Caird, J.K., Milloy, S., Ohlhauser, A., Jacobson, M., Skene, M. & Morrall, J. (2008). Evaluation of four bicycle lane treatments using driving simulation: Comprehension and driving performance results. Annual Conference of Canadian Road Safety Professionals. Whistler, British Columbia.

Evaluation of Four Bicycle Lane Treatments Using Driving Simulation: Comprehension and Driving Performance Results J.K. Caird,1 S. Milloy,1 A. Ohlhauser,1 M. Jacobson,2 M. Skene,2 & J. Morrall3 1Cognitive Ergonomics Research Laboratory, University of Calgary, Calgary 2Boulevard Transportation Group, Victoria 3Canadian Highways Institute, Calgary

Abstract An experimental evaluation of bicycle lane treatments was conducted using the University of Calgary Driving Simulator (UCDS). Specifically, white dashed, blue dashed, blue solid and sharrows (a bicycle icon with arrows) treatments were integrated into three experimental drives. Thirty participants, equally distributed in the age groups of 18 to 24, 25 to 54 and 55 to 80, volunteered for the study. Overall, the sharrows treatment had the highest (97%) level of comprehension. The blue solid (60%), blue dashed (67%) and white dashed (69%) treatments had similar, but significantly lower levels of comprehension. When specific bicycle conflicts were encountered, most drivers looked left for the cyclist while merging and did not overtake a bicyclist on the right. No age or treatment differences were found for either event. The sharrows bicycle lane treatment seems to be the most obvious choice from a driver and cyclists comprehension and preference analysis. Résumé Le simulateur d’automobile de l’Universite de Calgary (SAUC) a était utilisé pour une evaluation expérimentale des traitements pour indiquer une piste de bicyclettes sur la rue. Spécifiquement, les traitements blanc pointillé, bleu pointillé, bleu solide, et sharrows (une image de bicyclette avec flèches) ont été intégrée dans trois routes expérimentale. Trente participants avait une distribution egale entre les groupes des âges suivant : 18 a 24, 25 a 54, et 55 a 80. En general, le traitement des sharrows a etait lem mieux compris.(97%). Les traitement de bleu solide (60%), bleu pointillé (67%) et blanc pointillé (69%) ont tous reçu le niveau de comprehension similaire, mais significativement baisser on comparison avec le traitment des sharrow. Spécifiquement, quand les conflits des bicyclettes été recontrait, les conducteurs qui rentrer ont regardé a gauche pour les cyclistes, et à la droite il n’ont pas dépassé les cyclistes. Pour chaque évènement il n’y avait aucune difference pour le groupe de l’âge et traitement. Les differences de l’âge et les traitements n’ont pas été trouver pour les deux évènements. Le traitement du sharrows est le choix le plus évident pour la comprehension et la preference des conducteurs et des cylistes.

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INTRODUCTION Europe, the U.S. and Canada have begun to determine if coloured bicycle lane treatments improve awareness of bicyclists and reduce conflicts with drivers [1–2]. For instance, a blue bicycle lane treatment and a “Yield to Cyclist” sign were evaluated in Portland, Oregon [2]. Where motorists crossed a bicycle lane, significantly more yielded to bicyclists after the treatment was integrated at 10 locations. However, bicyclists did not turn their heads to scan for other traffic as frequently after the treatment and sign were installed. In another study, a high visibility green has been evaluated in the field in Burlington, Vermont [1]. Observational and survey methods found that bicyclists rode more in the bike lane, but motorists did not necessarily yield more to bicyclists at an intersection. Green treatments to bicycle lanes in New York City and St. Petersburg, Florida are undergoing evaluation by the U.S. Federal Highway Administration (FHWA). Intersections where motorists and bicyclists must cross travel paths account for 50 to 70 percent of bicycle-motor vehicle crashes [3–4]. Crashes between bicycles and cars occur when drivers do not detect or have unjustified expectations of bicyclists [5]. Traffic engineering efforts that improve the awareness of the presence of bicycles and increase the understanding of the right of way at crossings are likely to reduce conflicts and crashes between vehicles and bicycles. In Copenhagen, Denmark, integration of blue bicycle crossings with bicycle icons embedded at signalized crossing reduced accidents by an estimated 10% and injuries by 19% [6]. Where 2 or 4 legs of an intersection were treated, the estimated benefits significantly increased. With this greater goal of reducing conflicts, four specific treatments were selected by the Transportation Association of Canada (TAC) for experimental evaluation in the University of Calgary Driving Simulator (UCDS); namely, white dashed, blue dashed, blue solid and sharrows (a bicycle icon with arrows). Specifically, did the four different bicycle lane treatments differentially affect comprehension, speed and lane variability in a sample of drivers that included younger and older drivers who interacted with the treatments. Which of the four bicycle lane markings is the best? Are driving behaviours such as lane keeping, speed control and comprehension negatively affected? Do treatments reduce potential bicycle-vehicle conflicts? Finally, are older and younger drivers more likely to be positively or negatively impacted by the markings?

METHODS Participants Participants were recruited into the study using posters placed around the University of Calgary and Calgary community centres. Once a potential volunteer contacted the Cognitive Ergonomics Research Laboratory (CERL), they were interviewed by phone to determine if they met the screening criteria for the study. Participants had to have a valid driver’s license, drive at least 10,000 kilometres per year, report not being susceptible to car sickness and were not in an at-fault crash within the previous three years. All participants were screened for visual acuity (20/40), contrast sensitivity and colour deficiencies. Four volunteers failed one of the vision tests; namely, the Snellen visual acuity test (N = 3) or the colour blindness test (N = 1). These individuals were not allowed to participate and were advised to contact their optometrist or ophthalmologist to obtain more information about their visual condition. Participants were paid $40 to complete the study. If they became

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simulator sick and dropped out of the study, they received $25 (N = 5). A total of 30 participants, stratified into the age groups of 18 to 24, 25 to 54, and 55 to 80, participated in the study. An equal number of men and women were in each age group. Driving Simulator and Modeling The following description of the University of Calgary Driving Simulator (UCDS) and eye movement system is condensed from Caird et al. [7]. A Saturn sedan is situated in front of three screens. Each projector displays onto a wrap around screen, each of which measures 86.5” wide by 65” in height. The total projected forward field-of-view is 150 degrees. The brake, accelerator, and steering are interfaced to the graphics system by way of a computer under the hood of the Saturn. The steering wheel “stiffness” is controlled as a function of speed by a torque motor. Brake and accelerator inputs are modeled in software to result in appropriate deceleration and speeds. Road noise is presented through a stereo system with a base and surround speakers. An Applied Sciences Laboratory (ASL) 501 system was used to measure the participants’ eye movements. The authoring workstation is a development platform for traffic scenarios and experimental management. The host computer manages input/output, graphics, audio. The SimObserver system records camera images and data to digital video. Procedures

Each experimental session with a participant took between 90 minutes to two hours to complete and involved filling out forms, a structured interview, doing a number of vision tests and experimental procedures in the driving simulator. Once a participant arrived, they read and signed the informed consent form. A separate consent was used to determine whether participants were willing to allow video data to be shown at either a scientific conference or a general presentation. A verbal protocol or script was used to standardize all interactions between paricipants and the experimenters.

Visual acuity was tested monocularly using the Snellen eye chart that requires participants to read letters in descending size at 6.1 meters (20 feet). To participate in the study, a Snellen acuity of 20/40 or better was required, which is the legal requirement to receive a license in Alberta [8]. Contrast sensitivity was tested binocularly at a distance of 3 m using a Vistech Contrast Sensitivity Chart (Scialfa et al., 1991). Participants were required to score within the normal range for at least 4 of the 5 spatial frequency functions to participate in the study. Colour vision was tested using the Ishihara Test for Color Blindness (plate no. 27) [9].

Partipants were seated in the simulator and told how to operate it. The ASL 501 eye movement system was mounted on their head and calibrated [10]. A five-minute practice drive allowed participants to adapt to the handling of the driving simulator and to screen out those who may be disposed to simulator sickness. Throughout all drives, participants were told to drive as they ordinarily would in their own vehicles and to remember to obey all the rules of the road, such as speed limits, traffic lights and signs. Directions to turn were displayed on the centre sceen and/or verbally given by the experimenter through the internal communication system. Reminders to drive at the posted speed limit were given during the practice and experimental drives.

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Participants drove through three experimental drives. The first lasted seven minutes and the remaining second and third lasted approximately 12 minutes each. Drive 1 was a simple drive with no other traffic or events, and allowed participants to be exposed to the four bike treatments with out any other distractors. The order in which the four bike treatments were presented in Drive 1 were counterbalanced across participants. Drives 2 and 3 are similar except different events are interspersed in each. The total drive time was about 35 minutes and participants could take a break if they desired. Interspersed throughout Drives 2 and 3, a lead vehicle merged in front of the participant’s vehicle, braked a few times, and exited the drive. The presence of the lead vehicle was intended to focus the participant on being aware of their driving and their surroundings. The posted speed throughout the drives was 50 km/h and the driving culture was composed of urban tiles. Oncoming traffic was relatively light and was composed of a mixture of cars, trucks and SUVs.

Conflict Events Conflicts between the driver and cyclists were coordinated at some of the locations where the bicycle lane treatments (sharrows and blue dashed) were present. Specifically, a “right turn with a cyclist to the right” event and a “bicyclist to the left while merging” event were encountered by drivers in the second and third experimental drives.

Structured Interview After the completion of the experimental drivers, participants were given a structured interview that focused on comprehension and preference for the four bicycle lane treatments. Four pictures of the treatments were shown to participants from the driver’s perspective and four were shown from the bicyclist’s viewpoint (see Figure 1). The order in which the pictures of treatments were presented mirrored the order in which they were presented in Drive 1, and was thus counterbalanced across participants. The ordering of questions was always from the driver’s perspective first followed by the cyclist’s view pictures.

For each picture, participants were asked “what do these lane markings indicate to a driver?” They were also asked “what should the driver do when seeing such markings?” When a treatment was identified as being a bicycle lane marking, they were asked who had the right of way if the driver wanted to make a turn there. All responses were recorded by the experimenters.

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Figure 1. Representative pictures of the driver’s perspective (left) and bicyclists viewpoint (right) that were shown to participants during the structured interview. The sharrows treatment is shown on the left and the blue dashed on the right.

Questionnaires and Debriefing Before the vision testing, participants were asked to fill out the Simulator Sickness Questionnaire [11] and the Driving Experience Questionnaire (DEQ) and the Bicycling Experience Questionnaire (BEQ), which were developed in CERL. At the conclusion of the experimental drives, participants filled out the Post-Simulator Sickness Questionnaire. Participants were then debriefed about the purpose of the study. Any questions that participants had about the study were answered during the debriefing. Participants were then remunerated for their participation.

RESULTS

Experimental Design and Analysis The experimental design was analyzed using a 3 x 4 mixed factor, repeated measures ANOVA (SPSS v. 15). The within-subjects factor was treatment (white dashed, blue dashed, blue solid and sharrows) and the between-subjects factor was age (18-24, 25-54 and 55-80). Data from all measures and drivers were checked for missing values and outliers. No outliers were found using screening procedures from Tabachnick and Fidell [12]. The dependent variables of comprehension, speed and standard deviation of lane position (SDLP) were analyzed separately. Post hoc comparisons were all run using a Bonferonni correction. Greenhouse-Geisser corrections for violations of sphericity are indicated by a G-G next to adjusted F tests and degrees of freedom. Participant characteristics, comprehension, conflict analyses, preferences, speed, and standard deviation of lane position (SDLP) form the categories of subsequent analyses.

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Participant Characteristics Thirty participants completed all components of the study. Their characteristics are listed in Table 1. Younger drivers had slightly higher crash and violation means than other age groups, which is common [cf., 13].

Table 1. Age group, mean age, kilometres driven, crashes, violations and visual acuity of participant sample. Bicycle use and experience were also reported by participants through the BEQ (see Table 2). Average monthly bicycle riding was highest among middle-aged drivers, but bicycle ownership was highest among the youngest group (90%). Comparisons with characteristics of another bicycle sample [3], indicates that the sample in this study is somewhat older (M = 41.1) than the Portland study (M = 34). In addition to these background questions, participants were also asked what type of rider they were, and when and were they rode. Seventy-four percent reported they rode their bicycles from April to September, 19% rode from March to November and 7% rode year round. Winter weather in Calgary may shape when bicyclists can ride. When asked to classify the kind of rider they were, 71% thought of themselves as infrequent riders, whereas 18% called themselves commuters and 11% said they were recreational riders. Where participants reported riding included on residential roads (79%), on bicycle paths (75%), on major roads (25%) and trails (14%). In general, Calgary has an extensive bicycle path system with a limited number of marked bicycle lanes.

Group N Mean Age (SD)

Average Km/ Year (SD)

Crash, Last 5 Years

Moving Violat., Last 5 Years

Visual Acuity, Left Eye

Visual Acuity, Right Eye

Young

(18–24)

10 22.2 (1.5)

26,233 (23,579)

0.7 (0.5)

2.2 (3.2)

1.24 (0.5)

1.18 (0.5)

Middle

(25–54)

10 35.7 (10.1)

22,660 (16,249)

0.5 (0.7)

1.2 (1.7)

1.08 (0.3)

1.12 (0.3)

Older

(55–77)

10 65.5 (6.5)

19,660 (12,906)

0.5 (0.7)

0.7 (0.8)

1.50 (0.5)

1.38 (0.5)

Total 30 41.1 (19.6)

22,851 (17,710)

0.6 (0.6)

1.4 (2.2)

1.3 (0.4)

1.2 (0.4)

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Table 2. Participant bicycle experience and use. Comprehension The percent comprehension of each treatment was coded according to criteria developed by Dewar, Kline and Swanson [14]. Answers to the comprehension questions for each picture were scored as correct (2), partially correct (1) or incorrect (0). Correct and partially correct responses were combined and formed the correct category during the analysis. A response was deemed correct or partially correct if the participant identified the treatment as a bike lane, and/or indicated an understanding of right of way and that the lane was a protected zone for bicyclists. The responses of each participant were scored by two experimenters and classification issues resolved through discussion. From the driver’s viewpoint, the percentage of each treatment and age group correct and standard error (SE) is shown in Table 3. Understanding of each treatment varied by treatment type and age group. The main effect of treatment was significant (F (3, 17) = 9.3, p < .001). Pairwise comparisons indicated that the sharrows treatment had a significantly higher level of comprehension than the blue solid (p < .001), the blue dashed (p < .000) and the white dashed (p < .038) treatments. Overall, the sharrows treatment had the highest (97%) level of comprehension. The blue solid (60%), blue dashed (67%) and white dashed (69%) treatments had similar, but significantly lower levels of comprehension. The main effect of age was not significant (F (2, 19) = 2.3, p < .125). Comprehension of bicycle lane treatments was lower in the oldest age group, which is consistent with previous research on sign comprehension by older drivers [14]. The level of comprehension for all treatments was highest for the younger age group (83%) followed by the middle (77%) and older (60%) age groups (see Table 3).

Group N Mean Age (SD )

Average Km/Month (SD )

Bicycle Ownership

Years Riding (SD )

Young

10

22.2 (1.5)

58.2 (65.4)

90%

14 (6.4)

Middle

10

35.7 (10.1)

157.4 (306 .4 )

80%

25 (13.2)

Old

1 0

65.5 (6.5)

10.5 (14.6)

70%

39 (17.5)

Total

3 0

41.1 (19.6)

89 Km (185 .1 )

77%

25 (16)

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Table 3. Age group and treatment comprehension from the driver’s viewpoint.

Table 4. Age group and treatment comprehension from the bicyclist’s viewpoint. From the bicyclist’s viewpoint, the main effect of treatment was also significant (F (3, 15) = 7.7, p < .002). Pairwise comparisons indicated that the sharrows had a significantly higher level of understanding then the blue solid (p < .011) or white dashed (p < .047) treatments, but not the blue dashed treatment. Overall, the levels of comprehension by age and treatment were higher than those reported in the driver’s viewpoint, most likely due to learning or priming that occurred from the repetition of questions. The pattern of comprehension means was similar to the driver’s

Age Group

Sharrows Treatment (SE)

Blue Solid Treatment (SE)

Blue Dashed Treatment (SE)

White Dashed Treatment (SE)

All Treatments (SE)

Young (18-24)

96% (4.8)

67% (13.5)

94% (11.2)

75% (16.5)

83% (8.3)

Middle (25-54)

100% (4.2)

71% (11.9)

72% (9.9)

67% (14.6)

77% (7.3)

Older (55-77)

96% (4.3)

44% (12.0)

38% (10.0)

65% (14.7)

60% (7.4)

Tota l 97% (2.6)

60% (7.3)

67% (6.1)

69% (9.0)

73% (4.5)

Age Group

Sharrows Treatment (SE)

Blue Solid Treatment (SE)

Blue Dashed Treatment (SE)

White Dashed Treatment (SE)

All Treatments (SE)

Young (18-24)

100% (4.6)

92% (10.5)

100% (16.5)

63% (15.2)

89% (7.7)

Middle (25-54)

100% (3.9)

67% (8.8)

67% (13.8)

64% (12.7)

75% (6.5)

Older (55-77)

88% (3.9)

65% (8.9)

75% (13.9)

85% (12.9)

78% (6.5)

Tota l 96% (2.4)

75% (5.6)

82% (8.7)

71% (8.0)

81% (4.1)

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view in the order of sharrows (96%), blue dashed (82%), blue solid (75%) and white dashed (71%) treatments (see Table 4). Conflict Events Whether or not (Y/N) participants yielded to the cyclist during a potential conflict event was obtained by viewing and coding the digital video data. No age or treatment differences were found for either event. When specific bicycle conflicts were encountered (see Figure 2), most drivers looked left for the cyclist while merging and did not overtake a bicyclist on the right. Overtaking a bicycle and turning right in front of them is the most frequently occurring crash between vehicles and bicycles [5]. Although not significant, younger drivers accelerated and overtook the bicyclist on the right more frequently (see Table 5).

Table 5. The percentage of drivers in each age group and treatment who yielded to the bicyclist in the right lane as they approached the T intersection.

Figure 2. Right turn with cyclist present to the right (left picture) and look left for cyclist (right) events.

Age Group N Sharrows

Treatment

Blue Dashed Treatment

Young (18-24)

1 0

50%

80%

Middle (25-54)

1 0

90%

100%

Older

(55-77)

1 0

90%

90%

Total

3 0

77%

90%

10

For the look left event, a number of older drivers were not traveling at a sufficient speed as they merged to be classified as having yielded or not.

Table 6. The percentage of drivers in each age group and treatment who yielded to the bicyclist approaching from the left as they merged through the T intersection. Preferences Several preference questions were asked in the structured interview. Participants were asked to name which treatment they liked best out of all four. Participants were shown an image of all four treatments and asked to select their favourite. They were also asked to state whether the sharrows or blue dashed treatments were preferred. The frequency counts of these preference choices are shown in Table 7. When all four treatments could be chosen the sharrows treatment was preferred by 16 out of 30 participants. When given two options, sharrows and blue dashed, participants overwhelmingly chose the sharrows treatment (21/30).

Table 7. Preference frequency for all four and sharrows or dashed blue treatments.

Age Group N Sharrows

Treatment N Blue Dashed

Treatment

Young (18-24)

1 0

90%

1 0

100%

Middle (25-54)

1 0

90%

1 0

100%

Older

(55-77)

7

100%

8

100%

Total

2 7

93%

2 8

100%

Treatment Which of the four treatments

do you like best? Out of the Blue Dashed and

Sharrows treatments, which do you like best?

Sharrows 1 6 2 1 Blue Sol id 2 n / a

Blue Dashed 5 9 White Dashed 7 n / a

Tota l 3 0 3 0

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Speed and Standard Deviation of Lane Position (SDLP) Mean speed was collected in km/h during the four treatment conditions. SDLP was collected in the same locations and measured as the variance of distance in metres from the centre of the lane of travel. Speed and SDLP were measured as drivers encountered the treatments without the presence of other vehicles on the first experimental drive, and in Drive 2 with the presence of other vehicles. Speed and SDLP in the presence of treatments was not affected by age or treatment variables. This result is consistent with previous observational studies [1–2]. Younger (M = 51.9 kh/h) and middle-aged (51.2 km/h) groups adopted slightly higher mean speeds than the older age (50.7 km/h) group, although these differences were not significant they were consistent with previous research on speed adoption profiles [13].

DISCUSSION AND CONCLUSIONS The purpose of this driving simulation study was to determine the effects of four bicycle lane treatments on comprehension and driving performance. Specific research questions are addressed. Which of the four bicycle lane markings is the best? The sharrows bicycle treatment had the highest level of comprehension and was preferred by the majority of drivers. Based on levels of comprehension, stated preferences and a lack of adverse driving performance results, the sharrows treatment is the best. Are driving behaviours such as lane keeping, speed control and comprehension negatively affected? Speed and SDLP in the presence of treatments was not affected by age or treatment variables. A number of specific kinds of comprehension confusion should be examined carefully. Do the sharrows and blue dashed treatments reduce potential bicycle-vehicle conflicts? No age or treatment differences were found for either event. When specific bicycle conflicts were encountered, most drivers looked left for the cyclist while merging and did not overtake a bicyclist on the right. Are there age differences? Specifically, are older and younger drivers more likely to be positively or negatively impacted by the markings? Although the variable age was not significant for comprehension, the pattern of means is consistent with lower levels of comprehension for older drivers. There were no age differences in speed or SDLP.

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RECOMMENDATIONS 1) The sharrows bicycle lane treatment seems to be the most obvious choice from a driver

and cyclists comprehension and preference analysis.

2) The use of driving simulation to expose drivers to the bicycle treatments and ascertain

driving performance and comprehension measures provides an ecologically valid and controlled means to evaluate road design questions.

3) Further evaluation of the sharrows treatment is recommended. The removal of arrows

above the bicycle icon in the treatment, or use of colour paint in combination with the sharrows should be examined. Observational and before-after studies are natural complements.

Acknowledgements This research was supported by a contract from the Transportation Association of Canada to Boulevard Transportation Group.

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References [1] Sadek, A.W., Dickason, A., & Kaplan, J. (2007). Effectiveness of a green, high visibility bike

lane and crossing treatment. Transportation Research Board 86th Annual Meeing Compendium of Papers CD-ROM. Washington, D.C.: TRB.

[2] Hunter, W.W., Harkey, D.L., Stewart, R., & Birk, M.L. (2000). Evaluation of blue bike-lane

treatment in Portland, Oregon. Transportation Research Record, 1705, 107–115. [3] Dewar, R., & Hanscom, F. (2007). Pedestrian and bicyclists. In R. Dewar & P. Olson (Eds.),

Human factors in traffic safety (2nd ed., pp. 427–461). Tucson, AZ: Lawyers and Judges Publishing.

[4] Hunter, W.W., Stutts, J.C., Pein, W.E., & Cox, C.L. (1995). Pedestrian and bicycle crash

types of the early 1990’s (Rep. No. FHWA-RD-95-163). Washington, D.C.: Federal Highway Administration.

[5] Rasanen, M., & Summala, H. (1998). Attention and expectation problems in bicycle-car

collisions: An in-depth study. Accident Analysis and Prevention, 30(5), 657–667. [6] Jensen, S.U. (2008). Safety effects of blue cycle crossings: A before-after study. Accident

Analysis and Prevention, 40, 742–750. [7] Caird, J.K., Chisholm, S., Lockhart, J., Vacha, N., Creaser, J.I., Edwards, C., & Hatch, K.

(2006). In-vehicle intelligent transportation system (ITS) countermeasures to improve older driver intersection performance (Tech. Rep. No. TP 14610 E). Montreal: Transportation Development Centre, Transport Canada.

[8] Casson, E.J., & Recette, L. (2000). Vision standards for driving in Canada and the United

States. A review for the Canadian Ophthalmological Society. Canadian Journal Ophthalmology, 35, 192-203.

[9] Ishihara, S. (1993). Ishihara’s test for colour-blindness. Tokyo: Kanehara. [10] Applied Sciences Laboratory. (2001). Eyenal Manual (v. 1.59). Bedford, MA: Author. [11] Kennedy, R.S., Lane, N.E., Berbaum, K. S., & Lilienthal, M.G., (1993). Simulator sickness

questionnaire: An enhanced method for quantifying simulator sickness. International Journal of Aviation Psychology, 3(3), 203-220.

[12] Tabachnick, B.G., & Fidell, L.S. (2006). Using Multivariate Statistics (5th ed.). Pearson,

Allyn and Bacon, Boston, MA. [13] Caird, J.K., Chisholm, S., Edwards, C., & Creaser, J. (2007). The effect of yellow light onset

time on older and younger drivers’ perception response time (PRT) and intersection behavior. Transportation Research: Part F, 10(5), 470–483. doi:10.1016/j.trf.2007.03.002

[14] Dewar, R.E., Kline, D.W., & Swanson, A. (1994). Age differences in comprehension of

traffic sign symbols. Transportation Research Record, 1456, 1–10.