July 1983 DOT HS-806-430

Technical Report

US. Department

of Transportation

National Highway

Traffic Safety

Administration

An Evaluation of Side

Marker Lamps for Cars,

Trucks and Buses

PLANS AND PROGRAMS

Office of Program Evaluation

This document is available to the U.S. public through the National Technical Information

Service, Springfield, Virginia 22161
Technical Report Documentation Page

1. Report No.

DOT HS-806 430

2. Government Accession No. 3. Recipient's Catalog No.

4. Title and Subtitle

An Evaluation of Side Marker Lamps

for Cars, Trucks and Buses

5. Report Date

July 1983

6. Performing Organization Code

NPP-10

7. Author's)

Charles Jesse Kahane, Ph.D.

8. Performing Organizotion Report No.

9, Performing Organization Name and Address

Office of Program Evaluation

National Highway Traffic Safety Administration

400 7th St., S.W.

Washington. D.C. 20590

10. Work Unit No. (TRAIS)

1 1. Contract or Grant No.

12. Sponsoring Agency Name and Address

U.S. Department of Transportation

National Highway Traffic Safety Administration

Washington, D.C. 20590

13. Type of Report and Period Covered

NHTSA Technical Report

14. Sponsoring Agency Code

15. Supplementary Notes

An agency staff review of an existing Federal regulation performed in response to

Executive Order 12291.

16. Abstract

Side marker lamps were installed in cars, trucks, buses, trailers and multipurpose

passenger vehicles in response to Federal Motor Vehicle Safety Standard 108. The

purpose of side marker lamps is to enable a driver to see another vehicle that is

approaching at an angle at night—and to see it early enough that the driver can

stop in time to prevent a collision or, at least, slow down to reduce the

severity of the collision. The objectives of this agency staff evaluation are

to determine how many accidents, casualties and damages are prevented by side

marker lamps and to measure the actual cost of the lamps. The evaluation is based

on statistical, analyses of North Carolina, Texas and Fatal Accident Reporting

System data, a study of travelling speeds in fatal angle collisions, and cost

analyses of production lamp assemblies. It was found that:

o Side marker lamps annually prevent 106,000 accidents, 93,000 nonfatal

injuries and $347 million in property damage.

o The lamps have not been effective in reducing fatalities.

o They add $21 (in 1982 dollars) to the lifetime cost of owning and operating

a motor vehicle.

17. Key Words

side marker lamp; lighting; conspicuity

side impact; angle collision; accident

analysis; evaluation; statistical

analysis; cost effectiveness.

18. Distribution Statement

; Document is available to the public

through the National Technical Information

Service, Springfield, Virginia 22161.

19. Security Clossif. (of this report)

Unclassified

20. Security Classif. (of this page)

Unclassified

21. No. of Pages

177

22. Price

Form DOT F 1700.7 (8-72) Reproduction of completed page authorized

TABLE OF CONTENTS

Acknowledgements xi

Summary xiii

1. INTRODUCTION AND BACKGROUND 1

1.1 Evaluation of Federal Motor Vehicle Safety Standards 1

1.2 Evaluation of Standard 108 1

1. 3 Side marker lamps. . 3

1.4 Evaluation objectives and limitations 7

2. EARLIER STUDIES OF SIDE MARKER LAMPS 9

2.1 New York State Department of Motor Vehicles (1973) 9

2.2 Joksch (1973) - Texas data 12

2.3 Knoop, Ball and Northrop (1980) 13

2.4 Chi and Easterling (1983) - North Carolina data 17

2.5 Ford Motor Company (1976) 18

2.6 Indiana Tri-Level S tudy 18

2.7 Summary 19

3. DATA FOR ANALYZING SIDE MARKER LAMP EFFECTIVENESS 21

3.1 Data needs and guidelines 21

3.2 North Carolina data 25

3.3 Texas data 27

3.4 Fatal Accident Reporting System 28

3.5 Introduction dates for side marker lamps 29

iii
4. ANALYSES OF CONTINGENCY TABLES 39

4.1 Method 39

4.2 Accidents of all severities 42

4.2.1 North Carolina 42

4.2.2 Texas 46

4.3 Injury accidents ^8

4.3.1 North Carolina

 5 0

4.3.2 Texas

 5 2

4.4 Fatal accidents 54

4.5 Analyses for a control group of head-on and rear-end crashes 56

4.5.1 North Carolina 56

4.5.2 Texas 60

4.5.3 Fatal Accident Reporting System 62

4.6 Discussion 66

5. REGRESSION ANALYSES 69

5.1 Method 69

5.2 Accidents of all severities 75

5.2.1 North Carolina 75

5.2.2 Texas .80

5.3 Injury accidents 86

5.3.1 North Carolina 86

5.3.2 Texas ...89

5.4 Fatal accidents 89

5.5 Analyses for a control group of head-on and rear-end crashes 94

5.5.1 North Carolina 94

5.5.2 Texas 96

5.5.3 Fatal Accident Reporting System 100

iv
6. FATAL INVOLVEMENTS PER 1000 VEHICLE YEARS 105

6.1 Method, and exposure data sources 105

6.2 Tabulation of accident rates 106

6.3 Regression of accident rates 109

6.4 Analyses for a control group of head-on and rear-end crashes

7. "BEST" ESTIMATES OF SIDE MARKER LAMP EFFECTIVENESS 117

7.1 Effectiveness estimates from Chapters 4-6 117

7.2 "Best" estimates for nonfatal crashes 120

7.2.1 Accidents of all severities 121

7.2.2 Injury accidents 123

7.3 "Best" estimates for fatal crashes J-25

7.3.1 Statistical results J-25

7.3.2 Analysis of travelling speeds in fatal crashes 125

8. COSTS AND BENEFITS 131

8.1 Costs 131

8.2 Benefits J-36

8.3 Cost-effectiveness 143

References 147

Appendix A: Tabulations of North Carolina, Texas and fatal accidents 151

Appendix B: Programs and printouts for North Carolina analyses

Appendix C: Programs and printouts for Texas analyses

Appendix D: Programs and printouts for FARS analyses

Unpublished computer printouts
LIST OF TABLES

Table 3-1 Percent of new cars, trucks and buses equipped with side

marker lamps, by model year 32

3-2 Side marker lamp equipment on domestic cars, by model year,

make and model 33

3-3 Registered cars and trucks, by model year, in a given

calendar year (000) 36

3-4 Percent of registered vehicles equipped with side marker lamps,

by calendar year 37

4-1 North Carolina 1971-80: angle collision involvements by side

marker lamp status and light condition 43

4-2 North Carolina "refined test group" 1971-80: angle collision

involvements by side marker lamp status and light condition 45

4-3 Texas 1972-74: angle collision involvements by side marker

lamp status and light condition 47

4-4 North Carolina injury accidents 1971-80: anglt collision

involvements by side marker lamp status and light condition .49

4-5 North Carolina injury accidents, 1971-80, "refined test group":

angle collision involvements by side marker lamp status and

light condition ^

4-6 Texas injury accidents, 1972-74: angle collision involvements

by side marker lamp status and light condition 53

4-7 U.S. fatal accidents, 1975-81: angle collision involvements by

side marker lamp status and light condition 55

4-8 North Carolina, 1971-80: control group collision involvements

by side marker lamp status and light condition 57

4-9 North Carolina injury accidents, 1971-80: control group

collision involvements by side marker lamp status and light

condition 59

4-10 Texas 1972-74: control group collision involvements by

side marker lamp status and light condition 61

4-11 Texas injury accidents, 1972-74: control group collision

involvements by side marker lamp status and light condition 63

4-12 U.S. fatal accidents, 1975-81: control group collision

involvements by side marker lamp status and light condition ..65

vi
5-1 North Carolina 1971-80: angle collisions of all severities 79

5-2 North Carolina (refined test group) 1971-80: angle collisions

of all severities 81

5-3 Texas 1972-74: angle collisions of all severities.,., 8 5

5-4 North Carolina 1971-80: injury-producing

angle collisions 37

5-5 North Carolina (refined test group) 1971-80: injury-producing

angle collisions 88

5-6 Texas 1972-74: in jury-producing angle collisions 90

5-7 FARS 1975-81: fatal angle collisions 93

5-8 North Carolina control group.1971-80: head-on and rear-end

collisions of all severities 97

5-9 North Carolina control group 1971-80: injury producing head-on

and rear-end collisions 98

5-10 Texas control group 1972-74: head-on and rear-end collisions

of all severities

5-11 Texas control group 1972-74: injury-producing head-on and

rear-end collisions

6-4 FARS control group 1975-81: fatal nighttime head-on and rear-end

collisions per 1000 vehicle years

101

102

5-12 FARS control group 1975-81: fatal head-on and rear-end

collisions 104

6-1 U.S. fatal accidents 1975-81: nighttime angle collision

involvements per 1000 vehicle years, by side marker lamp status 10 7

6-2 FARS 1975-81: fatal nighttime angle collisions per 1000 vehicle

years

y Ill

6-3 U.S. fatal accidents, 1975-81: nighttime head-on and rear-end

collision involvements, per 1000 vehicle years, by side marker

lamp status 113

115

vii
7-1 Summary of effectiveness estimates for side marker lamps in

Chapters 4-6 118

7-2 North Carolina and Texas, combined: angle collisions of all

severities 122

7-3 North Carolina and Texas, combined: injury-producing angle

collisions 124

8-1 Cost and weight added by side marker lamps 133

8-2 Benefits of side marker lamps - 144

viii
LIST OF FIGURES

Figure 5-1 North Carolina: proportion of angle collisions occurring

at night, by model year and calendar year 76

5-2 North Carolina: proportion of angle collisions occurring

at night, by vehicle age and calendar year 7 7

5-3 Texas: proportion of angle collisions occurring at night,

by model year and calendar year 82

5-4 Texas: proportion of angle collisions occurring at night,

by vehicle age and calendar year 84

5-5 FARS: proportion of fatal accidents occurring at night,

by model year and calendar year. b 91

5-6 North Carolina control group: proportion of head-on and

rear-end crashes occurring at night, by vehicle age and

calendar year 95

5-7 Texas control group: proportion of head-on and rear-end

crashes occurring at night, by vehicle age and calendar year 99

IX
LIST OF ABBREVIATIONS

AMA Automobile Manufacturers Association (now known as MVMA)

AMC American Motors Corporation

CY Calendar Year

df degrees of freedom

FARS Fatal Accident Reporting System

MVMA Motor Vehicle Manufacturers Association

MY Model Year

NAS National Accident Summary

NASS National Accident Sampling System

NHTSA National Highway Traffic Safety Administration

SAE Society of Automotive Engineers

SAS Statistical Analysis System

SML Side Marker Lamp

TAD Traffic Accident Data project accident severity scale
ACKNOWLEDGEMENTS

I thank Roman Brooks, Kevin Cavey, Mike Perel and Taylor Vinson

for reviewing the manuscript and for their helpful suggestions on

data sources and analysis methods.

Alleyne Monkman and Michele Stewart typed the report.

xi
SUMMARY

The most notable change in motor vehicle lighting during the

period 1965-75 was the installation of side marker lamps on most cars,

trucks and buses in 1968. Before that year, most vehicles did not have

any illumination visible from the side. The purpose of side marker

lamps is to enable a driver to see another vehicle that is approaching

at an angle at night (or is standing still with its side facing the

driver)—and to see it early enough that the driver can stop in time to

prevent a nighttime angle collision or, at least, slow down or take

evasive action to reduce the severity of the collision.

Federal Motor Vehicle Safety Standard 108 regulates the lamps,

reflectors and associated equipment for cars, trucks, trailers, buses,

multi-purpose passenger vehicles and motorcycles. It became effective on

January 1, 1968, for vehicles wider than 80 inches (large trucks and buses)

and on January 1, 1969, for the other vehicles.

Executive Order 12291 (February 1981) requires agencies to evaluate

their existing major regulations, including any rule whose annual effect

on the economy is $100 million or more. The objectives of an evaluation

are to determine the actual benefits - lives saved, injuries prevented,

damages avoided - and costs of safety equipment installed in production

vehicles in response to a standard and to assess cost-effectiveness.

This report is an evaluation of side marker lamps for cars, trucks,

vans and buses—the only significant change in the lighting systems of

xiii
production vehicles that more or less coincided with the effective

date of Standard 108. They were introduced voluntarily by manufacturers,

typically one year before the standard's effective date. The other

lighting systems of motor vehicles (headlamps, brake lights, etc.) for

the most part already met Standard 108 many years in advance because

they complied with SAE Standards and Recommended Practices that were

incorporated, by reference, into Standard 108.

Estimates of the number of accidents and casualties prevented by

side marker lamps were obtained by statistically analyzing accident data

from the North Carolina and Texas State files and the Fatal Accident

Reporting System. The analyses of nonfatal accidents resulted in precise,

statistically significant effectiveness estimates. The analyses of fatal

crashes did not produce statistically significant estimates and were

supplemented by an engineering study: did drivers in fatal crashes have

enough room to stop or slow down after they saw the lamps? The cost of

side marker lamps was estimated by analyzing lamp components of a

representative sample of cars and by obtaining data on repair frequencies

and costs.

The evaluation does not develop a detailed model which predicts

side marker lamp effectiveness as a function of their intensity, size,

luminance or as a function of accident parameters. That model could be

useful for studying the effect of potential changes in side marker lamp

requirements, but the in-depth accident and laboratory data that would

be needed to develop it do not exist at this time. Instead, the

xiv
evaluation is limited to assessing the actual costs and benefits of

current production lamps—whose design has remained largely unchanged

during 1970-83.

The most important conclusion of this study is that side marker

lamps are effective in preventing nonfatal accidents and injuries—close

to 100,000 of each per year. The conclusion is based almost entirely on

statistical analyses of accident data, yet can be drawn firmly because

of the exceptional precision and consistency of those analyses:

o Identical results were obtained from North Carolina and Texas.

o Two virtually independent analysis techniques were used on

each file. One was straightforward (simple comparison of model years

1967 when most vehicles did not have the lamps and 1968 when most did)

and the other complex (regression): they produced the same effectiveness

estimate.

o Several techniques were used to check for biases in the

effectiveness estimates. They suggested that the estimates were unbiased,

The other conclusion is that side marker lamps had little or no

effect on fatalities. The conclusion is based on a combination of

statistical analysis and engineering judgement and it is less firm than

the preceding one. The statistical analysis of fatal crashes yielded an

effectiveness estimate just below zero but (because the Fatal Accident

Reporting System is a smaller file than North Carolina or Texas) with

relatively wider confidence bounds including a range of positive and

negative values. The engineering analysis did not yield a specific

xv
estimate but did suggest that the effect, if any, was a fraction of the

one in nonfatal crashes. The conclusion that the actual effect is

essentially zero is conservative and consistent with both analyses.

The principal findings and conclusions of the study are the

following:

Principal Findings

Effectiveness of side marker lamps

o If none of the cars, trucks and buses operating on the roads

during 1980 had been equipped with side marker lamps there would have

been 661,000 police-reported nighttime angle collisions. If all of

those cars, trucks and buses had been equipped with side marker lamps,

there would only have been 555,000 collisions. In other words, the

lamps reduce the number of nighttime angle collisions by 16 percent.

The accident reduction is statistically significant (confidence bounds:

10 to 22 percent).

o Side marker lamps reduce the number of personal injuries in

nighttime angle collisions by 21 percent. The reduction is statistically

significant (confidence bounds: 12 to 29 percent).

o The statistical analyses of fatal angle collisions did not

indicate a significant effect for side marker lamps (confidence bounds

for effectiveness: -25 to +13 percent). An analysis of crash speeds,

xvi
sighting and stopping distances suggested that the effectiveness of side

marker lamps in fatal crashes, if any, is at most 1/4 as high as in

nonfatal crashes: at the travelling speeds prevalent in most fatal crashes,

either the lamps are seen too late for drivers to react to them and stop or

slow down or the headlamps are more readily visible than the side marker lamps.

Cost

o The costs per vehicle (in 1982 dollars) for side marker lamps

are the following:

Initial purchase price increase $16.76

Lifetime fuel consumption due to

2 pound weight increase 2.00

Lifetime fuel consumption: electric

power to light the lamps 2.19

Lifetime cost of replacement bulbs 0.27

TOTAL COST PER VEHICLE $21.22

o The annual cost of side marker lamps in the United States

(based on 12.3 million cars, trucks and buses sold) is $261 million.

xvii
Annual benefits

o The annual benefits, when all cars, trucks and buses in the

United States have side marker lamps, will be:

Reduction of Best Estimate Confidence Bounds

Police-reported accidents 106,000 65,000 - 149,000

Nonfatal injuries 93,000 51,000 - 132,000

Property damage $347M $213 - 488M

Cost-effectiveness

o Since side marker lamps save 93,000 injuries and cost $261

million, they eliminate 360 injuries per million dollars of cost

(confidence bounds: 200 to 500).

o Since side marker lamps save $347 million in property damages

and cost $261 million, they save consumers $86 million per year (confidence

bounds: -48 to +227 million dollars saved per year).

xviii
Conclusions

o Side marker lamps have significantly reduced the number of

nighttime angle collisions that occur in the United States.

o The lamps have significantly reduced the number of nonfatal

injuries that occur in nighttime angle collisions, because they reduce

the severity of accidents and/or prevent them entirely.

o The lamps have little or no effect on fatalities. Most

fatal nighttime angle collisions involve one of the vehicles travelling

at high speed or both vehicles travelling at similar speeds. In the

first case, by the time that the high-speed driver sees the other vehicle's

side markers, there is no longer room to stop or substantially slow down;

in the second case, each driver can see the other vehicle's headlamps more

easily than the side marker lamps.

o Side marker lamps are a cost-effective safety device.

xix
CHAPTER 1

INTRODUCTION AND BACKGROUND

1.1 Evaluation of Federal Motor Vehicle Safety Standards

Executive Order 12291, dated February 17, 1981, requires

Federal agencies to perform evaluations of their existing regulations,

including those rules which result in an annual effect on the economy

of $100 million or more [8]. The evaluation shall determine the actual

costs and actual benefits of the existing rule.

The National Highway Traffic Safety Administration began to

evaluate its existing Federal Motor Vehicle Safety Standards in 1975.

Its goals have been to monitor the actual benefits and costs of safety

equipment installed in production vehicles in response to standards

and, more generally, to assess whether a standard has met the specifications of the National Traffic and Motor Vehicle Safety Act of

1966 [2ll: practicability, meet the need for motor vehicle safety,

protect against "unreasonable" risk of accidents, deaths or injuries,

provide objective criteria. The Agency has published 7 comprehensive

evaluations to date.

1.2 Evaluation of Standard 108

Federal Motor Vehicle Safety Standard 108 regulates lamps, reflective devices and associated equipment for passenger cars, trucks, trailers,

buses, multipurpose passenger vehicles and motorcycles [6]. Standard 108

took effect for motor vehicles wider than 80 inches (mostly large trucks and
buses) on January 1, 1968, and for motor vehicles less than 80 inches

wide (cars, light trucks, motorcycles, etc.) on January 1, 1969, with

a number of subsequent amendments. The lighting systems covered by

the standard include headlamps, taillamps, brake, license plate, parking,

side marker, backup, warnings identification and clearance lights, turn

signals, and the lenses, reflectors, and flashers associated with the

lights.

Standard 108 incorporates by reference a large number of SAE

Recommended Practices and Standards concerning lighting and makes them

mandatory for vehicles sold in the United States. The SAE Recommended

Practices cover each of the lighting systems in detail and in many cases

were written well before Standard 108, in some cases before 1940. The

development of lighting systems for vehicles has proceeded on a

more or less continuous basis during the 20th century. In most of the

lighting systemss Standard 108 did not result in dramatic changes but

tended to codify existing practices. Likewise, in most of the lighting

systems, there were no major changes made voluntarily by manufacturers

during, or just before, the period when Standard 108 took effect.

Side marker lamps are the one important exception. They were

voluntarily installed on most model year 1968 cars and light trucks-—two

years before Standard 108 required them and 4 years after the SAE issued

Recommended Practice J592 for optional side marker lamps—whereas most

1967 models had no side marker lamps or other form of illumination

visible from the side. Their objective is to enable a driver to see
another vehicle approaching at an angle, at night. Since nighttime

angle collisions are extremely common events (660,000 per year reported

in the United States)9 side marker lamps address an important safety

problem and, potentially, have large safety benefits.

By contrast, other vehicle lighting changes took place

many years before or after the implementation of Standard 108. They

were modifications of existing systems rather than introductions of

new ones and/or had more limited potential for safety benefits.

Other principal changes were: the use of 4 headlamps with separate

high beams, introduced in many 1958 models—but the earlier 2 headlamp

systems with combined high and low beams performed basically the same

functions. Backup lights were introduced in 1962, 7 years before

Standard 108—but collisions involving a backing vehicle are much

rarer than nighttime angle collisions, especially at higher levels of

severity. Standard 108 was amended to allow a more powerful upper beam

in headlamps beginning model year 1979—10 years after the effective

date of the original standard. Moreover, the use of more powerful

headlamps is an option, not a requirement and the lamps were only

installed on certain makes and models.

1.3 Side marker lamps

Standard 108 currently requires that passenger cars, trucks,

buses, trailers and multipurpose passenger vehicles have side marker

lamps at the front end and rear of each side of the vehicle. The front

lamp must be amber and the rear lamp red. They should be as close to

the end of the vehicle as possible and not less than 15 inches above the
ground. There are to be reflex reflectors, also, at the same general

location and of the same colors. If the vehicle is more than 30 feet

long, there shall be additional amber lamps and reflectors, one on each

side, at the midpoint of the side of the vehicle.

Standard 108 incorporates, by reference, SAE Recommended

Practice J592 on side marker lamps (and also clearance and identification

lamps) [23l. The Recommended Practice itself has been revised many times,

but its clauses referring to side marker lamps have remained virtually

unchanged since 1964; it requires a minimum candela of 0.62 for the

amber lamps and 0.25 for the red lamps from each of 9 measurement

points.

The lamps and reflectors became mandatory on vehicles over

80 inches wide on 1/1/68 (large trucks and buses). Narrower vehicles

(mostly cars and light trucks) were required to have the lamps and

reflectors after 1/1/70. Between 1/1/69 and 1/1/70, several options

were available for these vehicles. Manufacturers could use a lamp only,

a reflector only (or both, together) on the front. They had similar

choices available for the rear. They could choose different options

for the front and for the rear. Motorcycles do not have side marker

lamps.

Throughout this report, units that consist of a reflector but

no lamp are not counted as side marker lamps. Thus, the model year

1968 and 1969 cars that have reflectors only, front and rear, are

considered unequipped with SML. Those that have a reflector in the

front and a lamp in the back, or vice versa, are considered "half"
equipped with SML» The report does not separately evaluate the

benefits of reflectors, only of the lamp/reflector system.

The side marker lamps are lit whenever the vehicle's parking

and taillights are on.

In actual practice, two systems have been used to meet the.

requirement for lamps. The more common one is to mount small lamps on

the side of the vehicle—-in or on the fenders. The lens of the lamp

usually serves as a reflex reflector when the lights are off. Manufacturers typically use 2 candlepower bulbs (but the colored and

reflectorized lens reduces the amount of light emitted from the vehicle

to values close to the SAE minimum specifications). The other system

is to design parking and taillamps in a manner to make them visible

from the side of the vehicle—-they are called "wraparound" parking

and taillights in this report and are counted as side marker lamps.

As noted above, the domestic manufacturers installed SML

on most model year 1968 vehicles, one year before reflectors were

required and two years before lamps were mandatory. Nevertheless,

there were some 1968 and 1969 models that only had reflectors at the

front, rear, or both positions (see Section 3.5). All 1970 and

subsequent models have had the full lamp/reflector system at both

positions. Side marker lamps, (usually wraparound parking and taillights) appeared on a number of domestic passenger car models, beginning

in 1964, including all the luxury cars and also such high volume cars

as 1966-67 Chevrolet Impala (see Table 3-2). (There were occasional
models with wraparound lights even prior to 1964.) The voluntary

installation of SML on luxury cars, as well as the marketing of

retrofit kits for unequipped cars by a number of suppliers seems to

indicate that the lamps were appreciated by the public.

The objective of side marker lamps is to make a vehicle

visible from the side to drivers of other vehicles, at night or at

other times when there is reduced -visibility including dawn and

dusk [sl, p. 5-13. The advance warning provided by the lamps has the

potential to enable drivers to avoid a collision when approaching one

another at an angle, at night. The purpose of locating the lamps as

close to the ends of the vehicle as possible is to reveal its length;

the purpose of making the front lamp amber and the rear lamp red is to

reveal the vehicle's direction of travel.

Side marker lamps cannot be expected to prevent daytime

collisions because they are too dim to add appreciably to a vehicle's

conspicuity by day [5*1. They cannot be expected to prevent head-on,

rear-end or sideswipe collisions because they are considerably dimmer

than the headlights or taillights of the other vehicle, which are

usually visible prior to such collisions,

Thus, vehicle-to-vehicle nighttime angle collisions are the

specific type of crash which side marker lamps have the potential to

reduce in frequency or severity. Moreover, inatallation of SML on

either vehicle in a frbnt-to-side collision—the "striking" or the

"struck1* vehicle—might have been beneficial in preventing that

collision: when two vehicles approach each other at an angle, each
driver potentially has an opportunity to see the side of the other

vehicle and take action to avoid a collision (see Section 3.1). Also,

the determination of which vehicle is "striking" and which is "struck"

is not made until the last moments before contact: in many cases the

faster moving vehicle ends up being "struck" in the side. In other

words, SML could reduce the likelihood of a vehicle's involvement in

an angle collision, as a striking vehicle or as a struck vehicle.

1.4 Evaluation objectives and limitations

This report, then, consists of analyses of vehicle

involvements in nighttime angle collisions. The risk of nighttime

angle collision involvements, for vehicles of a certain model year,

is .expressed as a ratio of nighttime to daytime involvements (the

latter being unaffected by SML) in Chapters 4 and 5 or as a rate of

nighttime involvements per 1000 exposure years in Chapter 6. Since

1968 was the first year in which SML were installed in most vehicles,

the analyses of Chapter 4 focus on the accident experience of model

year 1968 versus model year 1967 vehicles. Chapter 5 considers a

wider range of model years (1964-72) and performs regressions on the

ratio of nighttime to daytime crashes as a function of SML installation,

vehicle age and other factors.

Since cars, trucks (including vans) and buses are equipped

with side marker lamps, all 3 types of vehicles are included in the

data. In fact, this is the first NHTSA evaluation that is not limited

to passenger cars.
The objective is to find out how many fewer nighttime angle

collisions there would be each year if every registered car, truck

and bus in the United States were equipped with side marker lamps

than if none of the vehicles on the road in this country had any side

marker lamps.

Likewise, the cost of side marker lamps is the average

annual fleetwide costs of lamps relative to a baseline case of vehicles

that have no side marker lamps at all. The cost includes the increase

in the initial purchase price of a vehicle, incremental fuel consumption

and any growth in repair costs.

line evaluation does not contain in-depth accident analyses

to show how side marker lamps helped prevent (or failed to prevent)

an individual accident. It does not develop a detailed model which

predicts SML effectiveness as a function of their intensity, size,

luminance or as a function of accident parameters (although the

rudiments of such a model are discussed in Section 7.3.2). Accident

and laboratory data are unavailable for either of those efforts.

Instead, the evaluation is based on statistical analyses of accident

data files that are considerably larger than any that were previously

used to study SMI, (see Chapter 2) and which, as a result, have generated

unambiguous, statistically significant results.
CHAPTER 2

EARLIER STUDIES OF SIDE MARKER LAMPS

There are four published studies of side marker lamp

effectiveness based on statistical analysis of State accident data.

All were performed under contract to NHTSA. One engineering study

of side marker lamps was found in the Agency's public dockets.

2.1 New York .State_Jtej^artment of Motor Vehicles (1973)

New York State accident files for 1968 and 1969 were

analyzed by the Department of Motor Vehicles under contract to NHTSA

L.22J . The effectiveness of side markers lamps was studied by tabulating

vehicle involvements in two-car intersection accidents. The vehicle

involvements were tabulated by

o side marker lamp status: MY 1968-69 - Yes; MY

1965-67 - No;

o light condition: Daylight; Dawn, dusk, or night

The resultant table was

65-67 68-69

Daylight 38,116 30,410

Reduced light 18,262 14,252

The table is comparable to those shown in Chapter 4 of

this report and can be analyzed by the same method. In other words,

it indicates that the installation of side marker lamps on one car

reduces its likelihood of nighttime intersection collision involvements

by

14»2 5 2

I - — — —. / — ~ « 2 percent

30,410 / 38,116
Since the chi-square for the table is 2.64, the reduction is not

statistically significant (one sidedoC= .05) although it comes close.

(Note that the chi-square of 74.2 reported for Table 4 of [22! is

inappropriate for the analysis of side marker lamp effectiveness

because the table includes an irrelevant control group.) The reduction

is lower than the 7-8 percent observed in the North Carolina and

Texas analyses of this report. A possible explanation for at least

part of the difference is that the category of "intersection accidents,"

as defined in New York data, may contain many crashes that were

not really angle collisions9 but merely occurred at an intersection.

The study contains data that make it possible to

analyze effectiveness by a different approach (although the analysis

itself is not presented injj22j). The next table is a subset of

preceding table, limited to those accident involvements where

both cars in the collision were in the same model year group (pre or post - SML)

65^67? 68^9**

Daylight 26,791 "5,016

Reduced light 12,823 2,208

* Other car in the collision: MY 50-67

Other car in the collision: MY 68-69

This table is essentially comparable to the approach used by Knoop,

Ball and Northrop to calculate "full effectiveness" (see Section 2.3).

It indicates that the installation of side marker lamps on two

cars reduces the likelihood of nighttime intersection collisions by

10
12^823 . 8 percen t

5016 26,796791

Since the chi-square is 9.14S the reduction is statistically significant.

The reduction, however, is lower than the 15 percent, derived in

this report, for equipping both vehicles with SML. Again, a possible

explanation is that "intersection collisions" include many accidents

that are not really angle collisions.

The efficacy of SML in injury-producing accidents was

tested by tabulating the fatal and serious (K or A--level) injuries,

as follows:

K + A

65-67* 6*H69**

Daylight 1045 163

Reduced light 749 83

*0ther car in the collision: MY 50-67

**0ther car in the collision: MY 68-69

(Note that the data are derived from Table 5 °f(22j

 and no t Table

6, where the SML-equipped sample size was inflated to equal the

pre-standard sample and an inappropriate chi-square was calculated.)

The table indicates a 29 percent reduction of injuries for side

marker lamps. Since chi-square is 5.75, the reduction is statistically

significant. The effectiveness is, in fact, considerably higher than

the levels obtained in this report. It should be noted, though, that

the table is based on a small sample (especially in comparison to

those used in this report) and the results could have substantial

sampling error.

11
In short, the New York study indicated that side marker

lamps significantly reduced nightime intersection collisions.

2.2 Joksch (1973) - Texas data

State accident files from Texas for 1971 and 1972 were

analyzed by Joksch f 12"]. He selected passenger cars that were struck

in the side, with some damage to the passenger compartment (TAD codes

LP, RP, LFQ, RFQ, LBQ, RBQ). It is a conservative approach, because

these are the cars most likely to have been visible from the side

immediately prior to the collision -i.e. the cars where side marker

lamps might have the largest potential effect. Necessarily, the

approach reduces the available sample size, because it excludes cars

in angle collisions that were damaged on the front or corners and

which, prior to the collision, might also have presented a side

view to the other car.

Joksch tabulated the side impact involvements by model

year and light condition (daytime vs. nighttime). About U percent

of the side impacts of 1967 cars happened at night versus just 13

percent for the 1968 cars. In relative terms, this is a reduction of

= 8 percent

in the likelihood of nighttime angle collisions, which is virtually

identical to the reductions found in this report.

Joksch notes, however, that there may have been a slight

(although nonsignificant) trend toward fewer nighttime accidents,

relative to daytime, in the model years before and after 1967-68.

If that trend is real and due to vehicle age$ he suggests that the

effect of side marker lamps may only have been to reduce nighttime

12
involvements from 13.5 to 13 percent of side impacts: a relative

reduction of 4 percent. That reduction would still be compatible

with the results of this report.

2. 3 Knoo^p, Ball and Northrop (1980)

Texas, New York and North Carolina data were analyzed under

contract to NHTSA [l?]. The study differs from the preceding two in that

the unit of analysis is an accident rather than a vehicle involvement.

Knoop selected the angle collisions involving two passenger cars

which occurred at an intersection or a driveway access and in which

one car had frontal damage and the other, side damage. Accidents

may belong to one of three categories with respect to side marker

lamps: neither car has SML, one car has them, both cars have them.

Thus, two measures of effectiveness were calculated:

o "full" effectiveness: both cars with SML versus

neither car with them

o "partial" effectiveness: one car with SML versus

neither car with them

The measure of effectiveness is the reduction of nighttime angle

collisions relative to daytime angle collisions.

The cars in [iff cover a relatively wide range of model

years and the SML-equipped cars are, on the average, 4-5 years newer

than the unequipped cars. That raises a possibility of vehicle age-related biases. The contractor was directed to control or compensate

for possible biases by the following techniques:

13
Use of control variables (such as rural/urban, type

of highway) and multidimensional contingency table

analysis

Use of a control group of single vehicle crashes. The

reduction of nighttime angle collisions relative to daytime

angle collisions is measured relative to the control

group, as follows:

l -

(Full)

("Number of Daylight Angle"]

I Collision!) between Pte- I

L Standard Vehicles J

f" Number ef Reduced Light")

I Angle Collision* between!

Lprs-Standard Vehicles J

rNumber of Reduced Light ~]

I Angle Collisions between I

LPost-Standard Vehicles J

("Number of Daylight Angle"")

I Collisions between PostLStandard Vehicles J

of Daylight Single *"]

Vehicle Accidents Involving

Lpra-Seandard Vehicle J

TNumber of Reduced Light Single"]

Vshicle Accidents Involving I

„ LPre-Standard Vshicle J

f"Number of Reduced Light Single")

Vehicle Accidents Involving I

LPost-Standard Vehicle J

r"Nu«aber of Daylight Single ~t

Vehicle Accidents Involving

LPost-Standard Vehicle J J

a 100

(Partial)

1 -

of Daylight Angle T

Collisions between Pre~

L Standard Vehicles J

rNumber of Reduced Light "1

j Angle Collisions between I

LPra-Standard Vehicles -*

r Number of Reduced Light Angle "|

I Collisions between One Pre- and I

x L One Post-Standard Vehicle J

C Number of Daylight Angle

j Collisions between One

L and One Poat-Standard Vehicle

1 . -]

Prel/ehicle J

f°Ku»b»r of DayliRht Single |

Vehicle Accidents Involving

L Pre-Standard Vehicle ->

r Numbar of Reduced Light Singlt

I Vehicle Accidents Involving

L Pre-Standard Vehicle

r Number of Reduced Light Single"]

I Vehicle Accidents Involving

x L Post-Standard Vehicle J

THumber of Daylight Single

Vehicle Accident! Involving

L Post-Standard Vehicle

x 100

14
The specific data sets used for the analysis were

Texas 1972, 73 and 74; New York 1974; and North Carolina 1973, 74 and

75. The Texas sample was 5 times as large as the other two.

The effectiveness of side marker lamps (percentage of

nightirae angle collisions eliminated) was

Full Effectiveness Partial Effectiveness

Texas 72-74

New York 74

North Carolina 73-75

3 States combined

Estimate

17

13

27

18

Confidence

Bounds*

14-21

3-22

19-34

14-22

Estimate

12

1

16

11

Confidence

Bounds*

9-15

-7-10

9-23

8-14

*one-sided/.=.05

Agency staff reviewed the results and concluded that

further analyses on side marker lamps should be performed, in part

on the same data sets, using different analytic techniques. The

reasons for that conclusion were:

o The full and partial accident avoidance estimates

of 18 and 11 percent, respectively, were higher than

those in the two preceding publications. They also

appeared high relative to "intuitive" expectations of

the effect of SML. That by itself was sufficient

motivation to check the results by using other analysis

techniques.

15
o Subsequent Agency experience gained in preparing an

evaluation of head restraints [l4] , Sections 5.3 and

5.6, provided insights on analysis of State data. It

showed that the use of a wide range of model years creates

a risk of vehicle-age related biases and that, with

State data, control variables and multidimensional

contingency table analyses do not appear to compensate

for much of the biases. Likewise, the use of a control

group consisting of a different crash mode may not

result in an appropriate correction for bias - especially

when the test and control groups are as dissimilar as

angle collisions and single-vehicle crashes. Indeed,

Knoop et al. found that both of these control techniques

had less than 1 percent effect on their overall effectiveness

estimates. It was found that the most suitable control

techniques with State data are to restrict the range

of model years as much as possible ( as in Section

5.6,2 of [lAj or Chapter 4 of this report) or to perform

regressions (as in Section 5.6.3 of (l4J or Chapter 5

of this report).

o 1969 was used as the initial model year that cars

has SML; in fact most new cars had them in 1968. This

creates a bias against side marker lamps in Knoop et

al's work (although the bias is relatively small in

view of the wide range of model years included in the

analysis).

16
2.4 Chi and Easterling (1983) - North Carolina data

Under contract to NHTSA, the Highway Safety Research Center

extracted records of cars, trucks and buses involved in angle collisions

in North Carolina during 1971-80 and ran preliminary regressions

on the ratios of nighttime to daytime collisions. The preliminary

regressions included vehicles of model years 1960-80. They generated

effectiveness estimates with obvious biases -viz., identical regressions

for a control group of rear-end and head-on collisions produced strongly

negative results. Based on a similar experience with Texas data on

side door beams [l5] , p. 277, C.J. Kahane, the NHTSA Contract Technical

Manager, concluded that the biases could be removed by limiting the

data to a narrower range of model years. Kahane performed the analyses

of Chapters 4 and 5 of this report, using Chi and Easterling1s accident

tabulations.

Chi decided, however, to independently pursue the same

method for controlling biases and produced a report \jt\ very similar

to Chapter 5 of this study, submitting it to NHTSA after Chapter 5 was

completed. The reports differ only in that

o Using information supplied by NHTSA, Chi assumed that all

MY 68 and 69 cars had SML. Subsequent investigation indicated that 12 percent

of MY 68 cars and 15 percent of MY 69 cars did not.

o Chapter 5 uses model years 1964-72; Chi uses model years

1964-71 and subsets thereof.

Given these minor discrepancies, it is reassuring to note

that Chi's results (15 percent accident reduction and 20 percent injury

reduction - see the second lines of Tables 10 and 11, respectively) are

nearly the same as the findings of this report (16 and 21 percent, respectively)

17
2.5

One engineering study of side marker lamps was found in

the literature and in public dockets. It forms part of a letter from

Ford to NHTSA £l8]. NHTSA had claimed that the rear side marker lamps on

1972-74 Mercury Capria did not conform to the color requirements of

Standard 108. Ford appealed the finding on various grounds, one of

which was ineonsequentiality to safety. Specifically, Ford pointed

out that the headlamps and taillamps of those cars were installed in

a manner that their beams could be seen from many points to the

side of the cars leaving just a small region where the side marker

lamps and no other lamps were visible'- Thus, Ford claimed that side

marker lamps had minimal benefits for Capris.

Ford's letter does not address other topics that would have

to be included in a detailed engineering study of SML effectiveness, such

as the distance at which the lamps become visible to an approaching driver

or a comparison of that distance and the, approaching vehicle's stopping

distance.

2.6

The University of Indiana's Tri-Level Study provided

detailed information on the causes of traffic accidents involving 2678

vehiclesf28). The information is often useful in identifying safety

problems relevant to some of the standards. But the Indiana causal

taxonomy ie not suitable for identifying problems relevant to side

marker lamps. The investigators found 10 cars that may have crashed

18
because the vehicle they struck "blended in with the background." But

the data are not further subdivided - as a result, it is unknown

whether any of these were nighttime angle collisions involving a car

without side marker lamps.

2.7

Four published statistical analyses of side marker

lamp effectiveness each strongly support a conclusion that the lamps

significantly reduce nighttime angle collisions. Their effectiveness

estimates are statistically compatible with the findings of this report.

19
CHAPTER 3

DATA FOR ANALYZING SIDE MARKER LAMP EFFECTIVENESS

Records of crash-involved vehicles are extracted from

North Carolina and Texas State accident files and from the Fatal Accident

Reporting System (FARS) for the statistical analyses of side marker lamp

effectiveness described in Chapters 4-7.

3«1 Data needs and guidelines

o Standard 108 requires that side marker lamps be installed

on passenger cars, trucks and buses and multipurpose passenger vehicles.

As a result it is appropriate to include all of these vehicle types in

the study. Only motorcycles, farm vehicles, etc., are excluded.

o The purpose of side marker lamps is to make the side of a

vehicle visible to other drivers. The type of crash in which side marker

lamps have an effect is one in which the side of one vehicle passes

through the field of view of the driver of another vehicle during the

pre-contact phase of the crash (or, perhaps, both vehicles' sides pass

through the other drivers' fields of view). The type of crash that can

be identified on State data files and comes closest to meeting these

requirements is a two-vehicle collision in which one vehicle is damaged

in the front and the other, in the side.

21
On State files where vehicle damage location is often unknown—

i.e., North Carolina—cases are selected on the basis of a description

of the crash mode or pre-crash maneuvers.

Both the "struck" (side-damaged) and "striking" (frontally

damaged) vehicles are included in the study, because the installation

of side marker lamps on either of the vehicles could have been beneficial

in preventing a collision: when two vehicles approach one another at

an angle, each driver potentially has an opportunity to see the side of

the other vehicle and take action to avoid a collision. Moreover, the

implications of "striking" and "struck" are quite different in angle and

rear-end collisions. In the latter, the lead car is always "struck"

and the burden of accident avoidance rests primarily on the driver of the

following car - "struck" denotes a passive role in the crash. But in

angle collisions, the determination of which car is "struck" in the side

often occurs at the last moment before contact and is not preordained

at the beginning of the crash sequence—both drivers may have an

opportunity to prevent contact and "struck" does not imply a passive

role in the crash.

o Side marker lamps are primarily effective in reduced light

conditions, when a car's lamps are lit but the rest of the vehicle's

side is difficult to see. Thus, accidents that occurred under reduced

light conditions—darkness (with or without lights), dawn, and dusk—are

extracted. The analyses, however, generally compare the number of

reduced-light angle collisions to the number of daylight angle collisions.

Therefore, daylight crashes are also extracted.

22
o The model year of the vehicle must be known in order to

determine whether it was equipped with side marker lamps. The analyses

of Chapters 4-7 are limited to model years 1964-72 or even smaller

ranges.

o It is desirable to have data files from as many calendar

years as possible. The more years of data, the larger the sample size.

Furthermore, for the regression analyses, it is desirable to have many

years of data in order to reduce the correlation among two independent

variables: side marker lamp installation and vehicle age. In other

words, there should be some old vehicles with lamps and some relatively

new ones without them. North Carolina, Texas and FARS are the only

files for which a long series of calendar years is available to NHTSA.

o The vehicles are subdivided into two groups according to

the severity of the accident in which they were involved: crashes

resulting only in property damage vs. those in which someone was injured

or killed. The subdivision is, of course, not made on FARS since all

its accidents are fatal. The motivation is that in Chapters 4 and 5

separate analyses will be performed for injury accidents alone and for

injury and property damage accidents combined—in order to check if

side marker lamps are equally effective at different severity levels.

Note that the severity level applies to the accident, not the

vehicle—i.e., a vehicle involvement is classified as an "injury

accident involvement" if someone in the other car was injured, even if

no one in the subject vehicle was injured.

23
o In summary, all cars, trucks and buses involved in angle

collisions (front-to-side, preferably) with another car, truck or bus,

with known light condition, model year and accident severity are

extracted and a 4-way table is prepared:

- by light condition (daylight, reduced light)

- by model year (1964, 65 , 72)

- by calendar year (depends on the State)

- by accident severity (property damage, injury or

fatal; n.a. on FARS)

The 4-way table is used to generate two 3-way tables; one adding up the

cell entries for property damage and Injury accidents and the other

limited to injury accidents.

For the contingency table analyses of Chapter 4, the table

entries of each 3-way table are summed across calendar years to obtain

2-way tables by light condition and model year. For the regression

analyses of Chapter 5, the entries in the 3-way tables are transformed

into data points for the regression, as explained in Section 5.1.

o Similar 4-way tables are prepared for a control group of

vehicles involved in 2-vehicle crashes that are not angle collisions

(i.e., mostly rear-end or head-on). The control group is not used

directly in the calculation of effectiveness estimates for side marker

lamps. Rather, some of the analyses of Chapters 4-6 are performed

independently on the control group to check if there are any spurious

"effects" for side marker lamps.

24
3.2 North Carolina data

Automated North Carolina accident files were available for

every year from 1971 to 1980. Dr. G. Y. H. Chi of the Highway Safety

Research Center, under contract to NHTSA, performed the data

extraction [ 4 ].

The principal difficulty in working with North Carolina

data is the definition of an angle collision. Vehicle damage location,

using the TAD classification scheme [29*|, is a data element on the file

but is missing on a large percentage of cases (up to 60% in the early

1970's). It was felt that selection of known front-to-side collisions,

based on TAD, would lead to an excessive data loss. As a result, the

contractor was directed to use the variable "accident type" which is a

sort of summary of precrash maneuvers. The objective was to be as

inclusive as possible and to use all accident types where one driver

might have been able to see the side of the other vehicle. . Three

accident types were included: "angle collision," "left turn across

traffic" and "right turn across traffic." (On the two latter types, the

side of the vehicle that is turning would usually become visible, at some

point in the turn, to an approaching vehicle).

The second difficulty is that the variable "accident type"

did not appear on the 1971 and 1972 files. For these two years, Chi

selected cases based on damage location and precrash maneuvers of each

vehicle, resulting in a large data loss due to missing data on damage

location.

25
Light condition, accident severity and vehicle model year

could be read directly from the data file, with few missing data.

Cases in which one or both vehicles were pre-1960 were

excluded from the study, since it was unknown if any of them had

wraparound lights that served the purpose of side marker lamps.

Collisions involving 2 trucks (and no passenger cars) were

inadvertently excluded, resulting in a small data loss.

These steps produced a sample of 26,726 model year 1967

vehicles and 33,426 model year 1968 vehicles involved in angle

collisions, with similar sample sizes for the other model years.

The control group consisted of the following accident types:

"rear-end," "one vehicle slowing or stopping," "one vehicle backing up"

and "head-on."

Chi felt that NHTSA's specifications for angle collisions were

perhaps too inclusive and extracted a subset, the "refined test group,"

in which he was more certain that the side of one vehicle passed

through the field of view of the other vehicle. Only those crashes

occurring at intersections or near a driveway entrance were included.

For the accident type "angle collision" he required that both vehicles

be going straight and that one have frontal damage and the other, side

damage. For the type "left turn across traffic," one vehicle had to be

making a left turn and the other going straight or turning left. For

26
the type "right turn across traffic," one vehicle had to be turning

right and the other going straight.

The "refined test group" contains 15,775 MY 67 vehicles and

19,256 MY 68 vehicles, which is about 40 percent fewer than the

NHTSA-specified sample. Much of the data loss is due to missing

information on damage location.

Throughout the remainder of this report, identical analyses

are performed on the NHTSA-specified sample and the refined test group.

The effectiveness estimates, it turns out, are nearly identical.

The basic 4-way data tables of calendar year x model year

x accident severity x light condition are shown in Appendix A.

3.3 Texas data

Automated Texas files were available for access by NHTSA for

the calendar years 1972, 73 and 74. (1977 data were also available but

were not used because all model years prior to 1967 are coded as "66"

on that file.) The 4-way tables of calendar year x model year x accident

severity x light condition, which are shown in Appendix A, were extracted

directly from the master files by a COBOL program.

In Texas, the TAD code for damage location [297 is only missing

on about 10 Dercent of the vehicles. Thus, angle collisions were defined

as those 2 vehicle collisions in which one vehicle was damaged in the

front (FC, FD, FL, FR) and the other, in the side (LP, RP, LF, RF, LB, RB,

LD, RD). The loss of data due to missing TAD codes was considered acceptable.

27
Each of the 2 vehicles had to be a car, truck or bus with

a known model year of 1960 or later. Light condition and accident

severity were read directly from the master file.

These steps produced a sample of 38,062 model year 1967

vehicles and 45,333 model year 1968 vehicles involved in angle

collisions, with similar samples for the other model years. Thus,

Texas provided a larger sample than North Carolina, although the latter

was derived from a longer range of calendar years. In view of these

offsetting advantages, results from the 2 States should be given about

equal weight.

In Texas, the control group was defined to be those vehicles

involved in 2-vehicle collisions for which the damage location was known

for both vehicles and which were not front-to-side impacts.

3.4 Fatal Accident Reporting System

The Fatal Accident Reporting System (FARS) is a census of the

Nation's fatal traffic accidents. FARS data were available for calendar

years 1975-81. The 3-way tables of calendar year x model year x light

condition, which are shown in Appendix A, were extracted directly from FARS

using SAS programs.

On FARS, damage location is indicated by a variable called

Impact Point-Principal which employs o'clock codes. The information is

missing in fewer than 5 percent of the 2-vehicle collision cases. Thus,

angle collisions were defined as those 2-vehicle collisions in which one

28
vehicle was damaged in the front (11, 12, 1) and the other, in the

side (2, 3, 4, 8, 9, 10). The loss of data due to missing codes was

considered acceptable.

Each of the 2 vehicles had to be a car, truck or bus with

a known model year of 1960 or later. Light condition was read directly

from the file (and the codes for reduced light conditions varied

slightly from year to year).

These steps produced a sample of 2220 model year 1967 vehicles

and 2924 model year 1968 vehicles involved in fatal angle collisions,

with similar samples for the other model years. These samples are less

than one-tenth as large as those from North Carolina and Texas and

results based on FARS will obviously be the least statistically reliable

of the three.

On FARS, as in Texas, the.control group was defined to be

those vehicles involved in 2-vehicle collisions for which damage location

was known for both vehicles and which were not front-to-side impacts.

3.5 Introduction dates for side marker lamps

The analyses of this report require accurate knowledge of the

proportion of the vehicle fleet, in a given model year, that was equipped

with side marker lamps.

The assessments of side marker lamp installation used in this

report are based on a variety of data sources:

o Chilton's Auto Air Conditioning and Wiring Diagrams Manual

shows in detail the lamp circuits for each make and model of domestic car,

29
indicating clearly if front and/or rear side marker lamps were installed

in a given model year. In general, it is the most satisfactory

information source, but there are some shortcomings: a small number of

the diagrams are missing; the diagrams, by themselves, do not indicate

if parking and taillamps were of the "wraparound" type and served as

side marker lamps, the data in this book occasionally disagree with some

of the other sources.

o Chilton's Auto Repair Manual, 1970 gives detailed listings

of the types of lightbulbs on each model of car, by model year. The

listings, however, are less complete than the preceding source.

o The "AMA Auto Identification Manuals" published by the

Motor Vehicle Manufacturers Association contain photographs that

indicate the presence or absence of side marker lamps and/or reflectors

on domestic passenger cars by make, model and model year [2*1. Exterior

photos alone, however, do not make it clear whether a device actually

contained a bulb on the inside or was merely a reflector. On the other

hand, the photos are especially useful for identifying wraparound

parking and taillights.

o Ward's Automotive Yearbooks and back issues of Automotive

News were consulted for photographs of light trucks, multipurpose

vehicles, etc.

o The agency's cost evaluation for side marker lamps [10]

contains detailed part-by-part photographs of the SML of a select group

of makes and models and provides authoritative information on those

models.

30
o Recollections of NHTSA staff

Based on these sources, the proportion of new cars, trucks

and buses equipped with side marker lamps is shown in Table 3-1.

The percentages are calculated by adding up the sales of

models equipped with SML and dividing it by the total number of vehicles

sold in a given model year. If a model had front SML but none at the

rear, or vice-versa, it was counted as being half equipped with

SML—i.e., half of the sales for that make and model were counted as

SML-equipped. Wraparound parking or taillights were counted as SML;

reflectors without a lamp inside were not.

The percentages are, moreover, based on the assumptions that

imported cars (which had only a small market share in those years) had

about the same proportion SML equipped as domestic cars; that heavy

trucks and buses initially received SML in 1968. Photographs indicated

that light trucks and MPV's had neither SML nor reflectors in 1967 and

earlier, but did have one or the other in 1968 and later. It is assumed

that the proportion of light trucks that had only reflectors, as opposed

to lamps, is the same as for cars.

Table 3-2 furnishes a detailed listing, by model year, of

which models were equipped with SML.

In the contingency table analyses of Chapter A, the objective

is to compare the nighttime-to-daytime angle collision ratios of vehicles

of the first model year "with" side marker lamps to those of the last model

31
TABLE 3-1

PERCENT OF NEW CARS, TRUCKS AND BUSES EQUIPPED

WITH SIDE MARKER LAMPS, BY MODEL YEAR

Model Year Percent with Side Marker Lamps

1964 5

1965 8

1966 15

1967 13

1968 88

1969 85

1970 and subsequently 100

32
TABLE 3-2

SIDE MARKER LAMP EQUIPMENT ON DOMESTIC

VEHICLES, BY MODEL YEAR, MAKE AND MODEL

1964: Buick Riviera and Cadillac—front lamp + wraparound taillight

Dodge Custom and Lincoln—wraparound taillight

Olds 98—front lamp

1965: AMC Classic, Mercury Comet, Plymouth Valiant and

Pontiac Tempest—wraparound taillight

Buick Electra, Cadillac and Olds 98—front lamp

Lincoln and Mercury—wraparound parking and taillights

1966: AMC Ambassador & Classic, Chevrolet Impale, Chrysler,

Plymouth Barracuda & Valiant^—wraparound taillight

Buick Electra, Cadillac, Olds 98 & Toronado—front lamp

Mercury—wraparound parking and taillights

1967: AMC Classic—rear lamp

Buick Electra, Cadillac, Olds Toronado—front lamp

Chevrolet Chevelle and Plymouth Satellite—wraparound tailllight

Chrysler New Yorker—wraparound parking and taillight

1968: All cars and light trucks have front and rear SML or wraparound

lights except Fords and Mercurys have them only in the front

(in back—reflectors only)

Caveats: Some sources do not indicate any lamps on AMC American,

Ford Fairlane or Mercury Comet.

1969: All cars and light trucks have front and rear SML or wraparound

lights except

Chrysler (other than Imperial), Dodge Polara & Monaco—rear

lamps and front reflectors

Dodge (other than Polara and Monaco), all Plymouths—

reflectors only; no lamps

Caveats: Some sources do not indicate any lamps on AMC American;

no front lamps on Ford Fairlane or Mercuty Comet

1970 and subsequent years: All vehicles have front and rear SML or

wraparound lights.

33
year "without" SML. From the Table 3-1, it is clear that the

appropriate comparison is MY 68 vhen 88 percent of new vehicles had

SML vs. MY 67 when 87 percent did not have them. It is also evident

that an analytic correction factor will have to be introduced in the

results, to account for the fact that 13 percent of the MY 67 fleet had

SML and 12 percent of the MY 68 fleet did not.

In the regression analyses of Chapter 5, there is one data

point for each case vehicle model year MY in each calendar year of

data CY. The dependent variable LOGODDS (MY, CY) is the log of the

ratio of nighttime to daytime angle collision involvements, for cars

of model year MY during calendar year CY. The most important independent

variable is LAMP (MY, CY) , which is the expected (or average) number of

vehicles with side marker lamps in a 2-vehicle collision, during

calendar year CY, in which the case vehicle is known to be of model

year MY. The model year of the other vehicle is unknown, except to the

extent that the distribution of vehicle registrations by model year in

calendar year CY is known. LAMP (MY, CY) is a number between 0 and 2 and

will reach 2 when every vehicle on the highway will be equipped with SML.

Why is the SML status of the other vehicle important? Because

the presence of side marker lamps on either vehicle has the potential of

helping prevent nighttime collisions; SML on both vehicles further

increase that potential. Thus, for example, cars of model year 1968

should experience relatively fewer nighttime angle collisions in 1975

than in 1970 because thre is a greater likelihood that the other vehicle

was also equipped with SML.

LAMP (MY, CY) is calculated in two steps:

3 4
LAMP (MY, CY) - LAMPMY (MY) + LAMPCY (CY)

where LAMPMY (MY) is the likelihood that the case vehicle of a certain

model year has SML and is taken directly from Table 3-1 and

CY

/ REG (MY, CY) LAMPMY (MY)

LAMPCY (CY)

CY

REG (MY, CY)

MY «= 50

is the proportion of vehicles registered in calendar year CY that have SML.

(Note that REG (MY, CY) is the number of vehicles of model year MY

registered in calendar year CY and is given by Table 3-3, which is

derived from "MVMA Motor Vehicle Facts and Figures '82" [20"].) The

proportion of registered vehicles with SML is shown in Table 3-4.

35

TABLE 3-4

PERCENT OF REGISTERED VEHICLES EQUIPPED

WITH SIDE MARKER LAMPS, BY CALENDAR YEAR

Calendar Year Percent of Registered Vehicles with SML

1971 40

1972 49

1973 58

1974 65

1975 71

1976 76

1977 80

1978 . 85

1979 87

1980 89

1981 91

37
CHAPTER 4

ANALYSES OF CONTINGENCY TABLES

Cars, trucks and buses of model year 1968—mostly equipped with

side marker lamps—are shown to have 7 percent fewer nonfatal nighttime

angle collision involvements than model year 1967 vehicles (mostly

not equipped with side marker lamps). The finding is based on

analyses of simple 2 by 2 tabulations of North Carolina and Texas

angle collision involvements: by model year and light condition. No

effect is found, however, in the crashes of the Fatal Accident Reporting

System (FARS).

4.1 Method

Analyses are conducted on the following tabulation of vehicles

involved in accidents:

VEHICLES INVOLVED IN

Daytime Nighttime, Dawn or Dusk

Angle Angle

Model Year Collisions Collisions

1967 - last model year before

most vehicles had SML N JJ

1968 - first year that most

vehicles had SML

The exact definition of "angle collision," "daytime," etc.,

depends on the data file and is given in Chapter 3. The ratio N /N

39
of daytime angle collisions is an indirect measure of the likelihood

of post-standard vehicle accident involvements relative to pre-standard.

It takes into account the differences in exposure and the effects of

safety devices other than lamps (if any). If side marker lamps had

no effect on nighttime collision risk, the expected number of

nighttime collision involvements for model year 1968 would be

N1 2 (N 2 1 / N n ) . Thus,

N22

N12 N21

is a measure of the collision-reducing effectiveness of equipping one

vehicle with side marker lamps.

Two underlying assumptions are:

o Side marker lamps have little or no effect on daytime

angle collision risk.

o The reduction in nighttime collision risk (relative to

daytime) is due to side marker lamps, not other factors.

The first assumption seems acceptable. The validity of the

second assumption is not nearly so clear and, as a minimum, requires

further testing.

As noted above, the basic analysis is limited to a comparison

of 1967 vs. 1968 model year vehicles. Thus, the age difference between

the pre- and post-standard cars is just one year. That minimizes potential

sources of bias such as the effect of changes in the vehicles other than

side marker lamps or the effects related to differences in vehicle age.

On the other hand., it raises a possibility that a result could be due

to an anomaly in vehicles of model year 1967 or 1968, or a statistical

Fi i s c h a n r e .

40
As a test, each basic analysis is repeated with an accident

sample broadened to include 1966 and 1967 vehicles vs. 1968 and 1969

vehicles. Does the larger sample yield effectiveness estimates

consistent with the basic analysis? As a further test, each analysis

is again repeated with the sample broadened to include 1965-67 vs.

1968-70 vehicles and, finally, 1964-67 vs. 1968-71 vehicles. Do the

effectiveness estimates from the 4 analyses (henceforth designated

+ + + +

as - 1 MY, - 2 MY, - 3 MY, - 4 MY) show any trend of, say, effectiveness increasing as the span of model years increases? If so, it

could indicate that the observed accident reduction is, at least in

part, due to vehicle age differences because as the span of model years

increases so does the average age difference between pre- and poststandard cars.

As a final test, the analyses are repeated in Section 4.5

using a control group of two-vehicle, accidents that are not angle

collisions. The exact definition of the control group varies from State

to State and is given in Chapter 3. The main purpose of the control

group analyses is to check if there are anomalies in the nighttime vs.

daytime accident ratios for the two specific model years 1967 and 1968

which cannot be attributed to side marker lamps (because they are

happening in crashes that are not angle collisions). A secondary

purpose is to check for vehicle age-related trends in those ratios.

In all analyses, the statistical significance of the

observed effect for side marker lamps is tested by taking the

ordinary chi-square for the 2x 2 table.

41
The analytic approach of this chapter was also used in

NHTSA's evaluations of energy-absorbing steering assemblies [13 "]

pp. 197-202, head restraints [ 14 1 pp. 161-170 and side door beams

[ 15 1 PP- 143-157 as well as in the New York State study of side

marker lamps (see Section 2.1).

4.2 Accidents of all severities

4.2.1 North Carolina

In Section 3.2, the accident sample for North Carolina was

selected based on the variable "accident type" and included 2 vehicle

crashes classified as "angle collision," "left turn across traffic"

or "right turn across traffic." During 1971-80, there were 60,152

model year 1967 and 1968 vehicles involved in those types of crashes.

Table 4-1 shows their distribution by light condition: daytime vs.

nighttime (including dawn or dusk). There were 5,971 MY 1967 vehicles

in nighttime angle collisions. Based on the ratio of MY 1968 to MY 1967

cars in daytime collisions, 5,971 (26,351/20,755) = 7,581 nighttime angle

collision involvements are expected for the MY 1968 vehicles. In fact, only

7,075 occurred. This is a reduction of

1 .20,755 « 7 percen t

5,971 . 26,351

in nighttime angle collision involvements for MY 1968 compared to MY

1967. Since the chi-square for the table is 12.08, the reduction is

statistically significant ("C = .05).

42
TABLE 4-1

NORTH CAROLINA 1971-80: ANGLE COLLISION INVOLVEMENTS

BY SIDE MARKER LAMP STATUS AND LIGHT CONDITION

Model Years

Daylight

1967 (last year w/o SML) 20,755

1968 (first year with SML) 26,351

volvements

Nighttime*

5,971

7,075

11,746

15,264

15,921

23,231

19,071

31,586

Nightime

Reduction

for

SML (%)

7**

6**

6

**

7

ChiSquare

12.08

17.36

33.36

46.45

1966-67 (last 2 yrs. w/o) 41,799

1968-69 (first 2 yrs. with) 57,546

1965-67 (last 3 yrs. w/o) 56,713

1968-70 (first 3 yrs. with) 88,491

1964-67 (last 4 yrs. w/o) 67,688

1968-71 (first 4 yrs. with) 120,302

Includes dawn and dusk

""Statistically significant reduction for SML (*' = .05)

43
When the sample is expanded to include model years 1966-67

vs. 1968-69 (the - 2 MY comparison), the result is nearly identical.

Table 4-1 indicates a 6 percent reduction in nighttime angle collision

involvements for model years 1968-69, which is again statistically

significant (chi-square - 17.36). In the - 3 MY comparison, the

reduction is again 6 percent and in the - 4 MY comparison it is

7 percent. The sequence of effectiveness estimates for the 4

consecutively larger samples - 7, 6, 6, 7 - shows little or no trend.

It indicates that the ratio of nighttime to daytime angle collisions is

more or less invariant across model years or vehicle ages except for a

significant 7 percent reduction between MY 1967 and 68, the year that

most cars received side marker lamps.

Dr. Chi of the Highway Safety Research Center expressed

concern that the preceding definition of "angle collision" was perhaps

too inclusive and extracted a subset which he called the "refined test

group" (see Section 3.2). It is limited to crashes at intersections

and driveway entrances and, in many cases, requires that one vehicle

be damaged in the front and the other in the side. The refined test

group is about 40 percent smaller than the basic sample, to a large

extent because many cases are deleted due to unknown damage location.

Table 4-2 presents the analyses for the refined test group.

+

In the - 1 MY comparison, there is an 8 percent reduction in nighttime

angle collision involvements for the MY 68 vehicles, which is

44
TABLE 4-2

NORTH CAROLINA "REFINED TEST GROUP" 1971-80: ANGLE COLLISION INVOLVEMENTS

BY SIDE MARKER LAMP STATUS AND LIGHT CONDITION

Model Years Angle Collision Involvements

Daylight Nighttime

1967 (last year w/o SML) 12,325

1968 (first year with SML) 15,327

3,450

3,929

Nighttime'

Reduction

for

SML (%)

ChiSquare

11.21

1966-67 (last 2 yrs. w/o) 24,834

1968-69 (first 2 yrs. with) 33,301

1965-67 (last 3 yrs. w/o) 33,959

1968-70 (first 3 yrs. with) 50,909

1964-67 (last 4 yrs. w/o) 40,775

1967-71 (first 4 yrs. with) 68,819

6,763

8,424

9,261

12,807

11,190

17,327

8**

8**

16

27

39

.15

.71

.90

Includes dawn and dusk •

^Statistically significant reduction for SML (<*• = .05)

45
statistically significant (chi-square = 11.21). It is also nearly

the same as the 7 percent observed for the more inclusive sample

of Table 4-1. For the -2,- 3 and _ 4 year comparisons, the reductions

are 7, 8 and 8 percent, respectively. In other words, there appears

to be no vehicle-age related trend and the results are almost the

same as for the more inclusive sample. Since the samples in Table 4-1

are nearly twice as large and since the results for the two tables are

nearly identical, it is recommended that the results from Table 4-1

be given greater weight than those from the refined test group. It

would also appear that the restrictions used in obtaining the refined

test group were of limited utility in pinpointing those crashes where

side marker lamps are most effective.

4.2.2 Texas

The accident sample for Texas consisted of cars, trucks and

buses involved in 2-vehicle collisions in which one vehicle was

frontally damaged and the other, in the side (based on the TAD

classification of damage - see Section 3.3). During 1972-74, there

were 83,395 model year 1967 and 1968 vehicles involved in those types

of crashes. Table 4-3 shows their distribution by light condition.

The MY 68 vehicles had a

reduction of nighttime angle collisions compared to MY 67. The

reduction is statistically significant (chi-square = 15.97). Moreover,

46
TABLE 4-3

TEXAS 1972-74: ANGLE COLLISION INVOLVEMENTS

BY SIDE MARKER LAMP STATUS AND LIGHT CONDITION

Model Years

Daylight

1967 (last year w/o SML) 30,324

1968 (first year with SML) 36,618

olvements

ighttime

7,738

8,715

14,939

18,168

21,458

26,875

26,386

35,737

Nighttime

Reduction

for

SML (%)

7

6**

9**

*•&

10

ChiSquare

15.97

27.07

72.97

133.96

1966-67 (last 2 yrs. w/o) 58,512

1968-69 (first 2 yrs. with) 75,877

1965-67 (last 3 yrs. w/o) 84,079

1968-70 (first 3 yrs. with) 114,907

1964-67 (last 4 yrs. w/o) 103,040

1968-71 (first 4 yrs. with) 154,977

Includes dawn and dusk

Statistically significant reduction for SML .05)

47
it is identical to the 7 percent effect observed in North Carolina

(Table 4-1).

When the sample is expanded to include model years

1966-67 vs. 1968-69, the observed effect of SML drops very slightly

to 6 percent, which is still a significant reduction (chi-square = 27.07)

In the - 3 MY comparison the effect increases, however, to 9 percent

and it reaches 10 percent in the - 4 MY comparison. The sequence of

estimates—7, 6, 9, 10 percent—does not show a strong age-related

trend. The estimates from the broader samples are compatible with

the 7 percent reduction in the _ 1 MY comparison, which appears to be

a good estimate of the effect of side marker lamps in MY 68 vehicles.

(The regression analyses of Chapter 5 are an attempt to analyze possible

trends in the data in more detail.)

The identical 7 percent estimates from the basic analyses

of North Carolina and Texas data, both of which were statistically

significant, suggest that this is a good figure for the effect of side

marker lamps in model year 1968. In other words, MY 68 vehicles,

88 percent of which are equipped with SML, have 7 percent fewer nighttime

angle collisions than MY 67 vehicles, only 13 percent of which are

equipped with SML.

4 . 3 Injury accidents

The analyses of Tables 4-1, 4-2 and 4-3 are repeated with

the data sets restricted to injury-producing accidents—in order to

48
TABLE 4-4

NORTH CAROLINA INJURY ACCIDENTS 1971-80: ANGLE COLLISION INVOLVEMENTS

BY SIDE MARKER LAMP STATUS AND LIGHT CONDITION

Model Years

1967 (last year w/o SML)

1968 (first year with SML)

Daylight

6,303

7,835

volvements

Nighttime*

2,240

2,554

4,463

5,498

6,059

8,378

7,248

11,418

Nighttime

Reduction

for

SML (%)

8**

8**

8**

ChiSquare

6.64

14.38

19.31

19.88

1966-67 (last 2 yrs. w/o) 12,644

1968-69 (first 2 yrs. with) 17,016

1965-67 (last 3 yrs. w/o) 17,485

1968-69 (first 3 yrs. with) 26,338

1964-67 (last 4 yrs. w/o) 21,035

1968-71 (first 4 yrs. with) 35,802

Includes dawn and dusk

rt-AStatistically significant reduction for SML (o(= .05)

49
check whether the 7 percent effect of side marker lamps found in

all types of accidents also persists in accidents of higher severity.

A vehicle is involved in an injury-producing accident if at least one

person in the accident—not necessarily an occupant of the case

vehicle—was injured or killed (see Section 3.1).

A.3.1 North Carolina

Table 4-4 shows that MY 68 vehicles were 8 percent less

likely to be involved in injury-producing nighttime angle collisions

than MY 67 vehicles in North Carolina during 1971-80. The reduction

is statistically significant (chi-square = 6.64). It is also almost

the same as the reduction in accidents of all severities (which was

7 percent in Table 4-1).

The reduction remains almost unchanged as the sample is

broadened to include additional model years. It is 8 percent in the

- 2 MY comparison, 8 percent for - 3 MY and 7 percent for - 4 MY.

All of those reductions are significant. The sequence of effectiveness

estimates—8, 8, 8, 7—shows little or no trend and indicates that the

8 percent observed in the - 1 MY comparison is probably a good,

unbiased estimate.

Table 4-5 gives corresponding results for the "refined test

group." The - 1 MY comparison indicates a 13 percent accident reduction

for SML, which is statistically significant. The reduction, however,

drops to 11 percent in the - 2 MY comparison and 10 percent in the - 3 >FY

and - 4 MY comparisons. There is little reason to believe that the50
TABLE 4-5

NORTH CAROLINA INJURY ACCIDENTS, 1971-80, "REFINED TEST GROUP": ANGLE

COLLISION INVOLVEMENTS BY SIDE MARKER LAMP STATUS AND LIGHT CONDITION

Model Years

1967 (last year w/o SML)

1968 (first year with SML)

Daylight

4,211

5,229

volvements

*

Nighttime

1,434

1,557

2,838

3,369

3,854

5,109

4,645

6,921

Nighttime

Reduction

for

SML (%)

**

13

11**

10**

10

ChiSquare

10.20

16.97

20.09

22.42

1966-67 (last 2 yrs. w/o) 8,439

1968-69 (first 2 yrs. with) 11,301

1965-67 (last 3 yrs. w/o) 11,746

1968-70 (first 3 yrs. with) 17,374

1964-67 (last 4 yrs. w/o) 14,249

1968-71 (first 4 yrs. with) 23,532

Includes dawn and dusk

"statistically significant reduction for SML (•* = .05)

51
gradual dropoff is due to a vehicle age-related trend, since no such

trend was seen in other tables. A more likely explanation is that

the 13 percent estimate is somewhat overstated, by statistical

mischance (in view of the reduced sample size of the refined test

group) and that enlargement of the sample yields more precise values

that are also more consistent with those seen in the other tables.

A.3.2 Texas

Table 4-6 shows that MY 68 vehicles experienced 8 percent

lower risk of injury-producing nighttime angle collisions than MY 67

vehicles in Texas during 1972-74. The reduction is statistically

significant (chi-square = 5.25) and identical to the one found in

North Carolina.

Extending the sample to include additional model years

hardly perturbs the results. The sequence of effectiveness estimates—

8, 7, 7, 9 for the - 1, 2, 3, 4 MY comparisons, respectively—indicates

little or no trend and is virtually identical to the North Carolina

sequence and the results for both States on accidents of all

severities.

It would appear reasonable to conclude that side marker

lamps are nearly equally effective in preventing injury accidents and

property-damage accidents, with, perhaps, a slightly greater effect

on injury accidents.

52
TABLE 4-6

TEXAS INJURY ACCIDENTS, 1972-74: ANGLE COLLISION INVOLVEMENTS

BY SIDE MARKER LAMP STATUS AND LIGHT CONDITION

Model Years

1967 (last year w/o SML)

1968 (first year with SML)

Daylight

6,123

7,248

volvements

Nighttime

2,185

2,391

4,279

4,925

6,145

7,259

7,608

9,617

Nighttime

Reduction

for

SML (%)

8**.

7**

**

9**

ChiSquare

5.25

10.09

14.86

27.14

1966-67 (last 2 yrs. w/o) 12,105

1968-69 (first 2 yrs. with) 15,046

1965-67 (last 3 yrs. w/o) 17,640

1968-70 (first 3 yrs. with) 22,511

1964-67 (last 4 yrs. w/o) 21,800

1968-71 (first 4 yrs. with) 30,223

-'Includes dawn and dusk

ArtStatistically significant reduction for SML .05)

53
4.4 Fatal accidents

The accident sample extracted from the Fatal Accident

Reporting System (FARS) consisted of cars, trucks and buses involved

in fatal 2-vehicle collisions in which one vehicle was frontally

damaged and the other, in the side (see Section 3.4). During

1975-81, there were 5,144 model year 1967 and 68 vehicles involved in

those types of crashes. Table 4-7 shows their distribution by light

condition. The smallest cell—nighttime involvements for MY 67 — is 965,

which is about 1/6 as large as the comparable cell in North Carolina

(Table 4-1) and 1/8 as large as in Texas (Table 4-3). Thus, estimates

based on FARS are less precise than those for nonfatal crashes.

The MY 68 vehicles had a

1292 . 1255 _ 3 percent increase

1 ~ 965 . 1632

in the risk of fatal nighttime angle collisions compared to MY 67.

The increase is not statistically significant (chi-square = 0.26).

When the sample is extended to include additional model years,

the results become slightly worse: -7 percent for the - 2 MY comparison

and -6 percent for both the - 3 MY and - 4 MY comparisons. The

sequence of estimates, however - -3, -7, -6, -6 - does not reveal any

obvious trend. More importantly, none of the observed increases is

statistically significant, even the one for - 4 MY.

54
TABLE 4-7

U.S. FATAL ACCIDENTS, 1975-81: ANGLE COLLISION INVOLVEMENTS

BY SIDE MARKER LAMP STATUS AND LIGHT CONDITION

Model Years

Daylight

1967 (last year w/o SML) 1,255

1968 (first year with SML) 1,632

volvements

Nighttime*

965

1,292

1,818

2,861

2,481

4,532

2,927

6,276

Nighttime

Reduction

for

SML (%)

-3

-7

-6

-6

ChiSquare

0.26

2.76

2.74

3.36

1966-67 (last 2 yrs. w/o) 2,440

1968-69 (first 2 yrs. with) 3,594

1965-67 (last 3 yrs. w/o) 3,334

1968-70 (first 3 yrs. with) 5,765

1964-67 (last 4 yrs. w/o) 3,976

1968-71 (first 4 yrs. with) 8,075

'Includes dawn and dusk

'Statistically significant change for SML (<X = .05)

55
From the data in Table 4-7 it is not possible to draw

any conclusion on the effect of side marker lamps in fatal accidents.

Other statistical analyses are needed and, if they do not resolve the

issue, an engineering analysis.

A.5 Analyses for a control group of head-on and rear-end crashes

The preceding tabulations and analyses of angle collision

involvements are reiterated for a control group of 2-vehicle crashes

that are not angle collisions—viz., head-on and rear-end collisions.

In those crashes, neither driver is likely to see the other vehicle

from the side for a significant time period before the crash. Even

if the driver does see the side of the other vehicle, it is probably

at an angle where the front (headlights) or rear (brake or taillights)

is also visible. In other words, side marker lamps should be of little

or no value in preventing those collisions at night. Any significant

"reduction" of nighttime collisions of MY 68 cars, relative to MY 67,

in the control group is not likely due to side marker lamps and could

indicate a bias in the basic analyses of angle collisions conducted

in the preceding sections.

A.5.1 North Carolina

The control group for North Carolina was defined to be vehicles

involved in 2-vehicle collisions that were specifically identified as

head-on or rear-end . (see Section 3.2). Table 4-8 shows their distribution

56
TABLE 4-8

NORTH CAROLINA, 1971-80: CONTROL GROUP COLLISION INVOLVEMENTS

BY SIDE MARKER LAMP STATUS AND LIGHT CONDITION

Model Years

1967 (last year w/o SML)

1968 (first year with SML)

Control Group

Collision Involvements

Daylight Nighttime

13,810

17,941

27,220

39,643

36,610

61,584

43,330

85,771

4,384

5,766

8,844

12,660

12,169

19,430

14,512

26,571

Nighttime"

"Reduction"

for

SML (%)

-1

2

5**

8**

ChiSquare

0.29

1.17

15.35

43.06

1966-67 (last 2 yrs. w/o)

1968-69 (first 2 yrs. with)

1965-67 (last 3 yrs. w/o)

1968-70 (first 3 yrs. with)

1964-67 (last 4 yrs. w/o)

1968-71 (first 4 yrs. with)

'Includes dawn and dusk

'Statistically significant "reduction" for SML (<X = .05)

57
by model year and light condition. The MY 68 vehicles experienced a

1 percent increase in nighttime control group collision risk, relative

to MY 67. The increase is not significant (chi-square = 0.29).

When the control group sample is extended to include

additional model years, there is a perfect linear trend in the

"effectiveness" estimates: -1, 2, 5, 8 for the "1,-2,- 3 and

- 4 MY comparisons, respectively. No trend like this was found in any

of the analyses of angle collisions. Evidently, the biasing effect

of vehicle age on the ratio of nighttime to daytime collisions is

strong in the control group and virtually absent in the test group.

That limits the usefulness of the control group as an analytic tool

in this study. For example, it would not appear valid to do a 3

dimensional contingency table analysis of collision type (angle vs.

control ) x light condition x SML status. The best use of the control

group is, as stated above, to search for specific anomalies in model

years 67 and 68.

When the linear trend in the "effectiveness" estimates -

- 1, 2, 5, 8 - is extrapolated one year to the left, an estimate of -4

percent is obtained. The estimates -1, 2, .5, 8 are based on samples

in which the average age difference of pre- and post-standard cars is

1, 2, 3, 4 years, respectively. The extrapolated estimate of -4

percent represents a condition where the age difference of pre- and

post-standard cars is zero. In other words, after controlling for

vehicle age differences, the "effect" of side marker lamps on the

58
TABLE 4-9

NORTH CAROLINA INJURY ACCIDENTS, 1971-80: CONTROL GROUP COLLISION INVOLVEMENTS

BY SIDE MARKER LAMP STATUS AND LIGHT CONDITION

Model Years

Control Group

Collision Involvements

Daylight Nighttime*

Nighttime

"Reduction"

for

SML (%)

ChiSquare

1967 (last year w/o SML) 4,037

1968 (first year with SML) 5,188

1,680

2,207 -2 0.32

1966-67 (last 2 yrs. w/o) 8,069

1968-69 (first 2 yrs. with) 11,244

3,474

4,806 0.07

1965-67 (last 3 yrs. w/o) 10,983

1968-70 (first 3 yrs. with) 17,215

4,834

7,286 3.11

1964-67 (last 4 yrs. w/o) 13,169

1968-71 (first 4 yrs. with) 23,617

5,778

9,868 5 6.08

Includes dawn and dusk

Statistically significant "reduction" for SML (oL = .05)

59
control group is -4 percent. Certainly, then, the control group

does not indicate a bias in favor of side marker lamps in the

preceding analyses.

Table 4-9 is limited to injury producing control group

accidents. The sequence of "effectiveness" estimates - -2, 1, 4, 5

percent - is nearly the same as in Table 4-8 and, again, does not

indicate the presence of a bias in favor of side marker lamps.

4.5.2 Texas

The control group for Texas was defined to be cars, trucks

and buses involved in 2-vehicle collisions in which the damage

location was known for both vehicles and which were not front-to-side

collisions (see Section 3.3). In part because of the inclusiveness

of the definition, the Texas control group is more than 3 times as

large as North Carolina's and will produce more statistically reliable

results.

Table 4-10 presents the results for crashes of all severities.

The "effectiveness" estimates for the t 1, t 2, t 3 and 1 4 MY

comparisons are on a straight line: 3, 6, 9 and 12 percent, respectively.

When the line is extrapolated back to a "1 0 MY comparison" the predicted

effectiveness is zero. In other words, after controlling for vehicle

age, side marker lamps have absolutely no effect on the nighttime to

daytime ratio of crashes in the control group.

60
TABLE 4-10

TEXAS 1972-7'4: CONTROL GROUP COLLISION INVOLVEMENTS

BY SIDE MARKER LAMP STATUS AND LIGHT CONDITION

Model Years

Control Group

Collision Involvements

Daylight Nighttime*

1967 (last year w/o SML)

1968 (first year with SML)

58,110

72,105

110,942

153,921

157,721

235,293

190,976

320,802

15,652

18,746

30,265

' 39,423

43,715

59,315

53,621

79,495

Nighttime

"Reduction"

for

SML (%)

,**

ChiSquare

8.45

1966-67 (last 2 yrs. w/o)

1968-69 (first 2 yrs. with)

1965-67 (last 3 yrs. w/o)

1968-70 (first 3 yrs. with)

1964-67 (last 4 yrs. w/o)

1968-71 (first 4 yrs. with)

6** 53.83

9** 178.77

12

**

394.53

*Includes dawn and dusk

^Statistically significant "reduction" for SML .05)

61
Table 4-11 is limited to injury producing control group

accidents. Again, the sequence of effectiveness estimates is perfectly

linear, with a 3 percent increase for each additional year of age

difference: 2, 5, 8, 11 percent. When the line is extrapolated to

zero age difference, the "effect" of side marker lamps on the control

group is -1 percent.

The control group results for North Carolina and Texas are

remarkably consistent with one another and indicate that side marker

lamps had no effect in property damage and injury crashes that are

not angle collisions.

4.5.3 Fatal Accident Reporting System

The control group for FARS, as in Texas, consisted of cars,

trucks and buses involved in 2-vehicle accidents that were not

front-to-side impacts (see Section 3.4). The majority of these

crashes on FARS, however, are head-on collisions whereas, among

nonfatal accidents, rear-end collisions predominate. As a result, the

FARS control group might be expected to behave differently from those

of North Carolina and Texas.

Table 4-12 shows that MY 68 vehicles experienced a 10 percent

increase in nighttime control group collision risk, relative to MY 67.

The increase is statistically significant (chi-square = 4.76).

Moreover, when the sample is extended to include additional model

years, the increase persists without any vehicle age-related trend:

62
TABLE 4-11

TEXAS INJURY ACCIDENTS, 1972-74: CONTROL GROUP COLLISION INVOLVEMENTS

BY SIDE MARKER LAMP STATUS AND LIGHT CONDITION

Model Years

1967 (last year w/o SML)

1968 (first year with SML)

Control Group

Collision Involvements

*

Daylight Nighttime

7,673

9,061

3,304

3,817

Nighttime

"Reduction"

for

SML (%)

ChiSquare

0.60

1966-67 (last 2 yrs. w/o)

1968-69 (first 2 yrs. with)

1965-67 (last 3 yrs. w/o)

1968-70 (first 3 yrs. with)

1964-67 (last 4 yrs. w/o)

1968-71 (first 4 yrs. with)

14,947

18,872

21,623

28,246

26,505

38,069

6,556

7,839

9,675

11,655

12,058

15,407

5**

8**

**

11

7

24

64

.41

.23

.62

""Includes dawn and dusk

**Statistically significant "reduction" for SML (o( = .05)

63
-10, -10, -11, -11 percent effects for the t 1, ± 2, t 3, ± 4 MY

comparisons, respectively.

The significant, persistent negative effect could be an

unfortunate statistical mischance or it could represent a genuine

effect of some change in MY 68 vehicles on control group accidents,

either increasing nighttime fatalities or, just as likely, decreasing

daytime fatalities.

It vould appear reasonable not to attribute the effect

to side marker lamps. A more plausible explanation of the effect

could be:

o A trend toward lighter, brighter exterior paint colors

for cars of the late 1960's [30], p. 106. That could have resulted

in a reduction of daytime crashes by making cars more visible. It

is hard to believe, however, that the reduction would be as large as

10 percent and concentrated in model year 68.

o Crashworthiness equipment installed in cars of the late

1960's might, perhaps, be more effective in daytime crashes than in

nighttime crashes because the latter are more likely to involve

alcohol and, as a result, extremely high speeds. Again, it is hard

to believe that the differential effect would be as large as 10 percent

and concentrated in MY 68.

In short, it is difficult to believe that the analysis

creates a 10 percent bias against side marker lamps. But if such a

64
TABLE 4-12

U.S. FATAL ACCIDENTS, 1975-81: CONTROL GROUP COLLISION INVOLVEMENTS

BY SIDE MARKER LAMP STATUS AND LIGHT CONDITION

Model Years

1967 (last year w/o iSML)

1968 (first year with SML)

1966-67

1968-69

1965-67

1968-70

1964-67

1968-71

(last 2 yrs.

(first 2 yrs

(last 3 yrs.

(first 3 yrs

(last 4 yrs.

(first 4 yrs

w/o)

. with)

w/o)

. with)

w/o)

. with)

Control Group

Collision Involvements

*

Daylight Nighttime

1,623

1,946

3,038

4,430

4,226

7,107

5,088

10,025

1,938

2,564

3,648

5,852

4,980

9,278

5,900

12,860

Nighttime

"Reduction"

for

SML (%)

**

-10

-10**

-11**

**

-11

ChiSquare

4.76

9.10

15.29

18.76

Includes dawn and dusk

^Statistically significant "change" for SML (o^= .05)

65
bias is really there, it might explain the negative results obtained

in the analyses of angle collisions on FARS (Table 4-7). In other

words, it is conceivable that the -3 percent effect observed for

SML in angle collisions could represent the sum of a 7 percent

benefit for SML and a 10 percent bias against them—conceivable, but

not too plausible.

Obviously, the contingency table analyses of this chapter

do not give a clear indication of the effect of side marker lamps, if

any, in fatal crashes. Further analyses are needed.

4.6 Discussion

The contingency table analyses of North Carolina and Texas

data showed unambiguously that model year 1968 vehicles have a 7 or 8

percent lower risk of nighttime angle collision involvement than model

year 1967 vehicles. A similar reduction was found in property damage

crashes and injury-producing accidents (but not in fatal crashes).

The observed reduction, however, understates the net benefits

of introducing side marker lamps in the entire vehicle fleet, for two

reasons:

(1) 13 percent of model year 67 cars, trucks and buses were

equipped with side marker lamps or wraparound parking or taillights;

88 percent of model year 68 vehicles were so equipped (see Section 3.5).

As a result, the observed accident reduction measures the effect of a

change from 13 percent to 88 percent SML installation. The effect of

changing from 0 to 100 percent would be higher.

66
(2) More important, the analytic approach has been to

consider the effect of changing one vehicle in a 2-vehicle collision

from model year 1967 (unequipped) to MY 68 (SML equipped). The

model year of the other vehicle was not specified. The effect of

installing SML on both vehicles approaching at an angle should be close

to double the effect of equipping just one of them.

These issues can be addressed more effectively by the

regression analyses of Chapter 5 than by the approach of this chapter.

The principal advantage of the contingency table analyses of this

chapter, however, is that they demonstrated in a straightforward

manner that side marker lamps reduce accident risk.

67
CHAPTER 5

REGRESSION ANALYSES

When a single car, truck or bus is equipped with side

marker lamps, its risk of having a nighttime angle collision is reduced

by 7-8 percent. When all cars, trucks and buses on the road have side marker

lamps there will be 14-16 percent fewer nighttime angle collisions than

if none of the vehicles had been so equipped. The finding is based on

regressions of the ratio of nighttime to daytime angle collisions in

North Carolina and Texas, as a function of side marker lamp installation,

vehicle age and other factors (separate regressions for each State). It

is close to the effectiveness obtained from the contingency table

analyses of Chapter 4. No accident reduction, however, was found in

the Fatal Accident Reporting System (FARS).

5.1 Method

In preparation for the regressions, involvements of

cars, trucks and buses in 2 vehicle angle collisions are tabulated

by calendar year of the accident (CY), model year of the vehicle

(MY) and light condition, as follows (see Section 3.1):

Calendar Year (CY) Model Year (MY) Number of Angle Collision Involvements

Daytime Nighttime

72 64 D(72,64) N(72,64)

65 D(72,65) N(72,65)

* # * .

» • *

72 D(72,72) N(72,72)

73 • 64 D(73,64) N(73,64)

65 D(73,65) N(73,65)

69
Each applicable calendar year/model year combination will produce one

data point for the regression. Calendar year ranges from 71 to

80 in North Carolina, 72-74 in Texas and 75-81 in FARS: The range

of model years used in each of the analyses is 64-72, which corresponds

to the period when side marker lamps were first introduced on a

significant number of makes and models, then became standard on all

vehicles.

The dependent variable is the logarithm of the ratio of

nighttime to daytime angle collision involvement of cars of a

given model year MY in a given calendar year CY:

N(CY, MY)

LOGODDS (CY, MY) = logD(CY, MY)

where N(CY, MY) and D(CY, MY) are the counts of nightime and daytime

angle collision involvements, respectively, from the preceding table.

The log of the odds ratio (nighttime to daytime) was

selected as the dependent variable because it makes it especially

simple to derive effectiveness estimates for side marker lamps from

the regression equation, as will be shown below. Other statistics

of N and D could have been used as the dependent variable but would

have made it more complicated to derive effectiveness, while eventually

producing almost the same results. This is because the relative

variation of N/D is fairly small in the data sets used for this

report: as a result, linear and log-linear models produce similar

results. (By contrast, in NHTSA's evaluation of braking improvements,

70
the brake failure rate increased enormously with vehicle age and

the choice of a linear rather than log-linear model was critical J16J ,

pp 40-43). In tact, all of the regressions in this chapter were

duplicated using a linear model with N/D+N as the dependent variable

and identical effectiveness estimates were obtained.

The independent variables are LAMP, AGE, AGE2

and CY:

LAMP (MY, CY) is a measure of the combined availability

of the side marker lamps of two vehicles involved in a

collision during calendar year CY when one of the vehicles is known

to be of model year MY and the other's model year is unknown.

LAMP (MY, CY) = LAMPMY (MY) + LAMPCY (CY)

LAMPMY (MY) is the proportion of vehicles of model year MY - the year

of the case vehicle - that were equipped with side marker lamps. The

values of LAMPMY are given by Table 3-1 and their derivation is

explained in Section 3.5.

LAMPCY (CY) is the proportion of all vehicles on the road during

calendar year CY that were equipped with side marker lamps -i.e., a

best guess of the SML status of the "other" vehicle in the 2 vehicle

accident. The values of LAMPCY are given by Table 3-4 and their derivation

explained in Section 3.5.

71
LAMPMY (MY) ranges from 0.05 (in model year 1964) to 1.00

(in model year 1970 and beyond). LAMPCY (CY) ranges from 0.40

in 1971 to 0.91 in 1981. Thus, in the regressions of this chapter,

LAMP ranges from LAMP (71, 64) = 0.45 to LAMP (81, 72) = 1.91.

AGE (CY, MY) = CY - MY, the age of the vehicle in years.

AGE and AGE are used to control for vehicle age-related trends in

the ratio of nighttime to daytime accidents.

CY, the calendar year of the accident, is used as a categorical

variable in the regression. Actually, it is a collection of independent

variables. For example, North Carolina data are available from each

year of 1971-80.

Let CY 71 = 1 if CY = 71, 0 otherwise

CY 72 = 1 if CY = 72, 0 otherwise

CY 79 = 1 if CY = 79, 0 otherwise

Note

that CY 71 = ... = CY79 = 0 when CY-80.

Thus, CY71, ..., CY79 are a collection of nine independent variables

that, together, denote the calendar year. They are needed for the

regression because the nighttime-to-daytime accident ratio varies

significantly from year to year. In general, it will be seen in

Tables 5-1 through 5-12 that nighttime accidents were relatively

less frequent during and after the economic recession of 1975.

72
Thus, the regression equation is

N(CY, MY)

log = ao + ax LAMP + A2 AGE+ a3 AGE''

D(CY, MY)

+ a4 CY71 + + a12 CY79

for North Carolina. (The equations for Texas and FARS are the same

except that the CY terms are changed to reflect the data years

used.)

A weighted regression is run - each (CY, MY) data point is

weighted by the total sample size of the collision involvements of

vehicles of model year MY in calendar year CY, i.e., T(CY, MY) =

N(CY,MY) + D(CY, MY). The runs were made by the General Linear

Model procedure of the Statistical Analysis System (SAS), which

allows weighted regressions with mixed linear and categorical

variables [26J.

The effectiveness of side marker lamps is derived from the

regression equation. Note that the risk of a nighttime angle

collision involvement for a given vehicle is

2

N = D exp (aQ + a1 LAMP +a2 AGE + a3A5E + ...)

where D is the risk of a daytime angle collision involvement. Now,

suppose that not a single car, truck or bus is equipped with side

marker lamps -i.e. LAMP=0. Under those circumstances, the risk is

No = D exp (ao + a2 AGE + a3 AGE2 + )

Suppose a single vehicle is then equipped with side marker lamps.

For this vehicle, LAMPMY = 1.00. But since no other vehicle on the road has the

73
lamps, LAMPCY = 0. Thus, for this single vehicle, LAMP - LAMPMY

+ LAMPCY = 1.00.Its nighttime angle collision risk is

N]_ = D exp (aQ + a. (1.00) + a2 AGE + a3 AGE2 + ...)

Thus, the reduction in nighttime angle collision risk for equipping

one vehicle with side marker lamps is

Nx D exp (aQ + a^ (1.00) + a2

 AG E + a3

 AGE 2 +•••)

0 D exp (aQ +a 2 AGE + a3 AGEZ +...)

= 1 - exp (a-^)

Finally let every vehicle on the road be equipped with side marker

lamps. At that point LAMPMY = LAMPCY =1.00 and LAMP = 2.00.

The nighttime angle collision risk becomes

N2 = D exp (a0 + a (2.0 0) + a2 AGE + a3 AGE2 +...)

The reduction of nighttime angle collision risk that occurs

when every vehicle on the road has SML, relative to the situation where

no vehicle on the road had them, is

N2

= 1 - — = 1 - exp (2

In other words, with the log-linear model, the effectiveness

of equipping a single vehicle with SML, or all vehicles on the

road with SML is a simple funtion of the regression coefficient for

LAMP.

The statistical significance of the effectiveness estimates

is determined by a t test on the regression coefficient for LAMP.

As in Chapter 4, the validity of the regression results

for angle collisions is tested by performing identical regressions

74
on control groups of crashes that are not angle collisions.

The analytic approach of this chapter was also used

in NHTSA's evaluations of head restraints |.4J, pp. 170-174, side

door beams [l5J, pp. 161-166 and, most extensively, braking

improvements for passenger cars [l6] , pp. 17-47.

5-2 Accidents of all severities

5.2.1 North Carolina

The accident sample for North Carolina consisted

of vehicles involved in 2 vehicle collisions designated as

"angle collision" or "turning across traffic" (see Section 3.2).

Figure 5-1 is a graph of the proportion of those collisions occurring

at night, by model year and calendar year. The model year

(1964-72) is indicated on the horizontal axis; the calendar years

(1971-80) are indicated, by their last digits, as numbered points

on the graph. The "X's" mark the approximate center of the distribution of points, for each model year. Figure 5-1 appears to

indicate a substantial reduction in nighttime accidents in model

year 1968, when side marker lamps became standard on most vehicles.

There may be small additional reductions in 1965-66, when SML became

standard on some cars and 1970 when they became standard on all (see

Section 3.5). It is not clear from Figure 5-1, however, whether

these latter effects are due to SML or vehicle age trends. In

Figure 5-2, the same points are graphed by vehicle age and calendar

year. The figure indicates a strong calendar year effect: a

much higher proportion of nighttime accidents in 1971-72, when a

75


different definition of angle collision was used (see Section 3.2).

Also, there appears to be a cancelling age effect: the proportion of

nighttime accidents first increases and, for older cars, levels off

or decreases as age increases. Thus, the net bias due to vehicle

age effects is probably not large.

The results of the regression analysis mirror and

clarify what was observed in the graphs. Table 5-1 shows that

side marker lamps significantly reduced the risk of nighttime angle

collisions: the coefficient for LAMP is -0.076 and its t-value is

-2.70 (df=76, p<.05). The installation of s de marker lamps

on a single vehicle reduces its risk of nighttime angle collisions by

£. = 1 - exp (-.076) = 7 percent relative to

a vehicle without SML. The installation of SML on the entire

vehicle fleet reduces the risk of nighttime angle collisions by

£ 2 = 1 - exp (-.0X6 x 2 ) = 1A percent relative to

a fleet in which no vehicles have SML. Since North Carolina had

10 calendar years of data available and Texas only 3, the regression

results from North Carolina should be considered more accurate.

AGE has a significant positive coefficient and AGE^ has

an equally* significant negative coefficient. As Figure 5-2 suggested,

the ratio of nighttime to daytime accidents first increases and

eventually decreases with increasing vehicle age. The net marginal

age effect is zero when

.025 - 2(.00161) AGE = 0

78

which is when the vehicles are 7.8 years old. In other words, for

cars of approximately median age, the net age effect is close to

zero.

Table 5-1 shows that, as expected, the calendar year

effect is most strongly positive for 1971-72 and most strongly

negative for the recession years 1975-76.

The results for Dr. Chi's "refined test group" (see

Section 3.2) are nearly the same as for the more inclusive set of

angle collisions. The t-values of the coefficients are a bit lower

because the sample size of the underlying data tabulation is smaller,

causing the dependent variable to have more residual error. Table

5-2 shows that side marker lamps significantly reduced nighttime

angle collision risk (t = -2.13, df = 76) - by 8 percent when

installed on a single vehicle and by 16 percent when installed on

the entire vehicle fleet. The two estimates are just slightly

higher than those of Table 5-1.

5.2.2 Texas

The accident sample for Texas consisted of cars, trucks

and buses in 2 vehicle collisions in which one vehicle was

frontally damaged and the other, in the side. Figure 5-3 is a

graph of the proportion of those collisions occurring at night,

by model year (1964-72) and calendar year (1972-74). The calendar

years are indicated, by their last digit, as numbered points on the

graph. The "X's" mark, for each model year, the approximate

80


average for the 3 calendar years of data available. Figure 5-3

indicates an obvious and substantial reduction of nighttime accidents in

MY 68, when SML became standard equipment on most cars. There is, however,

a second large reduction in MY 70, when they became standard on all cars.

In Figure 5-4, the same points are graphed by vehicle age and calendar year.

There may be some tendency, among the newer cars, for nighttime accidents

to increase with vehicle age, but not among the older cars. The calendar

effect does not appear to be strong.

The regression results are consistent with what was

observed in the graphs and generate a model not unlike the one

in North Carolina. Table 5-3 shows that side marker lamps

significantly reduced the risk of nighttime angle collisions:

the coefficient of LAMP is -0.084 with t= -2.52, df-21,

one-sided pA05. The installation of side marker lamps on

a single vehicle reduces its nighttime angle collision risk by

8 percent. The number of nighttime collisions when all vehicles on

the road are equipped with SML is 16 percent lower than what would

occur if none of them were so equipped. These effectiveness estimates

are nearly the same as those in North Carolina (which were 7 and 14

percent, respectively).

The effects of vehicle age and calendar year are relatively

weak.

83


5.3 Injury accidents

The regressions of Tables 5-1, 5-2 and 5-3 are

repeated with the data sets restricted to injury-producing accidents

- in order to check whether the effect of SML found in all types of

accidents persists in crashes of higher severity.

5.3.1 North Carolina

Table 5-4 indicates that side marker lamps significantly

reduced the risk of being involved in an injury-producing nighttime

angle collision in North Carolina. The t-value for the coefficient

of LAMP is -2.98, df=76. The effectiveness estimate for installing

SML on a single vehicle is 12 percent. The accident reduction for

installing theift in all vehicles on the road is 23 percent. The

estimates are higher than those obtained in accidents of all severities

(Table 5-1 - the estimates were 7 and 14 percent) although not signifcantly higher (based on the standard errors of the regression

coeffients for LAMP in Tables 5-1 and 5-4). The regression equation

for injury accidents shows effects for vehicle age and calendar year

that are reasonably similar to the effects in accidents of all severities.

In Dr. Chi's refined test group, the effectiveness

estimates are 16 percent for equipping a single vehicle and 30

percent for the entire vehicle fleet - a significant reduction according

to Table 5-5. These anomalously high estimates, as well as the

negative rather than positive coefficient for AGE, may have been

caused by a statistical mischance - an unreasonably high reduction

in nighttime crashes for MY 68 relative to MY 67 - which in turn is

86


due to the relatively small cell sample sizes (see Table 4-5).

5.3.2 Texas

Table 5-6 indicates that injury-producing nighttime

angle collisions were significantly reduced in Texas, too. The

t-value for the coefficient of LAMP is -1.89, df = 21, one-sided p<".05.

The effectiveness estimate for installing SML on a single vehicle is

10percent; for equipping the entire vehicle fleet, 19 percent.

These estimates are a bit higher than the ones obtained from Texas

data for accidents of all severities (6 and 12 percent, respectively)

but a bit lower than the results for North Carolina injury crashes

(12 and 23 percent, respectively).

In the regression model, the effects of vehicle age

and calendar year are relatively weak, similar to those in the

analysis of Texas accidents of all severities.

In all 3 regressions (North Carolina, "refined"

North Carolina, Texas) the effectiveness estimate for injury-produeing

crashes was higher than the estimate for crashes of all severities,

but not significantly higher.

5.4 Fatal accidents

The accident sample from FARS consisted of cars, trucks

and buses in 2 vehicle collisions in which one vehicle was frontally

damaged and the other, in the side (see Section 3.4). Figure 5-5

is a graph of the proportion of those collisions occurring at night,

by model year (1964-72) and calendar year (1975-81). (The

89


numbered points on the graph indicate the last digit of the calendar

year.) The "X's" mark, for each model year, the approximate

average for the 7 calendar years of data available. Figure 5-5

certainly does not indicate a reduction of nighttime accidents in

MY 68, when SML became standard equipment. In fact, the pattern

of the X's is more less a parabola - lowest in 1964 and 1972 and

attaining a broad peak in 1968-70. That suggests a strong role

for vehicle age, with a positive coefficient for AGE and a negative

one for AGE^ (nighttime fatal accidents first increase as cars get

older and then eventually decrease). Finally, the nighttime accident

risk is consistently highest for the most recent calendar years,

1979-81, when the largest proportion of registered vehicles was

SML-equipped. That is probably not a cause-and-effect relationship,

but since the regression sees no evidence of positive SML effectiveness in the model year trend, it is likely to attribute this

relationship to LAMP rather than CY, with unpleasant consequences

for the effectiveness estimate.

As Table 5-7 shows, the regression attributes a

statistically significant adverse effect to side marker lamps

(t = +1.90, df=53). Based on the model, the installation of SML on

a single vehicle increases its nighttime fatal angle collision

risk by 13 percent; on the entire vehicle fleet, by 28 percent.

The regression model behaves in the manner predicted from observation

of the graphed data points: there is a large significant positive

coefficient for AGE, negative for AGE2. The effect of the calendar vear

terms is not significant (F = 1.67, df

 s 6, 53), suggesting that

the nighttime accident increase in later calendar years has been,

92

to a large extent, charged against SML.

It is fair to argue, then,that the significant negative

effect found in the regression is largely spurious. Further evidence

for this is that nearly the same thing happens in the regression

for a control group of head-on and rear-end collisions on FARS (see

Table 5-12).

5.5 Analyses for a control group of head-on and rear-end

crashes

The preceding regressions are reiterated for a control

group of 2 vehicle crashes that are not angle collisions -

viz., head-on and rear-end collisions. Side marker lamps should

be of little or no value in preventing those collisions at night.

Any significant "reduction" of nighttime control group collisions

attributed to SML by the regression could indicate a bias in the

preceding analyses of angle collisions.

5.5.1 North Carolina

The control group for North Carolina was defined to be

vehicles involved in 2 vehicle collisions that were specifically identified

as head-on or rear-end (see Section 3.2). The definition used

for calendar years 1971-72 differed from 1973-80, because of

changes in the accident report form. Figure 5-6 is a graph of

the proportion of control group collisions occurring at night, by

vehicle age and calendar year. (The numbers on the graph indicate

the last digit of the calendar year.) Figure 5-6 appears to indicate

94

a nearly linear vehicle age effect for the points from CY 1971-72 and

another nearly linear effect for the points from CY 1973-80. The

two straight lines seem to explain most of the variation among the

data points.

The regression, Table 5-8, confirms what was observed in

the graph. The linear effect of vehicle AGE and the calendar year

effect (especially 1971-72 versus all others) explain most of the

variance. Side marker lamps do not have a statistically significant

"effect" on nighttime collision risk -in fact, a nonsignificant

increase in the risk was observed (4 percent on a single vehicle and

9 percent if SML are installed on the entire vehicle fleet).

When the North Carolina data are restricted to injury-producing accidents, the results are almost identical. Table 5-9

indicates that side marker lamps did not have a significant effect

in the control group. The observed "effectiveness" estimates were

-2 percent (on a single vehicle) and -3 percent (on the entire fleet).

5.5.2 Texas

Figure 5-7 is a graph of the proportion of accidents

occurring at night, by vehicle age and calendar year, for the Texas

control group (which was defined in Section 3.3). Thanks to the

very large sample cell sizes it shows an even stronger relationship

between vehicle age and the dependent variable than did the North

Carolina data. The "effect" of side marker lamps is obviously

negligible.

96



The regression analysis confirms what was observed in

the graphs. Table 5-10 shows that the accident "reduction" attributed

to side marker lamps is not statistically significant (t = -0.86)

and amounts to 2 percent, when SML are installed on a single vehicle

or 4 percent, when installed in the entire fleet. Most of the

variation in the data points is explained by the vehicle age variables.

Similarly, Table 5-11 shows that side marker lamps

had no significant effect on injury-producing nighttime control

group crashes (t = -0.30). The observed "effectiveness" of SML is

less than 1/2 percent, on a single vehicle, and 1 percent when they

are installed in the entire fleet.

The control group results for North Carolina and Texas

are consistent with one another. None of them produced a significant

effect for side marker lamps. All of the analyses of angle collisions

from those States showed significant benefits for SML. Thus, the

control group analyses do not indicate any bias in the analyses of

angle collisions.

5.5.3 Fatal Accident Reporting System

In the analysis of fatal angle collisions (Section 5.3)

the regression attributed a significant 13 percent increase in nighttime

collision risk to the installation of SML on a single vehicle. It

was argued that this was undoubtedly a spurious result, possibly

because the regression attributed calendar year effects to SML.

100


Table 5-12 shows that almost the same thing happened

in the control group. The model attributed a statistically significant

(t <• 2.19) increase in nighttime head-on and rear-end collision to

SML. The observed increase is 14 percent, when the lamps are

installed on a single vehicle and 29 percent, when installed on the

entire fleet.

The fact that the angle collision and control group

regressions produced nearly identical spurious, negative results

could, perhaps, be viewed as evidence that side marker lamps have

little or no effect in preventing fatal angle collisions. But it

is not very convinving evidence. More analyses of FARS are needed.

103

CHAPTER 6

FATAL INVOLVEMENTS PER 1000 VEHICLE YEARS

The rate of involvement in fatal nighttime angle collisions,

per 1000 vehicle exposure years, does not appear to have decreased as

a result of side marker lamps.

6.1 Method and exposure data sources

The contingency table analyses of Chapter 4 and regressions

of Chapter 5 provided clear, consistent evidence that side marker

lamps prevent nonfatal collisions, but did not provide corresponding

results for fatal crashes. Both chapters relied on comparing the

number of nighttime and daytime crash involvements. It is possible

that the FARS results (which are based on the smallest samples) were

thrown off by unanticipated variations in the number of daytime crashes.

It would be desirable to analyze FARS by another approach which does

not require information on daytime crashes.

Rather than calculating the risk of nighttime relative to

daytime crashes, calculate the absolute risk: the number of fatal

nighttime angle collision involvements per 1000 vehicle exposure years.

The number of vehicles, of a particular model year MY, involved in

nighttime angle collisions, is identified for a specific calendar year

CY of FARS. This number is divided by the quantity of cars, trucks

and buses of model year MY that were still on the road in the United

States in calendar year. CY - a quantity given by Table 3-3 of this

105
report and derived from "MVMA Motor Vehicle Facts and Figures '82 "

\L203. The analysis is feasible because FARS is a national fatality census.

Thus, an accident rate is obtained for each CY, MY

combination; CY ranges from 1975 to 1981, the years for which FARS

data were available; MY ranges from 1964 to 1972. These CY, MY accident

rates, or their logarithms, can be used as observations of the dependent

variable in a regression, using the same independent variables as in

Chapter 5. But a simpler approach is to calculate the average accident

rate for a model year MY by summing accidents and exposure across the

7 calendar years of FARS:

81

R(MY) = J~ Accidents (CY, MY)

CY - 75

81 •

Vehicle years (CY, MY)

75

Both approaches for analyzing exposure-based accident

rates were used in NHTSA's evaluations of head restraints \lb) , pp. 175-177

and side door beams \15~\ , pp. 167-179.

6.2 Tabulation of accident rates

Table 6-1 indicates the number of fatal nighttime angle

collision involvements per 1000 vehicle exposure years, by model year,

during 1975-81. Cars, trucks and buses of model year 1967 were involved

in 965 nighttime angle collisions on FARS during 1975-81. They

accumulated 33,915,000 vehicle exposure years during that time. That

is a rate of .0285 accidents per 1000 vehicle years. Cars, trucks

and buses of model year 1968 had 1292 accidents and 43,382,000

vehicle exposure years in 1975-81: a rate of .0298 accidents per

1000 years. In other words, MY 68 vehicles, most of which were equipped

106
TABLE 6-1

U.S. FATAL ACCIDENTS, 1975-81: NIGHTTIME ANGLE COLLISION INVOLVEMENTS

PER 1000 VEHICLE YEARS, BY SIDE MARKER LAMP STATUS

Model Years Exposure 1975-81 Nighttime* Angle Accident Reduction

(1000 Vehicle Years) Collision Rate for

Involvements SML (%)

1967 (last year w/o SML) 33,915 965 .0285

1968 (first year w. SML) 43,382 1292 .0298 -5

1966-67 64,744 1818 .0281

1968-69 95,965 • 2861 .0298

1965-67 . 89,374 2481 .0278

1968-70 152,177 4532 .0298

— D

• /

1964-67 106,077 2927 .0276

1968-71 212,434 6276 .0295

*Includes dawn and dusk

**Statistically significant accident increase (one-sided/, = .05)

107
with SML, had a 5 percent higher risk of fatal nighttime angle

collisions than MY 67 vehicles most of which were not equipped. The

increase, however, is not statistically significant because

1,292 _ 965

43,382 33,915

X « , = 1.08

1,292 965 1 1/2

43,3822 33,915^

When the sample is expanded to include model years 1966-67

vs. 1968-69 (the + 2 MY comparison), the result is slightly more

unfavorable to side marker lamps. Table 6-1 indicates that the MY

68-69 vehicles had a 6 percent higher accident rate than MY 66-67 -

a statistically significant increase because

2,861 _ 1,818

95,965 64,744

Z= 2.01

2,861 , l,818/\ 1/2

95,965Z 64,7442I

In the + 3 MY and + 4 MY comparisons, the increase in the accident

rate for SML-equipped vehicles is 7 percent.

At first glance, the results do not show any evidence of

a beneficial effect of side marker lamps in fatal crashes and even

leave open the possibility that they increased accident risk. On

closer inspection, though, the sequence of effectiveness estimates for

the 4 consecutively broader samples - -5,-6, -7, -7 - shows a modest

trend, probably due to the increasing difference in the age of the pre

and post-standard vehicles. Similarly, the accident rate for the pre-stan108
dard cars decreases as more and more older cars are added to the

sample: .0285, ,0281, .0278, .0276 in Table 6-1. This decrease is

not attributable to side marker lamps and could be creating an

unfavorable bias in the SML effectiveness estimate.

A regression analysis is perhaps more suitable to deal

with these vehicle age-related trends.

6. 3 Regression of accident rates

The method for regression of accident rates per 1000

years is virtually the same as for nighttime/daytime accident ratios.

Each applicable CY/MY combination yields one data point for the

regression, where CY ranges from 75 to 81 and MY from 64 to 72. The

dependent variable is the logarithm of the nighttime fatal accident

rate

N(CY, MY)

L0GR (CY, MY) = log

EXPO (CY, MY)

where N(CY, MY) is the count of nighttime angle collision involvements

of vehicles of model year MY on the FARS file for year CY and EXPO

(CY, MY) is the number of vehicles of model year MY that are still

on the road during CY (from Table 3-3).

The independent variables are LAMP, AGE, AGE2 and CY,

which are defined in Section 5.1. LAMP is a measure of the combined

availability of the side marker lamps of two vehicles involved

in an accident during calendar year CY, one of which is known to be of

model year MY. AGE •* CY - MY. CY is treated as a categorical

variable.

109
A weighted regression is run, with EXPO (CY.MY) as the

weight variable, using the General Linear Models procedure of SAS.

As explained in Section 5.1, LAMP •= 0 when none of the

vehicles on the road have side marker lamps. If a single vehicle is

equipped with side marker lamps, but no others are, LAMP = 1 in

calculations of the accident risk for this vehicle. If every vehicle

on the road is equipped with SML, LAMP * 2. Let a -^ be the calculated

regression coefficient for LAMP. Then, if a single vehicle is equipped

with SML, its nighttime angle collision risk is reduced by

£.l - 1 - exp (ap

When all vehicles on the -oad have SML, the angle collision risk per

1000 vehicle years is

£2 - 1 - exp (2 a1)

lower than if no vehicles have SML.

Table 6-2 indicates that side marker lamps had no

statistically significant effect on the rate of fatal nighttime angle

collisions per 1000 vehicle years. The t value for the regression

coefficient for LAMP is 0.39., df=53. The estimated effect of installing

side marker lamps on a single vehicle is that the accident rate would

increase by 2 percent: this estimate is closer to zero than the results

obtained in the preceding section. The regression assigns a

2

substantial negative coefficient to AGE , indicating that, for older

cars, the accident rate decreases as vehicle age increases. This

is a bias against side marker lamps which produced excessively unfavorable

results in the preceding section.

110

The standard deviation of the regression coefficient for

LAMP is 0.054, while the coefficient itself is 0.21. A lower confidence

bound (one-sided<L- .05) for the effect of installing SML on a single

vehicle is

1 - exp (.021 + 1.674 x .054) = -12 percent

(where 1.674 is the 90th percentile of a t distribution with 53 df).

The upper bound is

1 - exp (.021 - 1.674 x .054) = 7 percent

In short, the best estimate from the regression is that

side marker lamps had little or no effect on fatal nighttime angle

collisions, but the confidence bounds indicate a fair amount of

statistical uncertainty about this result. Based on statistical

analyses, alone, it cannot be firmly concluded that side marker lamps

have no effect on fatalities.

6.4 Analyses for a control group of head-on and rear-end

crashes

As in Chapter 4 and 5, it is desirable to repeat the

analyses for a control group of 2 vehicle crashes that are not angle

collisions - viz., head-on and rear-end collisions. If side marker

lamps appear to have the same "effects" in the control group and in

angle collisions, it would reinforce a conclusion that SML have little

or no effect in fatal angle collisions.

Table 6-3 indicates the number of fatal nighttime accident

involvements, in the control group, per 1000 vehicle years. The results

are virtually identical to the ones for angle collisions (Table 6-1).

The accident rate for MY 68 cars is a nonsignificant 3 percent

112
Model Years

TABLE 6-3

U.S. FATAL ACCIDENTS, 1975 - 81: NIGHTTIME HEAD-ON

AND REAR-END COLLISION INVOLVEMENTS, PER 1000 VEHICLE

YEARS, BY SIDE MARKER LAMP STATUS

Exposure 1975-81

(1000 Vehicle Years)

1967 (last year w/o SML) 33,915

1968 (first year w. SML) 43,382

Nighttime*

Control Gp.

Involvements

1938

2564

3648

5852

4980

9278

5900

12,860

Accident

Rate

,0571

.0591

.0563

.0609

.0557

.0610

.0556

0605

Reduction

for

SML <%)

-3

-8**

_9**

_9**

1966-67

1968-69

1965-67

1968-70

1964-67

1968-71

64,744

95,965

89,374

152,177

106,077

212,434

•Includes dawn and dusk

**Statistically significant accident increase (one-sided/, = .05)

113
higher in the control group than for MY 67 cars (it was a nonsignificant

5 percent higher in the angle collisions). The sequence of "effectiveness"

estimates in the control group, for progressively broader samples, is

-3, -8, -9, -9, It was -5, -6, -7, -7 in the angle collisions. Given

the relatively small sample sizes from FARS, the two sequences may be

considered equivalent. In other words, Table 6-3 helps support a

conclusion that side marker lamps had little effect in fatal crashes.

(Contrast this to the situation in Chapter 4, where the control

group and angle collisions behaved differently, possibly due to

confounding effects on daytime fatal accidents, and left more doubt

about the effect of SML.)

A regression analysis for the control group is carried out

in Table 6-4. Just as in bdth FARS regressions of Chapter 5, the

results are not meaningful because the model assigns a large negative

effect to side marker lamps, possibly confusing it with the calendar year

effect. It is not appropriate to compare the results to Table 6-2, the

regression on angle collision rates, which appeared to have modeled the

data points properly.

114

CHAPTER 7

"BEST" ESTIMATES OF SIDE MARKER LAMP EFFECTIVENESS

Regressions on the combined North Carolina and Texas data

sets provide good estimates of the effectiveness of side marker lamps in

preventing nonfatal crashes. It is estimated that installation of

side marker lamps reduces a vehicle's nighttime angle collision risk

by 8 percent (11 percent for injury-producing crashes). When all vehicles

on the road have side marker lamps, there will be 16 percent fewer

nighttime angle collisions (21 percent fewer injury-producing crashes)

than if none of them had the lamps. It is also concluded that side

marker lamps have little or no effect on fatal collision risk. The

conclusion is based on the statistical results of Chapter 6 and an

analysis of sighting and stopping distances to be carried out in this

chapter.

7.1 Effectiveness estimates from Chapters 4-6

Table 7-1 recapitulates the effectiveness estimates for

side marker lamps obtained by various methods and data sources in

Chapters 4-6. In the regression analyses, the effect of installing

SML on a single vehicle is shown rather than that of installing them on

the whole vehicle fleet, because the former is more comparable to the

reduction from MY67 to MY68.

The 6 results for accidents of all severities are extremely

consistent, varying only between 7 and 8 percent. All 6 reductions are

statistically significant.

117
TABLE 7-1

SUMMARY OF EFFECTIVENESS ESTIMATES

FOR SIDE MARKER LAMPS IN CHAPTERS 4- 6

Nighttime Angle

Collision Reduction (%)

* n J n J »Contingency

Analysis Procedure->Table ^

Basis for Comparison—> MY 68 vs. MY 67

Computation Method-^ Nighttime/Daytime

ACCIDENTS OF ALL SEVERITIES

North Carolina 7*

North Carolina (refined) 8*

Texas

INJURY-PRODUCING ACCIDENTS

North Carolina

7*

8*

North Carolina (refined) 13*

Texas 8*

FATAL ACCIDENTS

FARS - 3

Regression

Instal l SML on a Singl e Veh.

Nighttime/Daytime Nighttime/1000yrs.

7*

8*

8*

12*

16*

10*

-13** -2

* statistically significant effect

** analysis suspected of major biases

118
The 6 results for injury producing accidents are also

consistent with one another and slightly higher than the preceding ones,

varying between 8 and 16 percent. Again, all 6 reductions are statistically

significant. Two of the 3 results for fatal crashes are close to

zero. The third is based on a regression which was suspected of having

confused calendar year differences in the data with the effect of side

marker lamps (see Section 5.4).

It should be noted that the results based on comparison of

MY68 and MY67 are not exactly comparable to the regressions. Since 13

percent of MY67 cars already had SML, while 12 percent of MY68 cars did

not yet have them, the change from MY67 to 68 is not quite as drastic

as from a vehicle without SML to one with SML. Let R be the nighttime

angle collision risk with SML, R~ without them. Since, in North Carolina

and Texas

.07-1 -

 R6 8 - « 1 - .88R* + .12R"

R67 .13R+ + .87R"

.09

R"

In other words, a 7 percent accident reduction from MY 67 to MY 68 is

equivalent to an 9 percent reduction for equipping a single vehicle with

SML.

Thus, the results from Chapter 4 (comparison of MY67 and

68) need to be augmented by about 2/7 to make them directly comparable to

the regression results. That should be kept in mind in a review of

Table 7-1. After the contingency table analysis estimates are augmented,

they are still close to the regression results, especially so for injury

crashes.

119
7.2 "Best" estimates for nonfatal crashes

The North Carolina and Texas data sets obviously produced

compatible results. It would be desirable to combine the data files, somehow, to produce a single, statistically precise effectiveness estimate.

The estimate should be formulated as follows: the percent reduction of

nighttime angle collisions when all vehicles on the road have side

marker lamps, relative to a situation where no vehicles on the road have

SML. An estimate of this form can be obtained only by regression, not

contingency table analysis. In other words, the regressions of Chapter 5

should be performed on a combined North Carolina-Texas data set. There

is good reason to believe that the approach will be successful because, in

Chapter 5, not only the effectiveness estimates but the entire regression

equations were reasonably similar for the 2 States.

In the combined regression, each permissible combination of

State/Calendar Year/Model Year yields one data point. In other words,

the original 89 data points from North Carolina and 27 points from

Texas are left unchanged and pooled to provide a total of 116 data

points. The dependent variable, weight factor and independent variables

LAMP, AGE and AGE^ are the same as before. Only the independent variable

CY is changed to a new categorical variable STATECY which contains one

category for each calendar year of data from each State: NC71, NC72, ...,

NC80, TX72, TX73, TX7A.

120
7.2.1 Accidents of all severities '

Table 7-2 shows that side marker lamps significantly reduced

the risk of nighttime angle collisions: the coefficient for LAMP had

t value -4.40, df » 100. The regression fit the combined data set very

well (R2 = .87). It attributed a significant positive coefficient to

AGE and an equally significant negative coefficient to AGE2, consistent

with the trends observed in graphs of both States' data points.

When side marker lamps are installed in every vehicle on

the road, the number of nighttime angle collisions will be

1 - exp (-.088 x 2) = 6 percent lower than if none

of the vehicles on the road had SML (The regression coefficient for

LAMP is -.088; see Section 5.1 on the derivation of the effectiveness

estimate.) Confidence bounds (one-sided o(.= .05) for this estimate can

be obtained by noting that the standard deviation of the regression

coefficient for LAMP is .020. The confidence bounds are1

1 - exp (-.088 - (1.661 x .020) x 2)

« 10 to 22 percent

(Note that 1.661 is the 90th percentile of a t distribution with 100 df.)

Similarly, the installation of side marker lamps on a single

vehicle reduces its nighttime angle collision risk by 8 percent (confidence

bounds: 5 to 11 percent). This result is almost exactly in the middle of

the 6 earlier estimates summarized on Table 7-1, after the estimates based

on contingency tables are augmented as described in Section 7.1.

121

7.2.2 Injury accidents

Table 7-3 indicates that side marker lamps significantly

reduced the number of injury-producing nighttime angle collisions: the

coefficient for LAMP had t • 3.67. The other regression coefficients

were similar to those obtained when the analysis was performed on the

States separately (Tables 5-4 and 5-6).

When side marker lamps are installed in every vehicle on the

road, the number of injury-producing nighttime angle collisions will be

1 - exp (-.120 x 2) - 21 percent

lower then if none of the vehicles on the road had SML. The confidence

bounds for this estimate are 12 to 29 percent. The installation of

SML on a single vehicle reduces the risk by 11 percent (confidence

bounds: 6 to 16 percent). This result is, again, almost exactly in

the middle of the 6 estimates obtained earlier in the study (see Table

7-1).

The "best" estimate is that side marker lamps are slightly

more effective in preventing accidents of a severity likely to cause

injuries than in eliminating property damage accidents (21 vs. 16

percent, for the whole fleet; 11 vs. 8 percent for a single vehicle).

Since the best estimate of all-severity accident reduction is within

the confidence bounds for injury reduction, however, it cannot be

firmly concluded that the latter is higher than the former. A more

appropriate conclusion is that injury reduction is as high or slightly

higher than overall accident reduction.

123

^«3 "Best"estimates for fatal crashes

7.3.1 Statistical results

The statistical analyses of fatal crashes appear to indicate

that the effect of side marker lamps is close to zero. The statistical

approach that, perhaps, did the best job modeling the data and yielded the

most precise results was the regression of nighttime fatal crashes per

1000 vehicle exposure years (Section 6.3). It yielded a point estimate

that the installation of current side marker lamps on a single vehicle

raises the risk of a fatal nighttime angle collision by 2 percent.. The

increase was not statistically significant. Moreover, the confidence

bounds (one-sided <* = .05) for effectiveness ranged from -12 to +7 percent.

In other words, the statistical analyses would certainly

support a hypothesis that the effect of side marker lamps on fatal crashes

is negligible, but they are also compatible with possibilities that SML

have moderately large negative or positive effects.

7.3.2 Analysis of travelling speeds in fatal crashes

Another approach is tq analyze the distribution of precrash travelling speeds of vehicles in angle collisions and to identify

groups of crashes for which side marker lamps would have little or no

potential for preventing a collision or significantly reducing its

severity. Specifically, there are two situations where, based on precrash travelling speeds alone, it can be Inferred that SML would have been

of limited utility:

(1) One of the vehicles is travelling so fast that the

driver is unable to see and react to the SML of the other vehicle in time

to stop or significantly reduce speed.

125


Thus, side marker lamps will be of limited utility if V^**" 3.7V2 and

V2 <f 3.7Vi - situation (2) in the preceding discussion.

The Multidisciplinary Accident Investigation data file

contains records of 144 angle collisions in which the precrash travelling

speeds of both vehicles were known and in which someone in the struck

vehicle suffered a fatal or critical injury. There are 524 cases where

nobody in the struck vehicle suffered more than a minor injury. The

travelling speeds of the vehicles are distributed as follows:

(1) Percent with one car over

50 miles per hour

(2) Percent with V± < 3.7V2

and V2 < 3.7V., (both vehicles

< 50 mph)

Fatal and Critical

Inj uries

45

Minor

Injuries

10

42 47

Percent in which SML have

limited or no potential

Percent in which SML have

potential to be effective

87

13

57

43

Thus, based on travelling speeds, SML have the potential to provide an

adequate warning in 13 percent of fatal collisions and 43 percent of nonfatal injury collisions. (Of course, in many crash situations, the lamps

are not seen due to other vision obstructions, driver inattention, etc., so

the actual effectiveness of SML is well below 13 percent in fatal crashes

128
and 43 percent in nonfatal crashes.) In other words, based on speed

distributions alone, the potential benefit of SML in fatal crashes is,

at best, 1/3 as large as in nonfatal crashes.

Finally, alcohol is another factor that could reduce the

effectiveness of side marker lamps in fatal crashes. Approximately

60 percent of fatal nighttime multivehicle collisions involve at least

one intoxicated driver C33. The inattention or unsafe actions by that

person could nullify the potential benefits of side marker lamps:

When the effect of alcohol is added to that of speeds that

exceed SML sighting distances or make the headlamps visible to both drivers,

it can be concluded that the potential benefit of side marker lamps in

preventing fatal crashes or reducing their severity to a nonfatal level

is, at best, 1/4 as large as in nonfatal crashes—i.e., at best a 2 percent

reduction when the lamps are installed on a single vehicle. That reduction

is well within the confidence bounds obtained in the statistical analysis

of fatal crashes, which ranged from -12 to +7 percent effectiveness. Since

o None of the statistical analyses showed a positive

effect for side marker lamps (but only nonsignificant negative effects on

the order of -2 to -5 percent),

o The preceding analysis of sighting and stopping

distances indicates that the benefit in fatal crashes, if any, is

unlikely to exceed 2 percent,

129
o There is no intuitive basis for believing that side

marker lamps would increase the risk of fatal angle collisions,

it is concluded that side marker lamps have little or no effect in preventing

fatal angle collisions or reducing their severity to a level where no

fatalities occur.

130
CHAPTER 8

COSTS AND BENEFITS

One of the goals of the evaluation is to estimate the actual

benefits and actual costs of side marker lamps in a manner that allows

a meaningful comparison of benefits and costs.

The benefits of side marker lamps are the number of injuries

and the value of property damage that will be prevented annually when

all cars, trucks and buses on the road have side marker lamps — relative

to a baseline case where none of the vehicles on the road have any

side marker lamps.

Similarly, the cost of SML is the average annual fleetwide

cost of lamps that were installed in vehicles during 1970-83, a period

during which all new cars, trucks and buses were equipped with SML — relative

to a baseline case of vehicles that have no side marker lamps at all.

The cost includes the increase in the initial purchase price of a

vehicle, the incremental fuel consumption due to the weight and electrical

consumption of the equipment and any growth in repair and maintenance

costs. All costs are expressed in 1982 dollars.

8.1 Costs

A 1979 study performed under contract to NHTSA gave estimates

of the purchase price increase and weight added to passenger cars by

131
side marker lamps ClO3. Estimates were obtained for a representative

sample of 16 cars of model year 1970. The lamps in MY 1970 cars are

quite similar to those in subsequent model years and those of current

(1983) design. The study sample did not include any light trucks but

their side marker lamps are similar to cars'. Nor did it include heavy

trucks and buses, whose lamps are likewise similar to cars' except for

the possible inclusion of a third lamp at the vehicle's midpoint. Their

sales are small relative to cars and light trucks and therefore have

little effect on the fleetwide average cost of the lamps. Thus, the

average cost of SML per model year 1970 passenger car is close to the

average current cost per car, truck or,bus.

Table 8-1 indicates, for each of the 16 models, the total

cost and weight of SML in 1970. It is the total for all 4 lamps on the

car. In this evaluation, the "baseline" vehicle has no SML at all—i.e.,

zero cost and weight—so the figures in Table 8-1 represent the incremental

cost and weight for SML. (It should be noted that the contractor's

analysis uses as "baseline" the SML of cars of MY 1968 and 69 and

subtracts their cost from those of MY 70. That results in a much lower

incremental cost, but one which is inconsistent with the method by which

benefits are calculated in this evaluation—i.e., relative to no SML

at all.) The "cost" in Table 8-1, which is meant to approximate the

purchase price increase, includes materials, labor, tooling, assembly,

overhead, manufacturer's and dealer's markups and taxes. The cost is

expressed-in 1982 dollars, whereas the contractor report on which it is

based used 1979 dollars. The cost has been converted to 1982 dollars by

132
TABLE 8-1

COST AND WEIGHT ADDED BY SIDE MARKER LAMPS

(1982 dollars)

Specimen

Vehicle

70 AMC Gremlin

70 Plymouth Valiant

70 Plymouth Satellite

70 Plymouth Fury

70 Ford Maverick

70 Ford Fairlane

70 Ford Galaxie

70 Mercury Cougar

70 Chevrolet Nova

70 Chevrolet Malibu

70 Chevrolet Impala

70 Chevrolet Camaro

70 Buick Electra

70 Cadillac DeVille

70 Toyota Corona

70 Volkswagen Beetle

1970 Sales

(000)

23

242

161

268

211

329

807

72

315

394

891

125

403

215

35

400

SALES-WEIGHTED AVERAGE

Side Mai

Cost

$14.01

17.43

17.88

16.93

21.19

21.15

21.27

18.03

15.64

12.41

10.66

11.18

12.68

23.90

33.37

20.00

$16.76

rker Lamp

Weight

1.36 pounds

1.74

1.92

1.77

2.64

3.20

3.64

3.35

1.31

0.97

0.95

0.97

1.13

3.92

1.65

1.59

2.00 pounds

133
multiplying by the ratio of the Consumer Price Index for automobiles,

which was 159.8 in 1979 and 198.1 in 1982.

Thus, according to Table 8-1, the average purchase price

increase for side marker lamps is $16.76 per vehicle.

Table 8-1 also indicates that SML added an average of 2.0

pounds to the weight of a car. Each incremental pound of weight results

in the consumption of an average of one additional gallon of fuel over

the lifetime of a car [ 9 1, pp. VII-43-46. Table VII-16 of [ 9 1

calculates the discounted present value of consuming an additional

gallon of fuel over the lifetime of a car. When the costs in that

table are changed to reflect 1982 fuel prices ($1.21 per gallon in

February [ 191, p. 82), it is found that each incremental pound of

weight adds $1.00 to the discounted lifetime cost of owning and operating

a car. Since SML add 2 pounds, the weight-related fuel penalty is $2.00.

Lamps also add to fuel consumption because they use electricity

which is supplied by the battery which, in turn, is recharged by applying

a drag on the engine. The type 194 bulb, which is widely used for

side marker lamps (see Chilton's Auto Repair Manual, 1970), runs on 14

volts and .27 amperes — i.e., 3.78 watts {23}, p. 21.25. With 4 SML

to a car, that is 15.12 watts. Over its lifetime, the average car is

driven 28,000 miles at night (derived from the mileage-based fatality

rates in "Accident Facts, 1979"[l*\, p. 50). Under the assumption of

an average speed of 25 miles per hour, that amounts to 1120 hours with

the lamps on, over the life of a car. Thus, the electrical power

consumption by the lamps is

134
15.12 watts x 1120 hours =16.9 kilowatt hours

Finally, assume that the process by which the engine and alternator

—convert motor fuel to electricity is 20 percent efficient and that

the combustion of a gallon of fuel produces 38.68 kilowatt hours of

energy [ 24 1• It takes, then, 2.19 gallons of fuel to produce 16.9

kilowatt hours of electricity. The net present value of the fuel needed

to power the lamps, over the life of the car, is $2.19.

Side marker light bulbs can burn out and must be occasionally

replaced. The Hunter service job analysis indicates that 82 million

small light bulbs of all types are replaced annually C27^] • The average

motor vehicle contains 30 small bulbs, 4 of which are side marker lamps

(based on light bulb information in Chilton's Auto Repair Manual, 1970).

Under the assumption that bulbs of different types are replaced at

about the same rate, it is estimated that 10.9 million SML bulbs are

replaced per year (i.e., 4/30 of 82 million). Since 12.3 million

cars, trucks and buses are sold per year, it means there is a probability

of .89 » 10.9/12.3 that an SML bulb will be replaced sometime during

the life of a vehicle. Typically, replacement could occur in the

vehicle's 8th year. Since this is 7 years after purchase, the cost

should be discounted by .478, assuming a 10 percent discount rate.

Finally, inquiries to parts shops in the Washington area indicated

an average price of 63 cents for the bulbs. Thus, the discounted cost

of replacement bulbs per motor vehicle is

135
is

.89 x .478 x 63 = 27 cents

The total consumer cost per vehicle for side marker lamps

purchase price increase + fuel (weight) + fuel (electricity)

+ replacements = $16.76 + 2.00 + 2.19 + 0.27 = $21.22 (in 1982

dollars)

Since 12.3 million cars, trucks and buses are sold annually in the

United States, the total cost of side marker lamps is about $261

million.

8.2 Benefits

The best estimates of effectiveness (from Section 7.2) were

that if all cars, trucks and buses were equipped with side marker lamps

of current design, there would be 16 percent fewer nighttime angle

collisions than if none of the vehicles had SML (confidence bounds:

10to 22 percent). There would be 21 percent fewer injury-producing

nighttime angle collisions (confidence bounds: 12 to 29 percent).

Benefits are calculated by.applying these reductions to the number of

nighttime angle collisions that would occur annually if no vehicles

136
on the road had SML and to the number of injuries and amount of

damages that would occur in these crashes.

For example, according to National Accident Sampling

System (NASS) data, there are 6,773,000 police-reported motor vehicle

accidents per year [ 251 - What percentage of them would have occurred

in nighttime angle collisions? The most reliable information source

is the National Accident Summary (NAS), which is a census of policereported and encoded accidents from 39 States in 1971. The file

contains records of 3,964,469 accidents of which 375,642 are nighttime

angle collisions. Note, however, that the data were collected in 1971,

when 40 percent of cars, trucks and buses on the road were equipped with

SML (see Section 3.5). Thus, the number of nighttime angle collisions

on NAS must be augmented by the number which was already eliminated by

the SML in vehicles on the road in 1971:

375,642 = 375,642

1 -.40£A 1 -.40 x .16

(where £ = accident-reducing effectiveness of side marker lamps). Also

A

only 97 percent of the vehicles involved in angle collisions on NAS are

cars, trucks and buses; the 3 percent that are other vehicle types must

be removed from the total.

137
The appropriate formula, then, for accidents avoided by

side marker lamps is

A = NAC . £

Benefit us A

A . P . £

NASS NAC

 U

N A Us

where

. \CJ*. - accidents avoided (annual benefit)

ienefit

NACu g = nighttime angle collisions in the U.S. if no

vehicles have SML

£A = accident reducing effectiveness of SML = .16

(confidence bounds: .10 - .22)

= total number of police-reported accidents,

based on NASS = 6,773,000

P = proportion of crashes that are nighttime angle

collisions

NACN A g = nighttime angle collisions on NAS = 375,642

0 CNAS =- othe r crashes on NAS = 3,588,827

L,i = proportion of registered vehicles with SML in

1971 = .40

C T % A S ='Pr°P°rtion of vehicles involved in angle collisions

on NAS that are cars, trucks or buses = .97

138
Thus

PNAC " -0976

NAC = .0976 x 6,773,000 = 661,000

US

ABenefit = 6,773,000 x .0976 x .16

= 661,000 x .16

= 106,000 police-reported crashes avoided annually

Confidence bounds for the number of accidents avoided can be

computed by substituting the lower and upper confidence bounds for £^,

respectively, for the point estimate, in the 3 places where £•£ appears in

the formula for Agenef£t. The lower confidence bound (one-sided oC = .05)

for accident avoidance is 65,000; the upper bound is 149.,000 crashes

avoided per year.

Similarly, the total amount of property damage that occurs in

motor vehicle accidents is $22,200 million per year, according to NHTSA's

study of "The Economic Cost to Society of Motor Vehicle Accidents" [ 7 1,

p. 1-4 (converted from 1980 to 1982 dollars,"using the Consumer Price

Index for automobiles). As calculated above, P^AC ~ 9.76 percent of

all crashes would be nighttime angle collisions, in the absence of side

marker lamps. It is assumed that nighttime angle collisions, likewise,

139
account for 9.76 percent of all property damage. Finally, side marker

lamps eliminate 16 percent of those 9.76 percent:

PDB ,.. = PD —NAC . £.

Benefit us A

=PD t o t

where

P D B nefit = Pr o Pert y damage avoided (annual benefit)

PD — NACTJO = property damage in nighttime angle collisions

in the U.S. if no vehicles have SML .

£^ = accident reducing effectiveness of SML = .16

(confidence bounds: .10 -.22)

PD. . = property damage in all motor vehicle accidents

= $22,200 M

]?NAC = proportion of crashes that are nighttime angle

collisions (formula provided above)

Thus

PD -NACUS = .0976 x $22,200M = $2,167M

PDBeneflt = $ 2167 M x .16 = $347 million property damages

avoided annually

Confidence bounds for property damage avoidance can be computed

by using the confidence bounds for i-^ in the formulas for PDfienefit

PNAC# <^ae l° w e r confidence bound for damage savings is $213 million;

the upper bound is $488 million saved per year.

140
The calculation of the number of injuries avoided is similar

to the computation of crash avoidance, except that

o the injury reducing effectiveness of SML (21%) is

slightly higher than the overall accident reducing effectiveness (10

percent)

o The proportion of injury producing crashes that are

nighttime angle collisions (11.02 percent) is slightly higher than

I'NAC' the corresponding proportion for crashes of all severities

(9.76 percent) - as will be calculated below.

Thus, a somewhat larger proportion of the 4,000,000 motor vehicle crash

injuries that occur annually in the United States (according to NHTSA's

societal cost study [ 7 "], p. II-2) are eliminated by side marker lamps.

The appropriate formula for injury avoidance is

D ._, = 1 -NAC . £ Benefit US I

= T1 P £

tot * *NAC -I ' I

-

 L 7 /

where

IB £. = injuries avoided (annual benefit)

141
= injuries in nighttime angle collisions in

the U.S. if no vehicles have SML

= injury-reducing effectiveness of SML = .21

(confidence bounds: .12 -.29)

Itot

 = total number of persons injured in crashes in the

U.S. per year = 4,000,000

]?NAC T = proportion of crash injuries that occur in

nighttime angle collisions

= nighttime angle collision injuries on NAS

213,381

0 INAS = otne r

I injuries on NAS = 1,817,954 NAS

= proportion of registered vehicles with SML in

1971 = .40

proportion of vehicles involved in angle collisions

in NAS that are cars, trucks or buses = .97

Thus

PNAC -I = -H02

I -NACug = .1102 x 4,000,000 = 440,800

benefit

 = 4,000,000 x .H02 x .21

= 440,800 x .21

= 93,000 injuries avoided per year

Confidence bounds for the number of injuries avoided can be computed

by substituting the boundary values for £j for the point estimate in

142
the 3 places where £j appears in the formula for Ijjenefif ^ e lower

confidence bound is 51,000; the upper bound is 132,000 injuries

avoided per year.

Table 8-2 summarizes the benefits of side marker lamps.

8.3 Cost-effectiveness

Safety equipment designed for crash avoidance has the

potential to produce a variety of benefits. Specifically, side

marker lamps have been shown to reduce both property damage and

nonfatal injuries. Separate measures of cost-effectiveness will be

given for the two types of benefits. The two measures will not be

combined into .a single figure in this report, but will be discussed

together for a qualitative assessment of whether side marker lamps

are cost-effective.

o Damage reduction: side marker lamps annually save $347

million in property damage because they prevent accidents (confidence

bounds: $213-488 million) while costing consumers $261 million. In

other words, by this benefit alone, they are providing consumers an

estimated annual net saving of $86 million (confidence bounds: -48 to

+227 million dollars).

o Injury reduction: side marker lamps prevent 93,000

injuries and cost $261 million per year. In other words they eliminate

^ = 360 injuries per million dollars of cost

261

143
TABLE 8-2

BENEFITS OF SIDE MARKER LAMPS

Annual Occurrences in the United States

In All Types

of Crashes

Police-reported crashes . 6,773,000

Value of property damage $22,200M^

(1982 dollars)

Injuries (nonfatal) 4,000,000^

In Nighttime

Angle Collisions

661,000

$2,167M

441,000

Annual Benefits of Side Marker Lamps

Confidence Bounds

Best

Estimate

106,000

$347M

93,000

65,000 - 149,000

$213 - 488M

51,000 - 132,000

Source: NASS [ 25 ]

Source: NHTSA Societal Cost Study [ 7 ]
Since the confidence bounds for injury prevention were 51,000 - 132,000,

the confidence bounds for this measure of cost-effectiveness are

200 - 500 injuries per million dollars. The severity of these injuries is

unknown. The majority of them are minor but the lamps may also prevent

a substantial number of moderate or severe injuries which can occur in

side impacts of low severity Cl5 1, p. 86. But probably few if any of

them are life-threatening, because the lamps have little effect in crashes

severe enough to produce fatalities or life-threatening injuries.

Nevertheless, these figures compare very favorably with automotive head

restraints which prevent 64,000 injuries, almost all of them minor whiplash,

and cost $324 million per year—i.e., eliminate 200 minor injuries per

million dollars of cost.

Since side marker lamps eliminate a large number of injuries

while more than likely paying for themselves in property damage

reduction alone, it is obvious that they are a cost-effective

safety device.

145
REFERENCES

[ll Accident Facts, 1979 Edition, National Safety Council,

Chicago, 1979.

[2] "AMA Auto Identification Manual." Automobile Manufacturers

Association, Detroit, 1972.

[3l Cerrelli, E. C. "Alcohol in Fatal Accidents National

Estimates - U.S.A.; Executive Summary." National Highway

Traffic Safety Administration, Washington, 1983.

(DOT HS-806 370).

[4] Chi, G. Y. H. and Easterling, D. "Accident Tabulations for

Evaluation of Federal Motor Vehicle Safety Standard 108."

National Technical Information Service, Springfield, Virginia,

to appear in 1983.

[5] Cole, B.L., Dain, S.J. and Fisher, A.J. "Study of Motor

Vehicle Signal Systems." Road Safety Information Service,

Melbourne, 1977. (DOT HS-022 690)

[6l Code of Federal Regulations, Title 49, Government Printing

Office, Washington, 1981, Part 571.108.

[7l "The Economic Cost to Society of Motor Vehicle Accidents."

National Highway Traffic Safety Administration, Washington,

1983. (DOT HS-806 342)

[8l Federal Register, Volume 46, February 17, 1981, p. 13193.

"Final Regulatory Impact Analysis: Part 581 Bumper Standard."

National Highway Traffic Safety Administration, Washington,

1982.

Ciol Harvey, M. R., Lesczhik, J. A. and McLean, R. F. "Cost

Evaluation for Nine Federal Motor Vehicle Safety Standards,

Volume II, FMVSS 108." National Technical Information

Service, Springfield, Virginia, 1979. (DOT HS-805 316)

[ill Henderson, R. L., Sivak, M., Olson, P. L. and Elliott, W. M.

"Motor Vehicle Rear Lighting and Signaling." Paper No. 830565,

Society of Automotive Engineers, Warrendale, Pennsylvania, 1983.

[121 Joksch, H. "Evaluation of Federal Motor Vehicle Safety

Standards." National Technical Information Service,

Springfield, Virginia, 1973. (DOT HS-801 012).

147
[13*] Kahane, C. J. "An Evaluation of Federal Motor Vehicle Safety

Standards for Passenger Car Steering Assemblies: Standard 203 -

Impact Protection for the Driver; Standard 204 - Rearward

Column Displacement." National Technical Information Service,

Springfield, Virginia, 1981. (DOT HS-805 705).

[14] Kahane, C. J. "An Evaluation of Head Restraints: Federal Motor

Vehicle Safety Standard 202." National Technical Information

Service, Springfield, Virginia, 1982. (DOT HS-806 108).

[151 Kahane, C. J. "An Evaluation of Side Structure Improvements

in Response to Federal Motor Vehicle Safety Standard 214."

National Technical Information Service, Springfield, Virginia,

1982. (DOT HS-806 314).

[161 Kahane, C. J. "A Preliminary Evaluation of Two Braking

Improvements for Passenger Cars: Dual Master Cylinders and

Front Disc Brakes." National Technical Information Service,

Springfield, Virginia, 1983. (DOT HS-806 359).

[171 Knoop, J. C , Ball, J. T. and Northrop, G. M. "Statistical

Evaluation of the Effectiveness of Federal Motor Vehicle Safety

Standard 108: Side Marker Lamps (Only)." National Technical

Information Service, Springfield, Virginia, 1980. (DOT HS-805 657)

[l8l Martin, J. W., Jr. (Ford) Letter to F. Berndt (NHTSA) regarding

CIR 1123 N40-30. September 7, 1976.

[191 Monthly Energy Review, Department of Energy, Washington,

June 1982.

[201 "MVMA Motor Vehicle Facts & Figures '82." Motor Vehicle

Manufacturers Association, Detroit, 1982.

[2ll National Traffic and Motor Vehicle Safety Act of 1966. Public

Law 89-563, September 9, 1966.

[221 New York State Department of Motor Vehicles. "VSDSS Research

Studies." National Technical Information Service, Springfield,

Virginia, 1973. (DOT HS-800 780).

[23] 1983 SAE Handbook, Vol. 2. Society of Automotive Engineers,

Warrendale, Pennsylvania, 1983.

[241 Petroleum Facts and Figures, 1971 Edition. American Petroleum

Institute, New York, 1971.

148
[25] "Report on Traffic Accidents and Injuries for 1979-1980."

Government Printing Office, Washington, 1932. (DOT HS-806 176).

[26] SAS User's Guide, 1979 Edition. SAS Institute, Inc., Raleigh, 1979,

[27] "SJA78 - The 1978 Service Job Analysis." Hunter Publishing Co.,

Chicago, 1979.

[28"! Treat, J. R., et al. "A Tri-Level Study of the Causes of Traffic

Accidents," Vol. 1. National Technical Information Service,

Springfield, Virginia, 1977. (DOT HS-805 085).

[29] "Vehicle Damage Scale for Traffic Accident Investigators."

National Safety Council, Chicago, 1971.

[30i Ward's Automotive Yearbook, 1970. Ward's Communications, Detroit.

149
APPENDIX A

Tabulations of North Carolina, Texas and Fatal Accidents

Contents: Angle collisions

North Carolina 152

North Carolina "refined test group" 155

Texas 158

Fatal Accident Reporting System , -159

Control group

North Carolina 161

Texas 164

Fatal Accident Reporting System 165

ERRATUM - The values of LAMP shown in this

Appendix were not used in the report. The

correct values are obtained by adding the

percentages in Tables 3-1 and 3-4 of the

report.

151
TABULATION OF NORTH CAROLINA ANGLE COLLISIONS

MY

64

>

5

i 66

68

69

70

71

72

Dav

1286

1727

2524

2539

3148

3639

3472

3532

4493

Crash Involvements

Night

319

432

651

668

793

863

854

810

1108

P(night)

0.1988

0.2C01

0.2050

0.2C83

0.201?

0.1917

0.1974

0.1865

0.1978

CY=7 5 •

Injury

Day

395

b77

783

803

938

1C91

1C98

1092

1346

Crash

Night

120

161

244

249

273

299

280

280

3.97

Involvement!

P(night)

0.2330

0.2182

0.2376

0.2367

0.2254

0.2151

0.2032

0.2041

0.2278

AGE

11

10

9

8

. 7

6

5

4

3

LAMP

0.73

0.76

0.82

0.80

1.50

1.S6

1.63

1.63

1.64

MY AGE LAMP

64

65

66

67

68

69

70

71

72

1129

1634

2514

2449

3324

3983

3878

3902

4935

314

450

631

705

861

1026

970

935

1172

0.2176

0.2159

0.2006

0.2235

0.2G57

0.2051

0.2001

0.1933

0.1919

360

505

779

779

970

1144

1179

1152

1480

TV=77 -

132

164

236

259

314

366

340

344

455

0.2683

0.2451

0.2325

0.2495

0.2445

0.2424

0.2238

0.2299

0.2351

12

11

10

9

6

7

6

5

4

0.78

0.81

0.87

0.85

1.55

1.61

1.68

1.68

1.69

MY AGE LAMP

64

65

66

67

68

69

70

71

72

993

1403

2081

2260

3142

3742

3944

3958

4999

253

383

545

595

790

942

1049

1037

1245

0.2030

0.2144

0.2075

0.2084

0.2109

0.2011

0.2101

0.2076

0.1994

286

448

626

644

923

1G86

1143

, 1136

1398

98

141

213

•233

280

320

380

375

449

U.2552

0.2394

0.2539

0.2657

0.2328

0.2276

0.2495

0.2482

0.2431

13

12

11

10

9

8

7

6

5

0.82

0.85

0 . 91

0.89

i,69.;

1.65

1.78

1.72

1.73

MY AGE LAMP

61

65

66

67

68

69

!'•.

71

72

816

1134

1946

2C11

2766

3371,

36ciS

4fS2

5239

22:

312

49i,

570

7C7

915

943

1133

1327

0.2124

0.2158

0.2011

0.2208

0.2-:36

0.2135

0.2.)33

0.2185

0 . 2 i' 2 1

266

338

517

f 11

795

959

1 C66

1157

1^15

75

115

168

194

242

334

343

413

450

0.2199

0.2539

0.2667

0.2410

0.2334

0.P5H3

0.2434

0.?631

0.2290

14

13

12

11

10

9

6

7

6

U.86

0.89

0.95

0.93

1.63

1.69

1.76

1.76

1.77

152
TABULATION OF NORTH CAROLINA ANGLE COLLISIONS

MV

n f

64

65

66

- *7

68

69

70

71

MV

64

65

. 66

•7

68

69

: 70

71

72

MY

64

65

66

67

68

69

70

71

72

MY

64

65

66

67

68

69

70

71

72

Day

13C5

1472

1852

1607

1826

1880

1872

1357

1081

1427

1650

1521

1692

1966

1768

1831

1666

.—'- •

1872

2588

3335

3070

3623

3998

3703

3789

5003

-

1469

2P06

2778

2693

3296

3793

3593

3358

4567

Crash Involvements

Night

418

490

549

543

547

561

534

400

- • - -

393

438

586

530

552

566

520

54 0

549

543 '

703

854

853

930

103t

865

925

1193

406

589

815

765

87.1

943

835

842

1093

P(nlght)

0.2426

0.2497

0.2267

0.2526

0.2305

0.2298

0.2219

0.2277

0.2666

0.2349

0.2621

0.2584

0.2460

0.2296

0.2273

0.2278

0.2479

0.2248

0.2136

0.2039

0.2174

0.2043

0.2050

0.1894

0.1962

0.1925

0.2165

0.2270

0.2268

0.2212

0.2090

0.1991

0.1886

0.2005

0.1931

Injury

Day

440

502

579

528

577

608 ,

577

420

407

502

562 '

477

593

679

633

594

556

612

830

970

914

1009

1074

1078

, 1097

1372

463

617

828

7*80

969

1076 •

1019

997

1279

Crash

Might

160

199

229

193

215,

215

222

156

158

168

245

225

212

241

204

215

233

197

270

318

317

-344

369

317

325

4 05

139

224

301

302

309

329

292

309

3B9

Involvements

P(night)

0.2667

0.2839

0.2834 \

0.2677

0,2715

0.2612

0.2778 -

0*2708 '

T

'l

0*2796

0.2507 •

0.3036 W

0.3205 .

0.2634

0.2620

0.2437 :

0.2658

0.2953

0.2435

0.2455

0.2469

0.2575

0.2542 .

0.2557

0.2272

0.2286

0.2279

0.2909

0.2663

0.2666

0.2791

0.2418

0.2342

0.2227

0.2366

0.2332

An W BEb

7

6

5

4

i

2

I

0

Ml

6

7

6

5

4

3

• 2

1

0

ACE

9

§

7

6

5

4

3

2

1

AGE

10

9

8

7

6

5

4

3

2

LAM faP f ~ V

0.43

0.46

: 0.52

0.50

1*20

1.26

1.33 '

1*33

0.52

0,55

' 0.61

0.59

.\ " 1,29

1.35

1.42

1.42

. 1.45

0*61

^•••64 ,

0.70

0*66

•»;•»*.V

• •.•*#**•-. •

1.91

1.51

1.62

LAHP

0.68

0.71

0,77

0.75

1.45

1.51

1*58

1.58

1.59

153
TABULATIO N OF NORT H CAROLIN A ANGL E COLLISION S

MY

64

65

6 6

6 7

6B

69

7C

71

72

MY

64

6 5

66

67

66

6 9

70

71

72

Day

629*

9 1 7

1367

1496

2C47

2824

2783

3371

4568

3 9 5

6C6

9 9 7

1109

1487

2000

2237

2661

3821

Crash Involvenents

Night

170

2 1 9

388

4 3 9

604

74fi

7 6 6

1037

1229

114

159

266

303

. 420

572

631

696

1047

P(night)

0.2128

0.192B

0.2211

0.2269

0.2278

0.2094

0.2158

0.2353

0.2113

0.2240

0.2C78

0.2106

0.2146

0.2202

0.2224

0.2200

0.2.'73

0.2151

Injury

Day

2 1 4

3 0 9

400

4 3 8

625

6 6 7

834

102 9

131 2

107

2 1 3

2 9 7

3 2 9

4 3 6

5 9 7

6 9 5

790

1130

Crash

Night

64

90

139

1 6 4

2C9

269

260

374

432

46

6 4

110

1C4

156

2C2

242

249

353

Involvements

F(night)

0.2302

0.2256

0.257?

0.2724

0.2506

0.2368

0.2377

0.2666

0.2477

0.3007

0.2310

0.2703

0.2402

0.2635

0.2528

0.2583

0.2397

0.2380

4 C r

15

14

13

12

11

'10

9

8

7

AGt

16

15

14

13

12

11

10

9

8

1 IMP

0.89

0.92

0.98

0.96

1.66

1.72

1.79

1.79

1.80

LAMP

0.91

0.94

1.00

0.98

1.68

1.74

1.81

1.81

1.62

154
TABULATION OF NORTH CAROLINA REFINED TEST GROUP

H V

64

65

66

67

68

69

7 0

71

Day

1199

1334

1694

1448

1664

17C2

1707

l?40

Crash Involvements

Night

36 C

4 3 0

4 7 7

4 8 2

4 7 2

4 6 2

4 5 6

3 2 8

P(night)

0.2309

0.2438

0.2197

0.2497

0.221(1

O.?135

G . 21 0 6

0.2C92

CY=71 -

Injury

Day

4 1 9

4 6 6

5 4 7

4 8 5

5 4 0

5 6 9

5 4 6

1 ( 0

Crash

Night

143

176

212

180

202

190

194

1 4 5

Involvements

P(night)

0.2544

0.2741

0.2793

0.2707

0.2722

0.2503

0.2622

0.2661

AGE

7

6

5

4

3

'2

1

LAMP

0.4 3

0.46

0.52

O.bO

1.20

1.26

1.33

1.33

AGE LAMP

64

>65

66

6 7

6 8

69

70

71

72

9 9 2

13'.8

1482

13R8

155C

182 8

161 0

I6h 4

151 4

335

375

522

4 6 5

4 9 2

5 1 6

4 5 9

• 47 6

4 7 9

0.2524

0.2228

0.2605

0.2509

0.2409

0.2201

0.2218

0.2204

0.2416

3 8 2

4 8 1 •

523

4 4 1

5 5 7

6 3 8

5 8 6

5 5 9

5&6

146

146

227

199

193

2 1 6

180

1 9 8

2 0 8

0.2765

I).2329

0.3H27

0.3109

0.2573

0.2529

0.2350

0.2616

0.2913

8

7

6

5

4

3

2

1

0

0.52

0.55

0.61

0.59

l.? 9

1.35

1.42

1.42

1.43

MY AGE LAMP

64

65

66

67

6 8

69

70

71

72

1064

1496

1923

1784

2i.28

2289

2063

2150

2877

304

404

4 5 8

4 8 8

5 2 4

5 9 0

4 8C

533

637

0.2222

0.2126

0.1924

0.2148

0.2(5 3

0.2 r4 9

0.1888

0.1987

0.1813

3 9 2

5 3 6

6 1 8

5 9 6

6 4 5

710

6 9 4

6 9 6

8 8 3

113

164

182

211

217

228

192

201

2 2 1

0.2238

0.2343

0.2275

0.2615

0.2517

0.2431

0.2167

0.2241

0.2002

9

8

7

6

5

4

3

2

1

0.61

0.64

0.70

0.68

1.38

1.44

1.51

1.51

1.52

AGE LAMP

6 4

t>b

66

hi

e. 8

i 9

7"

71

7P

e&3

1132

1591

1562

1H87

2156

2 .26

If3 7

2567

2 3 4

3 3 2

4 3 5

4 0 7

4 8 2

5 1 7

45 8

4 7 9

6Cfc

0.215 3

0.2268

0.214 7

D.2ft>7

0.2,-35

0.1934

0.1b44

0.2 68

' 0.1912

3 1 0

3 9 3

531

5 , 5

f ?9

6S4

febl

6 3 7

8 1 7

89

14(1

1 6 5

174

1 8 3

195

1 7 3

1H5

2 3 5

0.2288

0.2627

0.2371

0.2563

0.2254

0.2193

0.2147

C.2251

0.P234

1C t

9 (

'.6 8

1.71

8 0.77

7 l

6 1

5 1

4 1

3 ]

? I

J.7 5

• *5

. 5 1

L.58

1.58

L .5 9

155
TABULATION OF NORTH CAROLINA REFINED TEST GKOUP

KY

64

6 5

66

67

68

6 9

70

71

72

Day

6 8 5

9 7 2

1320

1384

17 0 4

1952

1869

1872

2399

Crash Involvements

Night

175

2 3 1

3 3 3

3 4 6

4 2 3

4 3 5

4 6 6

4 1 9

590

P(night)

0.2035

0.192 0

0.21il 5

0 . 2 J 01)

0.1989

0.1622

0.1996

0.1829

0.1974

Injury

Day

246

362

4 6 5

5 1 1

5 9 3

6 8 2

6 5 8

6 6 4

Crash

Night

72

92

146

142

164

181

169

155

244

Involvamaats

P(night)

0.22S0

0.2026

0.2390 >

0.2175

0.2166

0.2D97

0*2044

0.1693

0.2247

AGE

11

in

9

8

7

"6

5

4

S

LAMP

0.7 3

0.76

0.62

0.80

1.50

1.56

1*63

1.63

1.64

MY AGE LAMP

64

. 65

6 6

67

68

6 9

70

71

72

6 0 1

8 4 7

13C 9

1311

1721

2 068

2029

2C89

2597

158

2 1 8

3 1 2

3 7 5

4 1 3

5 0 3

4 9 9

' 462

5 7 5

0.2C82

0.2047

0.1925

0.2224

0.1935

0.1956

0.1974

0.1811

0.1813

2 2 3

3 0 3 •

4 7 3

4 7 6

6 1 8

7C6

729

729

9 0 7

76

84

141

156

155

211

194

160

2 6 6

0.2542

0.2171

0.2296

0.2466

0.2005

0.2301

0.2102

0.1980

0.2266

12

11

1C

9

6

7

6

5

4

0.78

0.81

0.87

0.65

1.55

1.61

1*66

1.66

1.69

MY AGE LAMP

64

65

66

67

66

69

70

71

72

514

715

1C48

1114

1591

1918

1958

20C2

26C0

117

190

2 7 2

2 9 0

3 5 2

4 3 5

4 9 4

5 1 8

577

0.1854

0.2099

0.2061

0.2C66

0.1612

0.1849

0.2015

0.2C56

0.1816

181

2 6 9

3 7 5

3 8 5

5 5 3

6 3 8

6 8 2

7C1

8 6 4

52

77

113

X21

140

158

191

201

228

0.2232

0.2225

0.2316

0.2391

0.2020

0.1985

0.2188

0.2228

0.2088

13

12

11

10

9

8

7

6

5

0.82

0*85

0*91

0*69

1*59

1*65

1.72

1.72

1.73

MY AGE LAMP

64

6 5.

66

67

68

69

70

71

72

4 0 3

5 6 4

9 4 4

1CC 1

1420

17; 3

1H30

2C43

264 7

108

146

219

253

2 9 3

4 4 3

4 2 3

5 1 6

6 0 9

0.2114

0.2 056

0.1883

0.2U18

0.1710

0.2''64

0.1U77

0.2M6

• 0.187 0

160

192

2 8 7

3 5 3

4 7 3

5 6 7

6 4 6

6 9 3

897

39

58

95

101

118

184

187

221

222

0.1960

0.2320

0.2487

0.2225

0.1997

0.2450

0.2245

0.2418

0.1984

14

13

12

11

1G

9

fl

7

6

0.86

0.89

0.95

0.93

1.63

1.69

1.76

1.76

1.77

156
TAbULATIO N O F NORT H CAROLIN A REFINE D TtS T GROU P

HY

64

65

66

67

68

69

70

71

72

Day

3 2 8

4 4 5

b87

7 5 7

1033

13H4

14 C8

1676

23 04

Crash Involvements

Night

8J

110

166

2 0 3

2 8 3

3 4 3

3 3 7

4 7 4

5b7

P(night)

0.196 1

0.1H35

0.194 6

0.211 5

0.215 0

C.1986

0.193 1

0.220 5

0.194 7

Injury

Day

148

178

2 2 6

2 5 7

3fa9

5C7

4 8 3

6 3 2

7 9 9

Crash

Night

34

45

6 9

94

112

141

127

2T4

227

Involvement*

P(night)

0.1866

0 • 2 ti 1 8

0.2339

0.2678

0.2328

0.2176

0.2(<62

0.2440

0.2212

GE

15

14

13

12

11

10

9

8

7

LAn»

0.69

0.92

0.98

0.96

1.66

1.72

1.79

1.79

1*60

MY AGE LAM P

64

65

66

67

68

69

7 0

71

72

177

3 1 2

511

5 7 6

7 2 9

974.

11C8

1317

1877

58

72

1 1 9

141

195

2 5 1

3 1 1

3 1 5

5 0 0

0.246 8

0.187 5

0.188 9

0.196 7

0.211 0

0.204 9

0.219 2

0.193 0

0.210 3

50

127

1 8 3

2C2

2 5 2

3 6 1

3 9 8

4 4 7

6 5 4

27

34

54

56

73

ioa

128

122

2 0 0

0.3506

0.2112

0.2278

0.2171

0.2246

0.23C3

0.2433

0.2144

0.2342

16 t

15 (

14 1

1.91

1.94

. 0 0

13 0.98

12 1

11 1

10 1

9 1

8 1

. 6 8

. 7 4

1.61

1.81

1.62

157
TABULATION OF TEXAS ANGLE COLLISIONS

BY

64

65

66

67

68

69

70

71

72

MY

64

65

66

67

68

69

70

71

72

HY

64

65

66

67

68

6 9

70

71

72

toy

7856 '

10217

Itl715

11371

13524

14196

14262

14564

13076

6475

8927

9637

10475

12657

13588

13393

13866

17594

4630

6423

7636

8478

10437

•*£ 11475

•V, •• 1137 5

' 1164 0

14071

Crash Involvements

Night_

2049

2588

2810

2784

3176

3388

3145

3247

3020

1639

2206

2503

2686

2960

3174

2946

3026

3911

1240

1725

1888

2268

2579

2891

2616

2589

3193

P(night)

0.2069

0.2P21

0.2H7B

0.1967

0.1902

0.1927

0.1807

0.1823

0.1876

0.2020

0.1981

0.2028

0.2041

0.1895

0.1894

0.1803

0.1791

0.1819

0.2112

0.2117

0.1982

0.2111

0.1981

0.2C12 .

O.1870

0.1820

0.1850

CY = 72 -

Injury

Day

1785

2209

2239

2236

2683

2823

2730

2821

2510

1399

1873

2C91

21 14

2445

2704

2574

2642

3374

9 7 6

1453

1652

1773

2120

2271

2161

2249

2672

Crash Involvements

Night

615

729

790

791

810

913

870

8 6 8

780

t

483

625

745

725

8 6 2

801

7 4 5

772

1047

365

512

5 5 9

6 6 9

719

8 2 0

7 1 9

718

862

P(night)

0.2562

0.2481

0.2608,

0.2613

0.2319

0.2444

0.2417

0.2353

0.2371

0.2S66

0.2502

0.2627

0.2554

0.2607

0.2285

0.2245

0.2261

0.2368

0.2722

0.2606

0.2528

0.2740

0.2533

0.2653

0.2497

0.2420

0.2439

• 6t

8

7

6

5

4

' 3

2

1

0

AGE

9

8

7

6

5

4

3

2

1

AGE

10

9

8

7

6

5

4

3

2

LAMP

0.53

0.56

0.62

0.60

1.34

1.38

1.43

1.43

1.44

LAMP

0.61

0*64

0.70

0.68

1.42

1.46

1.51

1.51

1*52

LAMP

0.68

0.71

0.77

0.75

1.49

1.53

1.58

1.58

1.59

158
TABULATION OF PARS ANGLE COLLISIONS

MV

6 4

6 5

6 6

67

6 6

6 9

70

71

72

HV

64

65

66

67

66

69

70

71

72

MV

64

65

66

67

68

69

70

71

72

MY

64

6 5

6f>

6 7

f fl

6 9

I'-

ll

72

Day

153

233

2B9

261

314

3S1

401

407

503

126

175

231

266

334

381

404

394

604

118

153

192

207

254

362

394

391

550

64

122

160

185

264

3PB

326

3H5

55 0

------- - CY=75 ---- -

Crash Involvement*

Sight

116

153

177

198

239

274

287

275

288

89

137

182

190

238

287

265

239

349

68

119

145

165

225

262

289

280

360

. 60

87

132

147

196

251

226

•276

3f>7

P (night)

0.4312

0.3964

0.3798

0.4314

0.4322

0.4183

0.4172

0.4032

0.3641

*

0.4140

0.4391

C.44 07

0.4167

C.4161

C.4296

C.3961

0.3776

0.3662

0.3656

0.4375

0.4303

0.4435.

(1.4697

0.4199

0.4231

C.4173

0.4086

0.4167

n.4163

tl.4521

0.4428

u.42M

r.4490

C40S4

C.417 5

I . 41 3 n

AGE

11

10

9

8

7

6

5

4

3

AGE

12

11

10

9

8

7

6

5

4

AGE

13

12

11

ID

9

8

7

6

5

AGE

14

13

12

11

li.'

9

a

7

6

LAMP

0.73

0.76

0.82

0.80

1.50

1.56

1.63

1.63

1.64

LAMP

0.78

0.81

0.87

0.85

1.5S

1.61

1.68

1.68

1.69

LAMP

0.82

0.85

0.91

0.89

1.59

1.65

1.72

1.72

1.73

LAMP

0.86

0.89

0.95

0.93

1.63

1.69

1.76

1.7fc

1.77

159
TABULATION OF FAKS ANGLE COLLISIONS

MY

CY=79

Crash Involvement*

Day Might P(night)

A6£ LAMP

64

65

66

67

68

69

70

71

72

fc2

81

131

134

191

219

265

291

57

6H

9J

95

168

187

248

281

U.4T90

C.4564

T:.4O72

0.4148

0.4680

0.4606

U.4834

H.4913

i;.4142

15

14

13

12

11

10

9

8

7

0.89

0.92

0*9,8

0.96

1 .66

1.72

1.79

1.79

1.80

AGC LAMP

64

65

66

67

68

69

7 0

•71

72

49

75

104

116

149

170

223

241

333

28

52

78

99

120

17b

193

2D8

287

(!.3636

0.4094

H.4266

f..46f)5

(.44 61

T.5072

C.4639

f. .4633

t .4629

16

15

14

13

12

11

' in

9

8

0.91

0.94

1.00

0.98

1.68

1.74

1*81

1.81

1.82

MY AGE LAMP

64

65

66

67

68

69

7 0

71

72

5C

55

78

86

126

141

158

201

340

28

47

49

71

106

133

163

185

286

Ci.3590

0,4608

I).3858

1.4522 .

0.4569

0.4854

[1.5078

C.4793

0.4569

17

16

15

14

13

12

11

10

9

0.92

0.95

1.01

0.99

1.69

1.75

1.82

1.82

1*63

160
TABULATION OF NORTH CAROLINA CONTROL GROUP

H V

64

65

66

67

66

69

70

71

MY

64

65

66

67

66

69

70

71

72

MY

64

65

66

67

68

69

>Tflv-* -

71

72

MY

64

65

66

67

f>8

*9

7C

71

72

toy

794

950

1127

932

1230

1335

1364

1318

579

779

974

902

1097

122S

1201

1298

1211

1276

1693

2327

2216

2745

3177

3087

3133

4190

952

13*1

1936

1931

2374

?733

2720

2615

3728

Crash Involvements

Night

319

387

4P4

369

440

459

435

353

243

367

4G2

343

419

457

• 51

407

466

448

578

715

679

859

914

864

908

1176

297

454

566

57a

721

aic

741

71B

967

P(night)

0.2666

0.2b96

0.2639

0.2836

0.2635

0.2561

0*2418

0.2575

0.2956

0.3202

0.2922

0.2755

0.2764

0.2695

0.2730

0*2387

0.2779

0*2599

0.2545

0.2350

0*2345

0.2383

0.2234

0.2187

0.2247

0*2192

—

0.2378

0.2bl5

0.2262

0.2304

0.2330

0.2286

0.2141

0.2'32

O.2I'6O

CYS71 •

Injury

Day

227

261

279

211

312

332

308

221

205

228

262

230

292

340

333

312

292

424

533

700

632

779

849

734

792

1040

3 0 6

431

582

568

645

742

751

722

946

Crash Involvement*

Night

724

155

146

133

149

144

1§1

114

103

151

136

136

160

155

156

153

175

183

233

292

257

, 336

344

318

3U3

386

119

195

249

210

274

283

270

245

338

P(night)

0.3533

0.3726

0.3435

0*3866

0.3232

' 0.3025

0*3290

0.3403

I

• J 1 * '

0.3344

0.3984

0.3417

0.3716

0.3540

0.3131

0.3190

0.3290

0.3747

0.3015

0.3042

0.2944

0.2891

0.3013

0.2883

0.3023

0.2767

0.2707

0.280D

0.3115

0.2996

0.2699

0.2982

0.2761

0.2644

0.2534

0.2632

AGE

7

6

5

4

3

" 2

1

0

AGE

8

7

6

5

4

3

2

1

0

AGE

9

8

7

6

5

4

3

2

1

AGE

in

9

8

7

6

5

4 '

3

2

LAMP

0.43

0.46

0.52

0.50

1 .20

1.26

1*33

1.33

LAMP

0.52

0.55

0.61

0*59

1*29

1.35

1*42

1.42

1.43

LAMP

0.61

0.64

0.70

0*68

1.38

*••*

1.5J

1*51

1.52

LAMP

0.68

0.71

0.77

0.75

1.45

l.M

1.58

I.b8

1.59

161
TABULATION OF NORTH CAROLINA CONTROL GfcOUP

61

65

66

67

66

69

7C

71

72

Day

76l

llfcj

1668

1707

2241

2685

2b 13

2752

3541

Crash Involvements

Night

256

385

550

571

688

820

712

766

945

P(night)

0.2517

0.2477

0.2480

0.2507

0.2349

0.2340

0.2141

0.2177

0.2107

UY=7S -

Injury

Day

245

360

487

514

679

770

721

752

911

Crash

Night

91

159

205

219

264

310

250

252

324

Involvement*

P(night)

0.2706

0.3064

0.2962

0.2988

0.2800

0.2870

0.2575

0.2510

0.2623

AGE

11

10

9

e

.7

6

5

4

3

LAMP

0.73

0.76

0.S2

0.80

1.50

1.56

1.63

1.63

1.64

MY AGE LAMP

64

65

66

67

68

69

70

71

72

735

1052

1485

1744

2311

2679

2660

3045

3769

221

355

492

467

673

857

808

784

1059

0.2312

0.2523

0.2489

0*2183

0.2255

0.2424

0.2330

0.2046

0.2193

258

357 .

484

559

693

783

730

799

991

93

135

184

208

273

351

284

285

368

0.2650

0.2744

0.2754

0.2712

0.2826

0.3095

0.2801

0.2629

0.2708

12

11

10

9

8

7

6

5

4

0«,78

0*81

0.87

0.85

1.55

1.61

1.68

1.68

1.69

MY AGE LAMP

64

65

66

67

6a

69

70

71

72

546

750

1215

1376

lft20

2280

2432

2674

3523

167

226

393

408

594

707

751

775

959

0.2342

0.2316

0.2444

0.2287

0.2461

0.2367

0.2359

0.2247

0.2140

183

236

371

427

582

658

654

728

970

CV = 7A

65

9fe

175

1-5 0

229

282

274

303

363

0.2621

0.2892

0.3205

0.2600

0.2824

0.3C00

0.2953

0.2939

0.2723

13

12

11

10

9

8

7

6

5

0.82

0.85

0.91

0.B9

1.59

1.65

1,72

1.72

1.73

AGE LAMP

f>'l

6f.

bb

hi

fcH

69

T

71

72

493

721

1 1 4 I1

1281

1736

2392

2555

3'! 19

3H25

177

240

383

388

536

7 7 i'J

77b

923

1C71

0.2642

0.2497

0.2515

0.2325

0.2359

0.2435

C.233U

0.2341

. 0.2186

162

225

341

38D

503

676

74B

b27

1(15

78

98

179

160

186

319

2 87

347

376

0.3250

0.3034

0.3442

0.2963

0.27C0

0.3137

0.2773

0.2956

0.2703

14

13

12

11

10

9

a

7

6

0.86

0.89

0.95

0.93

1.63

1.69

1.76

1.76

1.77

162
TABULATION OF NORTH CAROLINA CONTROL GROUP

n l

64

65

6 6

6 7

6 8

6 9

7P

71

72

MV

6 4

65

66

67

68

69

70

71

72

Day

3 3 !

511

8 4 9

973

1377

1778

1805

2431

3312

253

420

689

748

1010

1406

1504

2002

2790

Crash Involvi

Night

121

179

310

313

473

596

626

803

1076

94

156

245

24 8

363

504

6 0 6

7 0 4

9 1 9

nenta

P(night)

0.2677

0.2594

0*2675

0*2434

0.2557

0.2511

0.2575

0.2483

0.2452

0*2709

0*2708

0.2623

0.2490

0.2644

0*2639

0.2872

0*2602

0.2478

Injury

Day

93

149

292

282

425

488

559

681

871

83

134

2 3 4

234

2 7 8

4 1 8

4 3 3

5 6 8

7 7 4

Crash

Night

86

86

128

116

188

227

243

312

416

32

52

100

91

148

194

247

266

387

Involvanenta

P(night)

0.3758

0*3660

0.3 048'

"9.2915

0.3067

9.3175

- 0*9030

C.3142

0.3232

• '' '. 1 !

0.2783 -

0.2796

0*2994

0*2800

0.3474

0.3170

0.3632

0.3206

0*3333

A #• r

AGE'

15

14

13

12

n10

9

8

7

AGE

J6

15

14

13 -

12

11

10

9

8

LAMP

0*89

0*92

0.9S

0.96

1*66

1.72

1.79

1.79

1.80

LAMP

0.9 1

0*94

1*00

0*98

1.68

1.74

1.81

1*81

1*82

163
TAfcULATJUN OF TEXAS CONTROL GROUP

U V

H T

64

65

6 6

67

6 8

69

70

71

72

Day

13448*

18283

2 0 046

211*2

25975

29319

?9092

3 0 844

28304

Crash Involvements

Night

3961

5153

5433

5453

6529

7130

6892

7210

7009

P(night)

0.2275

0.2199

0.2132

0.23 47

0 . 2 C 0 9

0.1956

0.1915

0.1895

0.1985

Injury

Day

1929

2611

2770

2758

3313

3470

3312

3518

3123

Crash Involvement!

Night

9 3 8

1164

1201

1118

1283

1386

1287

1295

1199

P(night)

0.3272

0.3120

0.3024

0.2884

0.2792

0.2857

0.2798

0.2691

0.2774

GF

B

7

6

5

4

"• 3

2

1

0

LAMP

0.53

0.56

0.62

0.60

1.34

1.36

1.43

1.43

1.44

HY AGE LAHP

64

65

66

67

68

69

70

71

72

11395

16124

18375

20345

25 01 0

2846b

2808b

2959b

38231

3423

4646

5070

5468

6490

7164

6871

6826

9290

0.2310

0.2237

0*2163

0.2118

0.2060

0.2011

0.1966

0.1B74

0.1955

1667

2224

2519

2625

3085

3350

3293

3398

4291

823

1105

1165

1194

1350

1411

1334

1334

1759

0.3305

0.3319

0.3162

0.3126

0.3044

0.2964

0.2883

0.2819

0.8907

9

a

7

6

5

4

3

2

1

0.61

0.64

0.70

0.68

1.42

1.46

1.51

1*51

1.52

HY AGE LAHP

64

65

6 6

6 7

6 6

6 9

70

71

72

8412

12372

14411

165H3

21120

24131

24195

25069

32P47

2522

3651

4110

4731

5727

6383

6129

6144

7659

0.2307

0.2279

0.2219

0.2220

0.2133

0.2099

0.202 1

0.1968

0.1929

1286

1641

1985

2290

, 2663

2991

2769

2907

3618

6 2 2

8 3 0

6 0 6

9 9 2

1184

1223

1195

1123

1426

0.3260

0.3107

0.3086

0.3023

0.3078

0.2902

0.3015

0.2787

0.2827

10

9

0

7

6

5

4

3

2

0.66

0.71

0.77

0.75

1.49

1.53

1*56

1.38

1.59

164
TABULATICN OF FARS CONTROL GROUP

MY

64

65

66

67

68

69

70

71

72

O»y

221

3 04

346

359

404

501

504

508

646

........ CY=75 -----

Crash Involvement*

Night

213

318

371

408

500

567

537

504

644

t(night)

0.49C8

0.9113

U5174

C.5319

0.5531 •

0.5309

0.5159

0.4960

0.4992

AGE

11

10

9

8

7

6

5

4

3

LAMP

0.73

0.76

0.8?

0*80

1.50

1.56

1.63

1.6 3

1.64

AGE LAMP

64

65

66

67

68

69

7J

71

72

171

220

260

342

367

474

489

461

569

189

247

327

358

440

585

531

532

598

0.5250

t.5289

0.5571

0.5114

0*5452

0.5524

0.5206

0.535ft

0.5124

12

11

10

9

8

7

6

5

4

0.76

0.81

0.B7

0.85

1.55

1.61

1.68

1.68

1.69

AGE LAMP

64

65

66

67

68

69

7 0

71

72

149

189

237

264

339

439

432

495

547

154

229

294

341

424

565

573

53R

666

0.5083

0.5478

fc.5537

0.5636 •

0.5557

0.5627

0.5701

f.5208

(.5491

13

12

11

10

9

8

7

6

5

0.82

0.85

0.91

0.89

1.59

1.65

1.72

1.72

1.73

AGE LAMP

f 4

65

66

b7

t-H

tl

7 L

71

72

127

178

219

232

285

399

417

524

bl9

126

175

247

26H

392

541

548

579

729

C.4980

0.4958

t.5300

r.5360

'.579(1

1.5755

-.5679

C .5249

'..5B41

14

13

12

11

10

9

8

7

6

0.86

0.69

0.95

0.93

1 .63

1.6"

1.76

1.76

1.77

165
TABULATION OF FARS CONTROL oROUP

CY = 79

MY

MY

Crash Involvements

Day Night F(night)

AGE

AGE

AGE:

LAHP

64

65

66

67

hfl

69

70

71

72

89

134

161

202

2 4 1

271

365

374

451

98

158

194

225

345

421

492

580

619

C.5241

P.5411

0.5465

C.5269

0.5897

0.6084

0,5741

0.6060

0.5785

15

14

13

12

11

10

9

8

7

0.89

0.92

0.94

0.96

1.66

1.72

1.79

1.79

1.60

LAMP

64

b5

66

67

6B

69

T~.

71

72

57

90

103

115

166

219

251

296

416

79

106

147

196

279

35 0

423

469

579

0.5809

G.S455

0.5880

P.6326

n.6270

0.6151

r.6276

C.6115

C.5819

16

15

14

13

12

11

10

9

a

0.91

0,94

1.00

0.98

1.66

1.74

1.81

1.61

1.62

LAHP

64

65

66

67

66

69

70

71

72

48

73

89

1P9

145

181

219

258

3B1

61

97

130

14fl

184

259

322

38(1

569

0.5596

U.5706

0,5936

D.5622

0.5593

0.5866

0.5952

C.5956

1.5989

17

16

15

14

13

12

11

10

9

D.92

0.95

1.01

0.99

1.69

1.75

1.62

1.62

1.83

166