameters in the SMOG-FVDM, we design a visual verification system based on SMOG-FVDM to arrive at an adequate solution which can show visual simulation results under different road scenarios and different degrees of smog by reconciling the parameters. Experimental results show that our model can give a realistic and efficient traffic simulation of smog weather conditions.

Preliminary study on visual recognition under low visibility conditions caused by artificial dynamic smog

AIM

To quantitatively evaluate the effect of a simulated smog environment on human visual function by psychophysical methods.

METHODS

The smog environment was simulated in a 40×40×60 cm³ glass chamber filled with a PM2.5 aerosol, and 14 subjects with normal visual function were examined by psychophysical methods with the foggy smog box placed in front of their eyes. The transmission of light through the smog box, an indication of the percentage concentration of smog, was determined with a luminance meter. Visual function under different smog concentrations was evaluated by the E-visual acuity, crowded E-visual acuity and contrast sensitivity.

RESULTS

E-visual acuity, crowded E-visual acuity and contrast sensitivity were all impaired with a decrease in the transmission rate (TR) according to power functions, with invariable exponents of -1.41, -1.62 and -0.7, respectively, and R² values of 0.99 for E and crowded E-visual acuity, 0.96 for contrast sensitivity. Crowded E-visual acuity decreased faster than E-visual acuity. There was a good correlation between the TR, extinction coefficient and visibility under heavy-smog conditions.

CONCLUSION

Increases in smog concentration have a strong effect on visual function.

Visual Acuity does not Moderate Effect Sizes of Higher-Level Cognitive Tasks

BACKGROUND/STUDY CONTEXT

Declining visual capacities in older adults have been posited as a driving force behind adult age differences in higher-order cognitive functions (e.g., the "common cause" hypothesis of Lindenberger & Baltes, 1994, Psychology and Aging, 9, 339-355). McGowan, Patterson, and Jordan (2013, Experimental Aging Research, 39, 70-79) also found that a surprisingly large number of published cognitive aging studies failed to include adequate measures of visual acuity. However, a recent meta-analysis of three studies (La Fleur and Salthouse, 2014, Psychonomic Bulletin & Review, 21, 1202-1208) failed to find evidence that visual acuity moderated or mediated age differences in higher-level cognitive processes. In order to provide a more extensive test of whether visual acuity moderates age differences in higher-level cognitive processes, we conducted a more extensive meta-analysis of topic.

METHODS

Using results from 456 studies, we calculated effect sizes for the main effect of age across four cognitive domains (attention, executive function, memory, and perception/language) separately for five levels of visual acuity criteria (no criteria, undisclosed criteria, self-reported acuity, 20/80-20/31, and 20/30 or better).

RESULTS

As expected, age had a significant effect on each cognitive domain. However, these age effects did not further differ as a function of visual acuity criteria.

CONCLUSION

The current meta-analytic, cross-sectional results suggest that visual acuity is not significantly related to age group differences in higher-level cognitive performance-thereby replicating La Fleur and Salthouse (2014). Further efforts are needed to determine whether other measures of visual functioning (e.g., contrast sensitivity, luminance) affect age differences in cognitive functioning.

Driving performance comparing older versus younger drivers

OBJECTIVES

A cross-sectional study was conducted at the Touro University California campus to compare differences in reaction times and driving performance of younger adult drivers (18-40 years) and older adult drivers (60 years and older). Each test group consisted of 38 participants.

METHODS

A Simple Visual Reaction Test (SVRT) tool was used to measure reaction times. The STISIM Drive M100 driving simulator was used to assess driving parameters. Driving performance parameters included mean lane position, standard deviation of mean lane position measured, mean speed, standard deviation of mean speed, car-following delay, car-following modulus, car-following coherence, off-road accidents, collisions, pedestrians hit, and traffic light tickets.

RESULTS

Compared to younger participants, older drivers experienced significantly slower reaction times (510.0 ± 208.8 vs. 372.4 ± 96.1 ms, P =.0004), had more collisions (0.18 ± 0.39 vs. none, P =.0044), drove slower (44.6 ± 6.6 vs. 54.9 ± 11.7 mph, P <.0001), deviated less in speed (12.6 ± 4.3 vs. 16.8 ± 6.3, P =.0011), and were less able to maintain a constant distance behind a pace car (0.42 ± 0.23 vs. 0.59 ± 0.24; P =.0025).

CONCLUSIONS

Differences exist in driving patterns of older and younger drivers as measured by reaction times and driving simulator outcomes. These results are the first to compare these 2 specific adult age groups' driving performance as measured by a standardized driving simulator scenario. Identifying these differences is essential in addressing them and preventing future traffic injuries.

Glaucoma and Driving Risk under Simulated Fog Conditions

Purpose

We evaluate driving risk under simulated fog conditions in glaucoma and healthy subjects.

Methods

This cross-sectional study included 41 glaucoma patients and 25 age-matched healthy subjects who underwent driving simulation. Tests consisted of curve negotiation without and with fog preview at 30 m of distance and two controlled speeds (slow and fast). Inverse time-to-line crossing (invTLC) was used as metric to quantify risk; higher invTLC values indicating higher risk, as less time is available to avoid drifting out of the road. Piecewise regression models were used to investigate the relationship between differences in invTLC in fog and nonfog conditions and visual field loss.

Results

Glaucoma patients had greater increase in driving risk under fog compared to controls, as indicated by invTLC differences (0.490 ± 0.578 s⁻¹ and 0.208 ± 0.106 s⁻¹, respectively; P = 0.002). Mean deviation (MD) of the better eye was significantly associated with driving risk under fog, with a breakpoint of −9 dB identified by piecewise regression. For values below the breakpoint, each 1 dB lower MD of better eye was associated with 0.117 s⁻¹ higher invTLC under fast speed (adjusted R² = 57.9%; P < 0.001).

Conclusions

Glaucoma patients have a steeper increase in driving risk under fog conditions when compared to healthy subjects, especially when the severity of visual field damage falls below −9 dB of MD in the better eye.

Translational Relevance

By investigating the relationship between driving risk and disease severity breakpoint, this study may provide guidance to clinicians in recognizing glaucoma patients who may be unfit to drive in complex situations such as fog.

Changes in Drivers' Visual Performance during the Collision Avoidance Process as a Function of Different Field of Views at Intersections

The intersection field of view (IFOV) indicates an extent that the visual information can be observed by drivers. It has been found that further enhancing IFOV can significantly improve emergent collision avoidance performance at intersections, such as faster brake reaction time, smaller deceleration rate, and lower traffic crash involvement risk. However, it is not known how IFOV affects drivers’ eye movements, visual attention and the relationship between visual searching and traffic safety. In this study, a driving simulation experiment was conducted to uncover the changes in drivers’ visual performance during the collision avoidance process as a function of different field of views at an intersection by using an eye tracking system. The experimental results showed that drivers’ ability in identifying the potential hazard in terms of visual searching was significantly affected by different IFOV conditions. As the IFOVs increased, drivers had longer gaze duration (GD) and more number of gazes (NG) in the intersection surrounding areas and paid more visual attention to capture critical visual information on the emerging conflict vehicle, thus leading to a better collision avoidance performance and a lower crash risk. It was also found that female drivers had a better visual performance and a lower crash rate than male drivers. From the perspective of drivers’ visual performance, the results strengthened the evidence that further increasing intersection sight distance standards should be encouraged for enhancing traffic safety.

Screening and assessment tools for determining fitness to drive: a review of the literature for the pathways project

With a brief introduction, 10 tables summarize the findings from the literature describing screening and assessment tools used with older adults to identify risk or determine fitness to drive. With a focus on occupational therapy's duty to address driving as a valued activity, this paper offers information about tools used by occupational therapy practitioners across practice settings and specialists in driver rehabilitation. The tables are organized into groups of key research studies of assessment tools, screening batteries, tools used in combination (i.e., as a battery), driving simulation as an assessment tool, and screening/assessment for individuals with stroke, vision impairment, Parkinson's disease, dementia, and aging. Each table has a summary of important concepts to consider as occupational therapists choose the methods and tools to evaluate fitness to drive.

Measuring listening effort: driving simulator versus simple dual-task paradigm

OBJECTIVES

The dual-task paradigm has been widely used to measure listening effort. The primary objectives of the study were to (1) investigate the effect of hearing aid amplification and a hearing aid directional technology on listening effort measured by a complicated, more real world dual-task paradigm and (2) compare the results obtained with this paradigm to a simpler laboratory-style dual-task paradigm.

DESIGN

The listening effort of adults with hearing impairment was measured using two dual-task paradigms, wherein participants performed a speech recognition task simultaneously with either a driving task in a simulator or a visual reaction-time task in a sound-treated booth. The speech materials and road noises for the speech recognition task were recorded in a van traveling on the highway in three hearing aid conditions: unaided, aided with omnidirectional processing (OMNI), and aided with directional processing (DIR). The change in the driving task or the visual reaction-time task performance across the conditions quantified the change in listening effort.

RESULTS

Compared to the driving-only condition, driving performance declined significantly with the addition of the speech recognition task. Although the speech recognition score was higher in the OMNI and DIR conditions than in the unaided condition, driving performance was similar across these three conditions, suggesting that listening effort was not affected by amplification and directional processing. Results from the simple dual-task paradigm showed a similar trend: hearing aid technologies improved speech recognition performance, but did not affect performance in the visual reaction-time task (i.e., reduce listening effort). The correlation between listening effort measured using the driving paradigm and the visual reaction-time task paradigm was significant. The finding showing that our older (56 to 85 years old) participants' better speech recognition performance did not result in reduced listening effort was not consistent with literature that evaluated younger (approximately 20 years old), normal hearing adults. Because of this, a follow-up study was conducted. In the follow-up study, the visual reaction-time dual-task experiment using the same speech materials and road noises was repeated on younger adults with normal hearing. Contrary to findings with older participants, the results indicated that the directional technology significantly improved performance in both speech recognition and visual reaction-time tasks.

CONCLUSIONS

Adding a speech listening task to driving undermined driving performance. Hearing aid technologies significantly improved speech recognition while driving, but did not significantly reduce listening effort. Listening effort measured by dual-task experiments using a simulated real-world driving task and a conventional laboratory-style task was generally consistent. For a given listening environment, the benefit of hearing aid technologies on listening effort measured from younger adults with normal hearing may not be fully translated to older listeners with hearing impairment.

Effects of fog, driver experience and gender on driving behavior on S-curved road segments

Driving on curved roads has been recognized as a significant safety issue for many years. However, driver behavior and the interactions among variables that affect driver performance on curves is complicated and not well understood. Previous studies have investigated various factors that influence driver performance on right- or left-turn curves, but have paid little attention to the effects of foggy weather, driver experience and gender on driver performance on complex curves. A driving simulator experiment was conducted in this study to evaluate the relationships between driving behavior on a continuous S-curve and foggy weather, driver experience and gender. The process of negotiating a curve was divided into three stages consisting of a straight segment, the transition from the straight segment to the S-curve and the S-curve. The experimental results indicated that drivers tended to drive more cautiously in heavy fog, but the driving risk was still increased, especially in the transition stage from the straight segment to the S-curve. The non-professional (NP) drivers were less sensitive to the impending change in the road geometry, and less skilled in both longitudinal and lateral vehicle control than the professional drivers. The NP female drivers in particular were found to be the most vulnerable group in S-curve driving.

Driving simulators for occupational therapy screening, assessment, and intervention

Simulation technology provides safe, objective, and repeatable performance measures pertaining to operational (e.g., avoiding a collision) or tactical (e.g., lane maintenance) driver behaviors. Many occupational therapy researchers and others are using driving simulators to test a variety of applications across diverse populations. A growing body of literature provides support for associations between simulated driving and actual on-road driving. One limitation of simulator technology is the occurrence of simulator sickness, but management strategies exist to curtail or mitigate its onset. Based on the literature review and a consensus process, five consensus statements are presented to support the use of driving simulation technology among occupational therapy practitioners. The evidence suggests that by using driving simulators occupational therapy practitioners may detect underlying impairments in driving performance, identify driving errors in at-risk drivers; differentiate between driving performance of impaired and healthy controls groups; show driving errors with absolute and relative validity compared to on-road studies; and mitigate the onset of simulator sickness. Much progress has been made among occupational therapy researchers and practitioners in the use of driving simulation technology; however, empirical support is needed to further justify the use of driving simulators in clinical practice settings as a valid, reliable, clinical useful, and cost effective tool for driving assessment and intervention.

Aging and the detection of imminent collisions under simulated fog conditions

The present study examined age-related differences in collision detection performance when contrast of the driving scene was reduced by simulated fog. Older and younger drivers were presented with a collision detection scenario in a simulator in which an object moved at a constant speed on a linear trajectory towards the driver. Drivers were shown part of the motion path of an approaching object that would eventually either collide with or pass by the driver and were required to determine whether or not the object would collide with the driver. Driver motion was either stationary or moving along a linear path down the roadway. A no fog condition and three different levels of fog were examined. Detection performance decreased when dense fog was simulated for older but not for younger observers. An age-related decrement was also found with shorter display durations (longer time to contact). When the vehicle was moving decrements in performance were observed for both younger and older drivers. These results suggest that under inclement weather conditions with reduced visibility, such as fog, older drivers may have an increased crash risk due to a decreased ability to detect impending collision events.

Why do drivers maintain short headways in fog? A driving-simulator study evaluating feeling of risk and lateral control during automated and manual car following

Drivers in fog tend to maintain short headways, but the reasons behind this phenomenon are not well understood. This study evaluated the effect of headway on lateral control and feeling of risk in both foggy and clear conditions. Twenty-seven participants completed four sessions in a driving simulator: clear automated (CA), clear manual (CM), fog automated (FA) and fog manual (FM). In CM and FM, the drivers used the steering wheel, throttle and brake pedals. In CA and FA, a controller regulated the distance to the lead car, and the driver only had to steer. Drivers indicated how much risk they felt on a touchscreen. Consistent with our hypothesis, feeling of risk and steering activity were elevated when the lead car was not visible. These results might explain why drivers adopt short headways in fog. Practitioner Summary: Fog poses a serious road safety hazard. Our driving-simulator study provides the first experimental evidence to explain the role of risk-feeling and lateral control in headway reduction. These results are valuable for devising effective driver assistance and support systems.