Knowing me, knowing you-A study on top-down requirements for compensatory scanning in drivers with homonymous visual field loss.

OBJECTIVE: It is currently still unknown why some drivers with visual field loss can compensate well for their visual impairment while others adopt ineffective strategies. This paper contributes to the methodological investigation of the associated top-down mechanisms and aims at validating a theoretical model on the requirements for successful compensation among drivers with homonymous visual field loss. METHODS: A driving simulator study was conducted with eight participants with homonymous visual field loss and eight participants with normal vision. Participants drove through an urban surrounding and experienced a baseline scenario and scenarios with visual precursors indicating increased likelihoods of crossing hazards. Novel measures for the assessment of the mental model of their visual abilities, the mental model of the driving scene and the perceived attention demand were developed and used to investigate the top-down mechanisms behind attention allocation and hazard avoidance. RESULTS: Participants with an overestimation of their visual field size tended to prioritize their seeing side over their blind side both in subjective and objective measures. The mental model of the driving scene showed close relations to the subjective and actual attention allocation. While participants with homonymous visual field loss were less anticipatory in their usage of the visual precursors and showed poorer performances compared to participants with normal vision, the results indicate a stronger reliance on top-down mechanism for drivers with visual impairments. A subjective focus on the seeing side or on near peripheries more frequently led to bad performances in terms of collisions with crossing cyclists. CONCLUSION: The study yielded promising indicators for the potential of novel measures to elucidate top-down mechanisms in drivers with homonymous visual field loss. Furthermore, the results largely support the model of requirements for successful compensatory scanning. The findings highlight the importance of individualized interventions and driver assistance systems tailored to address these mechanisms.

Gaze Scanning at Street Crossings by Pedestrians With Homonymous Hemianopia With and Without Hemispatial Neglect.

Purpose: To investigate compensatory gaze-scanning behaviors during street crossings by pedestrians with homonymous hemianopia (HH) and hemispatial neglect (HSN). Methods: Pedestrians with right homonymous hemianopia (RHH) and left homonymous hemianopia without (LHH) and with left spatial-neglect (LHSN) walked on city streets wearing a gaze-tracking system that also captured scene videos. Street-crossing instances were manually annotated, and horizontal gaze scan of magnitude ≥20° and scanning rates were compared within-subject, between the side of the hemifield loss (BlindSide) and the other side (SeeingSide). Proportion of instances with scans to both the left and the right side at nonsignalized crossings (indicative of safe scanning behavior) were compared among the three subject groups. Results: Data from 19 participants (6 LHH, 7 RHH, and 6 with mild [4] or moderate [2] LHSN), consisting of 521 street-crossing instances of a total duration of 201 minutes and 5375 gaze scans, were analyzed. The overall gaze magnitude (mean [95% confidence interval (CI)]) was significantly larger toward the BlindSide (40.4° [39.1°-41.9°]) than the SeeingSide (36° [34.8°-37.3°]; P < 0.001). The scanning rate (mean [95% CI] scans/min) toward the BlindSide (14 [12.5-15.6]) was significantly higher than the SeeingSide (11.5 [10.3°-12.9°]; P < 0.001). The scanning rate in the LHSN group (10.7 [8.9-12.8]) was significantly lower than the LHH group (14 [11.6-17.0]; P = 0.045). The proportion of nonsignalized crossings with scans to both sides was significantly lower in LHSN (58%; P = 0.039) and RHH (51%; P = 0.003) than LHH (75%) participants. Conclusions: All groups demonstrated compensatory scanning, making more gaze scans with larger magnitudes to the blind side. Mild to moderate LHSN adversely impacted the scanning rate.

Driving Difficulties and Preferences of Advanced Driver Assistance Systems by Older Drivers With Central Vision Loss.

Purpose: The purpose of this study was to investigate driving difficulties and Advanced Driver Assistance Systems (ADAS) use and preferences of drivers with and without central vision loss (CVL). Methods: Fifty-eight drivers with CVL (71 ± 13 years) and 68 without (72 ± 8 years) completed a telephone questionnaire. They rated their perceived driving difficulty and usefulness of technology support in 15 driving situations under good (daytime) and reduced visibility conditions, and reported their use experience and preferences for 12 available ADAS technologies. Results: Drivers with CVL reported more difficulty (P = 0.002) and greater usefulness of technology support (P = 0.003) than non-CVL drivers, especially in reduced visibility conditions. Increased driving difficulty was associated with higher perceived technology usefulness (r = 0.34, P < 0.001). Dealing with blind spot road users, glare, unexpected pedestrians, and unfamiliar areas were perceived as the most difficult tasks that would benefit from technology support. Drivers with CVL used more advanced ADAS features than non-CVL drivers (P = 0.02), preferred to own the blind spot warning, pedestrian warning, and forward collision avoidance systems, and favored ADAS support that provided both information and active intervention. The perceived benefits of and willingness to own ADAS technologies were high for both groups. Conclusions: Drivers with CVL used more advanced ADAS and perceived greater usefulness of driver assistance technology in supporting difficult driving situations, with a strong preference for collision prevention support. Translational Relevance: This study highlights the specific technology needs and preferences of older drivers with CVL, which can inform future ADAS development, evaluation, and training tailored to this group.

Head Scanning Behavior Predicts Hazard Detection Safety Before Entering an Intersection.

OBJECTIVE: We conducted a driving simulator study to investigate scanning and hazard detection before entering an intersection. BACKGROUND: Insufficient scanning has been suggested as a factor contributing to intersection crashes. However, little is known about the relative importance of the head and eye movement components of that scanning in peripheral hazard detection. METHODS: Eleven older (mean 67 years) and 18 younger (mean 27 years) current drivers drove in a simulator while their head and eye movements were tracked. They completed two city drives (42 intersections per drive) with motorcycle hazards appearing at 16 four-way intersections per drive. RESULTS: Older subjects missed more hazards (10.2% vs. 5.2%). Failing to make a scan with a substantial head movement was the primary reason for missed hazards. When hazards were detected, older drivers had longer RTs (2.6s vs. 2.3s), but drove more slowly; thus, safe response rates did not differ between the two groups (older 83%; younger 82%). Safe responses were associated with larger (28.8° vs. 20.6°) and more numerous (9.4 vs. 6.6) gaze scans. Scans containing a head movement were stronger predictors of safe responses than scans containing only eye movements. CONCLUSION: Our results highlight the importance of making large scans with a substantial head movement before entering an intersection. Eye-only scans played little role in detection and safe responses to peripheral hazards. APPLICATION: Driver training programs should address the importance of making large scans with a substantial head movement before entering an intersection.

Driving With Hemianopia X: Effects of Cross Traffic on Gaze Behaviors and Pedestrian Responses at Intersections.

Purpose: We conducted a driving simulator study to investigate the effects of monitoring intersection cross traffic on gaze behaviors and responses to pedestrians by drivers with hemianopic field loss (HFL). Methods: Sixteen HFL and sixteen normal vision (NV) participants completed two drives in an urban environment. At 30 intersections, a pedestrian ran across the road when the participant entered the intersection, requiring a braking response to avoid a collision. Intersections with these pedestrian events had either (1) no cross traffic, (2) one approaching car from the side opposite the pedestrian location, or (3) two approaching cars, one from each side at the same time. Results: Overall, HFL drivers made more (p < 0.001) and larger (p = 0.016) blind- than seeing-side scans and looked at the majority (>80%) of cross-traffic on both the blind and seeing sides. They made more numerous and larger gaze scans (p < 0.001) when they fixated cars on both sides (compared to one or no cars) and had lower rates of unsafe responses to blind- but not seeing-side pedestrians (interaction, p = 0.037). They were more likely to demonstrate compensatory blind-side fixation behaviors (faster time to fixate and longer fixation durations) when there was no car on the seeing side. Fixation behaviors and unsafe response rates were most similar to those of NV drivers when cars were fixated on both sides. Conclusion: For HFL participants, making more scans, larger scans and safer responses to pedestrians crossing from the blind side were associated with looking at cross traffic from both directions. Thus, cross traffic might serve as a reminder to scan and provide a reference point to guide blind-side scanning of drivers with HFL. Proactively checking for cross-traffic cars from both sides could be an important safety practice for drivers with HFL.

Use and Perceptions of Advanced Driver Assistance Systems by Older Drivers With and Without Age-Related Macular Degeneration.

Purpose: Advanced driver assistance systems (ADAS) have been reported to improve the safety of elderly and normally sighted drivers. The purpose of this study was to assess exposure to, perceived safety of, comfort level with, and interest in using ADAS among drivers with age-related macular degeneration (AMD). Methods: Current drivers aged 60+ years were recruited at four US sites to complete a survey about ADAS and driving habits. Frequency of use and/or perceptions of eight ADAS were investigated. An avoidance score was generated using questions about difficult driving situations. Results: The survey was completed by 166 participants (80 with AMD vs. 86 without). Participants with AMD had worse self-rated vision than those without (34% vs. 2% poor or fair rating), and drove fewer weekly miles (median [interquartile range [IQR] 30 [15 to 75] vs. 60 [30 to 121] miles, P = 0.002). Participants with AMD reported more avoidance of difficult driving situations (P < 0.001). There was no difference in the number of ADAS used by AMD status (median [IQR for AMD = 2.5 [1 to 5] vs. 3 [2 to 4] without, P = 0.87). Greater reported number of ADAS used was associated with less avoidance of difficult situations (P = 0.02). The majority perceived improved safety with most ADAS. Conclusions: Many drivers with AMD utilize common ADAS, which subjectively improve their road safety and may help to reduce self-imposed restrictions for difficult situations and mileage. Translational Relevance: Drivers with AMD are adopting readily available ADAS, for which they reported potential benefits, such as safety and less restrictive driving.

Clinical Report: Experiences of a Driver with Vision Impairment when Using a Tesla Car.

SIGNIFICANCE: Assisted and autonomous driving technologies may be a new paradigm shift for the driving rehabilitation field to enable less restricted driving, increase driving confidence, and maintain driving safety for drivers with vision impairment. PURPOSE: This study aimed to document how a driver with vision impairment uses assistance and automation systems in a Tesla car based on real-world experiences of using these technologies. METHODS: A 53-year-old man with Stargardt disease and 20/182 visual acuity self-explored the use of driver assistance technologies, which resulted in purchasing a Tesla Model Y with the full self-driving package in 2020. Two semistructured interviews were administered to quantify the driver's driving habits, adaptive strategies, use of the assisted and semiautonomous driving features in the Tesla car, and use of his bioptic telescope. RESULTS: When driving a Tesla car, the patient developed new driving strategies by codriving with different assisted and semiautonomous functions (e.g., Traffic-Aware Cruise Control, Traffic Light and Stop Sign Control, Autopilot) in different road environments. He shifted his main task from active driving to supervising the car automation systems in most driving situations. He also integrated a new use of his bioptic telescope to support him with monitoring the road environment before granting permission to the automated systems for car maneuver changes. The patient reported that driving confidence greatly increased and that he is able to drive more often and in situations that he would otherwise avoid because of difficulties related to his vision. CONCLUSIONS: This clinical report demonstrates how assisted and semiautonomous driving systems in a Tesla car were used to support daily driving by a driver with vision impairment. Codriving with these systems allows him to confidently drive more often and to avoid less situations than he used to.

Effects of Perceptual-motor Training on Collision Judgments with Peripheral Prism Expanded Vision.

SIGNIFICANCE: Peripheral prisms (p-prisms) improve blind-side detection of hazards in hemianopia by shifting the image of the hazard into the intact visual field. Collision judgments can be made accurately after detection by using a gaze shift to fixate the hazard in the prism-free portion of the lens, but this is slow relative to normal peripheral vision. A prior study found that prism adaptation for visual direction did not occur with general wear. We developed a perceptual-motor training regimen that resulted in accurate pointing at p-prism targets after six 1-hour sessions. PURPOSE: This study aimed to determine if improvements in pointing accuracy from perceptual-motor training generalized to collision judgments during simulated walking. METHODS: Participants with hemianopia (n = 13) made collision judgments in virtual reality for a person appearing 0.4 to 13.5° from the walking path. Judgments were measured under fixed gaze, requiring collision judgments via the p-prism image only, and free gaze, representing a more natural scenario. Measurements were made without and with p-prisms immediately after fitting, after a 2-week acclimation, after training, and 3 months later. Controls (n = 13) did one visit without p-prisms. RESULTS: Controls had 100% detection and symmetrically distributed collision judgments for the central 33 and 36% of hazards under fixed gaze and free gaze, respectively. In hemianopia, the seeing side was not different from controls. Blind-side detection was reduced without p-prisms to 40% fixed gaze and 82% free gaze and improved with p-prisms to 99% fixed gaze and 97% free gaze (P < .001). When first worn, fixed-gaze prism side collisions were 63 versus 37% on the seeing side and 41 versus 39% for free gaze (P < .001). There was a small improvement for fixed gaze after the 2-week acclimation (53%, P < .001), but no improvements from training or an additional 3 months of use. CONCLUSIONS: P-prisms improved detection, but collision judgments were inaccurate when seen only via the p-prisms and did not improve with perceptual-motor training. Patients should continue to be advised to turn their head and eyes to fixate the hazard after detection.

Auditory Reminder Cues to Promote Proactive Scanning on Approach to Intersections in Drivers With Homonymous Hemianopia: Driving With Hemianopia, IX.

IMPORTANCE: Individuals with homonymous hemianopia (HH) are permitted to drive in some jurisdictions. They could compensate for their hemifield vision loss by scanning toward the blind side. However, some drivers with HH do not scan adequately well to the blind side when approaching an intersection, resulting in delayed responses to hazards. OBJECTIVE: To evaluate whether auditory reminder cues promoted proactive scanning on approach to intersections. DESIGN, SETTING, AND PARTICIPANTS: This cross-sectional, single-visit driving simulator study was conducted from October 2018 to May 2019 at a vision rehabilitation research laboratory. A volunteer sample of individuals with HH without visual neglect are included in this analysis. This post hoc analysis was completed in July and August 2020. MAIN OUTCOMES AND MEASURES: Participants completed drives with and without scanning reminder cues (a single tone from a speaker on the blind side). Scanning was quantified by the percentage of intersections at which an early large scan was made (a scan with a head movement of at least 20° made before 30 m from the intersection). Responses to motorcycle hazards at intersections were quantified by the time to the first fixation and the time to the horn-press response. RESULTS: Sixteen individuals were recruited and completed the study. Two were subsequently excluded from analyses. Thus, data from 14 participants (median [IQR] age, 54 [36-66] years; 13 men [93%]) were included. Stroke was the primary cause of the HH (10 participants [71%]). Six (43%) had right-sided HH. Participants were more likely to make an early large scan to the blind side in drives with vs without cues (65% vs 45%; difference, 20% [95% CI, 5%-37%]; P < .001). When participants made an early large scan to the blind side, they were faster to make their first fixation on blind-side motorcycles (mean [SD], 1.77 [1.34] vs 3.88 [1.17] seconds; difference, -2.11 [95% CI, -2.46 to -1.75] seconds; P < .001) and faster to press the horn (mean [SD], 2.54 [1.19] vs 4.54 [1.37] seconds; difference, -2.00 [95% CI, -2.38 to -1.62] seconds; P < .001) than when they did not make an early scan. CONCLUSIONS AND RELEVANCE: This post hoc analysis suggests that auditory reminder cues may promote proactive scanning, which may be associated with faster responses to hazards. This hypothesis should be considered in future prospective studies.

Driving with hemianopia VIII: Effects of a vibro-tactile assistance system on safety and gaze behavior in pedestrian crossing situations.

People with homonymous visual field defects (HVFDs), the loss of vision in the same half of the visual field in both eyes, are permitted to drive in some jurisdictions. However, the HVFD may cause difficulties in detecting hazards approaching on the side of the field loss (the blind side). An advanced driver assistance system (ADAS) could assist with hazard detection, but little research has been conducted to evaluate the potential benefits of an ADAS for visually impaired drivers. We developed a prototype vibro-tactile assistance system for drivers with HVFDs and conducted a proof-of-concept driving simulation study to evaluate the system. Given that pedestrian accidents are the second most frequent cause of death in road traffic and most of those accidents occur in urban scenarios, we evaluated the potential of the assistance system to improve responses to pedestrian hazards in a city environment. Sixteen participants, of which eight had HVFDs and eight had normal vision, took part. Our analyses evaluated the effects of the driver assistance system, crossing direction and pedestrian behavior on the safety of pedestrian events and the participant's gaze behavior at each of the 256 crossing situations. Generalized linear mixed effects models were used to assess binomial outcome variables. Despite the limited sample size, the results suggest that the vibro-tactile directional warnings were effective in directing the drivers' gaze so that they were looking in the necessary direction before a potential hazard occurred. More time was spent fixating pedestrians on the blind side when the ADAS was engaged and as a result, the safety of street crossings from the blind side improved. The effect of the ADAS was greater on responses to pedestrians from the blind than the seeing side. With an activated ADAS, crossings from the participants' blind sides were as safe as from their seeing sides, and as safe as the crossings when normally-sighted participants were driving. The results suggest that the vibro-tactile ADAS is a promising approach to improve the safety of drivers with HVFD and surrounding traffic.

Home-Use Evaluation of a Wearable Collision Warning Device for Individuals With Severe Vision Impairments: A Randomized Clinical Trial.

IMPORTANCE: There is scant rigorous evidence about the real-world mobility benefit of electronic mobility aids. OBJECTIVE: To evaluate the effect of a collision warning device on the number of contacts experienced by blind and visually impaired people in their daily mobility. DESIGN, SETTING, AND PARTICIPANTS: In this double-masked randomized clinical trial, participants used a collision warning device during their daily mobility over a period of 4 weeks. A volunteer sample of 31 independently mobile individuals with severe visual impairments, including total blindness and peripheral visual field restrictions, who used a long cane or guide dog as their habitual mobility aid completed the study. The study was conducted from January 2018 to December 2019. INTERVENTIONS: The device automatically detected collision hazards using a chest-mounted video camera. It randomly switched between 2 modes: active mode (intervention condition), where it provided alerts for detected collision threats via 2 vibrotactile wristbands, and silent mode (control condition), where the device still detected collisions but did not provide any warnings to the user. Scene videos along with the collision warning information were recorded by the device. Potential collisions detected by the device were reviewed and scored, including contacts with the hazards, by 2 independent reviewers. Participants and reviewers were masked to the device operation mode. MAIN OUTCOMES AND MEASURES: Rate of contacts per 100 hazards per hour, compared between the 2 device modes within each participant. Modified intention-to-treat analysis was used. RESULTS: Of the 31 included participants, 18 (58%) were male, and the median (range) age was 61 (25-73) years. A total of 19 participants (61%) had a visual acuity (VA) of light perception or worse, and 28 (90%) reported a long cane as their habitual mobility aid. The median (interquartile range) number of contacts was lower in the active mode compared with silent mode (9.3 [6.6-14.9] vs 13.8 [6.9-24.3]; difference, 4.5; 95% CI, 1.5-10.7; P < .001). Controlling for demographic characteristics, presence of VA better than light perception, and fall history, the rate of contacts significantly reduced in the active mode compared with the silent mode (ß = 0.63; 95% CI, 0.54-0.73; P < .001). CONCLUSIONS AND RELEVANCE: In this study involving 31 visually impaired participants, the collision warnings were associated with a reduced rate of contacts with obstacles in daily mobility, indicating the potential of the device to augment habitual mobility aids. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT03057496.

Driving With Hemianopia VII: Predicting Hazard Detection With Gaze and Head Scan Magnitude.

Purpose: One rehabilitation strategy taught to individuals with hemianopic field loss (HFL) is to make a large blind side scan to quickly identify hazards. However, it is not clear what the minimum threshold is for how large the scan should be. Using driving simulation, we evaluated thresholds (criteria) for gaze and head scan magnitudes that best predict detection safety. Methods: Seventeen participants with complete HFL and 15 with normal vision (NV) drove through 4 routes in a virtual city while their eyes and head were tracked. Participants pressed the horn as soon as they detected a motorcycle (10 per drive) that appeared 54 degrees eccentricity on cross-streets and approached toward the driver. Results: Those with HFL detected fewer motorcycles than those with NV and had worse detection on the blind side than the seeing side. On the blind side, both safe detections and early detections (detections before the hazard entered the intersection) could be predicted with both gaze (safe 18.5 degrees and early 33.8 degrees) and head (safe 19.3 degrees and early 27 degrees) scans. However, on the seeing side, only early detections could be classified with gaze (25.3 degrees) and head (9.0 degrees). Conclusions: Both head and gaze scan magnitude were significant predictors of detection on the blind side, but less predictive on the seeing side, which was likely driven by the ability to use peripheral vision. Interestingly, head scans were as predictive as gaze scans. Translational Relevance: The minimum scan magnitude could be a useful criterion for scanning training or for developing assistive technologies to improve scanning.

Automatic processing of gaze movements to quantify gaze scanning behaviors in a driving simulator.

Eye and head movements are used to scan the environment when driving. In particular, when approaching an intersection, large gaze scans to the left and right, comprising head and multiple eye movements, are made. We detail an algorithm called the gaze scan algorithm that automatically quantifies the magnitude, duration, and composition of such large lateral gaze scans. The algorithm works by first detecting lateral saccades, then merging these lateral saccades into gaze scans, with the start and end points of each gaze scan marked in time and eccentricity. We evaluated the algorithm by comparing gaze scans generated by the algorithm to manually marked "consensus ground truth" gaze scans taken from gaze data collected in a high-fidelity driving simulator. We found that the gaze scan algorithm successfully marked 96% of gaze scans and produced magnitudes and durations close to ground truth. Furthermore, the differences between the algorithm and ground truth were similar to the differences found between expert coders. Therefore, the algorithm may be used in lieu of manual marking of gaze data, significantly accelerating the time-consuming marking of gaze movement data in driving simulator studies. The algorithm also complements existing eye tracking and mobility research by quantifying the number, direction, magnitude, and timing of gaze scans and can be used to better understand how individuals scan their environment.

The effects of age on the contributions of head and eye movements to scanning behavior at intersections.

The current study was aimed at evaluating the effects of age on the contributions of head and eye movements to scanning behavior at intersections. When approaching intersections, a wide area has to be scanned requiring large lateral head rotations as well as eye movements. Prior research suggests older drivers scan less extensively. However, due to the wide-ranging differences in methodologies and measures used in prior research, the extent to which age-related changes in eye or head movements contribute to these deficits is unclear. Eleven older (mean 67 years) and 18 younger (mean 27 years) current drivers drove in a simulator while their head and eye movements were tracked. Scans, analyzed for 15 four-way intersections in city drives, were split into two categories: eye-only (consisting only of eye movements) and head+eye (containing both head and eye movements). Older drivers made smaller head+eye scans than younger drivers (46.6° vs. 53°), as well as smaller eye-only scans (9.2° vs. 10.1°), resulting in overall smaller all- gaze scans. For head+eye scans, older drivers had both a smaller head and a smaller eye movement component. Older drivers made more eye-only scans than younger drivers (7 vs. 6) but fewer head+eye scans (2.1 vs. 2.7). This resulted in no age effects when considering all-gaze scans. Our results clarify the contributions of eye and head movements to age-related deficits in scanning at intersections, highlight the importance of analyzing both eye and head movements, and suggest the need for older driver training programs that emphasize the importance of making large scans before entering intersections.

Data Acquisition, Processing, and Reduction for Home-Use Trial of a Wearable Video Camera-Based Mobility Aid.

Purpose: Evaluating mobility aids in naturalistic conditions across many days is challenging owing to the sheer amount of data and hard-to-control environments. For a wearable video camera-based collision warning device, we present the methodology for acquisition, reduction, review, and coding of video data for quantitative analyses of mobility outcomes in blind and visually impaired participants. Methods: Scene videos along with collision detection information were obtained from a chest-mounted collision warning device during daily use of the device. The recorded data were analyzed after use. Collision risk events flagged by the device were manually reviewed and coded using a detailed annotation protocol by two independent masked reviewers. Data reduction was achieved by predicting agreements between reviewers based on a machine learning algorithm. Thus, only those events for which disagreements were predicted would be reviewed by the second reviewer. Finally, the ultimate disagreements were resolved via consensus, and mobility-related outcome measures such as percentage of body contacts were obtained. Results: There were 38 hours of device use from 10 participants that were reviewed by both reviewers, with an agreement level of 0.66 for body contacts. The machine learning algorithm trained on 2714 events correctly predicted 90.5% of disagreements. For another 1943 events, the trained model successfully predicted 82% of disagreements, resulting in 81% data reduction. Conclusions: The feasibility of mobility aid evaluation based on a large volume of naturalistic data is demonstrated. Machine learning-based disagreement prediction can lead to data reduction. Translational Relevance: These methods provide a template for determining the real-world benefit of a mobility aid.

Bioptic Telescope Use in Naturalistic Driving by People with Visual Impairment.

Purpose: The purpose of this study was to investigate the telescope use behaviors in natural daily driving of people with reduced visual acuity licensed to drive with a bioptic (a small spectacle-mounted telescope). Methods: A large dataset (477 hours) of naturalistic driving was collected from 19 bioptic drivers (visual acuity 20/60 to 20/160 without the telescope). To reduce the data volume, a multiloss 50-layer deep residual neural network (ResNet-50) was used to detect potential bioptic telescope use events. Then, a total of 120 hours of selected video clips were reviewed and annotated in detail. Results: The frequency of looking through their telescopes ranged from 4 to 308 times per hour (median: 27, interquartile range [IQR], 19-75), with each bioptic use lasting median 1.4 seconds (IQR, 1.2-1.8). Thus, participants spent only 1.6% (IQR, 0.7%-3.5%) driving time with their telescopes aiding their vision. Bioptic telescopes were used most often for checking the road ahead (84.8%), followed by looking at traffic lights (5.3%), and reading road signs (4.6%). Conclusions: In daily driving, the bioptic drivers mostly (>98% of driving time) drove under low visual acuity conditions. The bioptic telescope was mainly used for observing road and traffic conditions in the distance for situational awareness. Only a small portion of usage was for road sign reading. Translational Relevance: This study provides new insights into how the vision rehabilitation device-bioptic telescopes are used in daily driving. The findings may be helpful for designing bioptic driving training programs.

Hazard Detection With Monocular Bioptic Telescopes in a Driving Simulator.

Purpose: In most states, people with reduced visual acuity may legally drive with the aid of a bioptic telescope. However, concerns have been raised that the ring scotoma may impair detection of peripheral hazards. Using a driving simulator, we tested the hypothesis that the fellow eye would be able to compensate for the ring scotoma when using a monocular telescope. Methods: Sixteen bioptic users completed three drives with binocular viewing interleaved between three drives with monocular viewing. Forty pedestrians appeared and ran on the road for 1 second, including 26 within the ring scotoma, while participants were reading road signs through their own monocular telescopes. Head movements were analyzed to determine whether the pedestrian appeared before or only while using the telescope. Results: For pedestrians that appeared only during bioptic use and were likely in the area of the ring scotoma, detection rates were significantly higher in binocular (fellow eye can compensate) than monocular (fellow eye patched) viewing (69% vs. 32%; P < 0.001); this was true for both current and noncurrent drivers. For pedestrians appearing before or after bioptic use, detection rates did not differ in binocular and monocular viewing. However, detection rates were even higher and reaction times shorter when the telescope was not being used. Conclusions: Both current and noncurrent drivers'  fellow eyes were able to compensate, at least in part, for the ring scotoma. Translational Relevance: When using monocular telescopes, the fellow eye reduces the impact of the ring scotoma on hazard detection in binocular viewing.

The Effects of Age, Distraction, and Simulated Central Vision Impairment on Hazard Detection in a Driving Simulator.

SIGNIFICANCE: Despite similar levels of visual acuity and contrast sensitivity reductions, simulated central vision impairment increased response times to a much greater extent in older than in younger participants. PURPOSE: Driving is crucial for maintaining independence in older age, but age-related vision impairments and in-vehicle auditory distractions may impair driving safety. We investigated the effects of age, simulated central vision impairment, and auditory distraction on detection of pedestrian hazards. METHODS: Thirty-two normally sighted participants (16 younger and 16 older) completed four highway drives in a simulator and pressed the horn whenever they saw a pedestrian. Pedestrians ran toward the road on a collision course with the approaching vehicle. Simulated central vision impairment was achieved by attaching diffusing filters to a pair of laboratory goggles, which reduced visual acuity to 20/80 and contrast sensitivity by 0.35 log units. For drives with distraction, subjects listened to an audiobook and repeated out loud target words. RESULTS: Simulated central vision impairment had a greater effect on reaction times (660-millisecond increase) than age (350-millisecond increase) and distraction (160-millisecond increase) and had a greater effect on older than younger subjects (828- and 492-millisecond increase, respectively). Simulated central vision impairment decreased safe response rates from 94.7 to 78.3%. Distraction did not, however, affect safety because older subjects drove more slowly when distracted (but did not drive more slowly with vision impairment), suggesting that they might have perceived greater threat from the auditory distraction than the vision impairment. CONCLUSIONS: Older participants drove more slowly in response to auditory distraction. However, neither older nor younger participants adapted their speed in response to simulated vision impairment, resulting in unsafe detections. These results underline the importance of evaluating safety of responses to hazards as well as reaction times in a paradigm that flexibly allows participants to modify their driving behaviors.

Towards Wide Range Tracking of Head Scanning Movement in Driving.

Gaining environmental awareness through lateral head scanning (yaw rotations) is important for driving safety, especially when approaching intersections. Therefore, head scanning movements could be an important behavioral metric for driving safety research and driving risk mitigation systems. Tracking head scanning movements with a single in-car camera is preferred hardware-wise, but it is very challenging to track the head over almost a 180° range. In this paper we investigate two state-of-the-art methods, a multi-loss deep residual learning method with 50 layers (multi-loss ResNet-50) and an ORB feature-based simultaneous localization and mapping method (ORB-SLAM). While deep learning methods have been extensively studied for head pose detection, this is the first study in which SLAM has been employed to innovatively track head scanning over a very wide range. Our laboratory experimental results showed that ORB-SLAM was more accurate than multi-loss ResNet-50, which often failed when many facial features were not in the view. On the contrary, ORB-SLAM was able to continue tracking as it doesn't rely on particular facial features. Testing with real driving videos demonstrated the feasibility of using ORB-SLAM for tracking large lateral head scans in naturalistic video data.