729 research outputs found
Sort by
Driving Simulation as Virtual Reality Exposure Therapy to Rehabilitate Patients with Driving Fear After Traffic Accidents
No full textFollowing a traffic accident, up to 30% of the involved persons suffer from stress related symptoms often coming along with enduring fear of driving. Virtual reality exposure therapy (VRET) offers major advantages for treating anxiety disorders, but with respect to fear of driving it has been hardly investigated so far. In the present study a driving simulator exposure treatment for patients with fear of driving after a traffic accident was developed and evaluated. The therapy followed a standardized manual of 13 sessions including anamnesis, medical examination, two preparative psychotherapy sessions, five virtual reality exposure (VRE) sessions, a final behavioral avoidance test in real traffic with a driving instructor, a closing session, plus follow-up phone calls after six and twelve weeks. The exposure scenarios were individually tailored to the patients’ anxiety hierarchy. 14 patients were treated. Results indicate excellent treatment success. In the final behavioral avoidance test, all patients mastered driving tasks they had avoided before, 71% showed an adequate driving behavior as assessed by the driving instructor, 93% could maintain their treatment success until the second follow-up phone call. We conclude that VRET in a driving simulator is a highly promising tool to treat fear of driving. Major advantages are that traffic scenarios are highly controllable, safe and can be designed and presented to perfectly fit the individuals' anxieties
Driving Simulator Assessment of Fitness-to-Drive Following Traumatic Brain Injury
No full textReturning to driving is a major goal for individuals recovering from a traumatic brain injury (TBI). Clinicians have a variety of tools to assess the ability to return to driving for TBI patients, including cognitive assessments, but on-road instrumented vehicle driving assessments have been considered the gold standard. However, these on-road assessments are limited in the ability to ethically expose drivers to certain driving situations or environments. The purpose of this study was to examine the ability of a high-fidelity driving simulator to assess driving performance in individuals who have sustained a moderate-to-severe TBI, as well as associate cognitive measures commonly used in this population with simulated driving outcomes. Fourteen participants from a TBI clinic were recruited to drive in a simulator through a series of increasingly complex diving modules: 1) basic vehicle operation; 2) secondary task engagement while driving; 3) car following; 4) divided attention; and 5) navigating left hand turns across oncoming traffic. Half (n = 7) had been released to return to drive and half (n = 7) were considered to never be able to return to driving. Although general trends suggest non-drivers exhibit slower driving and increased lane position variation, group differences driving were not shown likely due to small sample sizes. Differences in patterns of cognitive correlates with driving were found, with higher order cognitive processes, like working memory, being more associated with driving outcomes in active drivers. Suggestions for driving scenario development in this population are discussed
Impact of Headlight Glare on Pedestrian Detection with Unilateral Cataract
No full textDetecting pedestrians while driving at night is difficult, and is further impeded by oncoming headlight glare (HLG). Cataracts increase intraocular light scattering, making the task even more challenging. We used a within-subjects repeated measures design to determine the impact of HLG on driving with unilateral cataract. Pedestrian detection performance of six young normal vision (NV) subjects was measured with clear lens glasses and with simulated unilateral cataract (0.8 Bangerter foil) glasses. The subjects drove night-time scenarios in a driving simulator with and without custom simulated headlight glare. With simulated unilateral cataracts, pedestrian detection rates decreased and response times increased with oncoming HLG. We verified these effects with six patients who already underwent cataract surgery for one eye and were scheduled to get cataract surgery in the other eye. We measured their performance before and after the second cataract surgery. The results were similar to those obtained with the simulated unilateral cataract, confirming that a negative impact of HLG persists with untreated cataract in one eye
Understanding Lane-Keeping Assist: Does Control Intervention Enhance Perceived Capability?
No full textDrivers of vehicles equipped with ADAS often show a flawed understanding of the limitations of these systems. In this study, two types of lane keeping assist (LKA) were investigated: a lane centering system that continuously repositioned the vehicle in the center of the lane, and a lane departure prevention system that intervened when the vehicle wandered near the lane edge. Driver knowledge of each LKA (and accompanied ACC) were tested over a series of five drives. Results suggest that greater capability may be attributed to the lane centering system, perhaps because its control intervention is more frequent and obvious than the lane departure prevention LKA
A Methodical Approach to Examine Conflicts in Context of Driver - Autonomous Vehicle - Interaction
No full textFuture autonomous vehicles will make their own maneuver decisions whereby situations will occur in which the maneuver performed by the autonomous vehicle contradicts the course of action preferred by the driver. In response, the uninformed driver takes over manual control of the vehicle and performs a potentially inappropriate and safety-critical maneuver due to a lack of information. To prevent such a behavior in future, a methodical paradigm is needed, which is able to create possible driver - autonomous vehicle - conflicts and examine preventive and cooperative solutions in a driving simulator. This study (n = 29) is a successful methodical approach to create possible, authentic and reproducible driver - autonomous vehicle - conflicts. Conflicts were caused by a combination of gradation of visibility by fog (full visibility, 150m, 100m, 50m) and a maneuver performed by the automation (overtaking, following) on a rural road. 83% of the drivers canceled an overtaking maneuver by the automation and took over manual control in the 50m condition compared to 2% in the full visibility condition (z=1.914,
Improving Driver Engagement During L2 Automation: A Pilot Study
No full textAdvanced technologies such as adaptive cruise control and lane keeping are key components of SAE Level 2 vehicle automation. As such automation becomes widespread, drivers may be less engaged in driving because they assume that vehicles can safely mitigate risks. However, L2 automation cannot handle the full spectrum of driving situations and will require manual control in many situations. Drivers unprepared to take control may make suboptimal, delayed, or dangerous decisions during and after reengaging with the driving task. This highlights the need for efficient ways to help drivers re-engage with driving. This paper describes an evaluation of a conceptual driver engagement system that combined driver data with contextual data to communicate appropriate information during L2 operations. The system was compared to a traditional, staged-alert system that only monitored driver gaze with no contextual information. Results indicate higher situation awareness, higher levels of trust and satisfaction, no increase in workload, with evidence of improve off-road glance behaviors when driving with the conceptual system. These findings can help inform further development and testing of driver engagement approaches using driver monitoring
Task Analysis for Measuring Mobility and Recovery Following Right-Sided TKA: Toward Determining Driver Readiness
No full textFollowing 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
Learning and Development of Mental Models during Interactions with Driving Automation: A Simulator Study
No full textHigher level cognitive processes such as learning and mental models play a fundamental role in the success of automated driving, as technology can only be as good as our understanding and expectations of it. The present study investigated the development of these processes during interactions with driving automation. In a driving simulator study, N=52 participants completed several transitions between manual and Society of Automotive Engineers (SAE) levels 2 and 3 automated driving. Self-reported learning progress and mental model development were assessed via questionnaires. In parallel, eye-tracking data were collected as a behavioral measure of higher level cognitive functions. The results demonstrated that self-reported learning and gaze behavior followed a power-law function; the power-law functions showed task specific parameter manifestations. The evolution of the mental models of the level 2 and level 3 human-machine interface continued up to the fifth contact, indicating a long lasting process. For researchers and practitioners, the present study implies that accurate mental models require up to 5 repeated interactions. Furthermore, learning progress with driving automation can be captured through gaze behavior
Eye Contact between Pedestrians and Drivers
No full textWhen asked a great number of people believe that, as pedestrians, they make eye contact with the driver of an approaching vehicle when making their crossing decisions. This work presents evidence that this widely held belief is false. We do so by showing that, in majority of cases where conflict is possible, pedestrians begin crossing long before they are able to see the driver through the windshield. In other words, we are able to circumvent the very difficult question of whether pedestrians choose to make eye contact with drivers, by showing that whether they think they do or not, they can’t. Specifically, we show that over 90% of people in representative lighting conditions cannot determine the gaze of the driver at 15m and see the driver at all at 30m. This means that, for example, that given the common city speed limit of 25mph, more than 99% of pedestrians would have begun crossing before being able to see either the driver or the driver’s gaze. In other words, from the perspective of the pedestrian, in most situations involving an approaching vehicle, the crossing decision is made by the pedestrian solely based on the kinematics of the vehicle without needing to determine that eye contact was made by explicitly detecting the eyes of the driver
Real-Time Effects of Age-Related Cognitive Dysfunction on Driver Vehicle Control
No full textThis study tackles the need to understand how driver behavior deteriorates in advancing age, with the direct goal of improving real-world assessments of age-related cognitive dysfunction and safety in older drivers. Older drivers are at-risk for cognitive dysfunction, which may lead to dementia and elevates the risk of errors that may lead to crashes. Prior research on older drivers is critically limited by studying behavior in laboratory and controlled settings. To advance the field and overcome these limitations, we combine sensor-based technologies for continuous, real-world monitoring of driver behavior with comprehensive assessments of older drivers’ cognitive function. We assess patterns of vehicle control across each driver’s personal profile of cognitive function and link age-related cognitive dysfunction to changes in safety-relevant vehicle control. We find that age-related cognitive dysfunction effects braking and accelerating behaviors, but not steering behaviors, across wide-spread driving environments. Older drivers with worse cognitive function drove less yet did not reduce exposure to specific environments that may carry greater risk. Exposure patterns suggest potential maladaptive compensatory behavioral tradeoffs that lessen older driver mobility without sufficiently mitigating safety risks. Results demonstrate that older driver behavior is highly context dependent, suggesting specific targets for interventions to improve safety while preserving mobility and quality of life, and underscore the value of using the vehicle for sensing and monitoring driver functional capacity and subsequent risk for age-related cognitive dysfunction