Decisions regarding driving fitness are currently based solely on ophthalmic vision function parameters, such as the extent of visual field, visual acuity, contrast sensitivity, and color vision. Therefore, patients with binocular visual field defects (VFDs), that is, VFDs affecting corresponding areas of the visual field in both eyes, are considered unsafe to drive and are prohibited from driving in many European countries and more than half of the states in the United States.1–3 However, in a few countries, such as the Netherlands, Belgium, the United Kingdom, and Canada, and in some states in the United States, patients with binocular field loss can be granted a driving license after passing an on-road test.
Glaucoma is the second leading cause of vision loss with nearly 66.8 million people affected worldwide, and this number is expected to rise in industrialized countries because of demographic aging.4,5 Glaucoma represents a progressive optic neuropathy leading to visual field loss and blindness if left untreated. It is associated with a variety of VFDs ranging from nasal steps, temporal wedge defects, arcuate defects, paracentral defects, to more severe generalized constriction (tunnel vision) or even total vision loss. The defects may be present in one or both eyes and they may affect the peripheral, midperipheral, or paracentral visual field. If they affect corresponding areas of the visual field in both eyes, they result in binocular visual field loss, which may pose significant limitations on personal mobility and quality of life.6,7
Driving fitness is an important aspect of everyday life, which allows personal independence especially to older people. In Europe, binocular visual field requirements typically follow the European Union standard of greater than or equal to 120 degrees on the horizontal meridian measured by the Goldmann perimeter on the III4e setting (or equivalent perimetry). In addition, there should be no significant field defect in the binocular field within 20 degrees from fixation either above or below the horizontal meridian. Hence, binocular glaucomatous visual field loss within 20 degrees from fixation has been considered unacceptable for safe driving. In support of this recommendation, a large body of literature based on self-reported accidents or police charts has suggested that glaucoma is associated with an increased risk of motor vehicle collisions.8–13 However, these results are inconsistent and some authors did not even find evidence that glaucoma increases the risk of injurious collisions14 owing to self-regulation (e.g., not driving by night or on rainy days).15,16 Findings from simulator experiments are also equivocal, with some studies showing adequate driving performance for patients with mild to moderate glaucoma,17 and others reporting a higher incidence of real-world and simulator accidents for glaucoma patients.11 Furthermore, patients with glaucoma display a wide variation in their driving performance, which may be attributed to differences in study design, patient inclusion criteria, and the ability to compensate. Although compensational ability appears to be a major factor influencing driving fitness, only a few studies have assessed compensatory gaze strategies in patients with glaucoma. Crabb et al.18 reported that patients with bilateral glaucomatous field loss made more eye movements than control participants when viewing a hazardous driving scene. Similarly, in our previous on-road study, patients with binocular visual field loss (homonymous VFD and glaucoma) who passed a driving test performed more gaze movements toward the area of the VFD and more head and shoulder movements.19
The aim of this study was to compare patients with glaucoma and control subjects regarding their fitness to drive and gaze-scanning behavior (eye and head movements) in one of the most advanced driving simulators worldwide. The fitness to drive was assessed according to the requirements of the official German driving test. We also analyzed several components of driving performance, such as lane keeping, steering stability, and speed.
Six patients with glaucoma (detailed demographic data and visual fields can be found in the Appendix, available at http://links.lww.com/OPX/A222) and eight age- and sex-matched healthy subjects participated in this study. All participants were at least 18 years old, had best-corrected monocular (near and distant) visual acuity of at least 20/25, and had normal function and morphology of the anterior segment and visual pathways. Time since diagnosis of glaucoma was 15.0 (±5.8) years. Monocular visual field results can be combined to obtain a binocular visual field.20,21 However, in this study, visual fields were assessed by means of binocular semiautomated 90-degree kinetic perimetry (SKP, OCTOPUS 101 Perimeter, Fa. HAAG-STREIT, Koeniz, Switzerland), to provide a more realistic representation of the patients’ visual field, in agreement with driving test requirements in Germany. The stimulus III/4e was used because this is the functionally relevant target that is typically used to define legal blindness and also the visual field extent in driving license forms in Germany.
Glaucoma patients had a confirmed diagnosis based on optic nerve damage and visual field loss. Only glaucoma patients with defects in the binocular visual field were included, that is, defects (1) in the upper visual field of both eyes (n = 3), (2) in the lower visual field of both eyes (n = 1), and (3) in both the upper and lower visual fields of both eyes (n = 2). Patients with significant cognitive decline or physical impairment, which could affect standard vehicle use, were excluded. Although all patients had owned a driving license for years, none of them met the legal criteria for driving because of their visual impairment.
Patients were recruited from the Department of Neuro-Ophthalmology at the University of Tübingen (Germany). The research study was approved by the Institutional Review Board of the University of Tübingen (Germany) and was performed according to the Declaration of Helsinki. After verbal and written explanation of the experimental protocol, all subjects gave their written consent, with the option of withdrawing from the study at any time (Clinical Trial Registration [http://www.clinicaltrials.gov] Identifier: NCT01372319).
The study was performed in the moving-base driving simulator22 at the Mercedes-Benz Technology Center in Sindelfingen, Germany (Fig. 1A). Acceleration forces, a 360-degree projection, and the real car body contributed to a close-to-realistic driving experience. The virtual driving task included nine hazardous situations that occurred at predefined positions during a route of 37.5 km length. The average (±SD) driving time for the whole course was 39 (±3) minutes. Two subjects had to skip a part of the ride because of motion sickness (Fig. 2). Speed limits varied between 100 and 50 km/h in rural highways and urban areas, respectively.
The driving task consisted of two parts. The first part of the drive simulated a realistic scenario of 30.7 km including four hazardous situations, for example, pedestrians suddenly appearing behind parked cars or risky overtaking maneuvers of oncoming traffic. This part of the drive began with an introductory simple straight road without oncoming traffic and gradually became more complex as it turned into an urban scenario, with denser traffic and more frequent traffic signs. The second part of the drive (6.8 km distance) was more demanding and involved five hazardous situations. A detailed description of the nine hazardous situations and their location during the drive is presented in Table 1.
Fig. 1B shows an example of a hazardous situation. Crashes were not simulated, even if the driver did not show a proper reaction, to avoid additional emotional stress; for example, pedestrians leaped backward or oncoming overtakers returned back to their lane.
The time to collision was equalized for objects approaching from either side of the road by hiding them behind parking vehicles, containers, and advertising pillars. Thus, we aimed at eliminating any side bias related to the lane of oncoming traffic, which would always give free sight on hazardous objects from the left.
Eye and Head Tracking
Eye movements were recorded at 25 Hz using a mobile, head-mounted Dikablis eye-tracking system by Ergoneers GmbH, Manching, Germany. It was worn over the participants’ habitual glasses. Head position and orientation were registered by means of a laserBIRD head tracker (Ascension Technology Corporation, Burlington, VT). The sensor was attached to a headband and the receiver was mounted over the passenger seat.
After the experiment, a certified driving instructor, who was masked to the participants’ medical status, evaluated the hazardous scene videos and rated the driving performance as passed or failed according to the requirements of the official German driving test.23 If a subject failed one hazardous situation, the whole driving test was considered as failed. If a subject responded properly to all hazards, driving performance was rated as passed. Because of missing data related to eye and head movement recordings or early experiment abortion owing to motion sickness, 113 (of theoretically 126 possible) hazardous situations were finally analyzed. The exact number of hazardous situations for each participant is shown in Fig. 2. As depicted in Fig. 2, two glaucoma patients aborted the drive after the first four hazardous situations. However, by then, they had already completed the longest part of the drive of about 30 (out of 37) km length. Thus, even for these subjects, head and eye movements as well as driving behavior were analyzed.
Eye-tracking calibration was accurate for about 20 minutes. Afterward, two-thirds of the recordings required offline calibration adjustment because of displacement of the eye tracker. A Bayesian online clustering algorithm24,25 was used to identify fixations and saccades. The parameters of the model were adapted to the individual viewing behavior during the introductory part of the course.
Because prior research with patients with VFDs reported problems with lane keeping,26,27 we analyzed the average lane position during the drive. Furthermore, according to the AIDE project,28 the time to line crossing (TLC) of second order29 was calculated. Time to line crossing represents the time remaining until either lane boundary is crossed by any of the wheels, when speed and steering wheel angle are not changed. This metric reflects the driver’s ability to keep the lane. In addition, heart rate and galvanic skin conductance were measured; the analysis of these parameters has been published separately.30
Eye movement and driving performance measures were analyzed for the whole drive, including—but not limited to—the nine hazardous situations. A statistical analysis was not performed because of the small number of subjects. Instead, results of descriptive statistics are presented in tables and graphs.
Fitness to Drive
Three out of six glaucoma patients passed the driving assessment. All control subjects (GC) passed the driving task. Fig. 2 presents the outcome of each hazardous situation for all participants. Cases associated with a failure of the driving test are marked in black.
Analysis of head movements during the whole drive showed that glaucoma patients who passed the driving test performed more extensive head movements (3.9 ± 2.9 degrees/s) than the age- and sex-matched control group (2.5 ± 0.4 degrees/s) (Fig. 3). On the other hand, patients who failed the driving test showed no increase in the amplitude of head movements compared with the control group (1.2 ± 1.9 degrees/s).
Patients who failed the driving test showed an eye position bias to the right side of the road (Fig. 4). Furthermore, the eye position distribution differed between patients who passed and those who failed the driving test. Patients who passed the test (Gp) showed a larger average distance between the straight-ahead position and current gaze direction (63 ± 58 pixels) than patients who failed (Gf) (45 ± 43 pixels). This finding indicates increased peripheral exploration activity by means of eye movements. Comparison of saccadic amplitudes between patients and control subjects revealed a tendency for longer saccades in patients who passed the driving test (63 ± 65 vs. 48 ± 52 pixels). Hence, patients who passed the driving test perform longer saccades, whereas patients who failed the test perform shorter saccades when compared with the control group (see also Fig. 5).
Fig. 5 presents various eye-tracking measures. Although the limited number of subjects does not allow a robust statistical analysis, several tendencies are found regarding the eye-tracking parameters. Glaucoma patients who passed the test had shorter fixation durations and increased number of fixations per minute when compared with glaucoma patients who failed the test. Such behavior indicates an increased scanning activity in glaucoma patients who passed. Furthermore, glaucoma patients who failed showed a lower ratio of horizontal to vertical fixations, indicating that their scanning behavior was primarily horizontal, whereas patients who passed performed more vertical scanning. In addition, a change in saccadic angle (saccadic orientation to x-axis) indicates a gaze shift because of compensation for the VFD.
Driving Performance Measures
Fig. 6 shows the average lateral lane position. The average lane position of control subjects was considered the optimal one, and in some cases, it deviated from the middle of the lane (curves and evasive driving). Glaucoma drivers did not show a different lane position when compared with the control group.
Time to Line Crossing
Fig. 7 shows the TLC for all participants. Regarding this parameter, which indicates steering stability, there were no differences between the patient group and the control group. Further steering steadiness measures such as lane position variance and steering reversals did not reveal clear trends either and are thus not depicted in the above figure.
The average speed is depicted in Fig. 8 and reveals that most patients do not have difficulties with identifying and keeping speed limits. However, glaucoma patients who passed the driving test drove slower (55 ± 25 km/h; control subjects, 59 ± 27 km/h) than patients who failed the driving test (63 ± 24 km/h), possibly indicating an attempt to increase safety.
Previous on-road and simulator studies7,17,29,30 on the driving ability of subjects with binocular visual field loss either reported the percentage of patients who were fit to drive without recording their eye and head movements or evaluated various aspects of driving behavior (i.e., hazard detection, lane keeping, steering, and head scanning), but without linking them to a driving test outcome measure. This means that patients with glaucoma were usually averaged as one group compared with normal subjects, although there is evidence for differences regarding gaze strategies and several driving components between patients who are fit to drive and patients with unsafe driving behavior. Hence, we tried to identify gaze scanning patterns and driving performance measures associated with successful completion of a simulated driving test.
Fitness to Drive
In the present simulator test, three out of six participants with glaucoma demonstrated a safe driving performance, despite the presence of VFDs within the central 30-degree visual field and the fact that they did not meet the legal requirements for driving. This study included only participants with binocular glaucomatous visual field loss, which would disqualify them from obtaining a driver’s license in many jurisdictions; therefore, our inclusion criteria might be less favorable than in other studies and our sample is not representative of the general glaucoma population. The reason was that we hypothesized that any potential gaze strategies would be more evident in the group with binocular glaucomatous visual field loss. We, thus, aimed to investigate whether patients with binocular VFDs are at increased risk for motor vehicle collisions, as suggested in previous studies based on self-reports and police charts.10,31
The first driving simulator study by Szlyk et al.17 in 2002 with glaucoma patients suggested that there were no significant differences for self-reported and simulator accidents between patients with mild to moderate glaucoma and a normal control group. Our results appear to be at odds with those findings, possibly because in the Szlyk et al. study, many patients had normal or near-normal visual fields in their better-seeing eye. The present results appear to be more consistent with a later study by the same authors, where they found a higher incidence of real-world and simulator accidents for a group with more advanced glaucoma.11 Our findings also appear consistent with a study by Coeckelbergh et al.,32 where 43% of patients with peripheral VFDs passed an on-road test (retinitis pigmentosa and glaucoma; binocular horizontal visual field extent, 84 [±35] degrees). Similar pass rates for patients with binocular glaucomatous visual field loss (40%) were obtained in our recent on-road test, which was also scored according to the German driving license regulations and included patients with similar advanced bilateral glaucomatous VFDs.19 Haymes et al. also found that 60% of glaucoma patients compared with 20% of control subjects had one or more at-fault critical interventions by the driving instructor.33
Gaze Patterns (Head Movements)
A few studies have assessed eye and head compensatory strategies in patients with glaucoma.19,32 We found that glaucoma patients who were safe to drive showed increased exploration activity in terms of more eccentric head movements, compared with glaucoma subjects who failed the test. Thus, the present simulator study replicated the findings of our recent on-road study and the study of Coeckelbergh et al.32 by means of sophisticated eye and head tracking and suggests that active scanning by means of head movements is an efficient way to compensate for a glaucomatous VFD affecting the binocular visual field.19
Gaze Patterns (Eye Movements)
Unsafe glaucoma drivers displayed a tendency for shorter saccadic amplitudes, a gaze bias to the right, and a more straight-ahead eye position. Increased gaze concentration toward the road center with increasing cognitive load, a phenomenon commonly coined as “tunnel vision” or ”cognitive tunneling,” was reported by Engström et al.34 in a driving simulator study and may suggest defective compensational mechanisms in patients who failed the test.
These findings are at odds with a recent simulator study, which showed that patients with mild to severe glaucoma displayed similar eye scanning behavior with the control group.35 However, the horizontal field of view in the above study was considerably smaller than that in the present study, only 9 of 23 participants had binocular field loss, the driving session lasted considerably shorter, there was no other traffic apart from static obstacles, and the detection task included targets that are not part of a driving scene, namely, verbalization of letters. Our results regarding longer saccadic amplitudes and more lateral eye position in safe drivers are more consistent with recent studies using video-based hazard perception tasks.18 The authors also reported that patients with binocular glaucomatous VFDs performed more eye movements than control participants.18 An increase in saccade rate in patients with glaucoma was also associated with better performance in a search task when viewing images of everyday scenes.36 A recent study investigating the viewing behavior of patients with binocular glaucomatous VFDs during a supermarket shopping task in a real setting reported that an increase in saccade rates strongly correlated with the ability to quickly find the objects of interest, probably an attempt to compensate for their restricted field of view.37
Additionally, patients who failed the test showed a tendency for longer fixation duration and less fixations per minute compared with patients who passed the test. The smaller number of fixations indicates decreased eye scanning activity, and longer fixation duration appears to be associated with an inability to acquire visual information in a quick and effective manner, as observed in patients who passed the test. Because new information is acquired during fixations, the finding that patients who failed made fewer saccades suggests that they were unable to process as much of the visual scene as patients who passed the test. In a recent study,36 patients with glaucoma had longer average fixation duration compared with control subjects when viewing everyday scenes. However, the latter study did not correlate gaze parameters with performance and the nature of the task was substantially different from the present one, as cognitive demands were minimal in that participants were presented with static, consistent information and were tasked to simply “enjoy” the images.36 Conversely, our results are more consistent within another study regarding eye movement behavior when viewing a dynamic driving scene. In the latter study, glaucoma patients produced more and, thus, shorter fixations than the control subjects when searching for hazards in the Hazard Perception Test.38 Hence, viewing behavior appears to be related not only to compensatory potential but also to the task complexity and quantity of visual information.
Interestingly, unsafe glaucoma drivers in our study showed a gaze bias to the right. This was probably an attempt to maintain a stable lane position, because no differences in lane position were found between safe and unsafe drivers. This is in line with Vega et al., who attributed this finding to the optimal control theory of manned-vehicle systems.39,40 A possible explanation is that safe glaucoma drivers paid more attention to avoiding traffic hazards (by gaze scanning), whereas unsafe glaucoma drivers attempted to maintain a stable lane position but failed to recognize traffic hazards because of limited gaze compensatory reserves.
Driving Performance Measures
Lane keeping difficulties and steering unsteadiness in glaucoma patients have been reported more often in on-road studies than in simulator studies. In accordance with previous studies,17 TLC and lane position were similar between glaucoma patients and control participants, probably because of behavioral hypervigilance in the patient group. In contrast to our findings, another simulator study reported that 89% of patients with peripheral VFDs (glaucoma and retinitis pigmentosa) made more lane boundary crossings.39 However, those authors did not include a normal control group or a separate subgroup analysis for glaucoma patients.
Speed control and adaptation to the speed limit is an important skill. Some drivers with glaucoma may try to compensate for their degraded visual ability by reducing their driving speed. We found that safe drivers drove at slower speeds and this strategy possibly provides enough time to scan their visual environment, because eye movements and especially head movements are time-consuming. However, very slow driving can be dangerous, because the vehicle may represent an obstacle for the other drivers.32 Other on-road studies reported adequate speed control in glaucoma subjects, and because of the variable results, we believe that this skill warrants further investigation in larger series of patients.19,33
Despite the total number of 14 participants in this costly study, the number of subjects in each subgroup was relatively small for statistical analysis. Additionally, although we have tried to design and score the driving test as close to real-world conditions as possible, effects arising from the use of a simulator in a virtual environment with a variable degree of fidelity cannot be avoided. We decided to do the experiment in the simulator because of the unique possibility of standardizing the traffic scenario and thereby establishing identical and thus comparable driving conditions for all participants. Finally, the severity of VFDs varied between patients from severe visual field loss to small circumscribed areas. However, a common characteristic was that they fail to meet the European driving regulations.
In conclusion, this study supports the hypothesis that a considerable subgroup of subjects with binocular visual field loss attributed to glaucoma shows a safe driving behavior in a virtual reality environment, because they adapt their viewing behavior by increasing scanning. By means of a driving simulator and sophisticated eye and head tracking, individual performance differences in terms of driving safety were related to visual exploratory behavior. This type of compensation improves traffic safety and may have practical implications in planning individualized driving fitness tests and driver rehabilitation programs.
Department of Computer Engineering
University of Tübingen
e-mail: [email protected]
Thomas C. Kübler and Enkelejda Kasneci contributed equally to this article.
The authors thank Pfizer and MSD Sharp & Dohme GmbH for supporting and enabling this study. The authors further thank Daimler AG for the use of the moving-base driving simulator, driving instructor Helmut Hanne, and clinicians Christian Heine and Kai Januschowski. The second author gratefully acknowledges financial support from the Margarete-von-Wrangell program of the MWK Baden-Württemberg.
Received September 5, 2014; accepted April 10, 2015.
The Appendix, demographic data and visual fields of glaucoma patients, is available at http://links.lww.com/OPX/A222.
1. Casson EJ, Racette L. Vision standards for driving in Canada and the United States. A review for the Canadian Ophthalmological Society. Can J Ophthalmol 2000; 35: 192–203.
2. Silveira S, Jolly N, Heard R, Clunas NJ, Kay L. Current licensing authority standards for peripheral visual field and safe on-road senior aged automobile driving performance. Clin Experiment Ophthalmol 2007; 35: 612–20.
3. International Council of Ophthalmology (ICOPH). Visual Standards: Vision Requirements for Driving Safety; 2006. Available at: www.icoph.org/pdf/visionfordriving.pdf
. Accessed April 17, 2015.
4. Quigley HA, Broman AT. The number of people with glaucoma worldwide in 2010 and 2020. Br J Ophthalmol 2006; 90: 262–7.
5. Michelson G, Groh MJ. Screening models for glaucoma. Curr Opin Ophthalmol 2001; 12: 105–11.
6. Ramulu PY, Hochberg C, Maul EA, Chan ES, Ferrucci L, Friedman DS. Glaucomatous visual field loss associated with less travel from home. Optom Vis Sci 2014; 91: 187–93.
7. Chan EW, Chiang PP, Liao J, Rees G, Wong TY, Lam JS, Aung T, Lamoureux E. Glaucoma and associated visual acuity and field loss significantly affect glaucoma-specific psychosocial functioning. Ophthalmology 2015; 122: 494–501.
8. Haymes SA, Leblanc RP, Nicolela MT, Chiasson LA, Chauhan BC. Risk of falls and motor vehicle collisions in glaucoma. Invest Ophthalmol Vis Sci 2007; 48: 1149–55.
9. Bowers A, Peli E, Elgin J, McGwin G Jr., Owsley C. On-road driving with moderate visual field loss. Optom Vis Sci 2005; 82: 657–67.
10. McGwin G Jr., Xie A, Mays A, Joiner W, DeCarlo DK, Hall TA, Owsley C. Visual field defects and the risk of motor vehicle collisions among patients with glaucoma. Invest Ophthalmol Vis Sci 2005; 46: 4437–41.
11. Szlyk JP, Mahler CL, Seiple W, Edward DP, Wilensky JT. Driving performance of glaucoma patients correlates with peripheral visual field loss. J Glaucoma 2005; 14: 145–50.
12. Johnson CA, Keltner JL. Incidence of visual field loss in 20,000 eyes and its relationship to driving performance. Arch Ophthalmol 1983; 101: 371–5.
13. Hu PS, Trumble DA, Foley DJ, Eberhard JW, Wallace RB. Crash risks of older drivers: a panel data analysis. Accid Anal Prev 1998; 30: 569–81.
14. McCloskey LW, Koepsell TD, Wolf ME, Buchner DM. Motor vehicle collision injuries and sensory impairments of older drivers. Age Ageing 1994; 23: 267–73.
15. McGwin G Jr., Mays A, Joiner W, Decarlo DK, McNeal S, Owsley C. Is glaucoma associated with motor vehicle collision involvement and driving avoidance? Invest Ophthalmol Vis Sci 2004; 45: 3934–9.
16. Yuki K, Asaoka R, Tsubota K. The relationship between central visual field damage and motor vehicle collisions in primary open-angle glaucoma patients. PLoS One 2014; 9: e115572.
17. Szlyk JP, Taglia DP, Paliga J, Edward DP, Wilensky JT. Driving performance in patients with mild to moderate glaucomatous clinical vision changes. J Rehabil Res Dev 2002; 39: 467–82.
18. Crabb DP, Smith ND, Rauscher FG, Chisholm CM, Barbur JL, Edgar DF, Garway-Heath DF. Exploring eye movements in patients with glaucoma when viewing a driving scene. PLoS One 2010; 5: e9710.
19. Kasneci E, Sippel K, Aehling K, Heister M, Rosenstiel W, Schiefer U, Papageorgiou E. Driving with binocular visual field loss? A study on a supervised on-road parcours with simultaneous eye and head tracking. PLoS One 2014; 9: e87470.
20. Crabb DP, Viswanathan AC. Integrated visual fields: a new approach to measuring the binocular field of view and visual disability. Graefes Arch Clin Exp Ophthalmol 2005; 243: 210–6.
21. Nelson-Quigg JM, Cello K, Johnson CA. Predicting binocular visual field sensitivity from monocular visual field results. Invest Ophthalmol Vis Sci 2000; 41: 2212–21.
22. Zeeb E. Daimler’s new full-scale, high-dynamic driving simulator
: a technical overview. Actes INRETS 2010: 157–65.
23. BMJV in Cooperation with Juris GmbH. Verordnung über die Zulassung von Personen zum Straßenverkehr (Fahrerlaubnis-Verordnung - FeV); 2013. Available at: http://www.gesetze-im-internet.de/bundesrecht/fev_2010/gesamt.pdf
. Accessed April 17, 2015.
24. Tafaj E, Kasneci G, Rosenstiel W, Bogdan M. Bayesian online clustering of eye movement data. In: Proceedings of the Symposium on Eye Tracking Research and Application, ETRA ’14. New York, NY: Association for Computing Machinery, Inc; 2014: 285–8. Available at: https://www.hpi.uni-potsdam.de/fileadmin/hpi/FG_Naumann/publications/p285-tafaj.pdf
. Accessed May 21, 2015.
25. Kasneci E, Kasneci G, Kübler T, Rosenstiel W. The applicability of probabilistic methods to the online recognition of fixations and saccades in dynamic scenes. In: Proceedings of the Symposium on Eye Tracking Research and Application, ETRA ’14. New York, NY: Association for Computing Machinery, Inc; 2014: 323–6. Available at: http://ti.uni-tuebingen.de/uploads/tx_timitarbeiter/p323-kasneci.pdf
. Accessed May 21, 2015.
26. Bowers AR, Mandel AJ, Goldstein RB, Peli E. Driving with hemianopia, I: detection performance in a driving simulator
. Invest Ophthalmol Vis Sci 2009; 50: 5137–47.
27. Bowers AR, Mandel AJ, Goldstein RB, Peli E. Driving with hemianopia, II: lane position and steering in a driving simulator
. Invest Ophthalmol Vis Sci 2010; 51: 6605–13.
28. Ostlund J, Peters B, Thorslund B, Engström J, Markkula G, Keinath A, Horst D, Juch S, Mattes S, Foehl U. Driving performance assessment-methods and metrics. EU Deliverable, Adaptive Integrated Driver-Vehicle Interface Project (AIDE) No. D2. 2.5; 2005. Available at: http://www.aide-eu.org/pdf/sp2_deliv_new/aide_d2_2_5.pdf
. Accessed May 21, 2015.
29. van Winsum W, Brookhuis KA, de Waard D. A comparison of different ways to approximate time-to-line crossing (TLC) during car driving. Accid Anal Prev 2000; 32: 47–56.
30. Kübler TC, Kasneci E, Rosenstiel W, Schiefer U, Papageorgiou E. Stress-indicators and exploratory gaze for the analysis of hazard perception in patients with visual field loss. Transport Res Part (F) 2014; 24: 231–43.
31. Tanabe S, Yuki K, Ozeki N, Shiba D, Abe T, Kouyama K, Tsubota K. The association between primary open-angle glaucoma and motor vehicle collisions. Invest Ophthalmol Vis Sci 2011; 52: 4177–81.
32. Coeckelbergh TR, Brouwer WH, Cornelissen FW, Van Wolffelaar P, Kooijman AC. The effect of visual field defects on driving performance: a driving simulator
study. Arch Ophthalmol 2002; 120: 1509–16.
33. Haymes SA, LeBlanc RP, Nicolela MT, Chiasson LA, Chauhan BC. Glaucoma and on-road driving performance. Invest Ophthalmol Vis Sci 2008; 49: 3035–41.
34. Engström J, Johansson E, Ostlund J. Effects of visual and cognitive load in real and simulated motorway driving. Transport Res Part (F) 2005; 8: 97–120.
35. Prado Vega R, van Leeuwen PM, Rendon Velez E, Lemij HG, de Winter JC. Obstacle avoidance, visual detection performance, and eye-scanning behavior of glaucoma patients in a driving simulator
: a preliminary study. PLoS One 2013; 8:e77294.
36. Smith ND, Crabb DP, Glen FC, Burton R, Garway-Heath DF. Eye movements in patients with glaucoma when viewing images of everyday scenes. Seeing Perceiving 2012; 25: 471–92.
37. Sippel K, Kasneci E, Aehling K, Heister M, Rosenstiel W, Schiefer U, Papageorgiou E. Binocular glaucomatous visual field loss and its impact on visual exploration—a supermarket study. PLoS One 2014; 9:e106089.
38. Smith ND, Glen FC, Crabb DP. Eye movements during visual search in patients with glaucoma. BMC Ophthalmol 2012; 12: 45.
39. Fisher DL, Rizzo M, Caird J, Lee JD, eds. Handbook of Driving Simulation for Engineering, Medicine, and Psychology. Boca Raton, FL: Taylor & Francis Group; 2011.
40. Coughlin JF, Reimer B, Mehler B. Driver Wellness, Safety & the Development of an AwareCar. Cambridge, MA: Massachusetts Institute of Technology, Center for Transportation & Logistics, AgeLab; 2009. Available at: http://fdnweb.org/santos/files/2014/11/agelab.pdf
. Accessed April 27, 2015.