The Role of Vision in Driving: An Overview

Joanne M. Wood MCOptom, PhD, FAAO School of Optometry and Vision Science, Institute of Health and Biomedical Innovation, Queensland University of Technology, Brisbane, AUSTRALIA Presentation Outline

• The importance of vision and driving research • Overview of research approaches used to investigate the relationship between vision and driving • Summary of studies that have investigated: • Effect of ocular conditions on driving • Visual predictors of driving ability and safety • Vision and night-time driving Vision and Driving Research

• Increase in the number of studies focusing on the relationship between vision and driving • Tripling of the number of literature citations on vision and driving indexed in Pubmed since the 1980s1 • Increased interest in this relationship motivated by: • Lack of evidence for determining vision standards for driving • Limited understanding of how different types of visual impairment impact on driving ability and safety

1. Owsley et al (2015) Vision and Driving Research

• Policy makers depend on the scientific literature on vision and driving • To develop guidelines that are evidence-based and fair to drivers with visual impairment • Clinicians depend on the scientific literature and government policies • To advise their patients about fitness to drive Driving Outcome Measures

• A range of outcome measures have been used to assess driving: • Each has a role in understanding the link between vision and driving • Information they provide is different and not directly interchangeable • Approaches include: • Motor vehicle crashes • Driving simulators • Real world driving • Closed-road • Open-road/In-traffic Driving Performance: Closed-Road

• Bitumen closed-road circuit • Standard road signs and markings • Hills, bends, straights • Collaboration with local transport authority from 1990 Driving Performance: Closed-Road

• Sign recognition • Obstacle avoidance • Gap judgements • Manoeuvring • Lane keeping • Reaction times • Driving speed • Eye movements Driving Performance: Closed-Road

• Sign recognition • Obstacle avoidance • Gap judgements • Manoeuvring • Lane keeping • Reaction times • Driving speed • Eye movements • Day and night-time testing Driving Performance: Open-Road

• Driving Instructor and driver-trained Occupational Therapist (masked) • Dual brake vehicle • Standard route in-traffic route (20 km) • Car park to more complex traffic situations • Quantitative driving scores • Errors in specific driving skills and locations of errors • Global driver safety rating (1-10) • In-vehicle measurement system • Accelerometers, inertial sensors, GPS • Vehicle-mounted cameras Relative Advantages of Assessment Methods

• Closed-road assessment • Provides detailed measurement of different aspects of driving • Can manipulate task difficulty and the nature of the driving task • Can assess both simulated and true visual impairment • Open-road assessment • More representative of real world driving • Standardised scores and driver safety ratings Research Objectives

• To better understand how visual impairment and ageing impact on driving performance • Under day and night-time conditions • To identify the optimum predictor tests of safe and unsafe driving • To develop and evaluate interventions that can extend safe driving for as long as possible Summary of Studies

Closed Road Open Road Simulated visual impairment: Older drivers: range of visual status cataracts, visual field loss, blur Predictor tests Young and old drivers Day and night VF defects (hemianopia and quadrantanopia) Simulated visual impairment Auditory and visual distracters Bioptic telescope wear Young and old drivers Head movements Older drivers: range of visual status True visual impairment: glaucoma and age-related macular True visual impairment: cataracts, degeneration glaucoma Presbyopic corrections Parkinson’s and Alzheimer's disease Day and night Mild cognitive impairment Eye and head movements Night-time pedestrian and cyclist visibility Young and old drivers Simulated visual impairment: cataracts, blur Clothing, glare, clutter, streetlights Cataracts: Driving

• Cataracts are linked with self-regulation, avoidance of challenging driving situations and cessation1 • Drivers with cataracts have 2.5x higher crash rates than controls1 • Cataract surgery reduces crash rates • Crash rates halved following surgery compared to controls2 • Australian population linked data (1997-2006): cataract surgery reduced crash risk by 13% with savings of $4.3 million3 • US simulation model suggested early cataract surgery rather than current practice reduces crash risk by 21%4

1. Owsley et al (1999); 2. Owsley et al (2002); 3. Meuleners et al (2012); 4. Mennemeyer et al (2014) Cataract Surgery: Driving Performance

• 29 patients undergoing bilateral cataract surgery; 18 controls • Closed-road: daytime

Test 1: Vision & Driving Assessment (before 1st cataract operation)

 4 weeks

Test 2: Vision & Driving Assessment (after 1st cataract operation)

 4 weeks

Test 3: Vision & Driving Assessment (after 2nd cataract operation) Cataract Surgery: • Cataract surgery resulted in significant improvements Driving Performance in driving performance: • Overall differences in • Sign recognition • Hazards seen driving performance • Hazards avoided following cataract surgery • Driving speeds best predicted by • Overall driving score • Letter contrast sensitivity

0.4 3.0 R2=0.29 2.5 0.2 Controls 2.0 0.0 (2-3*) (1-3*) 1.5 -0.2 1.0 (1-2*) -0.4 0.5 0.0 Overall Driving Score Overall Driving -0.6 Cataracts

Difference in Driving Score in Driving Difference -0.5 -0.8 -1.0 Pre-op Post-op Post-op -0.4 -0.2 0.0 0.2 0.4 0.6 0.8

Wood et et al al (2006) (2006) (1st eye) (2nd eye) Difference in Letter CS Visual Field Defects: Driving

• Individuals with hemianopic or

Example of HFA 24-2 (left) and quadrantanopic field defects prohibited Esterman (below) field plots of a right homonymous hemianopic driver with from driving in most jurisdictions macular sparing • No evidence that all individuals with hemianopia or quadrantanopia are unsafe to drive Hemianopia: Driving Performance

• 60 licensed participants • 22 hemianopes, 8 quadrantanopes; 30 controls • Open-road driving assessment • Vision and cognitive testing battery • High proportion of drivers rated as safe:

70 Hemianopes Quadrantanopes 60 • Hemianopes (73%) Controls • Quadrantanopes 50 (88%) 40 30

• Controls (100%) 20

Percentage of Group (%) 10

0 12345 Wood et al (2009) Driving Safety Rating Hemianopia: Driving Performance

• Significant differences for Backseat Evaluator Rating Scale for hemianopes and Specific Driving Skills/Behaviors: 1 = Failure to execute skill/behavior quadrantanopes vs 2 = Some problems with executing controls skill/behavior but not complete failure 3 = Good execution of skill/behavior • Lane position

• Steering steadiness 100 Hemianopes Quadrantanopes • Gap selection Controls 80 • No significant differences • Scanning 60

• Speed 40 •Braking 20 • Indicator use Percentage of Group (%) • Obeying signs/signals 0 123 Lane Position Rating

Wood et al (2009) Wood et al (2009) Hemianopia: Driving Performance

Head movements and vehicle control in the hemianopic and quadrantanopic drivers: 40 Seeing • Compared to safe drivers, those Blind rated as unsafe: 30 • Made less head movements into 20 their blind field 10 • Drove more slowly and had more

braking events Number of Head Movements 0 • Steered into their seeing field Safe Unsafe

Wood et al (2011) Hemianopia: Driving Performance

Predictors of driving safety in drivers with hemianopia or quadrantanopia • Unsafe driving associated with visual and cognitive function1: • Reduced contrast sensitivity • Visual field defects: Esterman, binocular field sensitivity • Recent studies in other populations suggest that lower field loss is most problematic2,3 • Slower visual processing speed and executive function

1. Wood et al (2009); 2. Huisingh et al (2015); 3. Kwon et al (2016) Predictors of Driving Safety

• 270 community-dwelling older adults > 70 yrs recruited via the electoral roll • Open-road driving assessment • 20 km (75% directed and 25% self- directed) • Clinic-based test battery • Vision • Cognitive • Motor test battery Vision tests • Visual acuity Laboratory-based • Contrast sensitivity Testing • Visual fields • Dot motion sensitivity Cognitive tests • Useful Field of • Visual search View • Digit symbol substitution • Trail making A and B • Self-ordered Motor tests pointing • Balance (firm, • Simple and foam) choice RT • Strength tests • Proprioception • Neck rotation Open Road Driving

• Multi-domain battery: best predictor measure from each domain: Ideal test * • Motion sensitivity • Colour choice reaction time • Postural sway • High levels of sensitivity and specificity in predicting the potential for unsafe driving

Wood et al (2008) Open Road Driving • 75 drivers with glaucoma and 70 age-matched controls • Drivers with glaucoma rated as • Of the vision tests, motion slightly less safe than controls sensitivity had the strongest (5.2 vs 5.8) and made 2x as many association with driving safety critical errors • High levels of sensitivity and specificity for multi-domain battery

18 * 16

14

12

10

8

6

4

2 Traffic light errors (proportion) lightTraffic errors 0 Glaucoma Controls

Wood et al (2016) Summary: Older Drivers with and without Visual Impairment

• Different types of visual impairment impact on driving ability and safety in different ways • Strong evidence that good vision is important for safe driving • Visual acuity is a poor visual predictor of driving performance and safety • Alternative visual tests including motion sensitivity, contrast sensitivity and visual fields better predict driving abilities but depends upon study population • No measure alone accounts for all the variation in driving ability - multi-domain batteries may be most useful • Licensing should be based on performance rather than age or disease status Night-time Driving

• Driving at night is dangerous • Fatality rates at night are 3x higher than in the day1 • Night-time safety risk is highest for pedestrians • Pedestrians 7x more vulnerable to a fatal collision at night than the day2 • Multiple factors • Poor visibility is the leading cause of vehicle collisions with pedestrians, cyclists, and other low- contrast obstacles3

1. National Safety Council (1999-2004); 2. Sullivan & Flannagan (2002); 3.Owens & Sivak (1996) Night-time Pedestrian Visibility

• Retro-reflective vests are the most common clothing used to improve night- time pedestrian conspicuity •BUT conspicuity is better enhanced using alternative placements of retro-reflective markers • A particularly promising configuration is ‘biological motion’ • Pattern of motion of living creatures is very different to that of inanimate objects

http://psych-s1.psy.vanderbilt.edu/faculty/blaker/BM/BioMot.html Biological Motion

http://www.biomotionlab.ca/ Application of Biological Motion

• Perceptual phenomenon of biological motion applied to night-time pedestrian visibility • Retro-reflective strips attached to moveable joints illuminated in headlamp beam • Our studies have explored the factors affecting night-time visibility • Driver age and visual status • Headlamp glare • Clothing manipulations Night-time Visibility Studies

• 1.8 km closed road circuit • Glare lights to simulate oncoming vehicle headlamps • Distracter cones • Distracter task: Call out all road signs • Announce “pedestrian!” and press touch pad when they recognize a pedestrian Black Night-time Visibility: Driver Age and Clothing

• 20 young; 20 old White visually normal licensed drivers • 4 pedestrian clothing conditions Retroreflective vest

Retroreflective biomotion Night-time Visibility: Driver Age and Clothing

• Older drivers had poorer recognition ability • Older drivers 250 Young recognised only 58% Elderly of the pedestrians and 200 at half the distance

• Clothing really 150 matters!

• Recognition distances 100 for biomotion 50x greater than black...

Recognition Distance (m) 50 • … and 3x greater than vest! 0 Black White Vest Biomotion Wood et al (2005) Night-time Visibility: Vision and Glare • 28 young participants • Visual impairment simulated using modified goggles: • Cataracts: frosted lenses ~6/12 • Blur: acuity matched to cataract condition: mean lens power was +1.30D • Normal: full distance refraction • Pedestrian clothing (3); glare between subjects factor (2)

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Start/Finish Night-time Visibility: Vision and Glare

• Glare and visual • Biomotion clothing maximized impairment both reduced pedestrian conspicuity in all pedestrian conspicuity conditions

100 300 No Glare Black Glare Vest Biomotion 80 250

200 60

150 40 100

20 Recognition Distance (m)

% Pedestrians Recognized % Pedestrians 50

0 0 Normal Blur Cataract Normal Blur Cataracts

Wood et al (2012) Effects of Blur: Day vs Night

• 12 young visually normal participants • Driving performance assessed (day and night-time) • Bilateral blur in a randomized order: • Control: optimal distance Rx • 3 blur conditions: +0.50D, +1.00D, +2.00D

Glare

Start/Finish Effects of Blur: Day vs Night

• Driving performance significantly impaired with blur and night-time conditions • Overall driving score • Road hazards seen and hit • Road signs seen and sign visibility distances • Time taken to complete course • BUT not lane keeping and gap judgements • Overall performance impaired with increasing blur • Even for +0.50D level of blur • Performance worse during night than daytime conditions • Effects of blur were exacerbated at night compared to day Wood et al (2014) Night-time Visibility: Blur and Age

• Bilateral blur in a random order: • Control: optimal distance Rx • 3 blur conditions: +0.50D, +1.00D, +2.00D

160 Young 140 Older

120

100 • 24 visually normal, licensed 80 60

drivers (12 young; 12 older) 40 Recognition Distance (m) Distance Recognition 20

0 • Older drivers shorter 0.00 +0.50 +1.00 +2.00 Refractive Blur (D) recognition distances

Wood et al (2015) Night-time Visibility: Blur and Age

• Even small amounts of blur (+0.50D) reduced

pedestrian recognition 200

Street • Biomotion clothing Vest Bio enhanced visibility even 150 under degraded viewing 100 conditions

50 Recognition Distance (m) Distance Recognition

0 0.00 +0.50 +1.00 +2.00 Refractive Blur (D)

Wood et al (2015) Summary: Night-time Driving

• Optimum refractive correction and cataract extraction have the potential to improve night-time driving safety • Even small amounts of blur (+0.50D) reduce night-time recognition • Visual acuity is a poor predictor of night-time driving ability • Photopic visual acuity of 6/12 does not ensure adequate visual capacity at night • Clothing matters! • Biomotion clothing is highly recommended for individuals walking or working at night

Conclusions

• Understanding the relationship between vision and driving is critical • For drivers as well as pedestrians and other vulnerable road users • Under day and night-time conditions • Optometrists have an IMPORTANT role in driving safety

Optometrists have the opportunity to save LIVES not just EYES! Acknowledgments

• Collaborators: • Kaarin Anstey, Alex Black, Ronald Braswell, Michael Collins, Dawn DeCarlo, Jennifer Elgin, Graham Kerr, Stephen Lord, Kerry Mallon, Lanning Kline, Philippe Lacherez, Gerald McGwin, Fred Owens, Cynthia Owsley, Ravi Thomas, Rick Tyrrell, Michael Vaphiades • Researchers: Vision and Driving team • All of our participants • Mt Cotton Driver Training Centre • Funding: ARC Linkage (LP0990292), NHMRC (0209799, 1008145, 1045024), QUT PDP