[Federal Register Volume 65, Number 106 (Thursday, June 1, 2000)]
[Proposed Rules]
[Pages 34998-35024]
From the Federal Register Online via the Government Publishing Office [www.gpo.gov]
[FR Doc No: 00-13443]


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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.

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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

[[Page 34999]]

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\
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    \1\ Light trucks include vans, minivans, SUVs, and pickup trucks 
under 4,536 kilograms (10,000 pounds) GVWR.
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    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 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 (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 tow-away rollovers were not 
using a safety

[[Page 35000]]

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.
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    \2\ A broken hip is an example of an AIS 3 injury.
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     The 1995-1997 General Estimates System (GES) data produce 
estimates that 240,000 light vehicles rolled over each year (on 
average) in police-reported 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 police-reported single-vehicle crashes 
rolled over. The estimated risk of rollover differs by vehicle type: 13 
percent of cars and 14 percent of vans in police-reported 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 skid-resistance 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 
single-vehicle 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,

[[Page 35001]]

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 Maneuver-Induced 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\.
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    \3\ Tripped 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.
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    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 step-steer 
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

[[Page 35002]]

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.
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    \5\ ``Report to Congress: Rollover Prevention and Roof Crush;'' 
NHTSA, 1992.
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    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.
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    \6\ ``Handling Test Procedures for Light Trucks, Vans, and 
Recreational Vehicles;'' NHTSA, DOT-HS-4-00853; February 1976.
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    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.
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    \7\ Research Note, ``Passenger Vehicles in Untripped 
Rollovers;'' NHTSA National Center for Statistics and Analysis; 
September 1999.
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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.
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    \8\ Consumers 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.''
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    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\
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    \9\ This 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.
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     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

[[Page 35003]]

     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 off-road 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 two-thirds 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

[[Page 35004]]

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.
---------------------------------------------------------------------------

    \10\ The meetings are documented in docket NHTSA-1998-3206.
---------------------------------------------------------------------------

    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-wheel-drive. 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 (path-following)
     Split-mu (wet epoxy and asphalt)
     Braking in a turn (``Brake and Steer'')
Some of these procedures, such as J-Turn, 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 path-following 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

[[Page 35005]]

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.
---------------------------------------------------------------------------

    \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.
---------------------------------------------------------------------------

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:
---------------------------------------------------------------------------

    \12\ Since 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.
---------------------------------------------------------------------------

     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\
---------------------------------------------------------------------------

    \13\ The 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.
---------------------------------------------------------------------------

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 (two-wheel 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-of-gravity 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

[[Page 35006]]

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, ``de-beading'', 
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. Maneuver-
induced 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 steering-induced 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\.)
---------------------------------------------------------------------------

    \14\ ``Technical Assessment Paper: Relationship between Rollover 
and Vehicle Factors''; NHTSA; July 1991.
---------------------------------------------------------------------------

    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

[[Page 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.
[GRAPHIC] [TIFF OMITTED] TP01JN00.000

    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.

[[Page 35008]]

[GRAPHIC] [TIFF OMITTED] TP01JN00.001

    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.
[GRAPHIC] [TIFF OMITTED] TP01JN00.002

    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.

[[Page 35009]]

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 single-vehicle 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.
---------------------------------------------------------------------------

    \15\ E.A. Harwin and L. Emery; ``The Crash-avoidance 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.
---------------------------------------------------------------------------

    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 on-road 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

[[Page 35010]]

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 single-vehicle 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 single-vehicle crashes.
---------------------------------------------------------------------------

    \17\ Ibid.
    \18\ E.A. Harwin and Howell K. Brewer; ``Analysis of the 
Relationship between Vehicle Rollover Stability and Rollover Risk 
using the NHTSA CARDfile;'' NHTSA, 1989.
---------------------------------------------------------------------------

    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/single-vehicle 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 single-vehicle 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 single-vehicle crashes was performed 
as a regression analysis, in which the square of the coefficient of 
regression (the R\2\ statistic) indicates the degree to which the 
differences between the data samples can be explained by the 
independent variables. In this case, the R\2\ 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 R\2\ 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 R\2\ 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 R\2\ 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 
non-vehicle 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 R\2\ 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

[[Page 35011]]

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\
---------------------------------------------------------------------------

    \19\ Heydinger, G.J., et al; ``Measured Vehicle Inertial 
Parameters--NHTSA's Data through November 1998;'' Society of 
Automotive Engineers 1999-01-1336; March, 1999.
---------------------------------------------------------------------------

    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 non-linear 
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

[[Page 35012]]

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 
single-vehicle 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 single-
vehicle 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

[[Page 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 well-known 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-of-purchase (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

[[Page 35014]]

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 run-off-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\
---------------------------------------------------------------------------

    \20\ Under 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.
---------------------------------------------------------------------------

    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

[[Page 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

[[Page 35016]]

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 
four-digit 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.''
    (4) On the next page, which contains docket summary information for 
the docket you selected, click on the desired comments. You may 
download the comments. Although the comments are imaged documents, 
instead of word processing documents, the ``pdf'' versions of the 
documents are word searchable.
    Please note that even after the comment closing date, we will 
continue to file relevant information in the Docket as it becomes 
available. Further, some people may submit late comments. Accordingly, 
we recommend that you periodically check the Docket for new material.

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 
two-passenger 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 four-wheel 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

[[Page 35017]]

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 single-vehicle 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.
---------------------------------------------------------------------------

    \21\ As described in our July 1991, Technical Assessment Paper: 
Relationship between Rollover and Vehicle Factors.
---------------------------------------------------------------------------

    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 single-vehicle 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 high-SSF 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 single-vehicle 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 more-complex 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 R-squared 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 single-vehicle crash to account for differences 
among vehicle groups in their road use

[[Page 35018]]

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 
single-vehicle 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  x  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  x  e(-3.7935  x  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 single-
vehicle 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 (DUMMY__FL, DUMMY__MD, 
DUMMY__NC, DUMMY__PA, and DUMMY__UT) 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 DUMMY__FL 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 DUMMY__FL 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 R-squared 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 single-vehicle 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

[[Page 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  x  
e(-3.7831  x  SSF).

This is the curve determined from the observed number of rollovers 
per single-vehicle 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 single-vehicle 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 after-market 
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 single-
vehicle 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  x  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
------------------------------------------------------------------------
                                                         Model
      Vehicle group                Make/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        88-96     1.38
                           Celebrity, Oldsmobile
                           Cutlass Ciera/Ciera,
                           Pontiac 6000.
10......................  Buick Regal, Pontiac Grand      88-96     1.41
                           Prix.
11......................  Chevrolet Lumina............    95-98     1.34
12......................  Buick Lesabre, Pontiac          92-96     1.39
                           Bonneville.
13......................  Buick Park Avenue,              91-96     1.38
                           Oldsmobile 98.
14......................  Buick Skylark/Somerset,         88-91     1.35
                           Oldsmobile Cutlass Calais/
                           Calais, Pontiac Grand Am.
15......................  Buick Skylark, Oldsmobile       92-97     1.38
                           Achieva, Pontiac Grand Am.
16......................  Chevrolet Camaro, Pontiac       88-92     1.53
                           Firebird.
17......................  Chevrolet Camaro, Pontiac       93-98     1.50
                           Firebird.
18......................  Buick Roadmaster, Chevrolet     91-96     1.40
                           Caprice.
19......................  Buick Skyhawk, Chevrolet        88-94     1.32
                           Cavalier, Pontiac Sunbird.
20......................  Chevrolet Corsica...........    88-96     1.30
21......................  Chevrolet Geo Metro, Suzuki     89-94     1.32
                           Swift.
22......................  Chevrolet Geo Metro, Suzuki     95-98     1.29
                           Swift.
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 Protege...............    95-98     1.40
30......................  Nissan Maxima...............    89-94     1.44

[[Page 35020]]

 
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
------------------------------------------------------------------------
                                               Model     Drive
   Vehicle group            Make/model         years    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,     88-94        2      1.10
                      GMC S-1500 Jimmy.
46.................  Chevrolet S-10 Blazer,     88-94        4      1.10
                      GMC S-1500 Jimmy.
47.................  Chevrolet Blazer, GMC      95-98   2a1.09
                      Jimmy.
48.................  Chevrolet Blazer, GMC      95-98        4      1.09
                      Jimmy.
49.................  Chevrolet V10/K10/K1500    88-91        4      1.09
                      Blazer.
50.................  Chevrolet K1500 Blazer/    92-98        4      1.12
                      Tahoe, GMC Yukon.
51.................  Chevrolet V1500/V2500      88-91        4      1.10
                      Suburban, GMC V1500/
                      V2500 Suburban.
52.................  Chevrolet K1500/K2500      92-98        4      1.08
                      Suburban, GMC K1500/
                      K2500 Suburban.
53.................  Chevrolet Geo Tracker,     89-98        4      1.13
                      Suzuki Sidekick.
54.................  Honda CR-V.............    97-98        4      1.19
55.................  Honda Passport, Isuzu      91-97        4      1.06
                      Rodeo.
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           95-98        4      1.09
                      Trooper.
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
------------------------------------------------------------------------
                                               Model     Drive
   Vehicle group            Make/Model         years    wheels     SSF
------------------------------------------------------------------------
67.................  Dodge Caravan/Grand        88-95        2      1.21
                      Caravan, Plymouth
                      Voyager/Grand Voyager.
68.................  Chrysler Town &            96-98        2      1.23
                      Country, Dodge Caravan/
                      Grand Caravan,
                      Plymouth Voyager/Grand
                      Voyager.
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       88-98        2      1.12
                      Safari.
75.................  Chevrolet Lumina APV,      90-96        2      1.12
                      Oldsmobile Silhouette,
                      Pontiac Transport.
76.................  Chevrolet Venture,         97-98        2      1.18
                      Oldsmobile Silhouette,
                      Pontiac Transport.

[[Page 35021]]

 
77.................  Chevrolet G10/G20          88-95        2      1.08
                      Sportsvan, GMC G1500/
                      G2500 Rally van.
78.................  Mazda MPV..............    89-97        2      1.17
79.................  Toyota Previa..........    91-97        2      1.23
------------------------------------------------------------------------


                  Table A-4.--The SSF for Pickup Trucks
------------------------------------------------------------------------
                                               Model     Drive
   Vehicle group            Make/model         years    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-      93-97        2      1.17
                      series.
89.................  Ford Ranger, Mazda B-      93-97        4      1.07
                      series.
90.................  Chevrolet C-1500, GMC C-   88-98        2      1.22
                      1500/Sierra.
91.................  Chevrolet K-1500, GMC K-   88-98        4      1.14
                      1500/Sierra.
92.................  Chevrolet S-10, GMC S-     88-93        2      1.19
                      15/Sonoma.
93.................  Chevrolet S-10, GMC S-     88-93        4      1.19
                      15/Sonoma.
94.................  Chevrolet S-10, GMC S-     94-98        2      1.14
                      15/Sonoma, Isuzu
                      Hombre.
95.................  Chevrolet S-10, GMC S-     94-98        4      1.14
                      15/Sonoma.
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
--------------------------------------------------------------------------------------------------------------------------------------------------------
                                                                                                                                       Six
                                                                      FL         MD         MO         NC         PA         UT       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
----------------------------------------------------------------------------------------------------------------


----------------------------------------------------------------------------------------------------------------
                                         Parameter                        Type II--Sum of
              Variable                   estimate       Standard error        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

[[Page 35022]]

 
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
DUMMY__FL...........................      1.17092992         0.07322547      1991.22295614     255.70     0.0001
DUMMY__MD...........................      0.64541483         0.09276482       376.95864460      48.41     0.0001
DUMMY__NC...........................      0.50232907         0.03749136      1397.96646995     179.52     0.0001
DUMMY__PA...........................      1.17247270         0.06537935      2504.41755183     321.61     0.0001
DUMMY__UT...........................      0.83176783         0.05431222      1826.38170253     234.54     0.0001
----------------------------------------------------------------------------------------------------------------

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[FR Doc. 00-13443 Filed 5-25-00; 3:01 pm]
BILLING CODE 4910-59-C