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The Possible Effects of Commercial Electronic Variable Message Signs (CEVMS) on Driver Attention and Distraction

Appendix A - Expanded Tables

A.1 Key Factors (Independent Variables)

Table 1. Expanded key factors (independent variables).

Variable Ref. # Advantages Disadvantages
1.0 Billboard      
1.1 Location 8, 129, 38, 15, 44, 32    
1.1.1 Lat./long.; GPS; mile marker; survey location; reference location; mobile 13, 53, 160 Important to define stimulus; Easy to measure. Likely to require travel expenses.
1.1.2 Distance from roadway; setback     Less important.
1.1.3 Sight distance; visual occlusions; distance first detected 13, 53 Determines exposure time.  
1.1.4 Orientation; angle to road; side of road; two-sided 144   Less important.
1.2 Display 144    
1.2.1 Type: Conventional; Digital; Tri-vision 125, 48 Digital type stands out. Tri-vision likely to disappear.
1.2.2 Size; length; height; visual angle; mounting height 129, 32 Off-premise sizes somewhat standard. On-premise sizes variable.
1.2.3 Resolution; dpi; LEDs/in 95, 48, 53 Crispness (sharpness) of image important.  
1.2.4 Luminance; contrast ratio; day/night settings 48, 53, 144 Brightness (luminance) extremely important. Night setting may depend upon background illumination.
1.3 Dynamics 31    
1.3.1 Type: static; changing 158, 129, 26 Changing images extremely important. Static serves as control.  
1.3.2 Change rate; dwell time; change time; sequencing 48, 50, 158, 94 Change pattern important. Easy to measure.  
1.3.3 Special effects: wipe, dissolve, scintillate   Adds to uniqueness and conspicuity. More difficult to measure.
1.3.4 Full motion video 125, 126 Full motion video extremely compelling. Difficult to specify exact content seen.
1.3.5 Engagement value: ability to hold attention   Important overall distraction variable Difficult to measure; requires subjective rating.
1.3.6 Sound      
1.4 Message 129, 44, 144, 53    
1.4.1 Type: text; graphics; mixed; targeted 32, 31 Particular message may be secondary.  
1.4.2 Text: word count; font size; color; content; legibility; affect 32, 48   Many variations. Less important.
1.4.3 Graphics: size; complexity; color; content; affect 31, 50   Difficult to specify. Many varieties.
1.4.4 Public safety alerts   Social benefit. May be more distracting than advertising.
1.4.5 Interactive: encourages driver response   Interactive may require more attention.  
2.0 Roadway      
2.1 Type      
2.1.1 Category: two-lane rural; collector; arterial; freeway 13, 15 71, 54 Important determinate of driver workload. Many variations even in single category.
2.1.2 Lanes: number; width; markings; medians; shoulders; rumble strips     Less important.
2.1.3 Speed: posted; advisory; 85th percentile; median 50 Changes urgency of correct driving responses.  
2.1.4 Condition: dry, wet, ice, rain; oil slick   Important to driver control over vehicle.  
2.1.5 Traction: coefficient of friction      
2.2 Complexity 15    
2.2.1 Tangent: level; grade     Less important.
2.2.2 Curve: horizontal; vertical 13, 44, 118 May place sudden demand on driver attention.  
2.2.3 Intersection: signalized; stop controlled 129, 38, 48 Increased driver workload. Wide variety of intersection complexities.
2.2.4 Interchange: exit, entrance, merge, gore 26, 44, 32, 48 Controlled access. More carefully engineered.  
2.2.5 Driveway; entrance     Less important.
2.2.6 Lane change: merge; diverge; lane drop   May place sudden demand on driver attention.  
2.2.7 Other: bicycle lane; fire house     Less important.
2.3 Traffic 158, 38, 15, 113,    
2.3.1 Average daily traffic; peak traffic; level of service 118 Likely to increase driver workload.  
2.3.2 Traffic mix: cars, trucks, buses, motorcycles     Less important.
2.3.3 Pedestrians     Mainly only in urban settings.
3.0 Vehicle 59    
3.1 Type: automobile; SUV; truck; motorcycle   Motorcycle has least obstructed view.  
3.2 Condition: response; vehicle dynamics     Hard to determine in field.
3.3 Windshield: size; tinting; field of view   Defines some stimulus exposure characteristics.  
4.0 Driver 10    
4.1 Characteristics: age; gender; demographics 53, 23, 12, 54   Less important.
4.2 Experience: years driving; route familiarity 15, 100 Route familiarity extremely important.  
4.3 State: alert; fatigue; alcohol; drugs     Difficult to measure.
4.4 Distractions: conversation; eating; cell phone 24, 90, 25    
5.0 Environment      
5.1 Visual—general 113    
5.1.1 Visual clutter; nearby billboards; ambient lighting 160, 15, 32, 44 Complexity of visual environment extremely important. Difficult to specify.
5.1.2 Day/night viewing: dawn; dusk; sun-glare 53 Nighttime viewing of bright images important.  
5.1.3 Visual flow     Less important.
5.2 Official signs 160, 2, 26, 100    
5.2.1 Type: regulatory, advisory, navigational 94 Regulatory most important.  
5.2.2 Location: left, right, overhead 44, 15 Billboard can conflict with sign.  
5.2.3 Lighting: illuminated; luminous (VMS); retro-reflective   Luminous (VMS) signs most important.  
5.2.4 Density: number in view, type mix 15   Many variations in urban settings.
5.2.5 Dynamics: change rate; motion; video   Extremely important point of possible conflict. Motion and video not yet allowed.
5.2.6 Message: text; graphics     Less important
5.3 On-premise signs      
5.3.1 Type: conventional; Tri-vision; digital; full motion video 144 Digital and video most important. Tri-vision likely to disappear.
5.3.2 Location: left, right, high, low 144    
5.3.3 Lighting: illuminated; luminous; LED 144 Bright, high resolution very compelling. Difficult to measure.
5.3.4 Density: number in view, type mix   Can add to visual clutter. Many variations possible.
5.3.4 Dynamics: change rate; motion; video; sound 144 Extremely important variable.  
5.3.5 Message: text; graphics; interactive   Interactive important. Text and graphics less important.
5.4 Geographic 15    
5.4.1 Population: urban; suburban; rural 13, 71 Can affect visual clutter. Many variations.
5.4.2 Terrain: mountain; valley; desert; hilly; near water   Can affect driver workload. Many variations.
5.4.3 Area: city; state; region     Less important.
5.5 Meteorological      
5.5.1 Temperature; humidity; cloud cover 53   Less important.
5.5.2 Precipitation: rain; snow; fog; ice; visibility 53 Can affect driver workload.  
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A.2 Key Measures (Dependent Variables)

Table 2. Expanded key measures (dependent variables).

Variable Ref. # Advantages Disadvantages
1.0 Vehicle Behavior 48    
1.1 Speed 125, 50    
1.1.1 Continuous   More accurate profile. Large amounts of data. Expensive.
1.1.2 Discrete locations   Less data. Cheaper.
1.1.3 Speed exceedances: high; low   Distraction indicator.  
1.1.4 Speed variance   Distraction indicator. Best with continuous data.
1.2 Lane position 161, 48, 54    
1.2.1 Continuous   More accurate profile. Large amounts of data. Expensive.
1.2.2 Discrete locations   Less data. Cheaper.
1.2.3 Lane excursions: right; left 23 Distraction indicator. More difficult to measure.
1.2.4 Lane variance   Distraction indicator. Best with continuous data.
1.3 Acceleration 48, 54    
1.3.1 Longitudinal: hard braking; delayed acceleration; braking without cause   Excellent surrogate for distraction.  
1.3.2 Lateral: swerves 39 Good surrogate for distraction.  
1.3.3 Heave: bumps 125, 48   Not important.
1.4 Other vehicle interactions 39    
1.4.1 Headway (car following); time to collision 125, 48, 118 Good surrogate for distraction.  
1.4.2 Gap acceptance: merge; passing   Good surrogate for distraction. Difficult to measure.
1.4.3 Conflicts; near-crashes 125 Extremely important measure.  
1.4.4 Violations: red light running; failure to yield; failure to stop     Low probability events.
1.4.5 Errors: missed exit; wrong lane   Good surrogate for distraction.  
1.4.6 Timing: late movements; premature movements     Difficult to measure.
1.5 Infrastructure interactions      
1.5.1 Response to roadway geometry: swerves; sudden braking 118, 15 Surrogate for distraction.  
1.5.2 Response to traffic control devices: misses, delays 15 Surrogate for distraction.  
1.5.3 Pedestrian interactions; yields     Only in urban settings.
1.6 Signals 39    
1.6.1 Brake light 125 Indication of sudden deceleration.  
1.6.2 Turn signals     Less important.
1.6.3 Other: backup lights     Not important.
2.0 Driver/Vehicle Interactions      
2.1 Steering       
2.1.1 Gross movements: curves; turns   Surrogate for distraction.  
2.1.2 Fine movements: lane keeping 60   Difficult to measure.
2.2 Throttle      
2.2.1 Pedal press; pedal position; duration     Less important.
2.2.2 Pedal release; duration     Less important.
2.3 Brake 125    
2.3.1 Pedal press; duration; excursion   Surrogate for distraction.  
2.3.2 Pedal release     Less important.
2.4 Shift (manual only)      
2.4.1 Gear selection (speed)     Not important.
2.4.2 Gear transitions (shifts)     Not important.
2.5 Displays 154    
2.5.1 Speedometer   Secondary visual distractor.  
2.5.2 Other: gauges; radio     Less important.
2.6 Other controls 154, 25    
2.6.1 Safety: windshield wipers; instrument lights; horn; turn signals 54   Less important, except turn signals.
2.6.2 Entertainment: radio; CD player 48, 24, 54 Secondary distractor.  
2.6.3 Auditory/vocal: voice actuated 154   Low probability of occurrence.
3.0 Driver Attention / Distraction 79, 113, 32, 146, 145    
3.1 Objective measures 129    
3.1.1 Eye glance behavior: eye movements; number of glances; duration of glances; glance object 129, 42, 125, 53, 160, 83, 161, 78 Excellent measure of unconscious attention / distraction. Delicate, expensive equipment. Difficult to calibrate. Expensive to analyze data.
3.1.2 Distractor performance; secondary task 83, 53 Excellent measure of distraction. Can increase risk in field experiments. Can be artificial.
3.1.3 Visual occlusion 15 Good measure of distraction. Can increase risk in field experiments. Unnatural driving task.
3.1.4 Feature detection 48    
3.1.5 Feature recognition 48 Good measure.  
3.1.6 Driver workload; task performance 38, 15, 113 Excellent indicator of distraction. Complicated to measure.
3.1.7 Head turning 78 Easy to measure. Less important.
3.1.8 Driver errors 83 Excellent measure of distraction. Many varieties. Low probability of occurrence.
3.1.9 Reaction time; perception-reaction time 15 Good indicator of distraction. Difficult to measure.
3.2 Inferred measures      
3.2.1 Surprise; orienting response     Difficult to measure.
3.2.2 Conspicuity; attention grabbing     Difficult to measure.
3.2.3 Search patterns 15 Indicative of visual hypotheses.  
3.2.4 Capacity: self-regulated attention; spare capacity 15 Extremely important concept. Hard to establish criterion threshold.
3.3 Subjective measures 161    
3.3.1 Conversational drive   Good possible method. Lots of extraneous data.
3.3.2 Rating scale   Inexpensive. Imprecise.
3.3.3 Questionnaire   Inexpensive. Imprecise.
3.3.4 Survey 125 Relatively inexpensive. Sampling frame difficult.
3.3.5 Focus group   Small sample. Lots of data. Confounding social variables.
4.0 Crashes 158, 125, 26, 44, 128, 161, 95, 121    
4.1 Type: head-on; sideswipe; rear-end; backing; run-off-road; pedestrian 39 Very important discriminator variable. Related to ultimate goal. Rare events. Many contributing factors. Difficult to estimate statistically.
4.2 Severity: fatal; injury; property damage; unreported   Important to determine impact. Rare events. Many factors. Difficult to estimate statistically.
4.3 Method of measurement     Rare events. Hard to estimate.
4.3.1 Direct observation: simulator; field camera 42 Best studied in simulator. No chance of injury.  
4.3.2 Before/after study 39, 158 Most common study type. No control site. Regression toward mean.
4.3.3 Before/after with control   Control adds rigor. Regression toward mean.
4.3.4 Before/after/before   More convincing causal effect. Regression toward mean.
4.3.5 Regression model   Directly account for multiple factors Large amounts of data on many variables
4.3.6 Empirical Bayes   Control for regression toward mean. More complicated statistical model.
4.3.7 Full Bayes   More complete treatment of conditional probabilities. Not widely used.
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A.3 Key Research Strategies

Table 3. Expanded key research strategies.

Method Ref. # Advantages Disadvantages
1.0 Crashes: Field 97, 95, 21    
1.1 Unobtrusive observation      
1.1.1 Participant: random, uncontrolled; usually unknown 49 No sampling bias. Do not know participant sample.
1.1.2 Experimenter: usually absent; remote observation; unknown to participant 49 No artificial participant behaviors due to experimenter.  
1.1.3 Stimuli: natural, ordinary, in context; variable, uncontrolled 49 Natural stimuli. Stimuli not uniform; e.g., weather effects.
1.1.4 Responses: crashes; antecedent vehicle behaviors; rare; few participant variables 49 Directly related to the safety goal. Extremely rare events; insensitive to participant variables.
1.1.5 Scenario: natural route and purpose; uses own vehicle 49 Completely natural experimental context; uses own vehicle. Long-term monitoring required.
1.2 Naturalistic driving      
1.2.1 Participant: selected, sampled 79, 78, 42 Know participant sample. Possible sampling bias.
1.2.2 Experimenter: absent; remote observation; known to participant 79, 78, 42   Possible artificial participant behaviors.
1.2.3 Stimuli: natural, ordinary, in context; variable, uncontrolled 79, 78, 64, 42 Natural stimuli. Stimuli not uniform; e.g., weather effects.
1.2.4 Responses: crashes; antecedent vehicle and participant behaviors; rare 79, 78, 64, 42 Directly related to ultimate goal; sensitive to some participant variables. Extremely rare events; difficult to collect adequate sample of crashes.
1.2.5 Scenario: natural route and trip purpose; uses own vehicle 79, 78, 64, 42 Mostly natural experimental context; uses own or borrowed vehicle. Participant aware of test status; may be injured or killed; vehicle may be damaged or destroyed; expensive.
1.3 Retrospective database: fatal, injury, property damage 87, 49, 128, 14, 58, Directly related to ultimate goal. Crashes are rare events; difficult to estimate.
1.3.1 Before-after study 158, 1, 130 Most common study type. No control site; regression toward mean.
1.3.2 Before-after study with control 120 Control adds rigor. Regression toward mean.
1.3.3 Before-after-before study   More convincing causal effect. Regression toward mean.
1.3.4 Regression model   Directly account for multiple factors. Large amounts of data on many variables.
1.3.5 Empirical Bayes   Control for regression toward mean. More complicated statistical model.
1.3.6 Full Bayes   More complete treatment of conditional probabilities. Not widely used.
2.0 Crashes: Laboratory      
2.1 Driving simulator      
2.1.1 Participant: selected, sampled 70 Know participant sample. Possible sampling bias.
2.1.2 Experimenter: remotely present, unobtrusive observation 70 More experimenter control. Possible artificial participant behaviors.
2.1.3 Stimuli: simulated, artificial; consistent, controlled 70 Extremely repeatable stimulus conditions. Artificial stimuli; hard to simulate conspicuity and legibility.
2.1.4 Responses: programmed crashes; antecedent participant and vehicle behaviors; can be more frequent crashes 70 Some control over crashes; can program more frequent crash opportunities. Lack of negative consequences can unnaturally alter frequency of crashes.
2.1.5 Scenario: contrived route, artificial; unnatural vehicle and environment; safe from harm 70 Control over driving scenario; participant safe from harm. Unnatural vehicle and environment; artificial scenario; simulator sickness.
2.2 Non-simulator laboratory 87    
2.2.1 Crash scenarios: movies, pictures, acting out   Relatively easy; less resources. Artificial, out-of-context testing environment.
2.2.2 Crash reconstructions: questionnaires, focus groups   Relatively easy; focus groups more expensive. Artificial, out-of-context testing environment; focus group social biases.
3.0 Safety Surrogate: Field 34, 85    
3.1 Unobtrusive observation      
3.1.1 Participant: random, uncontrolled; usually unknown 15 No sampling bias. Do not know participant sample.
3.1.2 Experimenter: usually absent; remote observation; unknown to participant 15 No artificial participant behaviors due to experimenter.  
3.1.3 Stimuli: natural, ordinary, in context; variable, uncontrolled 15 Natural stimuli. Stimuli not uniform; e.g., weather effects.
3.1.4 Responses: crash precursors; antecedent vehicle behaviors; more frequent; few participant variables 15 More frequent events than crashes; can collect more data with less risk. Crash precursors only indirect indicators; insensitive to participant variables.
3.1.5 Scenario: natural route and trip purpose; uses own vehicle 15 Completely natural experimental context; uses own vehicle.  
3.2 Naturalistic driving      
3.2.1 Participant: selected, sampled 79, 78, 42 Know participant sample. Possible sampling bias.
3.2.2 Experimenter: absent; remote observation; known to participant 79, 78, 42   Possible artificial participant behaviors.
3.2.3 Stimuli: natural, ordinary, in context; variable, uncontrolled 79, 78, 42 Natural stimuli. Stimuli not uniform; e.g., weather effects.
3.2.4 Responses: crash precursors; antecedent vehicle and participant behaviors; more frequent events 79, 78, 42 More frequent events than crashes; can collect more data with less risk. Crash precursors only indirect indicators.
3.2.5 Scenario: natural route and trip purpose; uses own vehicle 79, 78, 118, 42 Mostly natural experimental context; uses own or long-term borrowed vehicle. Participant aware of test status; may be injured or killed; vehicle may be damaged or destroyed; expensive.
3.3 On-road instrumented vehicle 14    
3.3.1 Participant: selected, sampled 54, 18 Know participant sample. Possible sampling bias.
3.3.2 Experimenter: present; direct observation and interaction 83 More experimenter control; increased experiment safety. Possible artificial participant behaviors.
3.3.3 Stimuli: selected; natural, in context 83, 18 Natural stimuli. Stimuli not uniform; e.g., weather effects.
3.3.4 Responses: crash precursors; antecedent vehicle and participant behaviors; more frequent 54, 18 More frequent events than crashes; can collect more data with less risk. Crash precursors only indirect indicators.
3.3.5 Scenario: natural route, artificial trip purpose; uses experimental vehicle 54, 83, 18 Semi-natural experimental context; more safe. Artificial trip purpose; unfamiliar vehicle.
3.4 Closed-course test track      
3.4.1 Participant: selected, sampled 136 Know participant sample. Possible sampling bias.
3.4.2 Experimenter: present; direct observation and interaction 136 More experimenter control; increased experiment safety. Possible artificial participant behaviors.
3.4.3 Stimuli: selected; out of context 136 Semi-natural stimuli. Stimuli not uniform; some possible control.
3.4.4 Responses: crash precursors; antecedent vehicle and participant behaviors; more frequent 136 More frequent events than crashes; can collect more data with less risk. Crash precursors only indirect indicators.
3.4.5 Scenario: unnatural route, artificial trip purpose; uses experimental vehicle 136 Low probability of harm to participant or vehicle. Unnatural experimental context.
3.5 Commentary driving      
3.5.1 Participant: selected, sampled 36 Know participant sample. Possible sampling bias.
3.5.2 Experimenter: present; direct observation; extensive interaction 36 More experimenter control; increased experiment safety. Possible artificial participant behaviors.
3.5.3 Stimuli: selected; natural, in context 36 Natural stimuli. Stimuli not uniform; e.g., weather effects.
3.5.4 Responses: extensive driver commentary; running verbal description; crash precursors observable   Collect large amounts of data; direct observation of gross attention. Commentary could interfere with driving task; artificial task.
3.5.5 Scenario: natural route, artificial trip purpose   Semi-natural experimental context; more safe. Artificial trip purpose.
3.6 Non-vehicle based field testing      
3.6.1 Roadside interviews 14, 125, 85 Relatively easy; less resources. Artificial, distal testing environment.
3.6.2 Fuel station, nearby mall interviews   Relatively easy; less resources. Artificial, out-of-context testing environment.
4.0 Safety Surrogate: Laboratory 36    
4.1 Driving simulator      
4.1.1 Participant: selected, sampled 161, 4, 70, 82 Know participant sample. Possible sampling bias.
4.1.2 Experimenter: remotely present, unobtrusive observation 161, 4, 70, 82 More experimenter control. Possible artificial participant behaviors.
4.1.3 Stimuli: simulated, artificial; consistent, controlled 161, 4, 70, 82 Extremely repeatable stimulus conditions. Artificial stimuli; hard to simulate conspicuity and legibility.
4.1.4 Responses: programmed crash precursors; antecedent participant and vehicle behaviors; can have more frequent events 10, 82, 4 Some control over near-crashes; can program more frequent near-crash opportunities. Lack of negative consequences can unnaturally alter frequency of near-crashes.
4.1.5 Scenario: contrived route, artificial; unnatural vehicle and environment; safe from harm 161, 4, 70, 82 Control over driving scenario; participant safe from harm. Unnatural vehicle and environment; artificial scenario; simulator sickness.
4.2 Non-simulator laboratory 75    
4.2.1 Pre-crash scenarios: movies, pictures, acting out 160, 36 Relatively easy; less resources. Artificial, out-of-context testing environment; weak response measure.
4.2.2 Pre-crash reconstructions: questionnaires, focus groups 36 Relatively easy; focus groups more expensive. Artificial, out-of-context testing environment; weak response measure; focus group social biases.
5.0 Social Survey 14, 125    
5.1 Telephone survey   Less resources; personal interviewer; more flexible. Out of context; opinions only; more labor intensive; smaller scale.
5.2 Mail survey   Less resources; standardized; larger scale. Out of context; opinions only.
5.3 E-mail survey   Less resources; standardized; large scale. Out of context; opinions only; internet user bias.
6.0 Analytical Study      
6.1 Literature review 53, 38, 26, 129, 52 Benefit from previous knowledge and mistakes. Based on old information; abstract; hard to apply.
6.2 Review of practice 15, 44 Socially oriented, practical, legal. Based on old information; not scientific; possibly misleading.
6.3 Deductive-inductive reasoning study 26 Less resources; no need for new data. Must often make dangerous assumptions; cannot fill in knowledge gaps.
Updated: 09/05/2014
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