The effects of visibility conditions, traffic density, and navigational challenge on speed compensation and driving performance in older adults

Quantification of safety improvements and human-machine tradeoffs in the transition to automated driving

The assumption of reduced human error-related crashes with increasing levels of automation in pursuing Level 5 automation lacks empirical evidence. As automation levels rise, human error-induced safety hazards are anticipated to decrease, while machine error-induced hazards will increase. However, a quantitative index capturing this tradeoff is absent. Additionally, theoretical modeling of safety improvements during the transition to automated driving remains unexplored, particularly concerning reducing human error-related hazards. These limitations impede the understanding of safety from human and machine perspectives for Automated Vehicle (AV) specialists and manufacturers. This research addresses these gaps by investigating safety performance associations between human and machine factors using the "Human-Machine conflict reduction ratio" (H/M ratio), a novel metric. The study aims to establish safety improvements related to human errors under various automation levels. Sixty participants completed driving tasks on a driving simulator at Levels 0, 4, 3, and 2. Safety performance measures, including conflict frequency and severity, were computed. As a result, Level 4 exhibits the largest decrease (93.3%) compared to manual driving, followed by Level 2 (70.7%) and Level 3 (40.5%). The H/M ratio measures the tradeoff between reducing human and machine error-induced hazards, with Level 2 demonstrating the highest ratio, followed by Levels 4 and 3. Safety performance is evaluated by considering all possible types of human errors at each automation level. Theoretical models from a human factor's perspective are employed to estimate safety improvements at each level. This research contributes to a comprehensive understanding of safety in the "human-machine cooperative driving" phase, offering insights to AV industry practitioners and stakeholders.

Individual differences, ADHD diagnosis, and driving performance: effects of traffic density and distraction type

The present study examined the impact of individual differences, attention, and memory deficits on distracted driving. Drivers with ADHD are more susceptible to distraction which results in more frequent collisions, violations, and licence suspensions. Consequently, the present investigation had 36 participants complete preliminary questionnaires, memory tasks, workload indices, and four, 4-min simulated driving scenarios to evaluate such impact. It was hypothesised ADHD diagnosis, type of cellular distraction, and traffic density would each differentially and substantively impact driving performance. Results indicated traffic density and distraction type significantly affected the objective driving facets measured, as well as subjective and secondary task performance. ADHD diagnosis directly impacted secondary task performance. Results further showed significant interactions between distraction type and traffic density on both brake pressure and steering wheel angle negatively impacting lateral and horizontal vehicle control. Altogether, these findings provide substantial empirical evidence for the deleterious effect of cellphone use on driving performance.Practitioner summary: This study examined how ADHD diagnosis, traffic density, and distraction type affect driver behaviour. Participants completed driving behaviour questionnaires, memory tasks, workload indices, and driving scenarios. Results showed that ADHD diagnosis impacted secondary task performance, while traffic and distractions significantly impacted driving performance as well secondary task performance and workload.

Electric Bicyclist Injury Severity during Peak Traffic Periods: A Random-Parameters Approach with Heterogeneity in Means and Variances

Accidents involving electric bicycles, a popular means of transportation in China during peak traffic periods, have increased. However, studies have seldom attempted to detect the unique crash consequences during this period. This study aims to explore the factors influencing injury severity in electric bicyclists during peak traffic periods and provide recommendations to help devise specific management strategies. The random-parameters logit or mixed logit model is used to identify the relationship between different factors and injury severity. The injury severity is divided into four categories. The analysis uses automobile and electric bicycle crash data of Xi’an, China, between 2014 and 2019. During the peak traffic periods, the impact of low visibility significantly varies with factors such as areas with traffic control or without streetlights. Furthermore, compared with traveling in a straight line, three different turnings before the crash reduce the likelihood of severe injuries. Roadside protection trees are the most crucial measure guaranteeing riders’ safety during peak traffic periods. This study reveals the direction, magnitude, and randomness of factors that contribute to electric bicycle crashes. The results can help safety authorities devise targeted transportation safety management and planning strategies for peak traffic periods.

Measuring Correlates of Mental Workload During Simulated Driving Using cEEGrid Electrodes: A Test-Retest Reliability Analysis

The EEG reflects mental processes, especially modulations in the alpha and theta frequency bands are associated with attention and the allocation of mental resources. EEG has also been used to study mental processes while driving, both in real environments and in virtual reality. However, conventional EEG methods are of limited use outside of controlled laboratory settings. While modern EEG technologies offer hardly any restrictions for the user, they often still have limitations in measurement reliability. We recently showed that low-density EEG methods using film-based round the ear electrodes (cEEGrids) are well-suited to map mental processes while driving a car in a driving simulator. In the present follow-up study, we explored aspects of ecological and internal validity of the cEEGrid measurements. We analyzed longitudinal data of 127 adults, who drove the same driving course in a virtual environment twice at intervals of 12-15 months while the EEG was recorded. Modulations in the alpha and theta frequency bands as well as within behavioral parameters (driving speed and steering wheel angular velocity) which were highly consistent over the two measurement time points were found to reflect the complexity of the driving task. At the intraindividual level, small to moderate (albeit significant) correlations were observed in about 2/3 of the participants, while other participants showed significant deviations between the two measurements. Thus, the test-retest reliability at the intra-individual level was rather low and challenges the value of the application for diagnostic purposes. However, across all participants the reliability and ecological validity of cEEGrid electrodes were satisfactory in the context of driving-related parameters.

Tactical and strategic driving behaviour in older drivers: The importance of readiness to change

The aim of this study was to explore the way in which reports of strategic and tactical driving self-regulation are influenced by readiness to change driving behaviour in older men and women, either reporting or not reporting modification of driving behaviour for health-related reasons, and/or increased driving difficulty. Current Australian drivers aged over 60 years (N = 258) responded to a self-report questionnaire. Hierarchical regression analyses indicated increased use of tactical behaviours were associated with greater driving difficulty, more readiness to change and male gender (R² = 23.2%) . These effects were moderated by a significant association between readiness to change, driving modifications for health reasons and age (R²_chg = 2.9%). Greater readiness to change was associated with increased use of tactical behaviours for older drivers who did not modify driving for health reasons, independent of ageIndependent of age. This association was also found for younger old drivers with health difficulties, but not for older old drivers with health difficulties. Hierarchical regression indicated that greater readiness to change, increased driving difficulty, female gender and modification of driving for health reasons were associated with reports of increased strategic self-regulation (R² = 50.8%). These effects were moderated by readiness to change and age, and readiness to change and gender (R²_chg = 2.1%). The association between readiness to change and strategic self-regulation was stronger for women than men, and the strength of this association became substantially stronger with increasing age. It was concluded that readiness to change driving behaviour may promote different forms of driving self-regulation for different individuals, and that older drivers may use the different forms of driving self-regulation independently of one another.

How visual information influences dual-task driving and tracking

The study examined the impact of visual predictability on dual-task performance in driving and tracking tasks. Participants (N = 27) performed a simulated driving task and a pursuit tracking task. In either task, visual predictability was manipulated by systematically varying the amount of advance visual information: in the driving task, participants drove at night with low beam, at night with high beam, or in daylight; in the tracking task, participants saw a white line that specified the future target trajectory for 200, 400 or 800 ms. Concurrently with driving or tracking, participants performed an auditory task. They had to discriminate between two sounds and press a pedal upon hearing the higher sound. Results show that in general, visual predictability benefited driving and tracking; however, dual-task driving performance was best with highest visual predictability (daylight), dual-task tracking performance was best with medium visual predictability (400 ms). Braking/reaction times were higher in dual tasks compared to single tasks, but were unaffected by visual predictability, showing that its beneficial effects did not transfer to the auditory task. In both tasks, manual accuracy decreased around the moment the foot pressed the pedal, indicating interference between tasks. We, therefore, conclude that despite a general beneficial impact of predictability, the integration of visual information seems to be rather task specific, and that interference between driving and audiomotor tasks, and tracking and audiomotor tasks, seems comparable.

Improving Safety and Efficiency of Roundabouts Through an Integrated System of Guide Signs

A roundabout can improve intersection capacity in some extent by reducing conflict points and traffic delays. However, the complex environment in a large roundabout does not provide essential directional information to motorists. Therefore, drivers must spend more time identifying the exit they want, which may influence the intersection capacity and safety. Using perceptual constancy, a new guide sign system for roundabouts was developed to improve sense of direction. In order to observe how the guide sign system would affect drivers’ sense of direction, a series of driving simulator experiments were conducted to evaluate driving performance. The test results revealed that the guide sign system can effectively improve the accuracy of exit identification and reduce travel time driving through a roundabout despite the gender and age differences among drivers. This paper proposes a continuous and gradual guide sign system for roundabouts that can be used to help improve drivers’ sense of direction, which is beneficial to improve the safety and efficiency of roundabout operations. These findings are indicative of the future development of traffic sign design and practice in a roundabout.

Evaluating Mental Load During Realistic Driving Simulations by Means of Round the Ear Electrodes

Film based round the ear electrodes (cEEGrids) provide both, the accessibility of unobtrusive mobile EEG as well as a rapid EEG application in stationary settings when extended measurements are not possible. In a large-scale evaluation of driving abilities of older adults (N > 350) in a realistic driving simulation, we evaluated to what extent mental demands can be measured using cEEGrids in a completely unrestricted environment. For a first frequency-based analysis, the driving scenario was subdivided into different street segments with respect to their task loads (low, medium, high) that was a priori rated by an expert. Theta activity increased with task load but no change in Alpha power was found. Effects gained clarity after removing pink noise effects, that were potentially high in this data set due to motion artifacts. Theta fraction increased with task load and Alpha fraction decreased. We mapped this effect to specific street segments by applying a track-frequency analysis. Whilst participants drove with constant speed and without high steering wheel activity, Alpha was high and theta low. The reverse was the case in sections that required either high activity or increased attentional allocation to the driving context. When calculating mental demands for different street segments based on EEG, this measure is highly significant correlated with the experts' rating of task load. Deviances can be explained by specific features within the segments. Thus, modulations in spectral power of the EEG were validly reflected in the cEEGrids data. All findings were in line with the prominent literature in the field. The results clearly demonstrate the usability of this low-density EEG method for application in real-world settings where an increase in ecological validity might outweigh the loss of certain aspects of internal validity.

Exploring causes and effects of automated vehicle disengagement using statistical modeling and classification tree based on field test data

Automated vehicles (AV) testing on the public roads is ongoing in several states in the US as well as in Europe and Asia. As long as the automated vehicle technology has not achieved full automation (Level 5), human drivers are still expected to take over the steering wheel and throttles when there is an automated vehicle disengagement. However, contributing factors and the mechanism about automated vehicle-initiated disengagement has not been quantitatively and comprehensively explored and investigated due to the lack of field test data. Besides, understanding human drivers' perception and promptness of reaction to the AV disengagement is essential to ensure safety transition between automated and manual driving. By harnessing California's Autonomous Vehicle Disengagement Report Database, which includes the AV disengagement data from field tests in 2016-2017, this paper quantitatively investigated the AV disengagement using multiple statistical modeling approaches that involve statistical modeling and classification tree. Specifically, the paper identifies the contributing factors impacting human drivers' promptness to AV disengagements, and quantitatively investigates the underlying causes to AV disengagements. Results indicate that current AV disengagement on public roads is dominated by causes due to a planning issue. The cause of an AV disengagement is significantly induced by lacking certain numbers of radar and LiDAR sensors installed on the automated vehicles. These thresholds of these sensors needed are revealed. Cause of disengagement and roadway characteristics significantly impact drivers' take-over time when facing an AV disengagement. AV perception or control issue-based disengagement can significantly extend drivers' perception-reaction time to take over the driving. The quantitative knowledge obtained ultimately facilitates revealing the mechanisms of the automated vehicle disengagements to ensure safe AV operations on public roads.

Useful field of view test performance throughout adulthood in subjects without ocular disorders

Previous research has shown an age-related decline in Useful Field of View (UFOV) test performance, which measures the duration required to extract relevant information from a scene in three subtasks. However, these results are mostly based on data that may have been confounded by (age-related) ocular diseases. We examined UFOV performance in subjects aged 19.5 to 70.3 years to investigate how UFOV performance changes throughout adulthood. All subjects underwent a thorough ophthalmological examination to exclude ocular disorders. We also examined some elementary visual functions, i.e., near and far visual acuity, crowding and contrast sensitivity. We investigated whether these functions were related to age and whether they could explain a possible age-related decline in UFOV performance. The subjects (n = 41) performed very well on almost every measure and reached far better UFOV and visual acuity scores than those reported by other studies that relied on self-reported absence of ocular pathology. We did not find significant relationships between age and any of the elementary visual functions or the first two UFOV subtasks (R2UFOV1 = 0.03, p = 0.25; R2UFOV2 = 0.07, p = 0.10). However, we found an age-related decline in performance on the third UFOV subtask (R2UFOV3 = 0.36, p < 0.001), which was unrelated to performance on the elementary visual function tasks. Our results show that performance on the first two UFOV subtasks as well as central elementary visual functions may remain high in the absence of obvious ophthalmological pathology.

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.

Age Differences in Visual-Auditory Self-Motion Perception during a Simulated Driving Task

Recent evidence suggests that visual-auditory cue integration may change as a function of age such that integration is heightened among older adults. Our goal was to determine whether these changes in multisensory integration are also observed in the context of self-motion perception under realistic task constraints. Thus, we developed a simulated driving paradigm in which we provided older and younger adults with visual motion cues (i.e., optic flow) and systematically manipulated the presence or absence of congruent auditory cues to self-motion (i.e., engine, tire, and wind sounds). Results demonstrated that the presence or absence of congruent auditory input had different effects on older and younger adults. Both age groups demonstrated a reduction in speed variability when auditory cues were present compared to when they were absent, but older adults demonstrated a proportionally greater reduction in speed variability under combined sensory conditions. These results are consistent with evidence indicating that multisensory integration is heightened in older adults. Importantly, this study is the first to provide evidence to suggest that age differences in multisensory integration may generalize from simple stimulus detection tasks to the integration of the more complex and dynamic visual and auditory cues that are experienced during self-motion.

Walking and Walkability: Is Wayfinding a Missing Link? Implications for Public Health Practice

BACKGROUND

Research on walking and walkability has yet to focus on wayfinding, the interactive, problem-solving process by which people use environmental information to locate themselves and navigate through various settings.

METHODS

We reviewed the literature on outdoor pedestrian-oriented wayfinding to examine its relationship to walking and walkability, 2 areas of importance to physical activity promotion.

RESULTS

Our findings document that wayfinding is cognitively demanding and can compete with other functions, including walking itself. Moreover, features of the environment can either facilitate or impede wayfinding, just as environmental features can influence walking.

CONCLUSIONS

Although there is still much to be learned about wayfinding and walking behaviors, our review helps frame the issues and lays out the importance of this area of research and practice.

Dropout during a driving simulator study: A survival analysis

INTRODUCTION

Simulator sickness is the occurrence of motion-sickness like symptoms that can occur during use of simulators and virtual reality technologies. This study investigated individual factors that contributed to simulator sickness and dropout while using a desktop driving simulator.

METHOD

Eighty-eight older adult drivers (mean age 72.82±5.42years) attempted a practice drive and two test drives. Participants also completed a battery of cognitive and visual assessments, provided information on their health and driving habits, and reported their experience of simulator sickness symptoms throughout the study.

RESULTS

Fifty-two participants dropped out before completing the driving tasks. A time-dependent Cox Proportional Hazards model showed that female gender (HR=2.02), prior motion sickness history (HR=2.22), and Mini-SSQ score (HR=1.55) were associated with dropout. There were no differences between dropouts and completers on any of the cognitive abilities tests.

CONCLUSIONS

Older adults are a high-risk group for simulator sickness. Within this group, female gender and prior motion sickness history are related to simulator dropout. Higher reported experience of symptoms of simulator sickness increased rates of dropout.

PRACTICAL APPLICATIONS

The results highlight the importance of screening and monitoring of participants in driving simulation studies. Older adults, females, and those with a prior history of motion sickness may be especially at risk.

Development of a novel driving behavior adaptations questionnaire

BACKGROUND

Driving a car requires adapting one's behavior to current task demands taking into account one's capacities. With increasing age, driving-relevant cognitive performance may decrease, creating a need for risk-reducing behavioral adaptations. Three different kinds of behavioral adaptations are known: selection, optimization, and compensation. These can occur on the tactical and the strategic level. Risk-reducing behavioral adaptations should be considered when evaluating older drivers' traffic-related risks.

METHODS

A questionnaire to assess driving-related behavioral adaptations in older drivers was created. The questionnaire was administered to 61 years older (age 65-87 years; mean age = 70.2 years; SD = 5.5 years; 30 female, 31 male) and 31 younger participants (age 22-55 years; mean age = 30.5 years; SD = 6.3 years; 16 female and 15 male) to explore age and gender differences in behavioral adaptations.

RESULTS

Two factors were extracted from the questionnaire, a risk-increasing factor and a risk-reducing factor. Group comparisons revealed significantly more risk-reducing behaviors in older participants (t(84.5) = 2.21, p = 0.013) and females (t(90) = 2.52, p = 0.014) compared, respectively, to younger participants and males. No differences for the risk-increasing factor were found (p > 0.05).

CONCLUSIONS

The questionnaire seems to be a useful tool to assess driving-related behavioral adaptations aimed at decreasing the risk while driving. The possibility to assess driving-related behavioral adaptations in a systematic way enables a more resource-oriented approach in the evaluation of fitness to drive in older drivers.

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.

Does attention capacity moderate the effect of driver distraction in older drivers?

With age, a decline in attention capacity may occur and this may impact driving performance especially while distracted. Although the effect of distraction on driving performance of older drivers has been investigated, the moderating effect of attention capacity on driving performance during distraction has not been investigated yet. Therefore, the aim was to investigate whether attention capacity has a moderating effect on older drivers' driving performance during visual distraction (experiment 1) and cognitive distraction (experiment 2). In a fixed-based driving simulator, older drivers completed a driving task without and with visual distraction (experiment 1, N=17, mean age 78 years) or cognitive distraction (experiment 2, N=35, mean age 76 years). Several specific driving measures of varying complexity (i.e., speed, lane keeping, following distance, braking behavior, and crashes) were investigated. In addition to these objective driving measures, subjective measures of workload and driving performance were also included. In experiment 1, crash occurrence increased with visual distraction and was negatively related to attention capacity. In experiment 2, complete stops at stop signs decreased, initiation of braking at pedestrian crossings was later, and crash occurrence increased with cognitive distraction. Interestingly, for a measure of lane keeping (i.e., standard deviation of lateral lane position (SDLP)), effects of both types of distraction were moderated by attention capacity. Despite the decrease of driving performance with distraction, participants estimated their driving performance during distraction as good. These results imply that attention capacity is important for driving. Driver assessment and training programs might therefore focus on attention capacity. Nonetheless, it is crucial to eliminate driver distraction as much as possible given the deterioration of performance on several driving measures in those with low and high attention capacity.

A simulator study of the effects of singing on driving performance

This study aimed to investigate how singing while driving affects driver performance. Twenty-one participants completed three trials of a simulated drive concurrently while performing a peripheral detection task (PDT); each trial was conducted either without music, with participants listening to music, or with participants singing along to music. It was hypothesised that driving performance and PDT response times would be impaired, and that driver subjective workload ratings would be higher, when participants were singing to music compared to when there was no music or when participants were listening to music. As expected, singing while driving was rated as more mentally demanding, and resulted in slower and more variable speeds, than driving without music. Listening to music was associated with the slowest speeds overall, and fewer lane excursions than the no music condition. Interestingly, both music conditions were associated with slower speed-adjusted PDT response times and significantly less deviation within the lane than was driving without music. Collectively, results suggest that singing while driving alters driving performance and impairs hazard perception while at the same time increasing subjective mental workload. However, singing while driving does not appear to affect driving performance more than simply listening to music. Further, drivers' efforts to compensate for the increased mental workload associated with singing and listening to music by slowing down appear to be insufficient, as evidenced by relative increases in PDT response times in these two conditions compared to baseline.

Driving in fog: the effects of driving experience and visibility on speed compensation and hazard avoidance

Inexperience is one of the strongest predictors for collisions, but it remains unclear how novice drivers differ from experienced drivers in terms of safety-related behavioural adaptations such as speed reduction in the presence of reduced visibility. To investigate the influence of driving experience on behavioural compensations to fog, average speed, speed variability, steering variability, collision rate, and hazard response time were measured in a driving simulator. Experienced drivers drove faster in clear visibility than novice drivers, yet they reduced their speed more in reduced visibility so that both groups drove at the same speed in simulated fog. Compared to experienced drivers, novice drivers had higher hazard response times, greater speed and steering variability, and were the only drivers to have collisions.

Useful field of view predicts driving in the presence of distracters

PURPOSE

The Useful Field of View (UFOV) test has been shown to be highly effective in predicting crash risk among older adults. An important question which we examined in this study is whether this association is due to the ability of the UFOV to predict difficulties in attention-demanding driving situations that involve either visual or auditory distracters.

METHODS

Participants included 92 community-living adults (mean age 73.6 ± 5.4 years; range 65-88 years) who completed all three subtests of the UFOV involving assessment of visual processing speed (subtest 1), divided attention (subtest 2), and selective attention (subtest 3); driving safety risk was also classified using the UFOV scoring system. Driving performance was assessed separately on a closed-road circuit while driving under three conditions: no distracters, visual distracters, and auditory distracters. Driving outcome measures included road sign recognition, hazard detection, gap perception, time to complete the course, and performance on the distracter tasks.

RESULTS

Those rated as safe on the UFOV (safety rating categories 1 and 2), as well as those responding faster than the recommended cut-off on the selective attention subtest (350 msec), performed significantly better in terms of overall driving performance and also experienced less interference from distracters. Of the three UFOV subtests, the selective attention subtest best predicted overall driving performance in the presence of distracters.

CONCLUSIONS

Older adults who were rated as higher risk on the UFOV, particularly on the selective attention subtest, demonstrated poorest driving performance in the presence of distracters. This finding suggests that the selective attention subtest of the UFOV may be differentially more effective in predicting driving difficulties in situations of divided attention which are commonly associated with crashes.

The effects of on-street parking and road environment visual complexity on travel speed and reaction time

On-street parking is associated with elevated crash risk. It is not known how drivers' mental workload and behaviour in the presence of on-street parking contributes to, or fails to reduce, this increased crash risk. On-street parking tends to co-exist with visually complex streetscapes that may affect workload and crash risk in their own right. The present paper reports results from a driving simulator study examining the effects of on-street parking and road environment visual complexity on driver behaviour and surrogate measures of crash risk. Twenty-nine participants drove a simulated urban commercial and arterial route. Compared to sections with no parking bays or empty parking bays, in the presence of occupied parking bays drivers lowered their speed and shifted their lateral position towards roadway centre to compensate for the higher mental workload they reported experiencing. However, this compensation was not sufficient to reduce drivers' reaction time on a safety-relevant peripheral detection task or to an unexpected pedestrian hazard. Compared to the urban road environments, the less visually complex arterial road environment was associated with speeds that were closer to the posted limit, lower speed variability and lower workload ratings. These results support theoretical positions that proffer workload as a mediating variable of speed choice. However, drivers in this study did not modify their speed sufficiently to maintain safe hazard response times in complex environments with on-street parking. This inadequate speed compensation is likely to affect real world crash risk.

Driving performance in a power wheelchair simulator

PURPOSE

A power wheelchair simulator can allow users to safely experience various driving tasks. For such training to be efficient, it is important that driving performance be equivalent to that in a real wheelchair. This study aimed at comparing driving performance in a real and in a simulated environment.

METHOD

Two groups of healthy young adults performed different driving tasks, either in a real power wheelchair or in a simulator. Smoothness of joystick control as well as the time necessary to complete each task were recorded and compared between the two groups. Driving strategies were analysed from video recordings. The sense of presence, of really being in the virtual environment, was assessed through a questionnaire.

RESULTS

Smoothness of joystick control was the same in the real and virtual groups. Task completion time was higher in the simulator for the more difficult tasks. Both groups showed similar strategies and difficulties. The simulator generated a good sense of presence, which is important for motivation.

CONCLUSIONS

Performance was very similar for power wheelchair driving in the simulator or in real life. Thus, the simulator could potentially be used to complement training of individuals who require a power wheelchair and use a regular joystick. [Box: see text].