34998 Federal Register / Vol. 65, No. 106 / Thursday, June 1, 2000 / Proposed Rules

Federal Communications Commission.

John A. Karousos,

Chief, Allocations Branch, Policy and Rules

Division, Mass Media Bureau.

[FR Doc. 00–13598 Filed 5–31–00; 8:45 am]

BILLING CODE 6712–01–P

FEDERAL COMMUNICATIONS

COMMISSION

47 CFR Part 73

[DA No. 00–1110; MM Docket No. 00–28;

RM–9796]

Radio Broadcasting Services;

Christine, TX

AGENCY: Federal Communications

Commission.

ACTION: Proposed rule; dismissal.

SUMMARY: This document dismisses a

proposal filed by Christine Radio

Broadcasting Company requesting the

allotment of Channel 245A at Christine,

Texas, as the community’s first local

service. See 65 FR 11537, March 3,

2000. As stated in the Notice, a showing

of continuing interest is required before

a channel will be allotted. Since there

has been no interest expressed for the

allotment of a channel at Christine, the

Report and Order dismisses the

proposal.

FOR FURTHER INFORMATION CONTACT:

Kathleen Scheuerle, Mass Media

Bureau, (202) 418–2180.

SUPPLEMENTARY INFORMATION: This is a

summary of the Commission’s Report

and Order, MM Docket No. 00–28,

adopted May 10, 2000, and released

May 19, 2000. The full text of this

Commission decision is available for

inspection and copying during normal

business hours in the Commission’s

Reference Center, 445 12th Street, SW,

Washington, DC. The complete text of

this decision may also be purchased

from the Commission’s copy

contractors, International Transcription

Services, Inc., 1231 20th Street, NW,

Washington, DC 20036, (202) 857–3800,

facsimile (202) 857–3805.

Federal Communications Commission.

John A. Karousos,

Chief, Allocations Branch, Policy and Rules

Division, Mass Media Bureau.

[FR Doc. 00–13597 Filed 5–31–00; 8:45 am]

BILLING CODE 6712–01–P

FEDERAL COMMUNICATIONS

COMMISSION

47 CFR Part 73

[DA 00–1109; MM Docket No. 99–115; RM–

9378]

Radio Broadcasting Services; Clio and

Tuscola, MI

AGENCY: Federal Communications

Commission.

ACTION: Proposed rule; denial.

SUMMARY: The Notice in this proceeding

proposed the reallotment of Channel

268A from Tuscola, Michigan, to Clio,

Michigan, and modification of the

license for Station WWBN accordingly.

The Notice was issued in response to a

petition filed by Faircom Flint Inc. See

64 FR 18569, 1999. Based on the

information submitted, it has been

determined that the reallotment from

Tuscola to Clio does not provide a

public interest benefit of enough

significance to outweigh the loss of a

transmission service to Tuscola or offset

the disruption of an existing service.

Therefore, the proposed reallotment

from Tuscola to Clio has been denied.

With this action, this docketed

proceeding is terminated.

FOR FURTHER INFORMATION CONTACT:

Kathleen Scheuerle, Mass Media

Bureau, (202) 418–2180.

SUPPLEMENTARY INFORMATION: This is a

summary of the Commission’s Report

and Order, MM Docket No. 99–115,

adopted May 10, 2000, and released

May 19, 2000. The full text of this

Commission decision is available for

inspection and copying during normal

business hours in the Commission’s

Reference Center, 445 12th Street, SW,

Washington, DC. The complete text of

this decision may also be purchased

from the Commission’s copy

contractors, International Transcription

Services, Inc., 1231 20th Street, NW,

Washington, DC 20036, (202) 857–3800,

facsimile (202) 857–3805.

Federal Communications Commission.

John A. Karousos,

Chief, Allocations Branch, Policy and Rules

Division, Mass Media Bureau.

[FR Doc. 00–13596 Filed 5–31–00; 8:45 am]

BILLING CODE 6712–01–P

DEPARTMENT OF TRANSPORTATION

National Highway Traffic Safety

Administration

49 CFR Part 575

[Docket No. NHTSA–2000–6859]

RIN 2127–AC64

Consumer Information Regulations;

Federal Motor Vehicle Safety

Standards; Rollover Prevention

AGENCY: National Highway Traffic

Safety Administration (NHTSA), DOT.

ACTION: Request for comments.

SUMMARY: The agency believes that

consumer information on the rollover

risk of passenger cars and light

multipurpose passenger vehicles and

trucks would reduce the number of

injuries and fatalities from rollover

crashes. This information would enable

prospective purchasers to make choices

about new vehicles based on differences

in rollover risk and serve as a market

incentive to manufacturers in striving to

design their vehicles with greater

rollover resistance. The consumer

information program would also inform

drivers who choose vehicles with less

rollover resistance that their risk of

harm can be greatly reduced with seat

belt use to avoid ejection.

The agency has tentatively decided

that the Static Stability Factor should be

used to indicate overall rollover risk in

single-vehicle crashes. This document

seeks comment on whether the

information should be presented as part

of NHTSA’s New Car Assessment

Program (NCAP), which provides

consumer information concerning

frontal and side impact protection.

DATES: Comment Date: Comments must

be received by July 31, 2000.

ADDRESSES: All comments should refer

to Docket No. NHTSA–2000–6859 and

be submitted to: Docket Management,

Room PL–401, 400 Seventh Street, SW,

Washington, DC 20590. Docket hours

are from 10 am to 5 pm Monday through

Friday.

For public comments and other

information related to previous notices

on this subject, please refer to Docket

No. 91–68; Notice 3, NHTSA Docket,

Room 5111, 400 Seventh Street, SW,

Washington, DC 20590. NHTSA Docket

hours are from 9:30 am to 4 pm Monday

through Friday.

FOR FURTHER INFORMATION CONTACT:

Gayle Dalrymple, NPS–23, Office of

Safety Performance Standards, National

Highway Traffic Safety Administration,

400 Seventh Street, SW, Washington,

DC 20590. Ms. Dalrymple can be

Federal Register / Vol. 65, No. 106 / Thursday, June 1, 2000 / Proposed Rules 34999

1Light trucks include vans, minivans, SUVs, and

pickup trucks under 4,536 kilograms (10,000

pounds) GVWR.

2A broken hip is an example of an AIS 3 injury.

reached by phone at (202) 366–5559 or

by facsimile at (202) 366–4329.

SUPPLEMENTARY INFORMATION:

I. Executive Summary

II. Background

III. Rulemaking History

IV. Recent Research on Maneuver-induced

Rollover Crashes

A. Why Study Untripped Rollovers?

B. Estimate of the Annual National

Incidence of On-Road, Untripped

Rollover Crashes

C. Dynamic Test Program

1. Preliminary Steps

a. NASS Case Studies

b. ODI Complaints

c. Survey of Available Test Procedures

2. Track Testing—Phase Ia

3. Track Testing—Phase Ib

4. Track Testing—Phase II

a. Test Vehicle Selection

b. Results

5. Plans for Continuing Dynamic Test

Research

D. How Do Dynamic Rollover Test Results

Compare With Metrics?

V. Why Choose SSF?

A. Description of Metrics

B. Tripped and Untripped Rollover

C. Correlation and Causation

D. Simplicity and Measurability

E. Unintended Consequences

VI. Why Not a Standard?

VII. Consumer Information Presentation

A. How Consumers Want to See

Information Displayed

B. Converting SSF Measurements to Star

Ratings

VIII. Rollover Information Dissemination

through NCAP

A. Why NCAP Rather than Vehicle

Labeling?

B. Addition of Rollover Resistance Stars to

NCAP

IX. Rulemaking Analyses and Notices

X. Submission of Comments

Appendix

I. Executive Summary

This notice requests comment from

the public on NHTSA’s intent to include

a vehicle measure of rollover resistance,

its Static Stability Factor, as an addition

to the 2001 New Car Assessment

Program (NCAP).

According to the 1997 Fatality

Analysis Reporting System (FARS),

9,529 people were killed as occupants

in light vehicle rollovers. FARS shows

that 53 percent of light vehicle occupant

fatalities in single-vehicle crashes

involved rollover. The proportion

differs greatly by vehicle type: 45

percent of car occupant fatalities in

single-vehicle crashes involved rollover,

compared to 60 percent for pickup

trucks, 65 percent for vans, and 79

percent for sport utility vehicles (SUVs).

The 1995–1997 National Automotive

Sampling System (NASS) estimates that

228,000 light vehicles were towed from

a rollover crash each year (on average),

and that 25,000 occupants of these

vehicles were seriously injured.

The action described by this notice

follows a decision by the agency in 1994

(59 CFR 33254) to terminate rulemaking

on a minimum standard for rollover

resistance and to propose a consumer

information approach instead. We have

decided to pursue consumer

information, through NCAP, to enable

consumers to make informed choices

about the tradeoffs in vehicle attributes,

such as high ground clearance, and

rollover resistance. NCAP provides

practical advantages over the mandatory

consumer information regulation

proposed in 1994:

• Implementation would be faster. The

program would be able to start almost

immediately, so consumers would have the

information sooner.

• NHTSA retains control of vehicle

measurement so the consumer will know

exactly which vehicle model/equipment

combination was tested.

• It takes advantage of the existing NCAP

organization within NHTSA equipped to

perform vehicle tests and disseminate

consumer information and avoids the need

for a compliance function within NHTSA to

collect and process manufacturers’ test

reports and provide to manufacturers the

vehicle ranges required on the labels.

The agency believes that consumer

information on the rollover risk of

passenger cars and light multipurpose

passenger vehicles and trucks, based on

the vehicle’s Static Stability Factor,

would reduce the number of injuries

and fatalities from rollover crashes. This

information would enable prospective

purchasers to make choices about new

vehicles based on differences in rollover

risk and serve as a market incentive to

manufacturers in striving to design their

vehicles with greater rollover resistance.

It would inform drivers of the general

difference in rollover resistance between

light trucks and cars and among

vehicles within the various classes.

Consumers who need, or desire, a

particularly large cargo space, high

ground clearance, or narrow track

width, would not be denied the chance

to purchase such vehicles. However,

consumers who choose vehicles with

relatively low rollover resistance could

do so with knowledge of that fact,

something that is not very likely today.

The consumer information program

would also inform drivers who choose

vehicles with less rollover resistance

that their risk of harm can be greatly

reduced with seat belt use to avoid

ejection.

In 1994, the agency proposed a

vehicle labeling requirement for rollover

information, but we believe that

including rollover information in the

NCAP program instead may be

preferable. The labeling of vehicles with

one safety attribute to the exclusion of

others may be misleading. A 1996 study

by the National Academy of Sciences

(NAS) recommended the development

of an overall measure of vehicle safety.

Until that goal can be met, the

presentation of our proposed measure of

rollover risk, in the context of our

established measures of frontal and side

impact crashworthiness in NCAP,

would go a long way toward addressing

NAS’s concern for presenting overall

vehicle safety.

II. Background

Rollover crashes are complex events

that reflect the interaction of driver,

road, vehicle, and environmental

factors. We can describe the relationship

between these factors and the risk of

rollover using information from the

agency’s crash data programs. We limit

our discussion here to light vehicles,

which are defined as the combination of

(1) passenger cars and (2) multipurpose

passenger vehicles and trucks under

4,536 kilograms (10,000 pounds) gross

vehicle weight rating (collectively,

‘‘light trucks’’).1

According to the 1997 Fatality

Analysis Reporting System (FARS),

9,529 people were killed as occupants

in light vehicle rollovers, including

7,697 killed in single-vehicle rollovers.

Eighty percent of the people who died

in single-vehicle rollovers were not

using a safety belt, and 63 percent were

ejected from the vehicle (including 52

percent who were completely ejected).

FARS shows that 53 percent of light

vehicle occupant fatalities in singlevehicle crashes involved rollover. The

proportion differs greatly by vehicle

type: 45 percent of car occupant

fatalities in single-vehicle crashes

involved rollover, compared to 60

percent for pickup trucks, 65 percent for

vans, and 79 percent for sport utility

vehicles (SUVs).

The 1995–1997 National Automotive

Sampling System (NASS) estimates that

228,000 light vehicles were towed from

a rollover crash each year (on average),

and that 25,000 occupants of these

vehicles were seriously injured (defined

as an Abbreviated Injury Scale rating of

at least 3).2 This includes 186,000

single-vehicle tow-away rollovers with

17,000 serious injuries. Seventy-six

percent of those people who suffered a

serious injury in single-vehicle towaway rollovers were not using a safety

35000 Federal Register / Vol. 65, No. 106 / Thursday, June 1, 2000 / Proposed Rules

belt, and 56 percent were ejected

(including 48 percent who were

completely ejected). Estimates from

NASS are that 82 percent of tow-away

rollovers occurred in single-vehicle

crashes, and 85 percent (159,000) of the

single-vehicle rollover crashes occurred

off the roadway.

The 1995–1997 General Estimates

System (GES) data produce estimates

that 240,000 light vehicles rolled over

each year (on average) in policereported crashes, and that 55,000

occupants in rollover crashes received

injuries rated as K or A on the police

injury scale. (The police KABCO scale

calls these injuries ‘‘incapacitating,’’ but

their actual severity depends on local

practice. ‘‘Incapacitating’’ injury may

mean that the injury was visible to the

reporting officer or that the officer

called for medical assistance.) This

includes 207,000 single-vehicle

rollovers with 45,000 K or A injuries.

Fifty-two percent of those with K or A

injury in single-vehicle rollovers were

not using a safety belt, and 18 percent

were ejected from the vehicle (including

16 percent who were completely

ejected). Estimates from GES are that 16

percent of light vehicles in policereported single-vehicle crashes rolled

over. The estimated risk of rollover

differs by vehicle type: 13 percent of

cars and 14 percent of vans in policereported single-vehicle crashes rolled

over, compared to 24 percent of pickup

trucks and 30 percent of SUVs.

III. Rulemaking History

In 1973 NHTSA issued an Advance

Notice of Proposed Rulemaking

(ANPRM) on resistance to rollover (38

FR 9598; April 18, 1973). The agency

was considering a safety standard

‘‘* * * that would specify minimum

performance requirements for the

resistance of vehicles to rollover in

simulations of extreme driving

conditions encountered in attempting to

avoid accidents.’’ Research projects

were undertaken to investigate handling

and stability of different types of

vehicles in severe steering maneuvers

associated with untripped rollovers. The

relevant conclusions of the research

were that ‘‘vehicle rollover response is

dominated by the vehicle’s rigid body

geometry (with dynamic contributions

from suspension effects),’’ and that

‘‘untripped rollover, even on high skidresistance surfaces, is difficult to predict

and accomplish.’’ The research

recommended computer simulation of

dynamic testing as a more repeatable

alternative to full-scale track testing.

Further work on untripped rollover was

discontinued in the late 70’s.

In September 1986, Congressman

Timothy Wirth petitioned NHTSA to

establish a safety standard for rollover

resistance by setting a minimum

allowable Static Stability Factor (SSF) of

1.2. The agency denied the petition in

December of 1987 (52 FR 49033,

December 29, 1987) stating that ‘‘* * *

while a vehicle’s stability factor can

reasonably predict whether a vehicle

which is already involved in a singlevehicle accident will roll over, it does

not accurately determine its likelihood

of becoming involved in an accident

that includes rollover.’’ An SSF of 1.2

‘‘* * * would neither adequately

encompass the causes of vehicle

rollover nor satisfactorily ameliorate the

problem.’’ In order to consider a

minimum standard, the agency believed

it was necessary to understand vehicle

characteristics making a single-vehicle

crash more likely as well as those

predictive of the rollover outcome of a

single-vehicle crash.

In June 1988 the Consumers Union

(CU) petitioned NHTSA to establish a

safety standard to protect occupants

against ‘‘unreasonable risk of rollover.’’

CU did not suggest a specific remedy.

The agency granted the petition in

September 1988. From 1988–1993

NHTSA undertook the most

comprehensive vehicle and data

analysis in its history, studying over

100,000 single-vehicle rollover crashes.

This study eventually focused on two

vehicle static measurements which

seemed promising: Tilt Table Angle and

Critical Sliding Velocity. Tilt Table

Angle is the angle at which a vehicle

will begin to tip off a gradually tilted

platform. Critical Sliding Velocity is the

minimum velocity needed to trip a

vehicle which is sliding sideways. Both

of these measurements address the

situation in which a vehicle encounters

something that trips it into a rollover,

such as a curb, soft dirt, or its own tire

rim digging into the pavement.

The NHTSA Authorization Act of

1991 (the Act) (part of the Intermodal

Surface Transportation Efficiency Act)

required the agency to address several

vehicle safety subjects through

rulemaking. One of the safety subjects

was protection against unreasonable risk

of rollovers of passenger cars and light

trucks. The Act required that NHTSA

publish, no later than May 31, 1992, an

ANPRM or a notice of proposed

rulemaking (NPRM) on this subject. The

Act also required the agency to

complete a rulemaking action on

rollover within 26 months of publishing

the ANPRM. The Act explained that this

rulemaking would be considered

completed when NHTSA either

published a final rule or decided and

announced that it would not promulgate

a rule.

On January 3, 1992 NHTSA fulfilled

the first mandate of the Act by

publishing an ANPRM (57 FR 242). In

the ANPRM the agency stated that it

was considering various regulatory

actions to reduce the frequency of

vehicle rollovers and/or the number and

severity of injuries resulting from

vehicle rollovers. The agency requested

comments on potential regulatory

actions in the areas of: improved

stability, improved crashworthiness,

and consumer information. NHTSA said

that it might issue a rule or rules in any

one of these three categories, or in any

combination of them.

The ANPRM discussed the agency’s

statistical analyses of the interaction of

driver characteristics, vehicle stability

metrics, roadway and environmental

conditions. The notice described the

following vehicle stability metrics as

having a potentially significant role in

vehicle rollover: center of gravity height;

static stability factor; tilt table ratio; side

pull ratio; wheelbase; critical sliding

velocity; rollover prevention metric;

braking stability metric; and percent of

total vehicle weight on the rear axle. A

vehicle stability metric is a measured

vehicle parameter thought to be related

to the vehicle’s likelihood of rollover

involvement. To supplement the

ANPRM, a Technical Assessment Paper

that discussed testing activities, testing

results, crash data collection, and

analysis of the data was placed in the

docket on January 6, 1992 (NHTSA–

1996–1683–4). A description of the

individual metrics can be found in the

Technical Assessment Paper.

During the development of the

ANPRM and after receiving and

analyzing comments to the ANPRM, it

became obvious that no single type of

rulemaking could solve all, or even a

majority of, the problems associated

with rollover. This view was

strengthened by the agency’s review and

analysis of the comments on the

ANPRM. To emphasize this conclusion

and inform the public further about the

complicated nature of the light duty

vehicle rollover problem, the agency

released a document titled ‘‘Planning

Document for Rollover Prevention and

Injury Mitigation’’ at a Society of

Automotive Engineers (SAE) meeting on

rollover on September 23, 1992. The

Planning Document gave an overview of

the rollover problem and a list of

alternative actions that NHTSA was

examining to address the problem.

Activities described in that document

were: crash avoidance research on

vehicle measures for rollover resistance,

research on antilock brake effectiveness,

Federal Register / Vol. 65, No. 106 / Thursday, June 1, 2000 / Proposed Rules 35001

3Tripped rollovers result from a vehicle’s

sideways motion, as opposed to its forward motion.

When sideways motion is suddenly interrupted, for

example, when a vehicle is sliding sideways and its

tires on one side encounter something that stops

them from sliding, the vehicle may roll over.

Whether or not the vehicle rolls over in that

situation depends on its speed in a sideways

direction (lateral velocity). By measuring certain

vehicle dimensions, it is possible to calculate each

make/model’s theoretical minimum lateral velocity

for this type of rollover to occur. These calcualted

speeds are relatively low, usually below 15mph, but

would be higher in actual crashes.

4 ‘‘Potential Reductions in Fatalities and Injuries

in Single-vehicle Rollover Crashes as a Result of a

Minimum Rollover Stability Standard;’’ NHTSA;

1994.

rulemaking on upper interior padding to

prevent head injury, research into

improved roof crush resistance to

prevent head and spinal injury, research

on improved side window glazing and

door latches to prevent occupant

ejection, and consumer information to

alert people to the severity of rollover

crashes and the benefits of safety belt

use in this type of crash. The document

was placed in Docket No. 91–68; Notice

02, on the same day. NHTSA published

a notice in the Federal Register

announcing the availability of the

Planning Document and requesting

comment (September 29, 1992; 57 FR

44721).

In June 1994 NHTSA terminated

rulemaking to establish a minimum

standard, fulfilling the second mandate

of the Act, because it found (using

statistical simulation of crash outcome)

that increasing several vehicle rollover

metrics to a level higher than is

currently seen in most compact sport

utility vehicles would not appreciably

decrease crash fatalities and injuries in

rollovers (59 FR 33254). In the

termination notice NHTSA said, ‘‘The

agency believes that no single type of

rulemaking or other agency action could

solve all, or even a majority of, the

problems associated with rollover.

Accordingly, it is pursuing a broad

range of actions to address those

problems.’’ The notice discussed the

wide range of ongoing agency activities

to address the rollover problem and

referred to the Planning Document.

In the same June 1994 notice NHTSA

proposed to require manufacturers to

label their vehicles with information on

their rollover stability using either Tilt

Table Angle (TTA) or Critical Sliding

Velocity (CSV). However, in September

1994, in NHTSA’s fiscal 1995

Appropriations Act, Congress stated that

NHTSA shall not issue any final rule on

vehicle rollover labeling until the

agency had reviewed a study by the

National Academy of Sciences (NAS) on

how to most effectively communicate

motor vehicle safety information to

consumers. The NAS study, ‘‘Shopping

for Safety—Providing Consumer

Automotive Safety Information,’’ was

released in March 1996 (TRB Special

Report 248). The NAS study

recommended that NHTSA expand the

scope of consumer information it

provides to the public. In the long term,

the study recommends the development

of one overall measure that combines

the relative importance of

crashworthiness and crash avoidance

features for a vehicle.

In May 1996 NHTSA issued the

‘‘Status Report for Rollover Prevention

and Injury Mitigation’’ (NHTSA–1996–

1811–2). This document updated the

progress of the programs discussed in

the Planning Document and added the

description of a planned project:

development of a dynamic test for

rollover and control stability in light

vehicles.

On June 5, 1996, NHTSA reopened

the comment period on its proposed

labeling rule (61 FR 28560). In that

notice NHTSA noted that it was

reviewing the 1994 proposal in light of

the NAS study. On the same day

NHTSA published a notice denying a

July 1994 petition for reconsideration of

the termination of rulemaking on a

rollover standard from the Advocates for

Highway and Auto Safety and the

Insurance Institute for Highway Safety.

In the denial the agency noted that it

had reviewed and expanded its work on

the benefits and cost of a standard based

on static vehicle measurements and

found the same results: such a standard

would eliminate a very popular vehicle

type (compact sport utility vehicles) and

would not decrease appreciably injuries

and fatalities in rollover crashes.

In August 1996 NHTSA received a

petition from Consumers Union (CU)

asking the agency to develop a test of

vehicle emergency handling capability

and to provide test results on new

vehicles to the public as consumer

information. The type of rollover that

would be addressed by such a test is

known as on-road, untripped rollover,

or maneuver-induced rollover. This type

of rollover was believed to represent

approximately 10 percent of annual

rollovers. Since the May 1996 Status

Report, the agency had been planning to

start a program on dynamic stability

testing. Funding for this research was

received for fiscal year 1997, and

therefore the agency granted the CU

petition in May 1997 saying, ‘‘NHTSA

will initially focus on exploring whether

it can develop a practicable, repeatable

and appropriate dynamic emergency

handling test that assesses, among other

issues, a vehicle’s propensity for

involvement in an on-road, untripped

rollover crash.’’ Section IV of this notice

details the additional research which

has been done since the 1996 CU

petition.

Since the vast majority of rollovers are

tripped, we have now decided that

primary consumer information should

be based on factors relevant to tripped

as well as untripped rollover, and we

have reconsidered the merits of Static

Stability Factor as an indicator of

rollover risk for consumer information.

IV. Recent Research on ManeuverInduced Rollover Crashes

A. Why Study Untripped Rollovers?

The causes of tripped rollover are

well understood. Any vehicle will roll

over if it impacts a tripping mechanism

with sufficient lateral velocity (such as

when the wheels on one side of a

vehicle that is sliding sideways hit a

curb and the vehicle tips over). A

vehicle’s static and dynamic rollover

metrics are related to the theoretical

minimum lateral velocity required for a

tripped rollover to occur. Improving a

vehicle’s static and dynamic rollover

metrics increases that theoretical

minimum lateral velocity and decreases

the potential for rollover.3

Unfortunately, as we reported in 1994,

there is currently no vehicle

measurement that can be used in a

minimum vehicle safety standard that

would decrease the risk of rollover

involvement without necessitating

drastic design changes to a vehicle type

that is sought after by consumers,

namely compact SUVs. This is because

the rollover rate of an individual make/

model is not very sensitive to small

changes in metrics, and larger changes

in metrics great enough to positively

influence rollover rate would

necessitate vehicle dimensional changes

that would prevent the manufacture of

current designs of compact light truck

(pickups and SUVs) 4.

In comparison, the causes of

untripped, on-road rollover are not well

understood. Past agency research has

never found a light vehicle for which,

when empty, the sharpest attainable

steady state (constant radius) turn

exceeds the vehicle’s rollover threshold

(although, in our recent track testing, a

compact pickup did tip up in a stepsteer test). However, our crash data

show that light vehicles do roll over on

the roadway, without tripping, due to

abrupt maneuvers. Currently-undefined

transient maneuvers may exist that

cause rollover for at least some light

vehicles. Various crash data studies

35002 Federal Register / Vol. 65, No. 106 / Thursday, June 1, 2000 / Proposed Rules

5 ‘‘Report to Congress: Rollover Prevention and

Roof Crush;’’ NHTSA, 1992.

6 ‘‘Handling Test Procedures for Light Trucks,

Vans, and Recreational Vehicles;’’ NHTSA, DOT–

HS–4–00853; February 1976.

7Research Note, ‘‘Passenger Vehicles in

Untripped Rollovers;’’ NHTSA National Center for

Statistics and Analysis; September 1999.

8Consumers Union of Yonkers, New York,

publishes vehicle evaluations in their Consumer

Reports magazine. Part of their evaluation is to have

experienced test drivers run each test vehicle

through an obstacle avoidance course marked out

with traffic cones. The test attempts to simulate an

emergency in which a driver, initially traveling

straight in a traffic lane, is suddenly forced to

swerve to the left into the adjacent lane by an

obstacle encroaching into his path from the right,

and then swerve back into the original lane. Thus

the term ‘‘double-lane change.’’

9This review of NASS CDS rollover cases was

made prior to the 1998 audit of NASS rollover

coding. The audit found that many ‘‘turnover’’ cases

should have been coded as other types, primarily

‘‘trip over’’. A discussion of the NASS CDS audit

is included in the Research Note cited in this

notice.

have indicated that loss of vehicle

directional control is a prelude to

rollover in 50 to 80 percent of all

rollover crashes 5. These traits would be

particularly important in on-road,

untripped rollovers and rollovers

resulting from loss of control due to a

poor road edge recovery maneuver.

An agency test project done in the

mid-1970’s on light truck handling

reported several interesting findings on

braking in a turn, trapezoidal steer,

sinusoidal steer, trapezoidal steer while

braking, and crosswind sensitivity for

light trucks (including utility vehicles) 6.

This study concentrated on discovering

the handling properties of ‘‘recreational

vehicles’’ in use at the time. The goal

was not necessarily to discover

maneuvers that would lead to rollover

for particular vehicles. It was intended

instead to ‘‘demonstrate the handling

behavior of recreational vehicles when

an external disturbance is encountered

or while engaged in a variety of evasive

actions * * * ’’ Maneuvers were not

chosen for their relevance to crash data.

No crash data study was done to

determine what maneuvers and

situations were common to most

rollover crashes.

We decided that in order to cover all

possible avenues, for even a small

portion of the rollover problem, we

should take a new look at untripped

rollovers. Our goal was two-fold: To

determine the extent of the national

incidence of untripped rollover, and to

examine commonly used track tests for

their potential in acting as an indicator

of vehicle tendency to roll over as the

result of an on-road maneuver.

Admittedly, this type of crash is a small

percentage of all rollovers. However, we

judged this new research to be

worthwhile because this type of crash is

very important to consumers (based on

comments to the NPRM, at the 1994

town meetings, telephone calls to

agency staff, and media interest). It

represents the most egregious type of

crash, where vehicle performance could

be said to be most involved, and it could

be the type of crash most affected by a

crash avoidance standard if an effective

maneuver could be developed.

Our goal was to find a test procedure

that would be relevant to what actually

happens to today’s vehicles on the road.

The best way to develop such a

procedure was to investigate which

situations and driving maneuvers are

most common in untripped rollover

crashes. Once these maneuvers and

situations were identified, field testing

could reveal which maneuvers can be

performed reliably and repeatably.

B. Estimate of the Annual National

Incidence of On-Road, Untripped

Rollover Crashes

One important element in

determining whether a new Federal

Motor Vehicle Safety Standard (FMVSS)

for untripped rollover prevention

should be established is to determine

how often that type of crash actually

occurs. Even if it does not occur very

often, if we were to develop a standard

that would prevent a great majority of

these crashes, a benefit would still

accrue to the motoring public. We have

known for many years that the

incidence of untripped, on-road rollover

is less than 10 percent of all rollovers.

However, exactly how much less was

not known and had not been

investigated.

The National Automotive Sampling

System Crashworthiness Data System

(NASS CDS) is a sample of all crashes

in the United States that involve damage

to a passenger vehicle (car, light truck

or van) of sufficient severity to require

towing. NASS CDS contains variables

describing the type of rollover for

vehicles involved in rollover crashes.

NHTSA’s National Center for Statistics

and Analysis recently completed an

estimate of the national incidence of

untripped rollover using 1992–96 NASS

data and a review of rollover crashes

completed by NHTSA in 1998. 7 NCSA

found that over those years an average

of 7,866 untripped rollovers happen

each year (standard error 2,340), 4.4

percent of all rollover crashes.

C. Dynamic Test Program

Our interest in untripped rollover,

combined with public interest in

vehicle stability arising in part from

Consumers Union double-lane change

tests, 8 led us to undertake a new

rollover test program. It was apparent

that, since the 1992 ANPRM, the light

truck market had expanded and was

continuing to grow.

Thus, in late 1996, we started

planning a test program in which the

goal was to evaluate the best available

dynamic rollover resistance test

procedures which could be used either

in a new vehicle safety standard or in

a consumer information program to

reduce light vehicle rollover risk. The

test program we envisioned would be a

full scale evaluation using production

vehicles with an emphasis on dynamic

track testing as opposed to static

laboratory measurements, the latter

having been well researched and

documented already by that time.

1. Preliminary Steps

As a first step, we identified the

candidate procedures for the purpose of

measuring light vehicle rollover

resistance from among many available

possibilities, with consideration given

to current ‘‘best practices’’ and to actual

rollover crash experience. We took the

following steps before conducting the

full scale test program:

a. Review of a selection of NASS CDS

cases in which untripped rollover was

the primary harmful event. The review

gave a general idea of the circumstances

surrounding on-road, untripped rollover

crashes and provided some perspective

on the types of track testing that would

be appropriate to reflect actual crashes

of that kind.

b. Review of consumer complaints

involving rollovers of light vehicles. The

complaints came from an agency

database maintained by NHTSA’s Office

of Defects Investigation (ODI).

c. Comprehensive review of a variety

of test procedures from several available

sources.

Each of these activities is briefly

discussed below.

a. NASS Case Studies

The NASS CDS database for the

calendar years 1992 to 1995 included 15

light vehicle rollover crashes which met

all of the following criteria:

• the crash was coded ‘‘turnover’’,

which indicates an untripped rollover,9

• a single vehicle was involved and

turned over on the road or paved

shoulder,

• the rollover was the first harmful

event,

• the vehicle was a 1990 or later

model year,

• the driver was not impaired, there

were no mechanical failures such as a

tire blow-out prior to the rollover, and

Federal Register / Vol. 65, No. 106 / Thursday, June 1, 2000 / Proposed Rules 35003

10The meetings are documented in docket

NHTSA–1998–3206.

• the rolled vehicle was not towing a

trailer.

These restrictions limited the cases to a

selection which could be described as

‘‘maneuver-induced’’ rollovers, that is,

rollover crashes in which tire-road

friction, rather than some other factor

such as a collision or contact with a

tripping mechanism, can be assumed to

have been the primary source of

overturning force.

We reviewed hard copy files from

each of those 15 cases. The following

are the pertinent observations from that

review:

• Thirteen of the cases involved LTVs

(vans, pickups, or SUVs); the other two

rollovers involved sub-compact cars in

a loaded condition (three or more

occupants).

• In ten of the 15 cases, the vehicle

was entering, exiting, or traveling on

highways, divided roadways, or

interstates with posted speeds of 55

mph or greater and associated entrance/

exit ramps prior to crashing. According

to the files, two cases involved

excessive speed prior to the incident.

The remaining five cases occurred in

lower speed zones (posted 35 mph or

less).

• Only one of the 15 rollovers

occurred in an urban setting; the

remainder occurred in a rural setting or

other non-urban location.

• None of the 15 cases appeared to

involve a driver attempting to avoid a

stationary or slow-moving object in the

roadway. In several cases, the driver

swerved or lost control of the vehicle,

but the reason for swerving was

reported as a moving vehicle, or

unknown.

• It appears that driving conditions

were generally good in all of the cases

(level roads, no precipitation, in

daylight or on lighted roadways) except

for wet pavement in a few of the

instances.

These observations indicated that

single-vehicle, untripped rollover

crashes most often occur on rural

highways; the speeds at which the

rollover crashes occur are relatively

high compared to, for example, those

experienced in the Consumers Union

obstacle avoidance maneuver

(approximately 30 to 40 mph,

depending on the vehicle); and they

occur because drivers lose control of

their vehicles, sometimes in attempting

to recover from having completely or

partially left the roadway, as opposed to

avoiding an obstacle.

The information derived from these

case studies led us to conclude that, in

order to evaluate untripped rollover

stability of production vehicles, at least

one of the test procedures should

involve a highway scenario with the test

vehicle moving at close to highway

speeds (45 mph or greater) and

attempting to re-enter the roadway from

a shoulder or from some partially offroad disposition.

In reviewing available test

procedures, we found mention of a test

procedure proposed at one time by

General Motors that emulates a roadway

recovery scenario. In addition, at a

meeting with NHTSA representatives in

March, 1997, Suzuki submitted

information on three variations of a

scenario in which a vehicle leaves or

partially leaves a roadway and then rolls

over after attempting to re-enter the

roadway. One of the three scenarios

suggested by Suzuki is similar to the

roadway recovery scenario indicated in

several of the NASS cases.

An expanded search of NASS CDS

data with fewer restrictions than those

listed above for the 15 NASS CDS cases

yielded 60 untripped rollover cases. In

many of those cases, the cause of

rollover was coded as ‘‘obstacle

avoidance.’’ This supported inclusion of

an obstacle avoidance test procedure in

addition to the roadway recovery test in

the NHTSA test program.

b. ODI Complaints

We reviewed a number of complaints

of light vehicle rollover in the database

maintained by ODI. As of March, 1997,

144 incidences of rollover involving

passenger cars, light trucks, SUVs, and

vans were found in the database (four

other rollover complaints were rejected

because they involved other types of

vehicles like motor homes and heavy

trucks).

Of the 144 complaints, roughly twothirds were the result of an alleged

component failure of some kind. In

other words, the rollovers occurred,

either directly or indirectly, because a

critical component of the vehicle

suddenly or unexpectedly broke (e.g.,

‘‘axle separated’’), seized (e.g., ‘‘brakes

locked’’), or otherwise failed (e.g.,

‘‘steering wobbled’’) while the vehicle

was in motion. The following are some

examples of typical complaint

descriptions taken verbatim from the

ODI files:

• ‘‘Axle ring broke, causing vehicle to

swerve/lose control/rollover,’’

• ‘‘Wheel assembly locked up,

causing uncontrollable spin/rollover,’’

• ‘‘ABS brake locked up after

reducing speed to 35 mph, vehicle slid

then rolled over.’’

• ‘‘Inner tie rod broke at threads near

outer tie rod. Vehicle swerved and

rolled over.’’

The most commonly reported

component failures in the rollover

complaints were:

• brake lock-up (both conventional

and ABS systems),

• other braking system failure

(including parking brake),

• steering or suspension component

lock-up, separation, or other failure,

• wheel rim, axle, or bearing,

separation or failure,

• tire went flat or other tire failure,

and

• sudden acceleration

(Note that these failures were allegedly

associated with the rollovers as reported

in the complaint records, and there was

no way to confirm them independently.)

In twenty-four of the complaints, no

component failure was cited, and severe

vehicle maneuvers were indicated. In

these instances, the lack of vehicle

rollover resistance appeared to be a

primary causal factor, if not the ultimate

cause. But this assumption is based

solely on the minimal event description

given in the ODI database. The

following are some examples of the

descriptions in which vehicle instability

appeared to be a key factor:

• ‘‘Truck rolled over when making

clockwise wide arc turn, came to rest on

its top.’’

• ‘‘While driving at 55 mph, went

around an animal on highway, vehicle

went out of control, rear fish-tailed,

vehicle rolled; injured head, back,

shoulder, and arm.’’

• ‘‘Lack of reinforcement around

sunroof; high center of gravity resulted

in rollover.’’

There was insufficient information in

the database in the remainder of the ODI

complaints to allow speculation on the

cause of the rollover.

Sixty-four percent of the ODI

complaints (92 of 144) involved light

trucks, vans, and sport utility vehicles

as compared with passenger cars.

c. Survey of Available Test Procedures

We reviewed information on a wide

range of test procedures related to

vehicle handling and stability,

including test methods already in use by

vehicle manufacturers, technical

standards organizations like SAE and

the International Standards

Organization, and consumer groups.

We also met with a number of major

vehicle manufacturers to discuss their

approach to vehicle design and testing

with respect to rollover.10 Each of the

manufacturers had a somewhat different

approach. In terms of track testing

vehicles, manufacturers generally used a

35004 Federal Register / Vol. 65, No. 106 / Thursday, June 1, 2000 / Proposed Rules

battery of maneuvers to assess both

handling and stability; no single test

was dedicated solely to rollover

resistance. Evaluations of rollover

resistance were usually associated with

more general handling evaluation tests.

One notable exception was a detailed

engineering procedure for a ‘‘fishhook’’

test devised specifically for rollover

propensity testing and submitted to the

agency by Toyota Motor Corporation.

Some tests were specifically mentioned

by other vehicle manufacturers. These

included step-steer (J-Turn), steering

reversal, slalom, double lane change,

and a resonant steering test. Two

variations of the ‘‘fishhook’’ and two

variations of a J-turn test were

eventually used in the agency’s

untripped rollover test program (see

sections 2 through 4, below).

Of particular importance among the

vehicle manufacturers was their reliance

to a very great extent on their own

experienced test drivers to provide

feedback on vehicle stability. It was

evident that, in the realm of a

manufacturer’s vehicle development

and testing programs, there was little

incentive to use the most objective

procedures possible, such as using a

programmable steering controller. For

the manufacturers’ own purposes in

designing the handling and stability

characteristics of their vehicles, the skill

and experience of test drivers was

sufficient.

In NHTSA’s review of dynamic

rollover resistance test procedures, the

initial objective had been to choose an

available procedure which could be

used, with minimal adaptation, in a test

program with a large group of vehicle

models. However, after review of

available procedures, we concluded that

there did not appear to be a single,

prominent test among industry users, or

one or two test procedures that were

clearly superior in most respects for the

purpose of rollover resistance testing.

We were unable to conclude from the

documentation that we reviewed

whether any of the test procedures alone

would provide an acceptable, practical,

and repeatable measure of rollover

stability, and one that would be accurate

enough to effectively distinguish among

many vehicle models of the same

vehicle type. Furthermore, there were

many procedures that were merely

variations of some of the more basic

ones. For example, we found reference

to at least a half dozen variations on an

obstacle avoidance test and each one

was essentially a double-lane change.

Since there was insufficient

information available on which to make

a definitive test procedure selection, we

decided to pursue a two phase test

program. The first phase would focus on

evaluating the various types of test

procedures found in our initial review.

This evaluation would allow us to

eliminate any impractical, repetitive, or

inapplicable test procedures. The

second phase would then focus on an

in-depth analysis of the relatively few

test procedures remaining.

2. Track Testing—Phase Ia

For Phase I testing, we selected three

popular SUVs in order to experiment

with a number of possible test

procedures. By using only a few vehicle

models in Phase I, we were able to focus

on narrowing down the extensive list of

possible test procedures to a relatively

few choices.

The three Phase I test vehicles were

selected based on our desire to gain

experience with SUVs in particular, as

opposed to passenger cars, vans, or

pickups. Also, it was necessary to

choose vehicles from the same class to

address the original goal of the test

program, which was to determine

whether dynamic test procedures could

differentiate performance among

vehicles of the same type. Once it had

been decided to concentrate on SUVs in

Phase I, the choice of models was made

in large part on what we had in hand

at the time or could obtain quickly and

at low cost. The three models selected

were: A 1997 Jeep Cherokee 4-door,

four-wheel drive, a 1990 Toyota

4Runner 4-door, four-wheel-drive, and a

1984 Ford Bronco II, 2-door, four-wheeldrive. The suspension of each of these

vehicles was mechanically refurbished

as necessary prior to testing.

The test procedures that we evaluated

in Phase I track testing included the

following:

• Step-steer (‘‘J-Turn’’)

• J-Turn with pulse braking

• Toyota Fishhook maneuver (with

pulse braking)

• Modified Toyota Fishhook

maneuver (no pulse braking)

• Steering reversal

• Double lane change (pathfollowing)

• Split-mu (wet epoxy and asphalt)

• Braking in a turn (‘‘Brake and

Steer’’)

Some of these procedures, such as JTurn, are generic and can be performed

using a range of input parameters

including various steering amplitudes

and speeds. Although we began Phase I

with specific variations of these test

procedures in mind, each having

predetermined test parameters, we did

not limit our evaluation to any

predetermined parameters. Instead, the

specific test procedure parameters were

used as starting points. As we gained

experience during the course of Phase I,

we made judgements about what were

appropriate modifications to suit our

testing objectives. For example, the

Double Lane Change test was initially

modeled after the Consumer’s Union

Short Course, using the same

dimensions and cone spacing, but we

experimented with a variety of course

layouts by adjusting the cone spacing to

give a different steering inputs. In

another example, we used a

modification of the Toyota Fishhook

maneuver to represent a loss of control

associated with driving errors in road

edge recovery.

The result of Phase I testing was the

selection of five procedures for further

evaluation in Phase II. The selected

maneuvers included two variations of

the ‘‘Fishhook’’ steering-reversal test,

two variations of the J-Turn (one with

and one without a pulse brake

application), plus a Resonant Steering

procedure.

Perhaps the most significant outcome

of Phase I testing was our decision to

eliminate ‘‘path-following’’ maneuvers,

including double-lane changes, from

further consideration. Our experience in

Phase I with path-following maneuvers

indicated that they are too subjective.

The reason for this was that steering

inputs could vary widely over any

course demarcated with cones or

barriers. When speeds were high enough

to push the vehicle to a limit condition,

the steering inputs could not be

repeated from one run to another. This

result was significant because pathfollowing tests, particularly double-lane

change (obstacle avoidance) tests such

as the so-called ‘‘moose’’ test were

popular with consumer groups and had

received fairly extensive public

attention.

Our NASS CDS case studies had

indicated that road-edge recovery was a

possible factor in five of the 15 rollover

crashes reviewed in subsection 1(a)

above. The circumstances of these

crashes were complex, usually

involving a vehicle leaving the paved

travel lanes, at least partially, so that

two or more of its wheels were on the

shoulder. Typically, the rollovers in

these cases occurred after the vehicle’s

driver attempted to steer back onto the

paved lanes. Since this scenario is

difficult to recreate on a test track, we

attempted to simulate it by driving test

vehicles on a ‘‘split mu’’ surface, that is,

with the wheels on one side of the

vehicle on dry asphalt and the wheels

on the opposite side on a slick surface.

In this procedure, the wheels on the

slick surface contributed little to the

turning force as the vehicle was sharply

steered towards the dry side of the test

Federal Register / Vol. 65, No. 106 / Thursday, June 1, 2000 / Proposed Rules 35005

11 ‘‘Unstable’’ means two wheels on the same side

of the vehicle lift completely off the roadway, to

any height for any amount of time.

12Since these issues were researched separately,

this phase of the test program was designated as

‘‘Phase Ib’’ to distinguish it from the earlier part of

Phase I which focused on evaluation of the

maneuvers. The earlier part of Phase I has since

been referred to as ‘‘Phase Ia.’’ Eventually, it is our

intention to make separate reports available

coverting Phases Ia and Ib.

13The final selection of twelve make/models is

documented in the Phase II final report which can

be found in the DOT docket management system

under number NHTSA–1998–3206.

track lane. The intent was to simulate

the lack of traction that exists when two

wheels are off the road, tending to resist

the driver’s effort to steer back onto the

paved surface. Unfortunately, this

procedure was of limited usefulness.

The results were inconsistent from run

to run, the lack of traction on one side

causing erratic trajectories and leading

to spin-outs in some cases. Overall, it

was an ineffective simulation of the

intended scenario.

A fundamental criticism of any

dynamic, path-following maneuver

having one or more steering reversals is

that it could arbitrarily excite a ‘‘roll

resonance’’ in some vehicles. That is,

the timing of the steering reversal,

which would be determined by the

geometry of the course layout, had the

potential to become synchronized with

the vehicle’s natural roll response so as

to increase the roll motion. The test

would be much more severe for any

vehicles at roll resonance than for

vehicles not at resonance. However, the

test results might differ significantly

merely by changing the course

geometry, so that a different vehicle

might have its roll resonance excited.

To address this resonance potential, it

was necessary to either identify the

conditions for resonance and

demonstrate its effect on vehicle

stability by intentionally inducing those

conditions in a test maneuver, or else

show that resonance is not a significant

factor in rollover because of suspension

damping or for some other reason that

mitigates the theoretical effect.

The roll resonance issue led us to

choose, as one of the candidate

maneuvers for Phase IIa ‘‘resonant

steering’’ test procedure. In that

procedure, the first step was to attempt

to determine each test vehicle’s roll

resonance frequency, and then to drive

the test vehicle while oscillating the

steering at the resonant frequency and

increasing either the velocity or steer

magnitude until the vehicle became

unstable.11 Ultimately, as discussed in

the Phase II report, the test vehicles

appeared to be well-damped and it was

not possible to identify a distinct roll

resonant frequency. This is an area

where we would like to conduct further

research and testing.

3. Track Testing—Phase Ib

After gaining some experience with

dynamic maneuvers in the early part of

Phase I, we decided that some issues

that had come up during track testing

warranted further exploration. 12 These

issues included:

• the effect of tire wear in successive,

severe test runs,

• repeatability of steering inputs from

one driver to another, and

• the effect of outriggers on vehicle

dynamics.

A key development during Phase Ib

was the opportunity to experiment with

a Programmable Steering Machine

(PSM). This device could be mounted in

any of the test vehicles and had the

capability of inputting high steering

rates and amplitudes. This device

proved to be a valuable tool for dynamic

testing and, to a great extent, addressed

the driver variability issue.

Even with the PSM, the driver was

still in the vehicle for braking and

acceleration. Therefore, outriggers were

still necessary. Testing found that

outriggers added only slightly to the

vehicle’s moment of inertia.

Testing in Phase Ib found that tire

shoulder wear was significant and

caused lateral acceleration to increase

with repeated test runs on the same

tires. This problem was addressed by

implementing a schedule of tire

replacement based on the number of test

runs.

Another important consideration in

Phase I testing was that two-wheel-lift

(TWL) could be difficult to recognize by

visual observation of test runs. Some

instances of TWL could be so small that

they might not be apparent to test

observers. We considered various

methods for positively determining

whether TWL occurred, as well as

methods for measuring the degree or

height of TWL. Ultimately, this issue

was not resolved prior to

commencement of Phase II. In Phase II,

TWL was identified and measured

either by direct visual observation of

tests or by close examination of

videotape records of them.

4. Track Testing—Phase II

a. Test Vehicle Selection

As a first step in conducting the Phase

II test program, test vehicle make/

models were selected to represent as

many light vehicle types as possible of

those currently in use on U.S. roads.

First, light vehicles were categorized

into four types: passenger cars, vans

(and mini-vans), pickups, and SUVs. We

decided that three vehicles in each

category was the minimum sufficient

number needed to represent each type

and should consist of one compact, one

mid-size and one large example from

each type, making a total of twelve test

vehicles. Additional criteria for

selection were the following:

• Only late model vehicles (MY1997–

98) to ensure that new vehicles could be

procured for testing, and

• Only popular (high-selling) vehicles

which had been in production without

significant design changes for at least

three years to ensure that they were

represented in available crash data. 13

b. Results

The Phase II results are reported in

detail in the Phase II Final Report. In

general, the results confirmed that light

trucks have a lower resistance to tip up

as a consequence of sharp steering

inputs (high magnitude and rate) than

passenger cars. Among the light trucks

tested in Phase II, those with more

truck-like characteristics (four-wheel

drive, higher center of gravity) had a

higher tendency to tip up than those

with more car-like characteristics (twowheel drive, lower center-of-gravity).

Furthermore, the dynamic tests

results were consistent to a great extent

with static measures of rollover

resistance. Thus, the dynamic tests

confirmed the significance of static

metrics as predictors of untripped

rollover propensity. This result is

significant because, previously, the

relationship of static metrics to tripped

rollover was well-established, but the

same has not necessarily been true of

untripped rollover. Certainly, center-ofgravity height and track width do

influence untripped rollover.

It is important to mention the

influence of test driver safety on the

Phase II test program. Even though

outriggers were used consistently, the

high speeds and abrupt direction

changes required in the dynamic tests

made it necessary to curtail some test

sequences at a point where the test

vehicle was starting to become unstable.

That is, when a vehicle showed a

tendency to begin to lift wheels at a

certain speed, repeated runs at that

speed may or may not have been

attempted depending on safety

considerations. Also, whereas runs at

even higher speeds might have

indicated whether major TWL would

occur, higher speed runs were not

attempted after the initial indications of

tip-up were reached. The question of

35006 Federal Register / Vol. 65, No. 106 / Thursday, June 1, 2000 / Proposed Rules

14 ‘‘Technical Assessment Paper: Relationship

between Rollover and Vehicle Factors’’; NHTSA;

July 1991.

whether minor TWL would become

major TWL at higher speeds could not

be answered due to the concern for test

driver safety.

Based on the results of Phase II

testing, we concluded from this research

that dynamic test methods are not

currently superior to simpler, less costly

methods, particularly static metrics. The

dynamic test results did not conflict

with predictions from static metrics.

Further, dynamic tests did not provide

greater capability to indicate the

rollover resistance, either untripped or

tripped, of light vehicles. Therefore, we

do not believe that dynamic test

procedures are developed to the point

necessary to be used for a minimum

standard or consumer information at

this time.

One of the rather surprising results of

our track testing was that three vehicles

experienced a similar tire problem, ‘‘debeading’’, which resulted in minor or

moderate TWL for two of the vehicles.

De-beading occurs when the tire loses

all of its air due to a separation of the

tire bead from its wheel rim. This

condition occurred in one SUV, one

pickup, and one car. TWL resulted for

the two light trucks. All tires were OEM

and inflated as prescribed by the

vehicles’ manufacturers. Why does this

de-beading concern us? When the tire

separates from the wheel rim, the

exposed rim can contact the surface

over which the vehicle is sliding. The

rim can then dig into the surface and act

as a tripping mechanism to initiate a

rollover crash. While these crashes are

not untripped, they can be on-road and

maneuver-induced.

After this unexpected result on the

test track, we were interested to know

whether this type of rollover initiation

is happening in the real world. The

NASS CDS data base does not have a

specific variable for rollover initiation

by tripping on the wheel rim, so a

combination of NASS variables was

used to estimate the nationwide

incidence of this problem. NASS cases

were tabulated for single-vehicle

rollovers coded ‘‘trip-over’’ in which the

pre-impact stability state was ‘‘skidding

laterally’’ (either clockwise or

counterclockwise), the ‘‘rollover object

contacted’’ was ‘‘ground’’, the tripping

location on the vehicle was ‘‘wheels/

tires’’, and the rollover initiation

occurred on the roadway or a paved

shoulder. Using NASS years 1992 thru

1997, we estimate this combination of

conditions occurs in an annual average

of 11,896 crashes. This preliminary

analysis was the best way to estimate

the incidence of rollover crashes

involving tire de-beading. Maneuverinduced tire debeading is a subject of

further research.

5. Plans for Continuing Dynamic Test

Research

As stated above, of the five maneuvers

evaluated in Phase II, no single one in

particular demonstrated greater

suitability than the others for the

intended purpose of comparing the

rollover propensity of the test vehicles.

Instead, the occurrences of TWL at any

level were distributed among the

different maneuvers, and the same is

true of TWLs of greater than a minor

amount. Thus, we did not succeed in

finding just one or two dynamic tests

that can effectively distinguish

untripped rollover resistance. Also, it

would be useful to investigate why the

same maneuver run in different

directions, for example a left versus

right J-turn at a given speed, sometimes

yielded different results. This, the

resonant steer issue, and steeringinduced tire debeading are some of

several areas where we plan to continue

research on dynamic rollover resistance

testing.

D. How Do Dynamic Rollover Test

Results Compare With Metrics?

As discussed above, TWL was the

primary criterion for evaluating vehicle

stability in Phase II dynamic tests. The

basic pattern of TWL outcomes in the

tests was fairly evident: vehicles with

more truck-like characteristics (SUVs,

4WD pick-ups, and full-size vans)

tended to have a higher frequency and

a greater degree of TWL than vehicles

with more car-like characteristics

(minivans, two-wheel drive pickups,

and passenger cars). As such, it was

possible, without detailed analysis of

the test results, to draw general

conclusions about each vehicle’s

relative stability and about the various

test maneuvers.

Nevertheless, it was desirable to

compare the TWL outcomes with some

objective indicators of vehicle stability,

particularly metrics including SSF,

Critical Sliding Velocity (CSV), and Tilt

Table Angle (TTA) and to attempt to

quantify the relationship between TWL

and these metrics to the greatest extent

possible using statistical methods.

To do so, the twelve test vehicles first

were grouped according to whether they

had any TWL in the Phase II tests. It was

readily apparent that vehicles with

lower metric values (less stable)

experienced more frequent and/or a

greater degree of TWL than vehicles

with higher metric values (more stable).

This was true using SSF, TTA, or CSV.

Also, test vehicles with below median

metric values (considering only the 12

test vehicles) were the only ones that

had any TWL (there were two

exceptions involving minor TWL, but in

one case a tire problem may have

influenced the outcome and in the other

case the vehicle’s CSV value was just

slightly above the median). In statistical

terms, a strong association was

demonstrated between each metric and

TWL as a yes/no variable by the fact that

TWL occurred only on vehicles with

below median SSF, CSV, and TTA

values.

Next, the 12 test vehicles were

grouped according to whether or not

they had any major TWL in Phase II, the

level of TWL which was thought to

represent an actual rollover. Since only

one vehicle had major TWL, this

grouping meant that the eleven test

vehicles without major TWL were all

lumped into one category even though

they represented a substantial range of

metric values. The result was that the

statistical tests did not identify a

significant correlation between metric

values and major TWL.

In a third analysis, the vehicles were

grouped according to the highest level

of TWL which they experienced during

the Phase II tests. Numerical values

were assigned as follows:

0=no TWL

1=minor TWL

2=moderate TWL

3=major TWL

When degree of TWL was identified

using these designations, the association

with metric values was statistically

significant and a positive correlation

between TWL level and metric values

was indicated. (Note that correlations

among various static metrics including

SSF, TTA, and CSV, has already been

established in past agency work 14.)

Overall, the results of the statistical

analyses were somewhat ambiguous, as

was expected given the low incidence of

TWL during testing and the very small

sample size overall.

V. Why Choose SSF?

A. Description of Metrics

The agency, vehicle manufacturers

and others have used various ‘‘metrics’’

and driving maneuvers to characterize

the rollover resistance of vehicles in

particular situations. Metrics are usually

measurements of dimensional, mass and

inertial properties of vehicles or

calculations combining these properties

in ways intended to represent rollover

resistance. They have also taken the

form of the results of simple static tests

Federal Register / Vol. 65, No. 106 / Thursday, June 1, 2000 / Proposed Rules 35007

such as tilt table ratio or the

combination of static measurements and

simple driving maneuver tests such as

‘‘stability margin’’. In its ongoing

rollover studies, the agency has used

several metrics including Static Stability

Factor, Tilt Table Angle or Ratio,

Critical Sliding Velocity and Side Pull

Ratio and various driving maneuvers

including J-turn and fishhook

maneuvers and sinusoidal steering.

Each of these indicators of rollover

resistance has both advantages and

disadvantages, and several would be

acceptable candidates for comparative

consumer information. The agency

favors static stability factor because it is

applicable to both tripped and

untripped rollover. The causal basis for

its good correlation to crash outcomes is

clear. It is relatively simple for

consumers to understand and can be

measured inexpensively with good

accuracy and repeatability. Also,

changes in vehicles to improve static

stability factor are very unlikely to cause

unintended consequences.

The Static Stability Factor (SSF) of a

vehicle is one half the track width, t,

divided by h, the height of the center of

gravity above the road. The inertial force

which causes a vehicle to sway on its

suspension (and roll over in extreme

cases) in response to cornering, rapid

steering reversals or striking a tripping

mechanism, like a curb, when sliding

laterally may be thought of as a force

acting at the center of gravity (c.g.) to

pull the vehicle body laterally. A

reduction in c.g. height increases the

lateral inertial force necessary to cause

rollover by reducing its leverage, and

the advantage is represented by an

increase in the computed value of SSF.

A wider track width also increases the

lateral force necessary to cause rollover

by increasing the leverage of the

vehicle’s weight in resisting rollover,

and that advantage also increases the

computed value of SSF. The factor of

two in the computation ‘‘t over 2h’’

makes SSF equal to the lateral

acceleration in g’s at which rollover

begins in the most simplified rollover

analysis of a vehicle represented by a

rigid body without suspension

movement or tire deflections. In this

form, it is easy to compare to the related

metrics, Tilt Table Angle and Side Pull

Ratio, which are similar except for the

inclusion of suspension movement and

tire deflections.

A simple test of rollover resistance is to place a vehicle entirely on a table which tilts about a longitudinal axis

and raises one side of the vehicle higher than another. As the table continues to tilt, it eventually reaches an angle

at which the high side tires lift from the table, and the vehicle rolls over if not restrained. The critical angle is

called the Tilt Table Angle. The trigonometric function, tangent, of this angle is the Tilt Table Ratio (TTR), which

is the ratio of the component of the tilted vehicle’s weight which acts laterally to overturn it, to the component

perpendicular to the table which resists overturning. For an idealized vehicle without suspension movements, the TTR

is the same as the SSF. The suspension movements of actual vehicles reduce the TTR about 10 to 15 percent relative

to the SSF.

35008 Federal Register / Vol. 65, No. 106 / Thursday, June 1, 2000 / Proposed Rules

The Side Pull Ratio (SPR) is the lateral force acting at the vehicle’s c.g. necessary to cause two wheel lift, divided

by the vehicle’s weight. It is determined by a test which is conceptually identical to the tilt table test but which

uses an externally applied lateral force to cause the wheels on one side of a vehicle parked on a horizontal surface

to lift up. It exercises the vehicle suspension more realistically because the whole weight of the vehicle remains on

its suspension. In the tilt table test, the vehicle can rise somewhat relative to the table surface because the component

of the vehicle weight which compresses the suspension springs steadily diminishes as the angle of the table increases.

For an idealized vehicle without suspension movements, the SPR also is the same as the SSF. Again, the suspension

movements of actual vehicles reduce the SPR relative to the SSF by about 10 to 15 percent.

Critical Sliding Velocity (CSV) is a

metric tied directly to tripped rollover.

It is a calculation of the lateral velocity

necessary to cause a rigid body

representation of a vehicle to overturn

upon impact with a rigid tripping

mechanism. It includes the c.g. height,

track width, mass and roll mass moment

of inertia of the vehicle in the

calculation.

Stability Margin is a metric directed

toward on-road untripped rollover. It is

the difference between the Side Pull

Ratio of a vehicle and its maximum

lateral acceleration in g’s, as measured

in a steady state cornering test. The

steady state cornering test consists of

finding the maximum speed the vehicle

can maintain while following a circular

path. The idea is that if the cornering

acceleration the vehicle can produce is

less than the SPR, it would not be

possible for a rollover to occur simply

as a result of steering maneuvers. GM

recommends a margin of 0.2 g’s because

lateral accelerations in maneuvers with

rapid steering reversals and/or brake

release in a curve can be greater than

those measured in a steady state test.

Federal Register / Vol. 65, No. 106 / Thursday, June 1, 2000 / Proposed Rules 35009

15E.A. Harwin and L. Emery; ‘‘The Crashavoidance Rollover Study: a Database for the

Investigation of Single-vehicle Rollover Crashes;’’

12th International Technical Conference on

Experimental Safety Vehicles, Goteburg, Sweden,

May 29–June 1, 1989; Vol 1, p. 470–477.

16 ‘‘Technical Assessment Paper: Relationship

between Rollover and Vehicle Factors’’; July 1991.

Computation of untripped rollover based on 1989

NASS.

B. Tripped and Untripped Rollover

The terms on-road and off-road

rollover are sometimes thought of as

surrogates for tripped and untripped

rollover. Off-road rollover does not refer

to vehicles rolling over while trying to

negotiate difficult trails away from

public roads. It refers to vehicles leaving

the road in the course of a crash and

rolling over off the pavement. Usually,

but not always, a curb, a soft shoulder,

a ditch, loose gravel, a guard rail or

another tripping mechanism initiates

the rollover. In contrast, most people

associate only the frictional force

between the tires and the pavement

rather than a tripping force with on-road

rollover involving a single vehicle. This

is also called maneuver-induced

rollover.

Past NHTSA studies of crash data

from the state of Maryland 15 and

NASS 16 suggested that between 8 and

10 percent of single-vehicle rollover

crashes were on-road rollover. However,

a recent study of audited NASS CDS

data (a data sampling system with

projection factors to represent the

national trends) estimated that while

over 13 percent of rollovers in singlevehicle crashes occur on-road or on a

paved shoulder, only 4.2 percent are

untripped. Examples of on-road tripped

rollovers are instances in which

potholes or differences in pavement

level acted as tripping mechanisms and

the more common instances in which

the wheel rim dug into the pavement

(possibly as a result of tire de-beading).

The study also estimated that only 0.2

percent of rollovers are untripped and

off-road.

The agency has conducted studies of

on-road untripped rollover because

these events are considered egregious by

the public and because the prospects of

developing objective, repeatable and

realistic vehicle tests of untripped

rollover appeared to be more favorable

than for tripped rollover, in which the

circumstances are limitless. Many of the

vehicle attributes that improve

resistance to untripped rollover also

improve resistance to tripped rollover.

Certainly, a low c.g. and a wide track

width are beneficial in resisting rollover

in general.

However, even objective and

repeatable steering maneuver tests

present a dilemma. Suppose the first

vehicle responds to steering maneuvers

up to a high test speed and two wheel

lift occurs. Suppose the second vehicle

spins out or plows out at a significantly

lower speed, but two wheel lift does not

occur. Which vehicle has better

performance in rollover resistance? If

untripped on-road rollover is the only

criterion, the second vehicle has

demonstrated better performance

because it cannot be controlled through

a test maneuver severe enough to cause

two wheel lift. But the test tells us

nothing about the far more likely risk of

tripped rollover. We do not know how

the second vehicle would have

performed under the same lateral

acceleration that caused two wheel lift

in the first vehicle.

Stability Margin shares the dilemma

for vehicle comparisons described

above. The SPR component of stability

margin compares vehicles on an equal

basis that would be meaningful for

tripped or untripped rollover, but the

subtraction of the maximum on-road

lateral acceleration limits the

applicability of the margin to on-road

untripped rollover. Simply fitting the

same vehicle with lower traction tires

increases the stability margin without

making any difference when a tripping

mechanism is encountered. Even when

the scope of interest is limited to onroad untripped rollover, Stability

Margin is unsuitable for comparative

purposes. A greater stability margin

does not necessarily mean more safety.

A margin in excess of the minimum

necessary to avoid untripped rollover

may simply represent poor cornering

capability.

The steering maneuver tests studied

by the agency were consistent with SSF,

TTR and CSV. The only vehicles that

experienced two wheel lift in the

maneuvers were those at the lower

range of the metrics. However, the

steering maneuver tests studied do not

distinguish between those vehicle

attributes that increase rollover

resistance in all circumstances and

those applicable only in the narrow risk

category of on-road untripped rollover.

Therefore, the steering maneuver tests

recently studied are not considered as

appropriate for general consumer

information on rollover as SSF, TTR or

CSV.

C. Correlation and Causation

Correlation means that two events

generally occur together. However, the

fact that event B occurs when event A

occurs does not mean that event B

occurs because event A has occurred.

Thomas Sowell, the economist and

columnist, notes that youngsters who

voyage on the Queen Elizabeth II or ride

on the Concorde tend to make more

money as adults, but that we don’t

recommend buying tickets for these as

a way to increase a child’s earning

potential. Childhood luxury trips are

correlated to future earnings, but do not

cause the higher income.

A causal relationship, on the other

hand, means that event B occurs

because event A has occurred. These

events are not simply linked in time,

like in a correlation, but event A is a

necessary element for event B to occur.

In a simple form, the plant grows

because of the light. Light is not the

only thing needed for the plant to grow,

and the plant may die even if it receives

plenty of light, but there is a causal

relationship between inadequate light

and plant death.

Just as with light and plants, a low

SSF is not the only thing that is needed

for a rollover and a rollover may occur

even if a vehicle has an excellent SSF,

but there is a causal relationship

between SSF and rollover. At the

initiation of either tripped or untripped

rollover, the moment arm for the

principal overturning force is the c.g.

height, and the moment arm of the

principal restoring force is the track

width divided by two. In the case of

tripped rollover, the severity of the

impact with a tripping mechanism

determines the principal overturning

force. Depending on the circumstances,

roll moment of inertia, suspension

deflections, tire properties and other

vehicle properties influence rollover—

but never to the exclusion of c.g. height

and track width. Among the many

causal factors included in mathematical

models of various rollover scenarios,

c.g. height and track width are always

present and usually exert the most

influence.

While the vehicle properties

represented by SSF, TTR, SPR and CSV

are directly and causally related to

vehicle rollover, that alone does not

prove that the vehicle properties exert

enough influence to be noticed in the

context of the driver and roadway

variables. Especially in the context of

tripped rollover, the circumstances of

the crashes and the nature of the

tripping mechanisms may be nearly

unique from crash to crash. Examination

of a large number of crashes may be

necessary to detect even powerful

influences with any degree of certainty.

Statistical correlation of the metrics to

the rate of rollover occurrences of

representative vehicles in actual crashes

is the usual method of determining their

influence. The agency has demonstrated

significant correlations between SSF,

TTR and CSV and the rate of rollovers

35010 Federal Register / Vol. 65, No. 106 / Thursday, June 1, 2000 / Proposed Rules

17 Ibid.

18E.A. Harwin and Howell K. Brewer; ‘‘Analysis

of the Relationship between Vehicle Rollover

Stability and Rollover Risk using the NHTSA

CARDfile;’’ NHTSA, 1989.

per single-vehicle crash in past studies

of the crash reports recorded by

particular states.17,18 The agency has

consistently found that given a singlevehicle crash, the SSF, TTR or CSV of

the vehicle is a good statistical predictor

of the likelihood that it will roll over.

The number of single-vehicle crashes

has been used as an index of exposure

to rollover because it eliminates the

additional complexity of multi-vehicle

impacts and because about 82 percent of

light vehicle rollovers occur in singlevehicle crashes.

The statistical study described in the

Appendix to this notice was undertaken

to develop a relationship between SSF

and rollover rate representative of the

whole country rather than a particular

state. The average rollover/singlevehicle crash rate varies from state to

state because of differences in reporting

thresholds for single-vehicle crashes

and real differences in road conditions,

vehicles and drivers. A relationship

between rollover rate and SSF

normalized to the national rollover rate

and to a nationally representative set of

driver and road use variables was

developed as a basis for a comparative

rating system for rollover risk in the

event of a single-vehicle crash. We had

available crash reports of 185,000

single-vehicle crashes from six states

from 1994 to 1997 in which it was

possible to determine the make/model

of the vehicles and whether rollover

occurred in the course of a singlevehicle crash, and for which SSF data

were also available. We also had the

NASS GES data sampling system, with

far fewer but nationally representative

crash reports, to determine the national

average rollover rate for the population

of vehicles investigated in the state

reports.

The study of state reports of singlevehicle crashes was performed as a

regression analysis, in which the square

of the coefficient of regression (the R2

statistic) indicates the degree to which

the differences between the data

samples can be explained by the

independent variables. In this case, the

R2 calculated for the rollover rates of

about 100 vehicle make/models as a

function of SSF ranged from 0.53 to 0.76

across the states. This means that

between 53 percent and 76 percent of

the differences in rollover rate of the

subject vehicles can be explained by

differences in SSF.

However, an analysis using only SSF

does not preclude the possibility that

cross correlations of SSF with other

factors could create a level of correlation

beyond the causal relationship of SSF to

rollover. For example, if the drivers of

vehicles with low SSF were generally

more aggressive, the degree of

correlation could be raised by the

greater chance of these vehicles leaving

the road at high speed. Likewise, if

vehicles in a particular range of SSF

were operated more often than others on

poor road surfaces, their exposure to

tripping mechanisms as well as their

rollover resistance would be reflected in

a correlation with SSF. Because of the

possibility that the apparent influence

of SSF on rollover could be due in part

to cross correlations, the agency also

performed a stepwise regression

analysis in which the available variables

describing driver and road

characteristics were given the first

opportunity to explain the differences

among vehicles in rollover rate. In this

analysis, cross correlations would

reduce the apparent influence of SSF

because part of its effect would have

already been included in a cross

correlated driver or road variable. The

driver and road use characteristics

recorded in the crash reports of the

various states included gender, age,

alcohol involvement, number of

occupants, day or night, stormy

weather, road speed limit over 50 mph,

bad road or road surface, rural location,

curve, and hill. When only the driver

and road use variables, but not the SSF,

for each vehicle were considered, it was

found that their cumulative information

could explain between 53 and 69

percent (differing with State) of the

variability between vehicles in rollover

rate. When SSF was added to the

available driver and road characteristics,

the explanatory power of the

information increased to between 85

and 90 percent. The addition of SSF

explained between 64 and 80 percent of

the variability remaining after

consideration of the driver and road

variables.

The six-state model that included all

185,000 single-vehicle crashes yielded

similar results. When only the SSF of

the vehicles is considered (with a

correction for systematic differences

between States) the R2 statistic was 0.73;

when the driver and road variables

rather than SSF were entered, the R2

statistic was 0.58; and when the SSF

was added to the driver and road

variables R2 statistic rose to 0.88. In the

direct correlation, SSF appeared to

explain about 72 percent of the

variability in rollover rate between crash

experiences of about 100 vehicle/make

models in six states. If cross correlations

between the vehicle SSF and driver and

road variables cause the direct

correlation to be optimistic, the same

cross correlations would diminish the

apparent influence of SSF in the

stepwise regression in which the driver

and road variables alone were entered

first. However, SSF remained influential

in the stepwise regression with the

power to explain 72 percent of the

remaining variability after the entry of

the driver and road use variables. (Note:

The similarity of 72 and 73 percent in

the two analyses is merely a

coincidence. While 73 percent is the R2

statistic in the direct correlation, 72

percent is the ratio (0.88¥0.58)/

(1.0¥0.58) in the stepwise analysis.)

Rollover is a very complex event,

heavily influenced by driver and road

characteristics as well as vehicle

properties. The most important nonvehicle variable may be the speed at

which the vehicle leaves the roadway,

for which some of the driver and road

use variables are only broadly

indicative. However, the directly causal

influence of SSF is sufficient to explain

a large portion of the variability among

vehicles in real-world crash experiences

in either a direct correlation or stepwise

analysis of the variability remaining

after consideration of driver and road

use variables. It is not lost in the noise

of complex circumstances, and its

explanatory power exceeds the

cumulative explanatory power of all

other available driver and road use

variables in most instances.

The same analyses using TTR or CSV

would be expected to yield similar

results based on past agency studies. In

fact, CSV might show slightly higher

correlations because most rollovers are

tripped. However, the choice of a rating

metric was not made simply for

incremental gains in R2 among metrics,

since each one provides a high level of

correlation to rollover crash rates. The

simplicity and generality of SSF have

value in a rating system intended for

consumers. In addition, there is only

modest room for improvement over a

metric which already explains 73

percent of the variability in rollover

rates left after application of driver and

road use variables.

In some analyses, the inclusion of

wheelbase, which is simple, improves

the correlation coefficient. Wheelbase

has not been included here because,

unlike the components of SSF, it does

not have a direct causal relationship

with rollover. It may be a surrogate for

roll moment of inertia, yaw moment of

inertia, or pitch moment of inertia, each

of which may influence rollover in

Federal Register / Vol. 65, No. 106 / Thursday, June 1, 2000 / Proposed Rules 35011

19Heydinger, G.J., et al; ‘‘Measured Vehicle

Inertial Parameters—NHTSA’s Data through

November 1998;’’ Society of Automotive Engineers

1999–01–1336; March, 1999.

certain circumstances. Alternatively,

wheelbase may be a surrogate for owner

demographics within certain vehicle

classes. We have chosen not to include

factors which correlate to rollover

through cross correlation to other

undefined factors.

D. Simplicity and Measurability

The principle of SSF is obvious. The

fact that an object which is more top

heavy or narrower at its base can be

turned over more easily is encountered

repeatedly in common experience and is

intuitive for most consumers. Track

width is a straightforward dimensional

measurement which can be measured

very accurately given sufficient care,

and special fixtures and calipers can be

constructed to make the task easy. In

past comments to the agency, lack of

repeatability of c.g. height measurement

between various labs was cited.

However, improvements in equipment

and technique have taken place. The

agency’s own lab and a contractor using

similar equipment report errors no

greater than one half of one percent in

c.g. height measurement of vehicles.19

Tilt Table measurements expressed

either as TTR or TTA also have the

advantage of accuracy and relative ease

of measurement. The process of tilt table

measurement should make intuitive

sense to the public, but the conversion

from an angle to a trigonometric ratio

may not. The reporting of the angle is

less complicated, but it creates a nonlinear measurement that does not

increase as rapidly as the actual

improvement of rollover resistance

expressed in TTR.

CSV would be easier for the public to

understand were it the result of a full

scale vehicle test rather than the

computation of a simplified model.

While the public should understand

track width and c.g. height, the

additional concept of roll moment of

inertia is outside common experience.

The simplified model also results in

CSVs that are unrealistic in absolute

value, though useful for comparison of

vehicles. The computation predicts that

lateral speeds of 10 to 15 mph are

sufficient for tripped rollover of

virtually all light vehicles from large

cars to compact SUVs. The low

threshold may not appear to be credible

to consumers who have experienced

hard curb contact with only wheel and

tire damage and may trivialize the

information by causing consumers

without such experience to conclude

that all vehicles will turn over so easily

that differences between vehicles are

not worth consideration.

In fact, the lateral speeds for tripped

rollovers of actual vehicles in common

circumstances would always be greater

than the computed CSV. Instead of

being available to raise the vehicle’s c.g.

to the rollover point, much of the

kinetic energy from the vehicle’s lateral

speed would be dissipated by tire

contact with the ground, stored or

dissipated in tire and suspension

deflections, and dissipated in the

permanent deformation of vehicle

suspension components and of the

tripping mechanism. The calculation of

CSV requires a measurement of roll

moment of inertia in addition to the

measurements needed to calculate SSF,

but that is not an obstacle. The agency’s

own lab and a contractor using similar

equipment report errors no greater than

two percent in roll moment of inertia

measurements of vehicles.

Side Pull Ratio has intuitive appeal if

one can understand that the inertial

forces which cause tripped or untripped

rollover can be represented by forces

applied in a laboratory with a cable

pulling at the c.g.. However, it is

difficult to coordinate the movement of

the outboard end of the cable with

vehicle roll motion and to avoid

applying extraneous vertical forces. For

this reason SPR is often estimated from

SSF with modifying factors for the roll

stiffness of the vehicle and its general

suspension type.

The simplicity and relative ease of

measurement of SSF and TTR are

advantageous for consumer information.

E. Unintended Consequences

In comments to the 1992 ANPRM on

rollover issues, several manufacturers

pointed out that some changes that

could improve a vehicle’s tilt table

performance may degrade its control

and handling attributes. Aspects of

suspension design, such as choices of

front to rear roll stiffness ratio and

overall roll stiffness, could be different

from those now chosen to balance ride

quality, handling, tire wear and other

important features if they were

influenced by a desire to maximize TTR.

Commenters to the same docket claimed

that measurements of c.g. height were

difficult and not repeatable in

comparison to the tilt table

measurement.

These comments presented the agency

with a dilemma. The most practical

rollover resistance metric from a

measurement viewpoint, TTR, had the

potential to introduce new trade-offs for

suspension designers. Obviously, the

agency does not want vehicle

manufacturers to depart from designs

which they believe optimize safe

handling and directional control.

Improvements in the methods of

measuring the c.g. height of vehicles

have occurred that resolve the concerns

raised in the comments. SSF is now as

practical and repeatable a measurement

as TTR.

Changes in track width or c.g. height

to improve SSF do not require trade-offs

of handling and control. In general,

those particular changes would make it

easier to achieve good handling. A

potential trade-off discussed in the

agency’s 1987 denial of a rulemaking

petition for a minimum level of SSF was

the possibility of manufacturers

reducing the strength of the upper

structure of vehicles in order to lower

the c.g.. At that time, FMVSS No. 216

on roof crush resistance did not apply

to SUVs, vans or pickup trucks.

Beginning with the 1995 model year, the

roof crush resistance of light trucks

including SUVs and vans has been

included in the regulation, making that

potential choice to compromise safety

even less likely.

VI. Why Not a Standard?

The action contemplated by this

notice follows a decision by the agency

(59 CFR 33254) to terminate rulemaking

on a minimum standard for rollover

resistance and to pursue the consumer

information approach instead. In the

analysis leading to that decision, the

agency concluded that both Tilt Table

Angle and Critical Sliding Velocity were

causally related to rollover and had a

strong statistical relationship to rollover

frequency. However, the benefits

achieved by setting a minimum level for

a rollover metric, even well beyond that

of truck-based SUVs or full size vans,

were not great enough to compel the

costs of fundamental vehicle changes

and the loss of attributes desired by

customers. Also the redesign could

result in the elimination of some classes

of vehicles, such as compact SUVs.

The above conclusions about a

general rollover standard recognized

that most rollovers are tripped. The

circumstances of tripped rollover

usually involve leaving the road surface

unintentionally and hitting a tripping

mechanisms such as a curb, a ditch or

soft soil. There is a nearly infinite

variety of tripping mechanisms and

ways in which vehicle can strike them.

Basic changes in the geometric

properties of vehicles, as reflected in

SSF, TTA, and CSV, are necessary for

realistic improvements in tripped

rollover resistence. However,

improvements in on-road untripped

rollover performance may not require

35012 Federal Register / Vol. 65, No. 106 / Thursday, June 1, 2000 / Proposed Rules

geometric changes at odds with the

attributes consumers seek in certain

classes of vehicles. While tripped

rollover is much more common than

untripped rollover, there is public

concern about the danger of untripped

rollover. The agency remains interested

in the possibility of a minimum

performance standard to address the

problem of untripped on-road rollover.

Its seeks comment on the need for a

standard addressing on-road untripped

rollover and requirements that may be

appropriate for such a standard.

The analysis of benefits in the 1994

notice to terminate rulemaking for a

minimum standard was concerned

primarily with tripped rollover. The

expected benefits of a potential

minimum standard were based on a

logistic regression analysis of the

sensitivity of rollover risk in singlevehicle crashes to changes in rollover

resistance metrics. Rollover metrics

such as TTA, CSV, and SSF are relevant

to tripped rollover. The outcome of each

crash in a data base of 90,000 singlevehicle crashes reported by the state of

Michigan was re-evaluated individually

changing the rollover resistance metric

but retaining the other vehicle, driver,

and road characteristics of the actual

crashes. The result was a set of

predictions by vehicle class of the

sensitivity of rollover rate to

incremental changes in the rollover

resistance metric, while preserving the

potentially influential demographic and

environmental factors associated with

actual crashes of vehicles in particular

classes. The percent improvement in

rollover rate for a vehicle class was

determined from the production

volume, single-vehicle crash rate, and

amount of change in the rollover

resistance metric demanded by a

potential standard for the vehicles in

that class. The benefits were calculated

from the reduction in rollover rate for

the vehicle class, the total number of

fatalities and injuries occurring in

vehicles of that class, and the degree of

harm mitigation accomplished when a

crash is prevented from becoming a

rollover crash.

Rollover prevention was not

considered crash prevention but rather

a reduction in the severity of crashes by

52 percent in fatalities and 25 percent

in injuries. The mitigation value of

rollover prevention was estimated by

comparing the harm to occupants in

single vehicle crashes with and without

rollover in the NASS database for the

years 1988–91.

Note that the demographic variables

are handled differently for estimating

the sensitivity of rollover risk to vehicle

metrics for analyses of a minimum

standard versus consumer information.

In the case of a minimum standard, it is

assumed that the driver and roadway

demographics of a vehicle class remains

unchanged but that the vehicle metric of

some vehicles in the class changes. In

the case of consumer information, the

rollover risk of all vehicles is estimated

using the same set of average

demographic variables because

individual consumers do not change

their age, gender or driving environment

as a result of vehicle choice.

At a minimum TTA of 46.4 degrees

(equal to a TTR of 1.05 and equivalent

to a minimum SSF of about 1.18),

reductions of 63 fatalities and 61 serious

injuries were estimated. No standard

van and few, if any, compact SUVs with

permanent top structures could meet

that hypothetical standard, and a third

to a half of compact pickups, minivans

and standard full size SUVs were found

to be unable to meet it. A parallel

analysis using CSV instead of TTA

yielded similar results except that

standard vans were unaffected because

their large roll moments of inertia

improve CSV. Most of the benefits were

calculated on the basis of increasing the

rollover resistance of some compact

pickups and many compact SUVs on the

order of 10 percent of the TTR.

Changes in c.g. height or track width

of vehicles to increase rollover

resistance by 10 percent are substantial

and compromise some of the attributes

consumers desire. For example, a 10

percent increase in track width (which

would increase TTR about equally) is

nearly 6 inches for a typical compact

SUV. Substantial chassis changes would

be required to accomplish that large an

increase in track width, and body

changes would be necessary to cover the

wheels. These changes would tend to

narrow the size distinction between

compact and standard SUVs. Similarly,

lower c.g. heights reduce ground

clearance and possibly the size of

objects that may be hauled. Vehicles

actually designed for off-road driving

where narrow width and high ground

clearance is necessary would be

eliminated by minimum requirements

for TTA, SSF or CSV found to have even

modest benefits. Compact SUVs with

enough ground clearance to negotiate

roads with unplowed snow would likely

have to be redesigned for greater width.

The agency decided instead to pursue

a consumer information program to

enable consumers to make informed

choices about the tradeoffs in vehicle

attributes, such as high ground

clearance, and rollover resistance. It

would inform drivers of the general

difference in rollover resistance between

light trucks and cars and among

vehicles within the various classes.

Consumers who need or desire a

particularly high cargo space or off-road

driving adaptations such as a large

amount of ground clearance and narrow

track width would not be denied the

chance to purchase such vehicles.

However, consumers who choose

vehicles with relatively low rollover

resistance would do so with knowledge

of that fact, something that is not true

today. The consumer information

program would also inform drivers who

choose vehicles with less rollover

resistance that their risk of harm can be

greatly reduced with seat belt use to

avoid ejection. In addition, NHTSA

believes that a consumer information

program would serve as a market

incentive to manufacturers in striving to

design new vehicles with greater

rollover resistance.

As explained above, NHTSA has

previously decided that it will not set a

vehicle rollover standard at a level that

would effectively force nearly all light

trucks to be redesigned to be more like

passenger cars (in the 1987 denial of the

Wirth petition, 52 FR 49033). NHTSA

has also previously decided that we will

not set a vehicle rollover standard at a

level that would effectively force a

redesign of some vehicle types like

small pickups and small sport utility

vehicles (in the 1994 termination of

rulemaking to establish a minimum

vehicle standard for rollover resistance

based on TTA or CSV, 59 FR 33254).

Even though we cannot justify

prohibiting the manufacture and sale of

these vehicles, we are now proposing to

provide the public with accurate and

meaningful information about the

rollover resistance of these vehicles and

allowing the public to make fully

informed choices when selecting a new

vehicle.

Some have previously argued that

NHTSA cannot and should not provide

consumer information about the relative

performance of vehicles until the agency

has first established a minimum

performance standard for performance

in that area. The implicit underpinning

of this argument is that the American

public deserves the protection of a

minimum performance standard if

NHTSA can show that performance in

an area is sufficiently related to on-road

safety performance. Only after the

agency has established a minimum

performance standard, according to this

argument, can NHTSA supplement the

standard with consumer information if

additional measures are needed.

Whatever the merits of this position

generally, NHTSA does not find this

argument persuasive in the context of

light vehicle rollover. Following this

Federal Register / Vol. 65, No. 106 / Thursday, June 1, 2000 / Proposed Rules 35013

position, NHTSA must devote time and

resources to establish a minimum

standard for SSF. Given the agency’s

previous conclusions about standards

that eliminate classes of light trucks, the

standard would likely be set at a level

that would not effectively eliminate

recognized vehicle types. Thus it would

have to be set at a level that small

pickups and small SUVs could meet.

Such a standard would have extremely

small benefits. After the rulemaking for

this minimal-benefit standard was

complete, NHTSA could then try to

develop a meaningful consumer

information program along the lines laid

out in this request for comments. The

effect of the minimal-benefit rulemaking

appears to be primarily to delay giving

the American public meaningful

rollover information. However,

commenters who advocate this

approach are invited to clarify why they

believe such an approach is appropriate

in the context of rollover and how this

approach would serve the safety

interests of the American people.

NHTSA agrees that it has a high

burden when it proposes to establish a

program for relative consumer

information in an area where the agency

has not established a minimum safety

standard. In the case of light vehicle

rollover, however, we believe there is a

compelling case to provide SSF as

consumer information. The physics of

SSF and its causal relationship to

rollover are indisputable. SSF is not an

untried approach that NHTSA has just

discovered in some research. Instead,

the formula for calculating SSF is wellknown and widely-accepted. Each of the

manufacturers with which NHTSA has

discussed light vehicle rollover said that

they know the SSF for each of the

vehicles they manufacture. The

correlation of SSF to rollovers per single

vehicle crash is remarkably robust in an

area as complex as rollover, as detailed

in the Appendix to this notice. When

the science suggests a causal

relationship between a vehicle metric

and a safety problem, real world data

confirm that relationship, the metric

that will be provided as consumer

information is already in general use by

the industry, and can be repeatably

measured at different facilities, we

believe that information ought to be

shared with the American people to

allow them to make informed purchase

decisions regardless of whether the

vehicle metric is also part of a minimum

safety standard. Again, public comment

is requested on this position.

VII. Consumer Information

Presentation

A. How Consumers Want To See

Information Displayed

Eighty percent of respondents to a

1997 NHTSA survey felt that

comparative safety ratings of motor

vehicles should be available to the

public. Therefore, we assume that

consumers would be interested in

comparative rollover information. In

April 1999, we conducted a series of six

focus groups to examine ways of

presenting comparative rollover

information. Two focus groups were

conducted in each of three locations:

Dallas, Texas; Overland Park, Kansas (a

suburb of Kansas City); and Richmond,

Virginia.

Our study found that:

• Participants underestimated the

size of the rollover problem and were

surprised when informed of the actual

size.

• Participants enthusiastically

supported the idea of having rollover

information available in both point-ofpurchase (label) and brochure formats.

• Among the options presented,

participants were most comfortable with

ratings based on stars.

• Participants also agreed that a

graphic showing a tilted car would be

the clearest in conveying the message of

rollover and would have the most

impact on purchasers.

We have placed the complete focus

group report in the docket for interested

parties. While the focus group results

support use of either stars or a tilting

vehicle graphic to represent the ratings,

NHTSA is considering the use of stars.

Stars are already used for the front and

side NCAP ratings, and thus use of stars

for rollover would be consistent.

B. Converting SSF Measurements to Star

Ratings

Since the consumer focus groups

recommended a simple representation

of comparative risk using stars, we have

devised a procedure to rank vehicles for

rollover risk and assign stars based on

the statistical study described in the

Appendix, which estimated the

relationship between the SSF of a

vehicle and the incidence of rollover in

single-vehicle crashes (82 percent of

rollover crashes are single-vehicle

crashes).

To repeat, any vehicle can be made to

roll over if it strikes an effective tripping

mechanism at a great enough lateral

speed. The combinations of conditions

in real-world single-vehicle crashes are

limitless. Some conditions are so severe

that any vehicle would roll, and others

would not trip even the least stable

vehicle. Nevertheless, when a statistical

sample of real-world crashes is taken, it

is clear that vehicles with a low SSF roll

over more frequently than those with a

high SSF despite the unique

circumstances of individual crashes.

The observed rollover rate for a

particular make/model in the statistical

study was not included unless it was

based on at least 25 single-vehicle

crashes in a particular state, and it

received less weighting unless it was

based on at least 250 single-vehicles

crashes in that state. Likewise, the

adjustment of individual vehicle

rollover rates to a common demographic

base in estimating the risk relationship

with SSF was a step to reduce the

influence of the variety of conditions in

single-vehicle crashes.

The result of the study was an

equation relating the SSF to the

estimated number of rollovers per

single-vehicle crash, after accounting for

differences in driver, road and

environmental factors. This estimate of

rollovers per single-vehicle crash

represents the risk of rollover given a

single-vehicle crash:

Estimated rollovers per single-vehicle crash =

13.25 * e(¥3.3731 * SSF).

The computation of SSF at

meaningful increments of estimated

rollover risk, using this equation, offers

a basis for a star rating. The risk of

rollover indicated by the star rating

pertains to the likelihood of rollover in

the event of a single vehicle crash of

sufficient severity to cause a police

report. It broadly estimates the risk, per

event, of a single vehicle crash

becoming a rollover; it is not a measure

of the risk of rollover over the life of the

vehicle. We are defining the rating

intervals as follows:

ONE STAR (★): Risk of Rollover 40

percent or greater is associated with SSF

1.04 or less.

TWO STARS (★★): Risk of Rollover

greater than 30 percent but less than 40

percent is associated with SSF 1.05 to

1.12.

THREE STARS (★★★): Risk of

Rollover greater than 20 percent but less

than 30 percent is associated with SSF

1.13 to 1.24.

FOUR STARS (★★★★): Risk of

Rollover greater than 10 percent but less

than 20 percent is associated with SSF

1.25 to 1.44.

FIVE STARS (★★★★★): Risk of

Rollover less than 10 percent is

associated with SSF 1.45 or more.

The relationship between SSF and

rollovers per single vehicle crash which

is reflected in the star ratings above was

derived by the statistical method

described in the Appendix to best

35014 Federal Register / Vol. 65, No. 106 / Thursday, June 1, 2000 / Proposed Rules

20Under this proposal the actual measurement,

not a star ranking, would have been reported on the

label, along with the range of data from all

manufacturers for cars and for light trucks, so the

consumer could see where each vehicle fell in range

of available choices.

estimate the national trend between

rollover risk and SSF. The relationship

appears to be constant over the four

years of state crash data analyzed, but

the agency intends to continue to

monitor it as newer crash data becomes

available. Should changes in road

conditions, demographics, or vehicles

alter the relationship, the levels of risk

associated with the star ratings would

be adjusted.

The rollover ratings should be

distinguished from the frontal and side

crash star ratings. The present star

ratings are measures of the

crashworthiness of the body structure

and restraint systems of a vehicle in the

event of a frontal or side crash. The

rollover risk rating does not pertain to

the crashworthiness of the vehicle in a

rollover crash. Instead, it estimates the

likelihood that a rollover will occur in

the event of a single vehicle crash. The

majority of rollovers occur in single

vehicle run-off-the-road crashes, and the

majority of deaths in rollover crashes

are the result of ejection from the

vehicle. The frontal and side crash

ratings are direct estimates of the

probability of serious injury in those

types of crashes. The rollover star rating

will estimate the probability of a single

vehicle crash becoming a rollover, but

the probability of a serious or fatal

injury in a rollover depends heavily on

the occupant’s decision to protect

himself or herself against ejection

through the use of seat belts.

Like frontal and side NCAP ratings,

the rollover rating is concerned with

vehicle attributes that affect the

outcome of a crash. None of the ratings

attempt to describe the probability of a

vehicle’s involvement in crashes in the

first place. It can be argued that vehicles

with anti-lock brakes are less likely to

have frontal crashes, but that possibility

does not alter the frontal

crashworthiness star rating. Likewise, it

may be argued that short wheelbase

vehicles are more likely to be involved

in single vehicle run-off-the-road

crashes, but that possibility would not

alter the star rating of the probability of

a rollover given the event of a single

vehicle crash. Stability control and

other advanced vehicle systems are

being developed to reduce the instances

of loss of control which can cause runoff-the-road crashes. However, such

advanced systems would not affect the

probability of rollover in those single

vehicle run-off-the-road crashes still

occurring even with those systems, and

would not affect the rollover star rating

given a vehicle. While the effectiveness

of stability control technology in crash

reduction is presently unproven, its

potential is of great interest. If stability

control technologies are proven to have

a significant effect on the exposure of

vehicles to off-road crashes, we would

consider adding information about the

equipment to the presentation of the

rollover information. Commenters are

invited to share any data they may have

on the effectiveness of these stability

control technologies in preventing

single vehicle crashes.

Of course, as in all NCAP information,

the numerical measurements as well as

the star interpretation of risk would be

available to consumers. The NAS study

recommended that NHTSA provide

consumer information in a hierarchy of

detail, so consumers can find

information at the level they are

comfortable with. In addition, various

focus groups have suggested that

making the more detailed information

available increases consumer

confidence in the ratings, even if the

consumer does not actually use the

information.

VIII. Rollover Information

Dissemination Through NCAP

A. Why NCAP Rather Than Vehicle

Labeling?

In the 1994 NPRM the agency

proposed a consumer information

regulation for rollover. The proposal

called for each new vehicle to be labeled

with information about its rollover

resistance and information about the

range of rollover resistance for cars and

light trucks. This regulation would have

mandated participation of the vehicle

manufacturers. The testing and labeling

would have been done by the

manufacturers, and associated costs

borne by them. Manufacturers would

have been required to report a rollover

resistance metric (TTA and CSV were

discussed in the proposal) for each

make/model to NHTSA by January 1 of

each year. Manufacturers would decide

how to group vehicle models for

reporting. NHTSA would mandate a

specific test procedure and accuracy

tolerance for reported data, to prevent

either over- or understatement of the

rollover metric. NHTSA would then

receive and process the information

reported by the manufacturers to

provide the manufacturers with the

ranges of metrics for cars and for light

trucks by April 1.20

By September 1 each year all new

vehicles would have been required to

have a window sticker showing this

rollover information. Again, the format,

location, and language of the label

would have been set forth by regulation.

The regulation would also have required

specific information about rollover to

appear in each vehicle owner’s manual.

The agency estimated, in 1994, that

the costs to manufacturers associated

with this mandatory program would be

between 3.93 and 6.35 million dollars,

depending on which specific vehicle

metric was required. These costs would

come from generating the metric for the

labels, printing the labels and affixing

the labels to the vehicles.

The advantage of a vehicle labeling

requirement is that the information is

provided to all consumers without the

need to ask for it. This advantage was

reflected in the focus group study.

However, the labeling of vehicles with

one safety attribute to the exclusion of

others may be misleading. Also, using a

label listing a single-vehicle safety

attribute would be contrary to the

principles of the NAS study on

consumer information that the agency

was directed to consider. That 1996

study recommended the development of

an overall measure of vehicle safety.

Until that goal can be met, the

presentation of our proposed measure of

rollover risk, in the context of our

established measures of frontal and side

impact crashworthiness in NCAP,

would, in our opinion, go a long way

toward addressing NAS’s concern for

presenting overall vehicle safety. It also

provides some practical advantages:

• Implementation would be faster.

The program would be able to start

almost immediately, so consumers

would have the information sooner.

• NHTSA retains control of vehicle

measurement so the consumer will

know exactly which vehicle model/

equipment combination was tested.

• It takes advantage of the existing

NCAP organization within NHTSA

equipped to perform vehicle tests and

disseminate consumer information and

avoids the need for a compliance

function within NHTSA to collect and

process manufacturers’ test reports and

provide to manufacturers the vehicle

ranges required on the labels.

While we believe NCAP is the most

immediate, inexpensive, and efficient

way to get rollover information to the

consumer, we would like to receive

comments from the public on the merits

of this type of program as compared to

labeling individual vehicles so that

consumers receive the information at

the point of sale. NHTSA, in partnership

with AAA, distributes approximately

600,000 Buying a Safer Car brochures

annually. Buying a Safer Car provides

NCAP ratings and other safety feature

Federal Register / Vol. 65, No. 106 / Thursday, June 1, 2000 / Proposed Rules 35015

information for new models. In

addition, NHTSA gets approximately

22,000 visitors per week (or

approximately a million visitors a year)

to the web site location for the NCAP

ratings.

B. Addition of Rollover Stability Stars to

NCAP

The agency has tentatively decided to

go forward with a pilot consumer

information program on vehicle rollover

resistance, using the SSF as a basis for

the rating system. This program would

be part of NCAP, which currently gives

consumers information on frontal and

side-impact crashworthiness. We hope

to have the pilot rollover information

program ready for the 2001 model year.

The rollover information program

would operate very much as the current

NCAP does today. New models would

be selected for testing before the

beginning of the model year. Selection

would be based primarily on production

levels predicted by the manufacturers

and submitted to the agency

confidentially. Consideration would

also be given to vehicles scheduled for

major changes, or new models with

specific features that may affect their

SSF’s. The vehicles chosen for NCAP

testing would be procured and

measured by NHTSA as the vehicles

become available. Vehicles would be

procured with popular equipment,

typical of a rental fleet, and the

equipment with possible influence on

SSF would be included in the vehicle

description. Two wheel drive and four

wheel drive versions of a vehicle would

be treated as separate models because a

four wheel drive option can have a

significant effect on SSF. As provided

for in the present NCAP, manufacturers

can, at their option, pay for tests of

vehicles, models or configurations not

included in NHTSA’s test plan if they

wish to inform consumers through the

program. (Vehicle purchase and testing

is done by a NHTSA-approved testing

laboratory.) The SSF would be

converted to a ‘‘star’’ rating according to

the curve presented earlier. The rollover

‘‘star’’ information would be published

by NHTSA and placed on the agency’s

web site. The brochures and the web

site presentation would explain the

basis of the ratings, make available the

SSF measurements, and discuss the

magnitude of rollover harm prevention

provided by safety belt use.

As part of the presentation on rollover

in NHTSA brochures and on our web

site, we will include explanatory

language for consumers. The following

two paragraphs are illustrative of the

information that would be presented:

Rollover is a very complex event, heavily

influenced by driver and road characteristics

as well as the design of the vehicle. Most

rollovers occur when a single vehicle runs off

the road and is tripped by a ditch, soft soil,

a curb or other object. The speed at which

the vehicle leaves the roadway is always

important to the risk of rollover. The NCAP

rating is based on Static Stability Factor,

essentially a measure of how ‘‘top heavy’’ a

vehicle is. Static Stability Factor can be used

to predict the risk of rollover in the real

world. In fact, a statistical study of 185,000

single vehicle crashes in six states involving

100 popular vehicle models confirmed Static

Stability Factor’s relationship to the actual

occurrence of rollover crashes. Vehicles with

greater Static Stability Factors are less ‘‘top

heavy’’ and are awarded more stars in

proportion to their reduced risk of rollover in

the event of a single-vehicle crash.

Regardless of vehicle choice, the consumer

and his or her passengers can reduce their

risk of being killed in a rollover crash

dramatically by simply using their seat belts.

Seat belt use has an even greater effect on

reducing the deadliness of rollover crashes

than on other crashes because so many

victims of rollover crashes die as a result of

being partially or fully thrown from the

vehicle. NHTSA estimates that belted

occupants are about 75% less likely to be

killed in a rollover crash than unbelted

occupants.

IX. Rulemaking Analyses and Notices

Executive Order 12866

This request for comment was not

reviewed under Executive Order 12866

(Regulatory Planning and Review).

NHTSA has analyzed the impact of this

request for comment and determined

that it is not a ‘‘significant regulatory

action’’ within the meaning of Executive

Order 12866. The agency anticipates

that providing information on rollover

risk under NHTSA’s New Car

Assessment Program would impose no

regulatory costs on the industry.

X. Submission of Comments

A. How Can I Influence NHTSA’s

Thinking on This Document?

In developing this document, we tried

to address the concerns of all our

stakeholders. Your comments will help

us improve this notice. We invite you to

provide different views on options we

propose, new approaches we have not

considered, new data, how this

document may affect you, or other

relevant information. We welcome your

views on all aspects of this document,

but request comments on specific issues

throughout this document. We grouped

these specific requests near the end of

the sections in which we discuss the

relevant issues. Your comments will be

most effective if you follow the

suggestions below:

• Explain your views and reasoning

as clearly as possible.

• Provide solid technical and cost

data to support your views.

• If you estimate potential costs,

explain how you arrived at the estimate.

• Tell us which parts of this

document you support, as well as those

with which you disagree.

• Provide specific examples to

illustrate your concerns.

• Offer specific alternatives.

• Refer your comments to specific

sections of this document, such as the

units or page numbers of the preamble,

or the regulatory sections.

• Be sure to include the name, date,

and docket number with your

comments.

B. How Do I Prepare and Submit

Comments?

Your comments must be written and

in English. To ensure that your

comments are correctly filed in the

Docket, please include the docket

number of this document in your

comments.

Your comments must not be more

than 15 pages long. (49 CFR 553.21). We

established this limit to encourage you

to write your primary comments in a

concise fashion. However, you may

attach necessary additional documents

to your comments. There is no limit on

the length of the attachments.

Please submit two copies of your

comments, including the attachments,

to Docket Management at the address

given above under ADDRESSES.

Comments may also be submitted to

the docket electronically by logging onto

the Dockets Management System

website at http://dms.dot.gov. Click on

‘‘Help & Information’’ or ‘‘Help/Info’’ to

obtain instructions for filing the

document electronically.

C. How Can I Be Sure That My

Comments Were Received?

If you wish Docket Management to

notify you upon its receipt of your

comments, enclose a self-addressed,

stamped postcard in the envelope

containing your comments. Upon

receiving your comments, Docket

Management will return the postcard by

mail.

D. How Do I Submit Confidential

Business Information?

If you wish to submit any information

under a claim of confidentiality, you

should submit three copies of your

complete submission, including the

information you claim to be confidential

business information, to the Chief

Counsel, NHTSA, at the address given

above under FOR FURTHER INFORMATION

35016 Federal Register / Vol. 65, No. 106 / Thursday, June 1, 2000 / Proposed Rules

CONTACT. In addition, you should

submit two copies, from which you

have deleted the claimed confidential

business information, to Docket

Management at the address given above

under ADDRESSES. When you send a

comment containing information

claimed to be confidential business

information, you should include a cover

letter setting forth the information

specified in our confidential business

information regulation. (49 CFR Part

512.)

E. Will the Agency Consider Late

Comments?

We will consider all comments that

Docket Management receives before the

close of business on the comment

closing date indicated above under

DATES. To the extent possible, we will

also consider comments that Docket

Management receives after that date. If

Docket Management receives a comment

too late for us to consider it in

developing a final rule (assuming that

one is issued), we will consider that

comment as an informal suggestion for

future rulemaking action.

F. How Can I Read the Comments

Submitted by Other People?

You may read the comments received

by Docket Management at the address

given above under ADDRESSES. The

hours of the Docket are indicated above

in the same location.

You may also see the comments on

the Internet. To read the comments on

the Internet, take the following steps:

(1) Go to the Docket Management

System (DMS) Web page of the

Department of Transportation (http://

dms.dot.gov/).

(2) On that page, click on ‘‘search.’’

(3) On the next page (http://

dms.dot.gov/search/), type in the fourdigit docket number shown at the

beginning of this document. Example: If

the docket number were ‘‘NHTSA–

1998–1234,’’ you would type ‘‘1234.’’

After typing the docket number, click on

‘‘search.’’

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Please note that even after the

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Accordingly, we recommend that you

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G. Plain Language

Executive Order 12866 and the

President’s memorandum of June 1,

1998, require each agency to write all

rules in plain language. Application of

the principles of plain language

includes consideration of the following

questions:

• Have we organized the material to

suit the public’s needs?

• Are the requirements in the rule

clearly stated?

• Does the rule contain technical

language or jargon that is not clear?

• Would a different format (grouping

and order of sections, use of headings,

paragraphing) make the rule easier to

understand?

• Would more (but shorter) sections

be better?

• Could we improve clarity by adding

tables, lists, or diagrams?

• What else could we do to make the

rule easier to understand?

If you have any responses to these

questions, please include them in your

comments on this document.

Issued on: May 24, 2000.

Stephen R. Kratzke,

Associate Administrator for Safety

Performance Standards.

Appendix: Association Between SSF

and Rollover Risk Estimated From

Crash Data

A. Purpose of the Analysis

Our purpose is to describe the relationship

between the Static Stability Factor (SSF) and

the risk of rollover in single-vehicle crashes

given the average mix of road use

characteristics nationwide. We know that

environmental, road, and driver factors affect

rollover risk, and we suspect that vehicles

with low SSFs may tend to be used

differently than vehicles with high SSFs.

(Another way to describe this is to say that

SSF may be confounded with road use

characteristics.) For example, some vehicles

with a low SSF may tend to be used on

curved roads or by young drivers, and these

may be conditions that increase rollover risk.

Therefore, our description of the association

between the SSF and rollover risk will be no

better than our ability to remove the

confounding effects of differences in road

use.

B. Data Availability

To compare the performance of different

vehicle models, we need a large number of

single-vehicle crashes. The National

Automotive Sampling System (NASS)

provides good data, but NASS is limited to

towaway crashes and includes too few cases

for this type of analysis. The Fatality

Analysis Reporting System (FARS) includes

a large number of cases, but the restriction to

fatal crashes limits its use for comparisons of

rollover propensity. The General Estimates

System (GES) includes a large number of

cases of all crash severities, and these data

will be valuable when used in conjunction

with the larger volume of cases available in

the state crash files.

The agency routinely obtains crash files

from seventeen states as part of its State Data

System (SDS). We questioned whether a

single state could represent the national

experience (given state-to-state differences in

road use and reporting practices), so we

decided to use as many states as possible.

This allowed us to compare the results

among states and to combine the results to

produce our best national estimate of the

relationship between the SSF and rollover

risk. Participants in the SDS include nine

states that have the Vehicle Identification

Number (VIN) on their crash files; we will

call them the ‘‘VIN states’’ here. We need the

VIN to completely and accurately describe

the vehicle, and this is an essential part of

our analysis. We eliminated three VIN states:

Illinois (because we have not yet obtained the

1996 and 1997 data from this state) and New

Mexico and Ohio (because we know that a

rollover is recorded in these states only if the

police identify it as the first harmful event in

the crash). The 1994–1997 calendar year files

for the other six VIN states in the SDS

(Florida, Maryland, Missouri, North Carolina,

Pennsylvania, and Utah) are the basis of our

analysis. We used GES to verify and calibrate

the results obtained from the six state files,

but these six states include 26 times as many

cases as GES alone.

C. Determination of the SSF

The main criterion for selecting the

vehicles used in this analysis was the

availability of a reasonable estimate of the

SSF, and our goal was to include as many

vehicle models as possible. We started with

an existing compilation of all the SSF

measurements made by the agency through

1998, but limited the study vehicles to model

years 1988 and later. We added

measurements provided by the General

Motors Corporation (GM) for other vehicles,

but we limited these additions to passenger

cars and vans because the GM data did not

distinguish between two- and four-wheel

drive versions of pickup trucks and sport

utility vehicles. We used data from vehicles

tested with a single passenger when these

were available, and from zero- or twopassenger loading when one-passenger

loading was not available. A handful of SSF

values were imputed, as in the following

example: We assigned a late-generation fourwheel drive S-series Blazer (model years

1995 to 1998, for which we had no SSF

measurement) the same SSF as the two-wheel

drive version because there was no difference

in the SSF between the two- and four-wheel

drive versions in the earlier generation of that

model (model years 1983 to 1994).

The result was a list of a hundred vehicle

models (vehicle models tested by the agency,

identified by GM, or imputed as described

above). The list includes the following

number of vehicle models for each of four

light vehicle types: 36 cars, 30 sport utility

vehicles, 13 vans, and 21 pickup trucks. The

number of vehicle models in the study (a

Federal Register / Vol. 65, No. 106 / Thursday, June 1, 2000 / Proposed Rules 35017

21As described in our July 1991, Technical

Assessment Paper: Relationship between Rollover

and Vehicle Factors.

hundred) is a nice round number, but this

was not by design. Our goal was to include

as many models as possible, and one

hundred was the number that was possible.

D. Data Processing

We identified vehicles for which we had a

SSF value (including corporate cousins of the

tested vehicles) in the state and national

crash files based on the VIN and with the

help of the 1998 version of The Polk

Company’s PC VINA software. The list of

vehicle models used in the analysis is shown

as Tables A–1 through A–4; note that some

vehicle groups include more than one vehicle

model because the tested vehicles had

corporate cousins. We restricted the crash

data to single-vehicle events, which we

defined to exclude crashes with another

motor vehicle in transport or with a

nonmotorist (such as a pedestrian or

pedalcyclist), animal, or train. We eliminated

any vehicle without a driver and all vehicles

that were parked, pulling a trailer, designed

for certain special or emergency uses

(ambulance, fire, police, or military), or on an

emergency run at the time of the crash.

All the files we used include variables that

describe the conditions of the road and

driver, and these are useful for understanding

the risk of rollover. A detailed review of the

agency’s GES and SDS documentation

showed that the following information is

available for most of the six states and for

GES. The name of the variable created from

this information is shown in capital letters,

in parentheses:

(1) Did the vehicle roll over? (ROLL)

(2) Was it dark when the crash occurred?

(DARK)

(3) Was the weather inclement? (STORM)

(4) Did the crash occur in a rural area?

(RURAL)

(5) Was the speed limit 50 mph or greater?

(FAST)

(6) Did the crash occur on a grade, dip, or

summit? (HILL)

(7) Did the crash occur on a curve?

(CURVE)

(8) Were there potholes or other bad road

conditions? (BADROAD)

(9) Was the road wet or icy or have another

bad surface condition? (BADSURF)

(10) Was the driver male? (MALE)

(11) Was the driver under 25 years old?

(YOUNG)

(12) Was the driver uninsured?

(NOINSURE)

(13) Was drinking or illegal drug use noted

for the driver? (DRINK)

(14) How many occupants were in the

vehicle? (NUMOCC)

For each state and GES, we calculated the

following summary statistics for each of the

hundred vehicle groups in the study:

(1) Number of single-vehicle crashes

during these four years;

(2) Number of rollovers per single-vehicle

crash;

(3) Involvement of the following per singlevehicle crash (as available on each file):

DARK, STORM, RURAL, FAST, HILL,

CURVE, BADROAD, BADSURF, MALE,

YOUNG, NOINSURE, and DRINK; and

(4) Average number of occupants per

vehicle in these crashes.

We used these summary-level data

(summarized as counts and averages per

vehicle group) as the basis for our analysis.

Each summary record, representing a vehicle

model group, is a data point in our linear

regressions.

E. State-by-State Data Analysis

For each state, we limited the analysis to

vehicle groups with at least 25 single-vehicle

crashes. This threshold is somewhat

arbitrary, but it is the one we used in an

earlier analysis of single-vehicle crashes in

state data.21 There are two valuable results:

(1) There is at least one rollover for each

vehicle group included in the model, and (2)

there is no vehicle group for which every

single-vehicle crash resulted in a rollover.

That is, the rollover rate is greater than zero

and less than one for every vehicle group we

included in the study. We could have had as

many as 600 data points (six states, each with

up to 100 vehicle groups) for this analysis.

We actually had (because of the threshold for

inclusion) 481 data points, which represent

the experience of 184,726 single-vehicle

crashes. A similar restriction on the GES data

file produced 60 data points representing the

experience of 7,022 vehicles. The number of

vehicle groups available for our analysis and

the total number of single-vehicle crashes

represented by these groups are shown in the

first two data rows of Table A–5.

The number of rollovers per single-vehicle

crash varies by state (from a low of 0.127 for

Missouri to a high of 0.363 for Utah). There

are two major reasons for this variation: (1)

Real differences among the states in road

conditions, vehicles, and drivers, and (2)

state-to-state reporting differences (and, in

particular, the conventions for reporting

nonrollover, nontowaway crashes). However,

it is encouraging that the average number of

rollovers per single-vehicle crash for the

study vehicles was 0.198 for the six states

combined, which is the same as the

proportion estimated from GES for the same

vehicles and time period.

We performed a number of stepwise linear

regressions (using forward variable selection

and a significance level of 0.15 for entry and

removal from the model) on the individual

states as preparation for an analysis of the six

states combined. In each case, we modeled

the natural logarithm of the number of

rollovers per single-vehicle crash, LN(ROLL),

as a function of a linear combination of the

road, vehicle, and driver variables available

in that state’s crash file. We chose this

transformation for three reasons: (1) A visual

inspection of the data suggested that this

form describes the relationship between

rollover risk and the SSF better than a simple

linear fit, (2) this form was consistent with

our understanding of the process (we

expected the biggest differences in the

number of rollovers per single-vehicle crash

to occur at relatively low values of the SSF,

with diminishing effects for higher values of

the SSF), and (3) this transformation has

convenient mathematical properties. The

form of the model implies that arithmetic

changes in the SSF (for example, an

additional 0.01 in the value) are associated

with geometric changes in the number of

rollovers per single-vehicle crash (about 3

percent fewer rollovers observed per singlevehicle crash for any 0.01 increase in the

SSF, before accounting for differences in road

use).

We ran stepwise regression models using

the option that gives more weight to data

points that are based on more observations,

so vehicle groups with more crashes count

for more in the analysis. Each data point was

weighted by the number of single-vehicle

crashes it represented, but the weighting was

capped at 250. That is, data points based on

more than 250 observations were weighted

by 250. The weighting threshold is somewhat

arbitrary, but it was chosen because it is 10

times the threshold for inclusion in the

analysis. The rationale for weighting the data

for the regression is that data points based on

more observations are more reliable; the

rationale for capping the weights is that at

some point there are only marginal

improvements in our estimates, and we want

estimates that fit well over the entire range

of the data (that is, for low-SSF and for highSSF vehicles).

Florida can be used to illustrate our

procedure. There are 85 vehicle groups

available for our analysis, which represent

the experiences of 34,521 vehicles in singlevehicle crashes during 1994-1997. There

were 0.208 rollovers per single-vehicle crash

in these data. A weighted linear regression of

LN(ROLL) as a function of the SSF alone has

an R-squared of 0.7074, which means that the

SSF alone explains 71 percent of the

variability in the data. This suggests that the

SSF has great explanatory power for the

number of rollovers per single-vehicle crash,

but we are concerned that differences among

vehicle groups in the mix of road use

characteristics may be confounding the

relationship. Therefore, we also used morecomplex models that explicitly include these

potentially confounding factors.

A weighted linear regression using a

stepwise approach to include the best of the

road use variables alone (that is, without the

SSF) produced an equation with an Rsquared of 0.5313. A second weighted linear

regression using a stepwise approach to

include the best of the road use variables

plus the SSF produced an equation with an

R-squared of 0.9041. The variability

unexplained by the first model is:

1¥0.5313 = 0.4687 (without the SSF),

and the variability unexplained by the

second model is:

1 ¥ 0.9041 = 0.0959 (with the SSF).

This means that 80 percent of the variability

in the data remaining after the effects of the

best of the road use variables are used is

eliminated by allowing the SSF to enter the

stepwise procedure. This is calculated as:

(0.4687 ¥ 0.0950)/0.4687 = 0.80.

We consider 80 percent to be the value of the

SSF in explaining the number of rollovers

per single-vehicle crash.

We used the results of the model to adjust

the observed number of rollovers per singlevehicle crash to account for differences

among vehicle groups in their road use

35018 Federal Register / Vol. 65, No. 106 / Thursday, June 1, 2000 / Proposed Rules

characteristics in single-vehicle crashes. For

each data point, we used the regression

results (the coefficients of the explanatory

road use variables, FAST, CURVE, MALE,

YOUNG, and DRINK) and the typical road

use (the observed averages of these road use

characteristics for the study vehicles as a

group) to estimate what LN(ROLL) would

have been if road use for that vehicle group

had been the typical road use for all the

vehicles in the Florida study. The approach

is similar to that described in our July 1991

Technical Assessment Paper. The average

adjusted number of rollovers per singlevehicle crash for all the study vehicles in

Florida is, by design, 0.208 (that is, the same

as the number estimated from the unadjusted

data). The line through the adjusted data is

described by:

LN(ROLL) = 3.1691 ¥ 3.7935 × SSF.

Exponentiating both sides of the equation

produces an estimate that the number of

rollovers per single-vehicle crash is

approximated by the curve described by:

ROLL = 23.79 × e(¥3.7935 × SSF)

.

This model form has very useful properties.

The equation can be used to estimate the

number of rollovers per single-vehicle crash

as a function of SSF alone, for the average

mix of road use characteristics for the study

vehicles in Florida during the years 1994–

1997. For example, we can use the statistical

model to identify the increase in the SSF that

is associated with an estimate of half as many

rollovers per single-vehicle crash. Note that

our model has the same form as that used to

describe radioactive decay as a function of

time (with SSF used in place of time as the

independent variable). Using the terminology

and theory from the physical application,

3.7935 is the decay constant, and the half-life

of the process is estimated as:

Half-life = LN(2)/(3.7935)

= 0.18.

This means that the increase in the SSF that

is associated with halving the number of

rollovers per single-vehicle crash in Florida

is estimated as 0.18. For example, the

number of rollovers per single-vehicle crash

under average conditions in Florida for the

study vehicles as a group is estimated as:

0.40 for a SSF of 1.08

0.20 for a SSF of 1.26, and

0.10 for a SSF of 1.44.

Thus, rollover risk drops by a half when the

SSF increases from 1.08 to 1.26, and it drops

in half again when the SSF increases from

1.26 to 1.44.

F. Comparison of the State Results

The results for the six individual states and

GES are shown in Table A–5. The value of

the SSF in explaining rollovers per singlevehicle crash (measured as the decrease in

unexplained variability when SSF is allowed

to enter the stepwise regression) for the six

states ranges from 64 percent for Utah to 80

percent for Florida; the value estimated from

GES is 54 percent. The estimated increase in

the SSF that is associated with halving the

number of rollovers per single-vehicle crash

is similar across the six states, ranging from

0.18 (Florida and Missouri) to 0.24

(Pennsylvania and Utah); the value estimated

from GES is 0.18.

There are also similarities in which

explanatory variables were chosen by the

stepwise regression procedure. The best

models for the states (the models that include

SSF and those road use variables that are

most useful in explaining the number of

rollovers per single-vehicle crash in each

state) include the following variables:

DARK: 2 states,

STORM: 1 state,

RURAL: 2 states (not available in 2 other

states),

FAST: 5 states,

HILL: 2 states,

CURVE: 4 states,

BADROAD: 1 state (not available in 2 other

states),

BADSURF: 1 state,

MALE: 6 states,

YOUNG: 5 states,

DRINK: 4 states, and

NUMOCC: 2 states (not available in 1 other

state).

The similarities among the individual state

models suggests that the six states can be

combined to form a best estimate of the

relationship between the SSF and the

number of rollovers per single-vehicle crash

if the differences among the states in road use

and crash reporting can be addressed. We

would not be surprised if a multi-state

stepwise regression selected FAST, CURVE,

MALE, YOUNG, and DRINK as explanatory

variables because these factors are important

in the individual state analyses. Note that

combining the data from individual states is

already done by FARS (a census of traffic

fatalities in all states) and by GES (a survey

of police-reported crashes in sampled states),

and this combination is done without

adjustment for differences in reporting

practices. Our efforts to model the combined

data from the six available VIN states are

described below.

G. Combined Six-State Data Analysis

We performed a weighted stepwise linear

regression analysis for the six states

combined using the 481 data points that

represent at least 25 single-vehicle crashes,

with the weighting capped at 250. These 481

data points represent the experience of

184,726 single-vehicle crashes in the six-state

combined data, including the following

number of data points for each of four light

vehicle types:

204 for cars,

124 for sport utility vehicles,

45 for vans, and

108 for pickup trucks.

The road use variables considered by the

model were those that are available in all six

states: DARK, STORM, FAST, HILL, CURVE,

BADSURF, MALE, YOUNG, and DRINK.

We modeled LN(ROLL) as a function of

these road use variables, and we created five

dummy variables (DUMMYlFL,

DUMMYlMD, DUMMYlNC,

DUMMYlPA, and DUMMYlUT) to capture

state-to-state differences. We needed dummy

variables to combine the state data because

the states have different reporting thresholds

and practices, which produce different levels

of rollovers per single-vehicle crash even

after accounting for differences in road use.

We chose Missouri as the baseline state for

two reasons. First, Missouri has the lowest

rollover rate (both before and after

accounting for differences in road use), and

this means that the coefficients of all the state

dummy variables will be positive; this makes

the results a little easier to describe, but it

has no analytical implications. And second,

there are significant differences between

Missouri and each of the other five states in

the number of rollovers per single-vehicle

crash; this allows all five state dummy

variables to enter the model and lets us

measure the relative reporting effect of every

state.

For example, the dummy variable

DUMMYlFL was defined as ‘‘one’’ for each

of the 85 Florida data points, and it was

defined as ‘‘zero’’ for each of the 396 data

point from the other five states. The

coefficient of DUMMYlFL estimated by the

regression analysis is interpreted as the

incremental risk of rollover in Florida

(compared to Missouri, the baseline state),

after considering differences in road use. The

other four dummy variables were handled

analogously. All five dummy variables were

defined as ‘‘zero’’ for all the Missouri data

points.

The best model without SSF has an Rsquared of 0.5753, and the best model with

SSF has an R-squared of 0.8829. This means

that allowing the SSF to enter the model

explains 72 percent of the variation that was

not explained by the model without SSF, and

so we say that the value of the SSF to our

model is 72 percent. The stepwise regression

procedure with SSF chose three variables

that describe the driving situation (DARK,

FAST, and CURVE), three variables that

describe the driver (MALE, YOUNG, and

DRINK), and all five state dummy variables.

We used forward variable selection and a

significance level of 0.15 for entry and

removal from the model, but only one

variable in the best model that included the

SSF had a significance level greater than

0.0001 (DARK, at 0.0663). The F-statistic for

the model as a whole was 294, and the

probability of a value this high by chance

alone is less than 0.0001. More details on the

fit of the model are included as Table A–6.

The variables FAST, MALE, and YOUNG

are unambiguous, and it seems likely that

they are consistently reported by all six states

(though there are some differences in the

rates of missing data). The coding of DARK

and CURVE may vary somewhat by state

(states may differ in how they code twilight

conditions, and states where most roads

curve may tend to call a slightly-curved road

‘‘straight’’). The coding of DRINK probably

differs among the states. The state dummy

variables describe systematic differences

between states, including differences in the

reporting threshold.

We used the results of the model to adjust

the observed number of rollovers per singlevehicle crash to account for differences

among states and vehicle groups in their road

use characteristics in single-vehicle crashes.

For each data point, we used the regression

results to calculate how many rollovers per

single-vehicle crash we would have expected

if road use for that vehicle group had been

the typical road use for all the vehicles in the

study. (The effects of the adjustments on

Federal Register / Vol. 65, No. 106 / Thursday, June 1, 2000 / Proposed Rules 35019

individual data points are sometimes large.

For example, one pickup truck group had

0.46 rollovers per single-vehicle crash in

Florida, in part because drivers of this

vehicle in Florida tended to be young. If the

vehicle had been driven like the average of

all the vehicles in the study, we estimate that

there would have been 0.35 rollovers per

single-vehicle crash. This second number is

what we are calling the ‘‘adjusted’’ rollover

risk.)

The average adjusted number of rollovers

per single-vehicle crash for all the study

vehicles is, by design, 0.198 (that is, it is the

number estimated from both the six-state

data and GES). The fit of the curve through

the adjusted data is described by:

Estimated rollovers per single-vehicle crash =

13.25 × e(¥3.7831 × SSF).

This is the curve determined from the

observed number of rollovers per singlevehicle crash, the results of the weighted

regression model, and with an average of

0.198 rollovers per single-vehicle crash for all

the vehicles used in the study. Figure A–1

shows the adjusted value of the rollover risk

for each vehicle group averaged over all six

states and the curve that describes the pattern

of rollover risk as a function of the SSF. Our

national estimate of the number of rollovers

per single-vehicle crash declines by half for

any increase of 0.21 in the SSF.

H. Discussion

The observed relationship between the SSF

and the number of rollovers per singlevehicle crash is confounded by (1) The

relationship between the SSF and road use

factors that directly affect the risk of rollover

and (2) state-to-state differences in reporting

practices, including the reporting threshold.

We attempted to correct for these biases in

order to isolate the effect of the SSF on

rollover risk, and the curve through the

adjusted data is our best estimate of the

relationship between the SSF and the risk of

rollover. The fit of the model (an R-squared

of 0.88), the significance of the SSF in the

model (the probability of a greater value of

the t statistic is less than 0.0001), the value

of the SSF in this model (a 72 percent

reduction in the R-squared compared to the

best model without the SSF), and the

implications from the model (rollovers

decrease by half for any increase of 0.21 in

the SSF) suggest a strong relationship

between the SSF and rollover risk. However,

this (in common with all statistical models)

is a simplification of a complex process.

There are important factors that were not

included in the model because they are not

available on the state data files. Some of the

unmeasured factors that may influence

rollover risk include driver skill (including

attitudes, habits, and experience) and aftermarket changes to the vehicle’s SSF

(including those caused by differences in tire

inflation, vehicle loading, and wheel size).

None of these factors was explicitly included

in the analysis, but some of them may be

included through their association with

other, measured variables. For example,

differences in driver skill as a function of

vehicle group are captured to the extent that

driver skill is a function of age (as measured

by YOUNG).

Statistical models are a method for dealing

with uncertainty. The results can suggest an

underlying process, but they do not (except

in the most trivial cases) produce

deterministic predictions. For example,

Figure A–1 shows some scatter around the

fitted curve. This may reflect omitted

variables, the effect of having only a few

vehicle groups at each level of the SSF, or the

effects of natural statistical variability

(reflecting, in part, sample size limitations).

We can put this unexplained variability in

perspective, and we will use Florida for

illustrative purposes.

Figure A–2 shows the Florida data adjusted

to the typical road use for all vehicles in the

study. (The amount of scatter in the Florida

data appears similar to that for the average

of the six states shown in Figure A–1.) The

natural variability in the data is suggested by

how much the rollover risk for a single

vehicle group varies from year-to-year. Figure

A–3 shows the number of rollovers per

single-vehicle crash (calculated directly from

the Florida data, without any adjustments for

confounding factors) for each vehicle group

for two calendar year groups: 1994–1995

versus 1996–1997. For this purpose, the data

were limited to vehicle groups that had at

least 25 single-vehicles crashes in both time

periods. The line fit to these data (weighting

each vehicle group by the number of singlevehicle crashes in Florida during these four

years, with the weighting capped at 250) has

an R-squared of 0.89 and the equation:

Rollover risk in 1996–1997 = 0.0111 + 0.946

× Rollover risk in 1994–1995.

That is, our model of rollover risk as a

function of SSF across vehicle groups seems

to fit the data about as well as a model of

year-to-year changes for each vehicle group,

which seems like a reasonably good fit for

such a complex process.

TABLE A–1.—THE SSF FOR PASSENGER CARS

Vehicle group Make/model Model

years SSF

1 ................... Dodge Neon, Plymouth Neon ............................................................................................................................... 95–98 1.44

2 ................... Ford Crown Victoria ............................................................................................................................................... 92–97 1.42

3 ................... Ford Escort ............................................................................................................................................................ 91–96 1.38

4 ................... Ford Escort, Mercury Tracer ................................................................................................................................. 97–98 1.37

5 ................... Ford Mustang ........................................................................................................................................................ 88–93 1.38

6 ................... Ford Probe ............................................................................................................................................................. 93–97 1.41

7 ................... Ford Taurus, Mercury Sable ................................................................................................................................. 88–95 1.45

8 ................... Lincoln Town Car .................................................................................................................................................. 90–96 1.44

9 ................... Buick Century, Chevrolet Celebrity, Oldsmobile Cutlass Ciera/Ciera, Pontiac 6000 ........................................... 88–96 1.38

10 ................. Buick Regal, Pontiac Grand Prix ........................................................................................................................... 88–96 1.41

11 ................. Chevrolet Lumina .................................................................................................................................................. 95–98 1.34

12 ................. Buick Lesabre, Pontiac Bonneville ........................................................................................................................ 92–96 1.39

13 ................. Buick Park Avenue, Oldsmobile 98 ....................................................................................................................... 91–96 1.38

14 ................. Buick Skylark/Somerset, Oldsmobile Cutlass Calais/Calais, Pontiac Grand Am ................................................. 88–91 1.35

15 ................. Buick Skylark, Oldsmobile Achieva, Pontiac Grand Am ....................................................................................... 92–97 1.38

16 ................. Chevrolet Camaro, Pontiac Firebird ...................................................................................................................... 88–92 1.53

17 ................. Chevrolet Camaro, Pontiac Firebird ...................................................................................................................... 93–98 1.50

18 ................. Buick Roadmaster, Chevrolet Caprice .................................................................................................................. 91–96 1.40

19 ................. Buick Skyhawk, Chevrolet Cavalier, Pontiac Sunbird ........................................................................................... 88–94 1.32

20 ................. Chevrolet Corsica .................................................................................................................................................. 88–96 1.30

21 ................. Chevrolet Geo Metro, Suzuki Swift ....................................................................................................................... 89–94 1.32

22 ................. Chevrolet Geo Metro, Suzuki Swift ....................................................................................................................... 95–98 1.29

23 ................. Saturn SL ............................................................................................................................................................... 90–95 1.39

24 ................. Saturn SL ............................................................................................................................................................... 96–98 1.35

25 ................. Chevrolet Geo Prizm ............................................................................................................................................. 89–92 1.38

26 ................. Honda Civic ........................................................................................................................................................... 92–95 1.48

27 ................. Honda Civic ........................................................................................................................................................... 96–98 1.43

28 ................. Honda Accord ........................................................................................................................................................ 90–93 1.47

29 ................. Mazda Prote ́ge ́ ...................................................................................................................................................... 95–98 1.40

30 ................. Nissan Maxima ...................................................................................................................................................... 89–94 1.44

35020 Federal Register / Vol. 65, No. 106 / Thursday, June 1, 2000 / Proposed Rules

TABLE A–1.—THE SSF FOR PASSENGER CARS—Continued

Vehicle group Make/model Model

years SSF

31 ................. Nissan Sentra ........................................................................................................................................................ 91–94 1.46

32 ................. Nissan Sentra ........................................................................................................................................................ 95–98 1.40

33 ................. Toyota Camry ........................................................................................................................................................ 92–96 1.46

34 ................. Toyota Corolla ....................................................................................................................................................... 89–92 1.36

35 ................. Toyota Tercel ......................................................................................................................................................... 91–94 1.41

36 ................. Toyota Tercel ......................................................................................................................................................... 95–98 1.39

TABLE A–2.—THE SSF FOR SUVS

Vehicle group Make/model Model

years

Drive

wheels SSF

37 ................. Dodge Ramcharger ............................................................................................................................... 88–93 4 1.13

38 ................. Ford Bronco ........................................................................................................................................... 88–96 4 1.13

39 ................. Ford Bronco II ....................................................................................................................................... 88–90 2 1.04

40 ................. Ford Bronco II ....................................................................................................................................... 88–90 4 1.04

41 ................. Ford Explorer ......................................................................................................................................... 91–94 2 1.07

42 ................. Ford Explorer ......................................................................................................................................... 91–94 4 1.08

43 ................. Ford Explorer ......................................................................................................................................... 95–98 2 1.06

44 ................. Ford Explorer ......................................................................................................................................... 95–98 4 1.06

45 ................. Chevrolet S–10 Blazer, GMC S–1500 Jimmy ...................................................................................... 88–94 2 1.10

46 ................. Chevrolet S–10 Blazer, GMC S–1500 Jimmy ...................................................................................... 88–94 4 1.10

47 ................. Chevrolet Blazer, GMC Jimmy .............................................................................................................. 95–98 2a1.09

48 ................. Chevrolet Blazer, GMC Jimmy .............................................................................................................. 95–98 4 1.09

49 ................. Chevrolet V10/K10/K1500 Blazer ......................................................................................................... 88–91 4 1.09

50 ................. Chevrolet K1500 Blazer/Tahoe, GMC Yukon ....................................................................................... 92–98 4 1.12

51 ................. Chevrolet V1500/V2500 Suburban, GMC V1500/V2500 Suburban ..................................................... 88–91 4 1.10

52 ................. Chevrolet K1500/K2500 Suburban, GMC K1500/K2500 Suburban ..................................................... 92–98 4 1.08

53 ................. Chevrolet Geo Tracker, Suzuki Sidekick .............................................................................................. 89–98 4 1.13

54 ................. Honda CR–V ......................................................................................................................................... 97–98 4 1.19

55 ................. Honda Passport, Isuzu Rodeo .............................................................................................................. 91–97 4 1.06

56 ................. Isuzu Trooper ........................................................................................................................................ 88–91 4 1.02

57 ................. Isuzu Trooper ........................................................................................................................................ 92–94 4 1.07

58 ................. Jeep Cherokee ...................................................................................................................................... 88–97 4 1.08

59 ................. Acura SLX, Isuzu Trooper ..................................................................................................................... 95–98 4 1.09

60 ................. Jeep Grand Cherokee ........................................................................................................................... 93–98 4 1.07

61 ................. Jeep Wrangler ....................................................................................................................................... 88–96 4 1.20

62 ................. Nissan Pathfinder .................................................................................................................................. 88–95 4 1.07

63 ................. Nissan Pathfinder .................................................................................................................................. 96–98 4 1.10

64 ................. Suzuki Samurai ..................................................................................................................................... 88–95 4 1.09

65 ................. Toyota 4Runner ..................................................................................................................................... 88–96 4 1.00

66 ................. Toyota 4Runner ..................................................................................................................................... 97–98 4 1.06

TABLE A–3.—THE SSF FOR VANS

Vehicle group Make/Model Model

years

Drive

wheels SSF

67 ................. Dodge Caravan/Grand Caravan, Plymouth Voyager/Grand Voyager .................................................. 88–95 2 1.21

68 ................. Chrysler Town & Country, Dodge Caravan/Grand Caravan, Plymouth Voyager/Grand Voyager ....... 96–98 2 1.23

69 ................. Dodge B–150 Ram Wagon ................................................................................................................... 88–98 2 1.09

70 ................. Ford Aerostar ........................................................................................................................................ 88–98 2 1.10

71 ................. Ford E–150 Clubwagon ........................................................................................................................ 88–91 2 1.11

72 ................. Ford E–150 Clubwagon ........................................................................................................................ 92–97 2 1.11

73 ................. Ford Windstar ........................................................................................................................................ 95–98 2 1.24

74 ................. Chevrolet Astro, GMC Safari ................................................................................................................ 88–98 2 1.12

75 ................. Chevrolet Lumina APV, Oldsmobile Silhouette, Pontiac Transport ...................................................... 90–96 2 1.12

76 ................. Chevrolet Venture, Oldsmobile Silhouette, Pontiac Transport ............................................................. 97–98 2 1.18

Federal Register / Vol. 65, No. 106 / Thursday, June 1, 2000 / Proposed Rules 35021

TABLE A–3.—THE SSF FOR VANS—Continued

Vehicle group Make/Model Model

years

Drive

wheels SSF

77 ................. Chevrolet G10/G20 Sportsvan, GMC G1500/G2500 Rally van ........................................................... 88–95 2 1.08

78 ................. Mazda MPV ........................................................................................................................................... 89–97 2 1.17

79 ................. Toyota Previa ........................................................................................................................................ 91–97 2 1.23

TABLE A–4.—THE SSF FOR PICKUP TRUCKS

Vehicle group Make/model Model

years

Drive

wheels SSF

80 ................. Dodge Dakota ....................................................................................................................................... 97–98 2 1.25

81 ................. Dodge Ram 1500 .................................................................................................................................. 94–98 2 1.22

82 ................. Dodge D–150 Ram ............................................................................................................................... 88–93 2 1.28

83 ................. Ford F–150 ............................................................................................................................................ 88–96 2 1.19

84 ................. Ford F–150 ............................................................................................................................................ 88–96 4 1.15

85 ................. Ford F–150 ............................................................................................................................................ 97–98 2 1.18

86 ................. Ford Ranger .......................................................................................................................................... 88–92 2 1.13

87 ................. Ford Ranger .......................................................................................................................................... 88–92 4 1.03

88 ................. Ford Ranger, Mazda B-series ............................................................................................................... 93–97 2 1.17

89 ................. Ford Ranger, Mazda B-series ............................................................................................................... 93–97 4 1.07

90 ................. Chevrolet C–1500, GMC C–1500/Sierra .............................................................................................. 88–98 2 1.22

91 ................. Chevrolet K–1500, GMC K–1500/Sierra ............................................................................................... 88–98 4 1.14

92 ................. Chevrolet S–10, GMC S–15/Sonoma ................................................................................................... 88–93 2 1.19

93 ................. Chevrolet S–10, GMC S–15/Sonoma ................................................................................................... 88–93 4 1.19

94 ................. Chevrolet S–10, GMC S–15/Sonoma, Isuzu Hombre .......................................................................... 94–98 2 1.14

95 ................. Chevrolet S–10, GMC S–15/Sonoma ................................................................................................... 94–98 4 1.14

96 ................. Nissan Pickup ........................................................................................................................................ 88–97 2 1.20

97 ................. Nissan Pickup ........................................................................................................................................ 88–97 4 1.11

98 ................. Toyota Pickup ........................................................................................................................................ 89–94 2 1.23

99 ................. Toyota Pickup ........................................................................................................................................ 89–94 4 1.07

100 ............... Toyota Tacoma ..................................................................................................................................... 95–98 2 1.26

TABLE A–5.—ROLLOVERS PER SINGLE-VEHICLE (SV) CRASH AS A FUNCTION OF THE SSF AND ROAD USE VARIABLES

FL MD MO NC PA UT Six states GES

Vehicle groups for study .................................. 85 81 82 86 86 61 481 60

Single-vehicle crashes ..................................... 34,521 17,683 31,517 45,440 48,519 7,046 184,726 7,022

Rollovers per SV crash .................................... 0.208 0.159 0.127 0.177 0.246 0.363 0.198 0.198

R-squared for models of LN (ROLL) with:

SSF only ................................................... 0.7074 0.6072 0.7266 0.5304 0.7281 0.7606 0.5386 0.4456

SSF and state ........................................... ................ ................ ................ ................ ................ ................ 0.7334 ................

Road use only ........................................... 0.5313 0.6550 0.5520 0.5479 0.6878 0.5461 ................ 0.4147

Road use and state .................................. ................ ................ ................ ................ ................ ................ 0.5753 ................

SSF plus road use .................................... 0.9041 0.8818 0.8559 0.8945 0.8879 0.8548 ................ 0.7332

SSF, road use, and state ......................... ................ ................ ................ ................ ................ ................ 0.8829 ................

Value of SSF ............................................ 80% 66% 68% 77% 64% 68% 72% 54%

Best model of ROLL:

Intercept .................................................... 23.79 8.28 15.15 13.53 8.33 11.39 13.25 5.84

Coefficient of SSF ..................................... ¥3.7935 ¥3.1414 ¥3.8627 ¥3.4328 ¥2.8494 ¥2.8784 ¥3.3731 ¥2.6943

Standard error of coefficient of SSF ......... 0.1729 0.2552 0.2141 0.1798 0.1488 0.2391 0.0761 0.3192

Increase in SSF to halve rollovers per SV

crash ...................................................... 0.18 0.22 0.18 0.20 0.24 0.24 0.21 0.18

TABLE A–6.—FIT OF THE MODEL OF ROLLOVERS PER SINGLE-VEHICLE CRASH AS A FUNCTION OF THE SSF AND ROAD

USE VARIABLES

[R-square=0.88290867 C(p)=10.21256387]

DF Sum of squares Mean square F Prob>F

Regression ............................................................................... 12 27480.16301362 2290.01358447 294.07 0.0001

Error ......................................................................................... 468 3644.41878744 7.78721963

Total ......................................................................................... 480 31124.58180106

Variable Parameter estimate Standard error Type II—Sum of

squares F Prob>F

INTERCEP ............................................................................... 0.98462872 0.19748866 193.57224437 24.86 0.0001

SSF .......................................................................................... ¥3.37314841 0.07612591 15289.32722322 1963.39 0.0001

35022 Federal Register / Vol. 65, No. 106 / Thursday, June 1, 2000 / Proposed Rules

Variable Parameter estimate Standard error Type II—Sum of

squares F Prob>F

DARK ....................................................................................... ¥0.38680987 0.21016386 26.37918835 3.39 0.0663

FAST ........................................................................................ 1.52493695 0.19916920 456.50110043 58.62 0.0001

CURVE ..................................................................................... 1.55970317 0.25046223 301.98254463 38.78 0.0001

MALE ....................................................................................... ¥1.33399065 0.10621334 1228.37181405 157.74 0.0001

YOUNG .................................................................................... 0.86034711 0.09977145 579.05158823 74.36 0.0001

DRINK ...................................................................................... 1.73507462 0.27938756 300.33406907 38.57 0.0001

DUMMYlFL ............................................................................ 1.17092992 0.07322547 1991.22295614 255.70 0.0001

DUMMYlMD .......................................................................... 0.64541483 0.09276482 376.95864460 48.41 0.0001

DUMMYlNC ........................................................................... 0.50232907 0.03749136 1397.96646995 179.52 0.0001

DUMMYlPA ........................................................................... 1.17247270 0.06537935 2504.41755183 321.61 0.0001

DUMMYlUT ........................................................................... 0.83176783 0.05431222 1826.38170253 234.54 0.0001

Federal Register / Vol. 65, No. 106 / Thursday, June 1, 2000 / Proposed Rules 35023

35024 Federal Register / Vol. 65, No. 106 / Thursday, June 1, 2000 / Proposed Rules

[FR Doc. 00–13443 Filed 5–25–00; 3:01 pm]

BILLING CODE 4910–59–C