Are Driving Simulators Suitable to Measure the Driving Competence of Elderly Drivers?

oai:driving:id:28330The present project aimed to develop and validate a methodology for driving simulators to assess and diagnose driving ability of elderly drivers. A driving simulation course has been developed which covered a representative selection of driving tasks of moderate difficulty as well as scenarios which are particularly difficult for elderly drivers. Driving errors were semi-automatically registered and classified by a tablet PC application. Based on the registered driving errors, the driving competence of each driver was rated on an 11-point fitness-to-drive (FtD) rating scale by specifically trained raters. The driving course was validated on the basis of a 60-minute standardized driving test in real traffic. By including similar driving tasks, it was ensured that it was structurally comparable to the simulated course. 30 elderly drivers (> 70 years) and 30 control drivers (25-50 years) were assessed in the simulation and in real traffic. During the driving tests, more driving errors were registered for the elderly drivers than for the controls both in the simulator and in real traffic. FtD-ratings and total number of driving errors during the driving tests in the simulation correlated up to r = .80 with the FtD-ratings of the driving tests in real traffic. ROC-Analyses revealed at Sensitivity-Specificity Ratio of 85.71 : 82.61 at best. Overall, driving simulation was well accepted by the subjects. The findings of the study confirm the validity of driving simulation as a tool to diagnose driving ability and argue for its introduction as a diagnostic tool

Task Analysis for Measuring Mobility and Recovery Following Right-Sided TKA: Toward Determining Driver Readiness

Following a right-sided total knee arthroplasty (TKA), standard clinical recommendations for patients is to refrain from driving for 6 weeks. Clinical assessments of recovery include mobility tests but do not specifically assess fitness to drive. As a first step in assessment of driver readiness, this study aimed to compare vehicle entry behaviors and mobility assessments between TKA patients and healthy controls. 18 participants (9 TKA participants) completed three in-laboratory visits where they completed mobility tests and entered a full-cab car. Videos of vehicle entry were reviewed and annotated for time—timed vehicle entry (TVE)—and to categorize entry mode. TVE was significantly slower for TKA participants before surgery and 3 weeks after the procedure (p < 0.05) but not 6 weeks after (p < 0.05). TVE was positively correlated with timed up and go (TUG, r = 0.65, p < 0.05) and negatively correlated with right knee range of motion (ROM, r = -0.5, p < 0.05). Range of motion was not significantly different across entry modes between TKA participants and controls. This study was not conclusive to the utility of TVE to replace ROM and TUG for driver readiness; however, this work demonstrated the use of a real-world task that is related to driving for providing patient recovery and behavioral information

Mind-Wandering and Driving: Comparing Thought Report and Individual Difference Measures

Mind-wandering is a cognitive state in which attention is diverted from the main task and towards more personal thoughts, which can interfere with performance. This study investigated differences in patterns of mind-wandering and driving performance measured during thought-probe versus post-task selfreport conditions, and further differentiated based on individual differences in working memory—as measured by the Operation Span (OSPAN) and Sustained Attention to Response Task (SART). Participants completed two 30-minute drives. Those in the thought-probe condition were asked whether they were thinking of driving; the proportion of trials where they answered “no” was used as the index of mind-wandering. In the post-task condition participants estimated the percentage of time they had mind-wandered during each drive. Speed, steering variability, headway distance, and hazard response time to a lead vehicle braking were also measured. Results showed that the magnitude of mind-wandering captured in the thought-probe condition was greater than in the post-task condition, though hazard response times were also faster despite greater mindwandering reports. Higher OSPAN scores were associated with greater reports of mind-wandering, but only in the post-task condition. Conversely, in the post-task condition those with low SART scores responded slower to hazards than those with high scores; in the thought-probe condition these groups did not differ. Findings indicate a differential impact of report-type on participant experience, emphasizing the need for more covert measures of mind-wandering—e.g., eyetracking or electroencephalography—that provide accurate estimates of task engagement but don’t interfere with task flow

Consumer Comfort with Vehicle Automation: Changes Over Time

Higher levels of vehicle automation are forecast as a potential mobility solution for many, but understanding consumer comfort and acceptance of selfdriving technologies remains an open question. Results from a series of surveys over three years showed a slight increase in the percentage of people comfortable with full self-driving automation in 2018, following a drop from 2016 to 2017. The recovery in comfort with higher levels of automation was most pronounced among younger adults between ages 25 and 44. However, the percentage of people only comfortable with no automation or features that activate only in certain situations such as in an emergency also increased in the past year, indicating a polarizing trend. Results from the survey also showed that acceptance of self-driving vehicles is conditional on people’s ability to drive as well as having assurance regarding the safety of the technology. Responses also point to a possible misunderstanding among the public regarding the definition and availability of full self-driving technology, indicating a need for improved messaging and consumer education

German Validation of the Prosocial and Aggressive Driving Inventory (PADI)

This paper presents the German adaptation of the Prosocial and Aggressive Driving Inventory (PADI) (Harris et al., 2014). The self-report questionnaire measures safe (prosocial) and unsafe (aggressive) driving behavior. The questionnaire was translated using a forward-backward method. The translation clarity and its applicability were tested in a pilot study. The German version was then validated online with N = 291 participants. Confirmatory factor analysis revealed the same factor structure as in the English original. Multiple regression analysis was employed to investigate existing connections between driving behavior and the Big Five personality traits. Aggressive driving behavior was associated with higher scores on Extraversion and lower scores on Agreeableness, Openness, and Conscientiousness. Prosocial driving behavior was associated with higher scores on Openness and Conscientiousness and with participants that were older and female. This questionnaire might be used to investigate effective forms of driving behavior

A Survey Study Measuring People\u27s Preferences Towards Automated and Non-Automated Ridesplitting

Ridesplitting is both common and important as it facilitates daily transportation needs. Alongside an increase in ridesplitting is the introduction of automated driving systems, which together, bring out the possibility of automated ridesplitting. However, previous studies have identified resistance in the acceptance of automated driving systems. In light of past research on automated driving systems, we used a survey to compare people’s preferences of automated ridesplitting to non-automated ridesplitting. Statistical and text mining techniques were leveraged to analyze the results. We found similarities in the numeric responses of important factors concerning automated and non-automated ridesplitting whereas there were large differences between automated and nonautomated ridesplitting in the text responses. Additionally, people prioritized cost and time in both automated and non-automated ridesplitting. These results can be used in the design of future ridesplitting services, especially with respect to increasing acceptance of and trust in automated ridesplitting services

Drivers\u27 Assessment of Hazard Perception

Encountering dangerous situations while driving is ubiquitous. Existing research suggest that specific populations such as, novice drivers are more prone to errors in detecting and responding to driving hazards. Hazard perception training programs have been developed in attempts to improve or accelerate the acquisition of such skills. However, drivers’ attitudes and knowledge regarding vulnerable populations and hazard perception training programs remain largely unknown. Three-hundred-five participants completed an online survey assessing their beliefs about influential factors affecting hazard detection and response, perceived usefulness and preferred types of training programs, and self-assessment of driving skills. Although many existing training programs are computer-based, participants preferred on-road hazard perception training. Such findings may assist in improving existing programs, which currently fail to show near- and far-transfer effects. Similarly, novice drivers reported being most likely to engage in training programs – possibly linked to their reported high value of the usefulness of such programs and awareness of their vulnerability to commit errors. Although autonomous vehicles should mitigate these errors, researchers and government officials suggest automated vehicles will not be commercially available for 10 years. Therefore, the results of the present study provide insight into drivers’ beliefs about dangerous situations, which may prove useful in developing and improving training programs aimed at mitigating crash risk

Cognitive Load During Automation Affects Gaze Behaviours and Transitions to Manual Steering Control

Automated vehicles (AVs) are being tested on-road with plans for imminent large-scale deployment. Many AVs are being designed to control vehicles without human input, whilst still relying on a human driver to remain vigilant and responsible for taking control in case of failure. Drivers are likely to use AV control periods to perform additional non-driving related tasks, however the impact of this load on successful steering control transitions (from AV to the human) remains unclear. Here, we used a driving simulator to examine the effect of an additional cognitive load on gaze behavior during automated driving, and on subsequent manual steering control. Drivers were asked to take-over control after a short period of automation caused trajectories to drift towards the outside edge of a bending road. Drivers needed to correct lane position when there was no additional task (“NoLoad”), or whilst also performing an auditory detection task (“Load”). Load might have affected gaze patterns, so to control for this we used either: i) Free gaze, or ii) Fixed gaze (to the road center). Results showed that Load impaired steering, causing insufficient corrections for lane drift. Free gaze patterns were influenced by the added cognitive load, but impaired steering was also observed when gaze was fixed. It seems then that the driver state (cognitive load and gaze direction) during automation may have important consequences for whether the takeover of manual vehicle control is successful

Driving with Foresight - Evaluating the Effect of Cognitive Distraction and Experience on Anticipating Events in Traffic

Driving with foresight is essential for road safety. Anticipating upcoming events and intended maneuvers of other traffic participants requires the perception and processing of meaningful and valid cues. To provide insights into the cognitive mechanisms of anticipation, we investigated the effect of cognitive load, experience and cue characteristic on the anticipation of upcoming lane changes in urban driving scenarios. A two-step reaction method gathered low and high certainty anticipatory reactions of student and ambulance drivers. Results indicated that different anticipatory cues affected anticipatory performance. Target cues highly associated with the intended behavior of another traffic participant increased while context cues in the surrounding environment seemed to hamper anticipatory reactions. Furthermore, high cognitive load prolonged the latencies of low certainty anticipation but did not affect the performance quality. This initial intuition of an upcoming lane change was indicated earlier by experienced than by inexperienced drivers. These findings enhance the understanding of the human process of anticipation in dynamic uncritical traffic situations

Where You Look During Automation Influences Where You Steer After Take-Over

When driving a vehicle, gaze direction (where the driver is looking) is tightly coupled with steering actions. For example, previous research has shown that gaze direction directly influences steering behavior. In the context of transitions of control from automated to manual driving, a new question arises: Does gaze direction before a transition influence the manual steering after it? Here we addressed this question in a simplified simulated driving scenario, for maximum experimental control. Participants (N=26) were driven around a constant curvature bend by an automated vehicle, which gradually drifted toward the outside of the bend. An auditory tone cued manual take-over of steering control and participants were required to correct the drift and return to the lane center. Gaze direction was controlled using an onscreen fixation point with a position that varied from trial to trial horizontally and/or vertically. The results showed that steering during manual control was systematically biased by gaze direction during the automated period, but notably in the opposite direction to what might have been expected based on previous research. Whilst further research is needed to understand the causal mechanisms, these findings do suggest that where a driver looks during the seconds preceding a transition to manual control may be critical in determining whether the subsequent steering actions are successful