DOT HS 809 735

May 2004

Technical Report

Analysis of Crashes

Involving 15-Passenger Vans

This document is available to the pubilic from the National Techinical Information Service, Springfield, VA 22161
National Center for Statistics and Analysis - Technical Report

This publication is distributed by the U.S. Department of Transportation, National Highway Traffic Safety 

Administration, in the interest of information exchange. The opinions, findings and conclusions expressed in 

this publication are those of the author(s) and not necessarily those of the Department of Transportation or the 

National Highway Traffic Safety Administration. The United States Government assumes no liability for its 

contents or use thereof. If trade or manufacturers’ names are mentioned, it is only because they are considered 

essential to the object of the publication and should not be construed as an endorsement. The United States 

Government does not endorse products or manufacturers.
Analysis of Crashes Involving 15-Passenger Vans 

Technical Report Documentation Page

1. Report No. 2. Government Accession No. 3. Recipient’s Catalog No.

DOT HS 809 735 

4. Title and Subtitle 5. Report Date

Analysis of Crashes Involving 15-Passenger Vans May 2004

6. Performing Organization Code

NRD-31

7. Author(s) 8. Performing Organization Report No.

Rajesh Subramanian

9. Performing Organization Name and Address 10. Work Unit No. (TRAIS)

Mathematical Analysis Division, National Center for Statistics and Analysis

National Highway Traffic Safety Administration

U.S. Department of Transportation 11. Contract or Grant No.

NRD-31, 400 Seventh Street, S.W.

Washington, D.C. 20590

12. Sponsoring Agency Name and Address 13. Type of Report and Period Covered

Mathematical Analysis Division, National Center for Statistics and Analysis NHTSA Technical Report

National Highway Traffic Safety Administration

U.S. Department of Transportation 14. Sponsoring Agency Code

NRD-31, 400 Seventh Street, S.W.

Washington, D.C. 20590

15. Supplementary Notes

The author would like to thank Joseph Tessmer, Ph.D. of the Mathematical Analysis Division for his advice 

on the Logistic Regression Analysis in the report. The author would also like to thank Dennis Utter and 

Chou-Lin Chen of the Mathematical Analysis Division for their review and valuable comments.

Abstract

This study explores the relationship between vehicle occupancy and several other variables in the National 

Highway Traffic Safety Administration’s (NHTSA) Fatality Analysis Reporting System (FARS) database 

and a 15-passenger van’s risk of rollover. A univariate analysis is used to demonstrate the effect of selected 

variables on single-vehicle rollover crashes. Variables used include speed, number of occupants, driver 

experience and avoidance maneuvers. Also, a logistic regression model is constructed using data from 

NHTSA’s State Data System – a collection of all police reported crashes for that state. The resulting 

model permits jointly estimating the effect of these variables on the odds and rate of rollover occurrence, 

conditional on being in a single-vehicle police-reported crash.

17. Key Words 18. Distribution Statement 

15- Passenger Vans, Rollover, Occupancy Document is available to the public through 

Maneuvers the National Technical Information Service, 

 Springfield, VA 22161

 http://www.ntis.gov

19. Security Classif. (of this report) 20. Security Classif. (of this page) 21. No. of Pages 22. Price

Unclassified Unclassified

Form DOT F 1700.7 (8-72) Reproduction of completed page authorized
National Center for Statistics and Analysis - Technical Report
Analysis of Crashes Involving 15-Passenger Vans 

Table of Contents

Executive Summary

1. Introduction....................................................................... .......................................................................... 3

1.1 Vehicle Models and Exposure................ .............................................................................................. 4

2. 15-Passenger Vans Involved in Fatal Crashes, 1990-2002 ..................................................................... 5

2.1 Vehicles Involved and Fatalities .......................................................................................................... 5

2.2 Restraint Use Among Occupants of 15-Passenger Vans ................................................................. 11

2.3 Comparison with Other Vehicle Types Involved in Fatal Crashes ............................................... 13

3. Analysis using Crash Data from NHTSA’s State Data System (SDS) ............................................... 15

3.1 Data and Methodology ........................................................................................................................ 15

3.2 Descriptive Statistics ............................................................................................................................ 16

3.3 Logistic Regression Analysis .............................................................................................................. 22

3.3.1 Logistic Regression Analysis Performed Independently for Each Type of Vehicle ................ 24

3.3.2 Logistic Regression Analysis Performed for the Vehicle Population as a Whole .................... 27

7. Conclusions ................� 31

8. References ..................� 33

9. Glossary ......................� 35

Appendix A: VIN Pattern to Identify 15-Passenger Vans ....................................................................... 37

Appendix B: SAS® Code to Identify 15-Passenger Vans in FARS ......................................................... 38

Appendix C: Useful Resources ................................................................................................................... 39
National Center for Statistics and Analysis - Technical Report
Analysis of Crashes Involving 15-Passenger Vans 1

Executive Summary

The National Highway Traffic Safety 

Administration’s (NHTSA) National Center 

for Statistics and Analysis (NCSA), along with 

NHTSA’s Vehicle Research and Test Center 

(VRTC), released a Research Note titled “Rollover 

Propensity of 15-Passenger Vans” in April 2001. 

This report combined crash data and engineering 

analysis to conclude that the rollover risk of 15-

passenger vans increases with loading (Garrott, 

et al. [1]). 

This Technical Report provides an in-depth 

analysis of crashes involving 15-passenger vans 

to assess the effect of occupancy level on the 

risk of rollover. The report is organized into 

two major sections, the first of which provides 

statistics on fatal crashes involving 15-passenger 

vans from 1990 to 2002 using data from NHTSA’s 

Fatality Analysis Reporting System (FARS). 

The statistics in this section are for descriptive 

purposes only and should not be used to interpret 

propensity or risk of rollover in 15-passenger 

vans. The second section constructs a logistic 

regression model to model the effect of various 

factors, most importantly occupancy level, on the 

risk of rollover. The model is constructed using 

data from 1994 to 2001 on police-reported motor 

vehicle traffic crashes in Florida, Maryland, 

Pennsylvania, North Carolina and Utah that 

are part of NHTSA’s State Data System (SDS). 

The data represent the entire cross-section of 

police-reported crashes and are hence more 

representative of the real-world experience of 

these vehicles.

Data from fatal crashes show that between 1990 

and 2002, there were 1,576 15-passenger vans 

involved in fatal crashes that resulted in 1,111 

fatalities to occupants of such vans. Of these, 

657 vans were in fatal, single vehicle crashes, 

of which 349 rolled over. In 450 of these vans, 

there was at least one fatality, totaling up to 684 

occupant fatalities in single-vehicle crashes.

A large proportion of the fatally injured van 

occupants were not wearing seat belts. Only 

14 percent of the fatally injured occupants were 

properly restrained. Also, 92 percent of the belted 

occupants survived. About 61 percent of the 

occupants killed in single-vehicle crashes were 

ejected from the van. Proper restraining greatly 

reduces the chances of ejection from the van. 

The rate of ejection for unrestrained occupants is 

about 72 percent as compared to 18 percent for 

restrained occupants.

Single vehicle crashes are used as an exposure 

measure to assess the risk of rollover, as every 

single-vehicle crash is an opportunity for a 

rollover to occur. In single-vehicle crashes, the 

vehicle characteristics that contribute to rollover 

are not obscured by the effect of the forces of 

collision. Also, a majority of rollovers occur in 

single-vehicle crashes.

Analysis of data from NHTSA’s State Data 

System reveals that the rate of rollover observed 

for 15-passenger vans that are loaded above 

half their designed seating capacity is 2.2 times 

the rate observed for vans loaded to or below 

half their capacity. This disparity is the widest 

among all vehicle categories. A large proportion 

of these high-occupancy rollovers are observed 

to take place on high-speed roads. However, a 

comparison of rates of rollover, conditional on 

being on a high speed road, between the two 

loading scenarios still show the widest disparity 

for 15-passenger vans.

Logistic Regression modeling of NHTSA’s State 

data reveals that the risk of rollover in a singlevehicle crash, measured in terms of predicted 

odds, of vehicles loaded to their designed capacity 

is most elevated in the case of 15-passenger vans 

as compared to passenger cars, SUVs, minivans 

and pickup trucks. Odds are a statistical 

transformation of probability that is widely used 

to compare the chances of occurrence versus
2 National Center for Statistics and Analysis - Technical Report

non-occurrence. This metric, directly related 

to parameters in the logistic regression model, 

neatly fits into the exercise of assessing the risk 

of occurrence versus non-occurrence of rollover 

of vehicles involved in crashes. 

The odds of a rollover for a 15-passenger van at 

its designed seating capacity, is more than five 

times the odds of a rollover when the driver is 

the only occupant in the van. This compares to 

ratios of close to two for SUVs and Minivans, 1.6 

for pickup trucks and 1.2 for passenger cars. This 

disparity in the risk of rollover between lightly 

loaded and fully loaded scenarios is the most 

significant conclusion in this report.

Speed and curved road geometry were determined 

to be statistically significant factors affecting 

rollover outcome. The odds of a rollover in highspeed roads (50+ mph) are about five times the 

odds in a low-speed road (Under 50 mph). The 

odds of a rollover on curved roads increase by 

two times as compared to straight roads.

High occupancy single-vehicle crashes involving 

15-passenger vans are significantly fewer in 

number as compared to other types of vehicles. 

While noting the disparity in sample size and 

comparable overall risk of rollover, it is important 

to observe that there is a wider disparity in 

the risk of rollover between nominal and full 

occupancy scenarios in 15-passenger vans as 

compared to Passenger Cars, SUVs, Pickup 

Trucks or Minivans. 

The conclusions in this report merely point to 

a higher observed rate of rollover under certain 

vehicle, driver and crash-related factors. The 

conclusions should not be misconstrued to be 

indicative of a specific vehicle defect or a driverrelated problem. 
Analysis of Crashes Involving 15-Passenger Vans 3

Prior Research (Garrott, et. al. [1]) has shown 

that fully-loaded 15-passenger vans are observed 

to have a higher rate of rollover as compared to 

lightly loaded vans. NHTSA’s consumer advisory 

of April, 2001 was based on this research. Also, 

NHTSA re-issued its Consumer Advisory on the 

rollover propensity of these vans in April, 2002. 

Fifteen-passenger vans1 are primarily used by 

organizations for the transportation of groups 

such as college sports teams, commuters, church 

groups, recreational groups and inmates of 

correctional facilities.

Fifteen-passenger vans differ from most lighttrucks in that they have a larger payload capacity 

and the occupants sit fairly high up in the vehicle 

(Garrott, et. al. [1]). Loading these vans to their 

Gross Vehicle Weight Rating (GVWR) has an 

adverse effect on the rollover propensity due to 

the increase in center-of-gravity height. Loading 

the vans with passengers and cargo also moves 

the center of gravity rearward, increasing the 

vertical load on the rear tires. 

This report is organized into two sections. The 

first section uses data from NHTSA’s Fatality 

Analysis Reporting System (FARS). This section 

contains raw cross tabulations of the data to 

identify the circumstances surrounding fatal 

crashes involving these vans during the thirteen 

years from 1990 to 2002. FARS data also shows 

that the rate of safety belt use among occupants of 

15-Passenger vans involved in fatal crashes. The 

use of safety belts in a rollover scenario can be 

a significant factor in preventing serious injury 

to the occupants of these vans and also prevent 

them from being ejected from the vehicle. It is 

known that fatality rates among non-ejected 

occupants are dramatically lower compared 

with the ejected occupants in the same crash 

(Winnicki, J. [2]).

The second section constructs logistic regression 

models using NHTSA’s State Data System (SDS) 

to correlate the risk of rollover with factors related 

to the environment, vehicle and driver. The state 

data system is a database of all police-reported 

crashes (fatal, injury or property-damage-only 

crashes) in a state. Of particular interest are 

rollovers in single-vehicle crashes involving 

such vans. Single vehicle crashes are used as an 

exposure measure to assess the risk of rollover, as 

every single-vehicle crash is an opportunity for a 

rollover to occur. In single-vehicle crashes, the 

vehicle characteristics that contribute to rollover 

are not obscured by the effect of the forces of 

collision. Also, a majority of rollovers occur in 

single-vehicle crashes. The correlation between 

the loading condition (occupancy) and rollover 

is also presented to illustrate the adverse effect of 

loading on the rollover propensity of these vans.

The conclusions in this report merely point to a 

higher observed rate of rollover under certain 

vehicle, driver and crash-related factors. The 

conclusions should not be misconstrued to be 

indicative of a specific vehicle defect or a driverrelated problem. 

1. Introduction

1

 While these vehicles actually have seating positions for a driver plus fourteen passengers, they are typically called 15-passenger vans. 

Also, these vehicles are actually classified as buses under 49 CFR 571.3.
4 National Center for Statistics and Analysis - Technical Report

Only DaimlerChrysler, Ford and General Motors 

manufacture vans that can be configured to seat 

15 passengers. The series of vans used for this 

study are:

• Ford E-350 Super Duty XLT (Econoline and 

Club Wagons)

• Dodge Ram Van B3500/Wagon B350 (1 ton) 

– Discontinued in 2002.

• GMC Savanna/Rally 1-ton Extended

• Chevrolet Express 1-ton Extended

The vehicles of interest were identified in 

FARS and SDS using the Vehicle Identification 

Numbers (VINs). Although the first eleven digits 

of the VIN are reported in FARS, only the first 

seven digits of the VIN are needed to identify 

these vans. Although the SDS consists of data 

reported by seventeen states, only those states 

that report the VIN in their databases were 

included in logistic regression portion of this 

study. The VIN pattern and the SAS® code used 

to identify these vans in NCSA’s FARS and SDRS 

database are documented in the Appendices A 

and B, respectively, of this report. Vehicles from 

all model years were included in the study.

1.1 Vehicle Models and Exposure

The vans identified for inclusion in this study 

are the extended versions, where identifiable, of 

their series. Only the extended versions of the 

series can be configured to carry 15 passengers. 

However, it is conceivable that some unknown 

number of these vehicles left the manufacturer 

with seating for fewer than 15 persons, as the 

seating configuration/capacity is not reported in 

FARS, and also cannot be deciphered from the 

VIN. Also, there is flexibility to alter the seating 

capacity in such vans post-production for the 

purpose of carrying cargo, etc. 

Figure 1 shows the number of 15-passenger vans 

that were registered in the U.S. as of July 1 of 

each year. The chart shows more than a threefold increase in the estimated number of 15-

passenger vans from 1990 to 2002. According to 

the figures available to NHTSA as of July 1, 2002, 

about 500,000 15-passenger vans were registered 

in the U.S. This constitutes 0.25 percent of the 

passenger vehicle fleet (Passenger Cars, Light 

trucks and Vans) in the U.S. in 2002.
Analysis of Crashes Involving 15-Passenger Vans 5

2. 15-Passenger Vans Involved in

Fatal Crashes, 1990-2002

Data from NHTSA’s Fatality Analysis Reporting 

System (FARS) is used in this section to present 

raw cross tabulations in order to identify 

the circumstances surrounding fatal crashes

involving these vans during the twelve years 

from 1990 to 2002. It is important to note that 

fatal crash data provided in this section should 

2.1 Vehicles Involved and Fatalities

Vehicles Involved

In the period between 1990 and 2002, a total of 1,576 15-passenger vans were involved in fatal crashes 

resulting in 1,111 fatalities to occupants of such vans. Figure 2 shows the trend of the number of vans 

involved in fatal crashes.

not be used to interpret rollover propensity of 

vehicles, as the interpretation would be based 

on a small domain of crashes. Fatalities are a 

subsequent event to rollover causation where the 

crashworthiness of the vehicles and other factors 

like the use of restraints play a role in the severity 

of injuries. 
6 National Center for Statistics and Analysis - Technical Report

Vehicle Involvement Rate

Figure 3 presents the vehicle involvement rate in fatal crashes per 100,000 registered 15-passenger 

vans.

In the period from 1990 to 2002, the vehicle involvement rate per 100,000 registered vans decreased 

from 62.8 in 1990 to an all time low of 26.6 in 2002.

Fatalities

In crashes involving the 1,576 15-passenger vans between 1990 and 2002, fatalities occurred to 

occupants of 15-passenger vans, occupants of other vehicles that were also involved in the crash as 

well as nonoccupants (pedestrians and pedalcyclists). Figure 4 illustrates the trend of fatalities by the 

role of the persons killed in the crash. 
Analysis of Crashes Involving 15-Passenger Vans 7

Table 1 depicts the data underlying Figure 4.

As seen in Figure 4 and Table 1, about two-thirds of all fatalities in crashes involving 15-passenger 

vans in 2002 occurred to the occupants of the vans themselves. This proportion has increased from a 

low of 35 percent in 1990 to a high of 64 percent in 2001

Year Van Occupants Occupants of Other Vehicles Non-Occupants Total

1990 37 (35%) 50 (47%) 19 (18%) 106 (100%)

1991 39 (42%) 42 (45%) 12 (13%) 93 (100%)

1992 48 (41%) 57 (48%) 13 (11%) 118 (100%)

1993 48 (40%) 55 (46%) 17 (14%) 120 (100%)

1994 70 (49%) 56 (39%) 17 (12%) 143 (100%)

1995 94 (55%) 55 (32%) 23 (13%) 172 (100%)

1996 89 (52%) 58 (34%) 25 (15%) 172 (100%)

1997 108 (59%) 56 (31%) 19 (10%) 183 (100%)

1998 112 (54%) 82 (39%) 15 ( 7%) 209 (100%)

1999 116 (54%) 72 (33%) 27 (13%) 215 (100%)

2000 112 (57%) 69 (35%) 17 ( 9%) 198 (100%)

2001 130 (64%) 58 (28%) 16 ( 8%) 204 (100%)

2002 108 (60%) 56 (31%) 16 (9%) 180 (100%)

Total 1,111 (53%) 766 (36%) 236 (11%) 2,113 (100%)

Source: NCSA, FARS 1990-2001 (Final), 2002 (ARF)

Table1 - Fatalities in Crashes Involving 15-Passenger Vans by Person Role, 1990-2002

15-Passenger Van Occupant Fatalities by Crash Type

Figure 5 breaks down occupant fatalities by the type of the crash, i.e., if the 15-passenger van was 

involved in a single-vehicle or multiple-vehicle crash.
8 National Center for Statistics and Analysis - Technical Report

As seen in Table 2, about 62 percent (684/1,111) 

of fatalities to occupants of 15-passenger vans 

occur in single-vehicle crashes, i.e., the vans 

were the only vehicles involved in the crash, 

although there might have been pedestrians or 

pedal-cyclists involved in the crash. Some of the 

events that could result in single vehicle crashes 

are when the van hits a guardrail/tree or rolls 

over or a combination of the two. Table 3 depicts 

the distribution of the number of fatalities in the 

1,576 vehicles involved in fatal crashes. It can be 

inferred from the data in Table 3 that there were 

722 (1,576-854 [Table 3]) 15-passenger vans that 

had at least one fatally injured occupant. 

Of these 722 vehicles, 450 (657-207 [Table 3]) were 

involved in single-vehicle crashes accounting for 

684 fatalities to occupants of those vans.

Table 2 depicts the data underlying Figure 5.

Year

Single-Vehicle* Multiple-Vehicle All Crashes

Vehicles Fatalities Vehicles Fatalities Vehicles Fatalities

1990 32 22 58 15 90 37

1991 29 25 44 14 73 39

1992 31 23 62 25 93 48

1993 38 30 65 18 103 48

1994 42 36 68 34 110 70

1995 58 60 70 34 128 94

1996 64 56 69 33 133 89

1997 56 67 71 41 127 108

1998 59 62 99 50 158 112

1999 63 69 87 47 150 116

2000 60 81 71 31 131 112

2001 69 82 78 48 147 130

2002 56 71 77 37 133 108

Total 657 684 919 427 1,576 1,111

Source: NCSA, NHTSA, FARS 1990-2001 (Final), 2002 (ARF) Files

Table 2 - 15-Passenger Vans Involved in Fatal Crashes and Occupant Fatalities 

by Crash Type, 1990-2002 

*Some years have more vehicles than occupant fatalities as there are crashes with no 15-passenger van occupant fatality but a 

pedestrian or pedal-cyclist died in the crash.

Table 3 - 15-P Vans in Fatal Crashes, By Number 

of Fatally Injured Occupants in Van, 1990-2002

Fatalities in Vehicle

Number of Vehicles

All 

Crashes

Single-Vehicle 

Crashes

None 854 207

1 521 319

2 121 81

3 41 33

4 10 4

5 13 5

6 5 1

7 7 5

8 2 1

11 1 0

14 1 1

TOTAL 1,576 647
Analysis of Crashes Involving 15-Passenger Vans 9

Table 4 shows the occurrence of rollover in fatal 

crashes and the number of van occupants that 

were killed in these crashes between 1990 and 

2002. The rollovers shown in this table consist 

of all crashes for which rollover was a first or 

subsequent event. Rollover as a first event is 

About two-thirds (725/1,111) of the fatalities to 

occupants of 15-passenger vans occurred when 

the vans rolled over. Table 5 shows the vehicles 

Table 4 -15-Passenger Vans Involved and Occupant Fatalities by Rollover Occurrence, 1990-2002

Year

Rollovers No Rollovers All Crashes

Vehicles Fatalities Vehicles Fatalities Vehicles Fatalities

1990 21 23 69 14 90 37

1991 20 28 53 11 73 39

1992 25 21 68 27 93 48

1993 22 27 81 21 103 48

1994 29 42 81 28 110 70

1995 41 64 87 30 128 94

1996 41 52 92 37 133 89

1997 42 69 85 39 127 108

1998 53 71 105 41 158 112

1999 45 76 105 40 150 116

2000 55 91 76 21 131 112

2001 66 91 81 39 145 130

2002 50 70 83 38 133 108

Total 510 725 1,066 386 1,576 1,111

Source: NCSA, NHTSA, FARS 1990-2001 (Final), 2002 (ARF) Files

coded in those crashes where the First Harmful 

Event in the crash was a rollover. Rollover as a 

subsequent event is coded in those crashes where 

the vehicle rolled over after an initiating first 

harmful event (e.g., collision with a guard-rail etc 

or collision with another vehicle, etc.).

involved and the fatalities to occupants of these 

vehicles that rolled over (725 fatalities – Table 3) 

by the type of the crash.
10 National Center for Statistics and Analysis - Technical Report

More than three-quarters (556/725) of all fatalities 

that occurred in rollover crashes between 1990 

and 2002 were in vans involved in single-vehicle 

crashes. Single vehicle crashes are used as an 

exposure measure to assess the risk of rollover, as 

every single-vehicle crash is an opportunity for 

a rollover to occur. In single-vehicle crashes, the 

vehicle characteristics that contribute to rollover 

are not obscured by the effect of the forces of 

collision. Also, a majority of rollovers occur in 

single-vehicle crashes.

Table 5 - 15-Passenger Vans that Rolled Over and Subsequent Fatalities by Type of Crash, 1990-2002

Year

Single Vehicle Multiple Vehicle All Rollovers

Vehicles Fatalities Vehicles Fatalities Vehicles Fatalities

1990 12 17 9 6 21 23

1991 15 20 5 8 20 28

1992 15 16 10 5 25 21

1993 18 24 4 3 22 27

1994 19 25 10 17 29 42

1995 29 49 12 15 41 64

1996 31 42 10 10 41 52

1997 28 55 14 14 42 69

1998 35 49 18 22 53 71

1999 31 60 14 16 45 76

2000 39 72 16 19 55 91

2001 44 70 22 21 66 91

2002 33 57 17 13 50 70

Total 349 556 161 169 510 725

Source: NCSA, NHTSA, FARS 1990-2001 (Final), 2002 (ARF) Files

Table 6 shows the proportion of crashes when 

the van rolled over by the type of the crash. In 

2002, 15-passenger vans involved in fatal singlevehicle crashes were more than twice as likely 

to have rolled over as compared to those vans 

that were involved in multiple-vehicle crashes. 

Also, about 53 percent of the 15-passenger vans 

involved in fatal, single-vehicle crashes rolled 

over. This proportion has increased from a low of 

38 percent in 1990 to a high of 65 percent in 2000 

and has decreased to 59 percent in 2002.
Analysis of Crashes Involving 15-Passenger Vans 11

In the period from 1990 to 2002 about 68 percent 

(349/510) of all rollovers involving these vans 

occurred in single-vehicle crashes. Driver-related 

factors and vehicle dynamics (non-driver related 

factors) along with the influence of environmental 

Fifteen-passenger vans are equipped with a safety 

belt (lap or lap-shoulder belt) in every seating 

position (driver and 14 passengers). A total of 684 

occupants of 15-passenger vans were killed in a 

Table 6 - Proportion of 15-Passenger Vans Rollovers by Type of the Crash, 1990-2002

Year Single-Vehicle Crashes Multiple-Vehicle Crashes All Crashes

Crashes Rollovers % Crashes Rollovers % Crashes Rollovers %

1990 32 12 38% 58 9 16% 90 21 23%

1991 29 15 52% 44 5 11% 73 20 27%

1992 31 15 48% 62 10 16% 93 25 27%

1993 38 18 47% 65 4 6% 103 22 21%

1994 42 19 45% 68 10 15% 110 29 26%

1995 58 29 50% 70 12 17% 128 41 32%

1996 64 31 48% 69 10 14% 133 41 31%

1997 56 28 50% 71 14 20% 127 42 33%

1998 59 35 59% 99 18 18% 158 53 34%

1999 63 31 49% 87 14 16% 150 45 30%

2000 60 39 65% 71 16 23% 131 55 42%

2001 69 44 64% 78 22 28% 147 66 46%

2002 56 33 59% 77 17 22% 133 50 38%

Total 657 349 53% 919 161 18% 1,576 510 32%

Source: NCSA, NHTSA, FARS 1990-2001 (Final), 2002 (ARF) Files

factors can be contributing factors in a singlevehicle crash resulting in a rollover. There were 

657 such crashes from 1990 to 2002 resulting in 

556 fatalities of occupants of 15-passenger vans. 

2.2 Restraint Use Among Occupants of 

15-Passenger Vans

single-vehicle crash. Table 7 depicts the extent of 

restraint use among fatally injured occupants of 

15-passenger vans in single-vehicle crashes.
12 National Center for Statistics and Analysis - Technical Report

As shown in Table 7, 75.6 percent of 

the occupants killed in fatal singlevehicle crashes were not restrained, 

i.e., they were not wearing safetybelts or not properly restrained in 

child-safety seats, etc. The chance of 

a serious injury is higher when an 

occupant is not restrained, among 

other things, the chances of being 

ejected out of the vehicle increases. 

Fatality rates among non-ejected 

occupants are dramatically lower 

compared with the ejected 

occupants in the same crash 

(Winnicki, J. [2]).

As shown in Table 8, about 72 

percent (371/517) of the fatally 

injured, unrestrained occupants 

of 15-passenger vans in single 

vehicle crashes were ejected 

(partially or totally) from the 

van.

As seen in Table 9, an 

unrestrained occupant 

in a fatal, single vehicle 

crash involving a 

15-passenger van is 

about three times as 

likely to have been 

killed as compared to 

a restrained occupant 

(22 percent versus 8 

percent). The lack of 

data did not permit a 

more reasonable metric 

that would have been 

based the restraint usage rate among occupants in all crashes and the ensuing severity of injuries.

Table 10 depicts the proportion 

of fatally injured occupants, in 

2002, that were unrestrained by 

the type of vehicle that they were 

driving/riding in. Fatally injured 

occupants of 15-passenger vans 

and Pickup Trucks have the lowest 

rate of restraint use as compared 

to occupants of passenger cars, 

SUVs, and Vans.

Table 7 - Restraint Use Among Fatally Injured Occupants of 

15-Passenger Vans in Fatal, Single-Vehicle Crashes, 

1990-2002

Restraint Use Number Percent

Unrestrained 517 75.6

Restrained 95 13.9

Unknown 72 10.5

Total 684 100.0

Source: NCSA, NHTSA, FARS 1990-2001 (Final), 2002 (ARF) Files

Table 8 - Ejection and Restraint Use Among Fatally Injured 

Occupants of 15-Passenger Vans in Fatal, Single-Vehicle 

Crashes, 1990-2002

Restraint Use

Ejection

Ejected Not Ejected Unknown Total

Restrained 17 78 0 95

Unrestrained 371 134 12 517

Unknown 26 41 5 72

Total 414 253 17 684

Source: NCSA, NHTSA, FARS 1990-2001 (Final), 2002 (ARF) Files

Restraint Use Killed Survived Total p-value

Unrestrained 517 (22%) 1,816 (78%) 2,333 (100%) <0.0001

Restrained 95 ( 8%) 1,055 (92%) 1,150 (100%) <0.0001

Unknown 72 (88%) 420 (12%) 492 (100%) -

Total 684 (17%) 3,291 (83%) 3,975 (100%) -

Source: NCSA, NHTSA, FARS 1990-2001 (Final), 2002 (ARF) Files

Table 9 - Injury Severity by Restraint Use Among Occupants of 

15-Passenger Vans in Fatal Single-Vehicle Crashes, 1990-2002

Vehicle Type Restrained Unrestrained Unknown

Passenger Cars 30 62 8

SUVs 25 70 5

Pickup Trucks 18 76 6

Vans 26 65 9

15-Passenger Vans 14 76 11

Source: NCSA, NHTSA, FARS 2002 (ARF) Files

Table 10 - Restraint Use Among Fatally Injured Occupants in 

Single Vehicle Crashes by Vehicle Type, 2002
Analysis of Crashes Involving 15-Passenger Vans 13

Table 11 depicts the rate of fatal, single vehicle 

crashes per 100,000 registered vehicles by vehicle 

type from 1995 to 2002 [only back to 1995 as 

reliable registration data exists only back to that 

year]. As shown in Table 6, the number of 15-

passenger vans involved in fatal, single vehicle 

crashes per 100,000 registered vans has been 

2.3 Comparison with Other Vehicle Types

Involved in Fatal Crashes

Table 11 - Number of Fatal, Single-Vehicle Crashes per 100,000 Registered Vehicles, 1995-2001

Vehicle Type 1995 1996 1997 1998 1999 2000 2001

Passenger Cars 9.6 9.3 8.9 8.6 8.2 8.1 8.0

SUVs 14.3 14.1 13.6 13.3 13.0 12.7 11.8

Pickup Trucks 13.0 12.3 11.8 11.8 11.7 11.3 11.4

15-Passenger Vans 19.8 19.6 14.7 14.3 14.2 12.9 13.9

Other Vans 7.3 7.4 7.5 7.7 7.4 7.2 6.5

Source: NCSA, NHTSA, FARS 1990-2001 (Final), 2002 (ARF) Files, R.L.Polk and Company NVPP Registration Data

decreasing since 1995, but is still higher than 

other categories of passenger vehicles like cars, 

SUVs, other vans, etc. The higher rate of fatal, 

single-vehicle crashes is also due to the fact that 

the occupancy levels in these vans are larger than 

those in the smaller passenger vehicles and this 

in turn results in a higher probability of at least 

one occupant fatality in the van.
14 National Center for Statistics and Analysis - Technical Report
Analysis of Crashes Involving 15-Passenger Vans 15

3. Analysis Using Crash Data from NHTSA’s 

State Data System (SDS)

The descriptive statistics in the previous section 

were based on data on fatal crashes, i.e., crashes 

that resulted in at least one fatally injured person. 

This section presents a detailed analysis of crash 

data from five states that are part of NHTSA’s 

State Data System (SDS). The data are a census 

of all police-reported crashes in that state 

3.1 Data and Methodology

 NHTSA’s state data system consists of crash 

data from seventeen participating states. 

However, not all states report the Vehicle 

Identification Number (VIN) that is necessary 

to identify 15-passenger vans. The five states 

that report VINs were chosen for this study. 

Data, spanning multiple years from these 

states, were included in this analysis. Table 12 

depicts the states chosen and the years of data 

included. In order to identify vehicle types 

(e.g., passenger cars, SUVs, 15-passenger vans, 

etc.), the VIN was decoded to extract vehicle 

model codes. These codes are stored as part 

of a supplemental analytic file in the SDS. The 

model year of the vehicle is also derived in this 

manner. Other variables of interest were all 

re-coded into a uniform variable for analysis. 

These variables included rollover occurrence, 

occupancy1, age of the driver, driver impairment, 

weather conditions, roadway surface conditions, 

speed-limit (as a proxy for travel speed). The 

variables and data chosen are along the lines of 

those chosen for NHTSA’s Rollover Assessment 

Program that generates star-ratings for rollover 

risk of passenger vehicles. Of particular interest 

are single vehicle crashes involving these 

vehicles. Single vehicle crashes are used as an 

exposure measure to assess the risk of rollover, as 

every single-vehicle crash is an opportunity for a 

rollover to occur. In single-vehicle crashes, the 

vehicle characteristics that contribute to rollover 

are not obscured by the effect of the forces of 

collision. Also, a majority of rollovers occur in 

single-vehicle crashes.

The results from the analysis of the state data 

are presented in two parts – a descriptive part 

outlining summary crash data by vehicle type 

containing rollover and crash ratios and an 

analytic part containing the results of a logistic 

regression model to predict rollover as an 

outcome conditional on given vehicle, driver and 

environmental characteristics.

1

 Occupancy is derived by adding up the number of occupants in the person level file. All states chosen for this analysis report all persons, 

injured or uninjured, involved in the crash. For this reason, the Missouri data, while fulfilling other requirements, was dropped from this 

analysis as not all uninjured persons are reported in the data.

States Years

Florida 1994 to 2001

Maryland 1994 to 2001

North Carolina 1994 to 1999

Pennsylvania 1994 to 2000

Utah 1994 to 2001

Source: NHTSA State Data Reporting System 

(SDRS)

Table 12 - States and Years of Data Chosen 

for Analysis

comprising of serious crashes (those resulting 

in a fatality or injury) as well as those that only 

resulted in damage to property. Consequently, 

the data are representative of the population of 

police-reported crashes in these states for those 

years. 
16 National Center for Statistics and Analysis - Technical Report

The data in this section will describe the 

occurrence of crashes and rollovers by vehicle 

type. The major vehicle categories chosen for 

analysis are 

• Sport Utility Vehicles (SUVs)

• Pickup Trucks (Pickups)

• Minivans

• Passenger Cars

• 15-Passenger Vans

• Other Vans

• Others/Unknown

The metric that will be used in this section, for 

a given crash type, is the ratio of vehicles that 

rolled over to number of vehicles involved in a 

given type of crash. This metric will be used to 

compare the 15-passenger van’s ‘propensity’ to 

rollover as compared to that for other vehicles. 

At this stage, it is important to highlight the 

differences between the handling characteristics 

of a vehicle and its resistance to rollover. Some 

vehicle characteristics, such as handling problems, 

may result in a relatively high frequency of single 

vehicle crashes. The vehicle’s rollover resistance 

can then be assessed by whether a single vehicle 

crash results in a rollover. The vehicle’s rollover 

resistance is measured by the propensity of the 

vehicle to roll over, conditional on a single vehicle 

crash having occurred.

Table 13 presents the overall picture on the 

number of crashes by vehicle type as reported to 

the six states used in this analysis.

Single-vehicle crashes, expressed as a percentage 

of all crashes, have low rates of incidence for 

15-passenger vans as compared to other vehicle 

types. About 9 percent of all crashes involving 

15-passenger vans were single vehicle crashes. 

The incidence of single-vehicle crashes as a 

proportion of all crashes was the lowest for 

Minivans (8 percent) and highest for SUVs (14 

percent). So overall, it seems that 15-passenger 

vans do not have any unusual handling issues, 

which would have manifested itself in a higher 

incidence of single vehicle crashes, as compared 

to the other types of vehicles. Also, there may 

be various driver characteristics, including 

some not reported/measured, may contribute 

to a relatively higher incidence of single-vehicle 

crashes. Making the analysis of rollovers 

conditional on being in a single-vehicle crash 

also captures these factors.

3.2 Descriptive Statistics

Vehicle Type

All Crashes Single Vehicle Crash Multiple Vehicle Crash

Vehicles Vehicles Percent Vehicles Percent

15-P Vans 15,622 1,441 9.22% 14,181 90.78%

Passenger Cars 3,625,467 423,760 11.69% 3,201,707 88.31%

SUVs 440,917 61,968 14.05% 378,949 85.95%

Pickup Trucks 752,814 98,282 13.06% 654,532 86.94%

Minivans 202,429 16,205 8.01% 186,224 91.99%

Other Vans 170,105 15,745 9.26% 154,360 90.74%

Other/Unknown 615,555 71,855 11.67% 543,700 88.33%

Total 5,822,909 689,256 11.84% 5,133,653 88.16%

Source: NHTSA State Data Reporting System (SDRS) FL, MD, NC, PA and UT data.

Table 13 - Vehicles Involved in Crashes by Crash Type and Type of Vehicle
Analysis of Crashes Involving 15-Passenger Vans 17

Table 14 depicts the incidence of rollover by 

vehicle type and type of crash (single or multiple 

vehicle). Single vehicle crashes are the preferred 

domain of analysis as the vehicle dynamics are 

more likely to have played a part in rollover 

causation as compared to multiple vehicle 

crashes, where the impact dynamics can also 

play a role.

Overall, the incidence of rollover in single 

vehicle crashes for 15-passenger vans, expressed, 

as a percentage of vehicles involved in such 

crashes, is comparable with those for other types 

of vehicles. SUVs had the highest incidence (39 

percent) among all the vehicle categories while 

passenger cars had the lowest incidence rates (16 

percent). However, the issue at hand is to analyze 

the rate of rollover at various occupancies for the 

different vehicle types. Prior research (Garrott, 

et. al) has indicated that the rate of rollover for 

15-passenger vans increases three-fold when the 

vans have 10 occupants or more as compared to 

those that have fewer than 10 occupants.

Vehicle Type

Single Vehicle Crashes Multiple Vehicle Crashes All Crashes

Crashes Rollovers % Crashes Rollovers % Crashes Rollovers %

15-P Vans 1,441 315 22 14,181 172 1 15,622 487 3

Passenger Cars 423,760 66,318 16 3,201,707 24,320 1 3,625,467 90,638 3

SUVs 61,968 23,927 39 378,949 9,625 3 440,917 33,552 8

Pickup Trucks 98,282 26,187 27 654,532 9,936 2 752,814 36,123 5

Minivans 16,205 2,746 17 186,224 2,389 1 202,429 5,135 3

Other Vans 15,745 3,592 23 154,360 2,476 2 170,105 6,068 4

Other/Unknown 71,855 14,491 - 543,700 7,943 - 615,555 22,434 -

Total 689,256 137,576 20 5,133,653 56,861 1 5,822,909 194,437 3

Source: NHTSA State Data Reporting System (SDRS) FL, MD, NC, PA and UT data.

Table 14 - Crashes and Rollovers by Crashes Type and Type of Vehicle
18 National Center for Statistics and Analysis - Technical Report

Fully loaded conditions for the various vehicle 

categories are shown in Table 15. It is entirely 

conceivable that some individual models within 

a vehicle category might have a higher seating 

capacity than the one indicated in Table 15. 

Figure 6 depicts the rate of rollover in single 

vehicle crashes for the different vehicle types 

by occupancy. It is to be noted that in the chart, 

occupancy of 4 for passenger cars, pickup trucks 

and SUVs is actually 4 or more, occupancy of 

7 is actually 7 or more occupants. It is entirely 

conceivable that some of the vehicles may have 

a designed seating capacity that exceeds those 

shown in Table 13. It is not possible to identify 

the seating configuration of passenger vehicles 

from NHTSA’s databases or VINs. Also vehicles 

with much larger seating capacities than those 

mentioned in Table 13, especially SUVs, have 

been late entrants to the fleet. The latest data 

year in this analysis was 2001 and it is reasonable 

to assume that the fleet was heavily weighted 

towards the seating capacities mentioned in 

Table 13.

Figure 6 compares the rates of rollover for 

various vehicle types by when they are loaded to 

half or under their seating capacity versus over 

half their seating capacity. For the sake of this 

analysis, passenger cars, SUVs and pickup trucks 

with two occupants or less, minivans with three 

occupants or less and 15-passenger vans with 

seven occupants or less are defined as vehicles 

loaded to half their capacity or under.

Occupancy and Rate of Rollover

Vehicle Type Number of 

Occupants

15-Passenger Van 15+

Passenger Cars 4+

SUVs 4+

Pickup Trucks 4+

Minivans 7+

Table 15 - Occupancies Assumed as FullyLoaded Conditions by Type of Vehicles
Analysis of Crashes Involving 15-Passenger Vans 19

As seen in Figure 7, when the vehicles are loaded 

to more than half of their seating capacity, the 

rates of rollover are higher as compared to when 

they are loaded to half their seating capacity 

or less. However, the relative difference in the 

rates of rollover under the two different loading 

scenarios is most pronounced for 15-passenger 

vans. This relative difference is shown in Table 

16 for other vehicle categories. It is noted that a 

15-passenger van that is loaded to half its 

designed seating capacity has as many occupants 

as any other type of passenger vehicle that is fully 

loaded. The differences for all vehicle categories 

are statistically significant, as indicated by the 

p-values in Table 16.

As shown in Table 16, occupancy seems to have 

a pronounced effect on the rates of rollover 

observed in single vehicle crashes. However, 

there are factors other than occupancy that can 

have an adverse effect on a vehicles propensity to 

roll over. These may include the speed of travel, 

surface and weather conditions, experience/

training of the driver and impaired driving. 

The speed of travel can be a significant factor in 

affecting rollover outcome because greater travel 

speed of the vehicle provides more energy to 

initiate rollover. Figure 7 un-confounds the effect 

of speed on the proportions shown in Figure 7. In 

the absence of reliable measures of travel speed, 

the posted speed limit at the scene of the crash is 

used as a proxy for the speed of travel. Figure 7 

shows, by vehicle type, the composition of the 

rollovers by occupancy and the speed limit of the 

road they were traveling at the time of the crash. 

The percentages in each of the bars in Figure 8 

indicate the proportion of the rollovers in that 

category that occurred on high-speed roads (50+ 

mph). So, 62 percent of rollovers of 15-passenger 

vans that loaded to half or under half of their 

designed capacity were in high-speed roads. In 

comparison, 91 percent of rollovers involving 15-

passenger vans that were loaded at or above half 

their designed seating capacity occurred on highspeed roads.

The data in Figure 7 indicate that a great 

proportion of rollovers of 15-passenger vans in 

heavily loaded scenarios occur on high-speed 

roads, as compared to other types of vehicles. It 

is appropriate to examine if 15-passenger vans 

traveling on high-speed roads, when loaded at or 

above half their seating capacity, have a higher 

risk of rollover as compared to other types of 

vehicles under similar circumstances. Table 17 

examines this issue by comparing the rate of 

rollover under various combinations of speed 

and occupancy for the various types of vehicles 

involved in single-vehicle crashes. The terms 

lightly-loaded and heavily-loaded have been 

used loosely to define loading conditions above 

and below half the designed seating capacity.

Vehicle Type Half the Seating 

Capacity or Under

Over Half the 

Seating Capacity

Relative 

Difference(Ratio)

Statistical 

Significance

15-Passenger Van 20% 44% 2.2 p<0.0001

Passenger Cars 15% 19% 1.3 p<0.0001

SUVs 37% 50% 1.4 p<0.0001

Pickup Trucks 26% 34% 1.3 p<0.0001

Minivans 16% 26% 1.7 p<0.0001

NHTSA State Data Reporting System (SDRS) FL, MD, NC, PA and UT data.

Table 16 - Rollover Rates by Occupancy and Vehicle Type in Single Vehicle Crashes
20 National Center for Statistics and Analysis - Technical Report

As shown in Table 17, 15-passenger vans seem to 

have the highest risk of rolling over under heavily 

loaded scenarios in high-speed roads. Under 

similar circumstances, SUVs have comparable 

risks of rollover too. It is to be noted that the 

sample size of crashes for 15-passenger vans is 

significantly smaller than those for other types 

of vehicles. However, the number of crashes 

involving 15-passenger vans in these categories 

is large enough to perform a statistically valid 

comparison with other types of vehicles. Even 

though the crude rate of rollover on high-speed 

roads under heavily loaded scenarios for 15-

passenger vans is comparable with SUVs, it 

is much higher than the rate for other types of 

vehicles. It will be noteworthy to examine the 

relative disparity in the rates of rollover between 

heavily loaded and lightly loaded scenarios on 

high speed roads. Table 18 depicts this relative 

risk ratio.

The disparity in the rates of rollover between 

Scenario 15-P Vans Cars SUVs Pickup Trucks Minivans

Lightly Loaded+ Low Speed 

Roads

11.7% 

[727]

11.5% 

[216,447]

29.8%

[29,922]

19.6%

[48,512]

11.1%

[8,364]

Lightly Loaded+ High Speed 

Roads

29.6% 

[458]

22.2%

[141,389]

49.2%

[20,793]

35.8%

[37,204]

25.6%

[5,077]

Heavily Loaded+ Low Speed 

Roads

13.2% 

[ 38]

13.8%

[3,038]

39.0%

[3,379]

25.8%

[2,918]

13.7%

[619]

Heavily Loaded+ High Speed 

Roads

61.6% 

[ 86]

25.7%

[4,897]

60.5%

[3,565]

42.8%

[2,673]

33.7%

[1,050]

Source: NHTSA State Data Reporting System (SDRS) FL, MD, NC, PA and UT data.

Table 17 - Rates of Rollover [Sample Size of Crashes] for Various Scenarios of 

Occupancy and Speed Limit for Vehicles Involved in Single Vehicle Crashes
Analysis of Crashes Involving 15-Passenger Vans 21

Vehicle Type Half the Seating 

Capacity or Under

Over Half the Seating 

Capacity Relative Difference (Ratio)

15-Passenger Van 29.6% 61.6% 2.08

Passenger Cars 22.2% 25.7% 1.16

SUVs 49.2% 60.5% 1.23

Pickup Trucks 35.8% 42.8% 1.20

Minivans 25.6% 33.7% 1.32

Source: NHTSA State Data Reporting System (SDRS) FL, MD, NC, PA and UT data.

Table 18 - Rollover Rates by Occupancy and Vehicle Type in Single Vehicle Crashes in 

High-Speed Roads (50+ mph)

light and heavy loading conditions on highspeed roads is the largest for 15-passenger 

vans. However, one can assess the true effect 

of occupancy on rollover propensity by taking 

into account the effect of various other factors 

that can affect rollover outcome. Statistically, 

a logistic regression model is very suitable to 

predict rollover as a dichotomous outcome (yes 

or no), based on explanatory variables. Logistic 

regression permits the joint estimation of the 

effect or significance of a variable in affecting 

rollover.
22 National Center for Statistics and Analysis - Technical Report

The logit model is a regression model that is 

tailored to fit a dichotomous dependent variable, 

in this case, the occurrence or non-occurrence 

of rollover. The independent variables can be 

quantitative (e.g., number of occupants from 1 

to 15+) or dichotomous (drinking/no drinking, 

etc.).

To appreciate the logit model, it is helpful to 

have an understanding of odds and odds ratios. 

Probabilities quantify the chances that an event 

will occur. The probability that a rollover will 

occur ranges from 0 to 1, with a 0 meaning that 

the event will almost certainly not occur, and a 

1 meaning that the event will almost certainly 

occur. Odds of a rollover is the ratio of the 

expected number of times that an event will 

occur to the expected number of times it will not 

occur. An odds of 2 means that twice as many 

occurrences as non-occurrences can be expected. 

Similarly, an odds of 1⁄4 means that one-fourth 

as many occurrences as non-occurrences are 

expected. So, if p is the probability of rollover 

and O is the odds of rollover, then:

If the value of the odds is less than 1, the 

probability of rollover is below 0.5, while odds 

greater than 1 correspond to probabilities greater 

than 0.5. Like probabilities, odds have a lower 

bound of 0 but there is no upper bound on odds. 

Odds are a more sensible scale for multiplicative 

comparisons. For example, if vehicle 1 is 

observed to have a probability of rollover of 0.30 

and vehicle 2 has a probability of rollover of 0.60, 

then it is reasonable to claim that the probability 

of vehicle 2 rolling over is twice as great as the 

probability of vehicle 1 rolling over. However, 

no vehicle can have twice as much probability of 

rolling over as vehicle 2 (probability of 0.6x2=1.2 

is not possible). On the odds scale, there are no 

limitations on multiplicative comparisons. A 

probability of 0.60 corresponds to odds of 1.5. 

Doubling odds of 1.5 yields odds of 3 which 

converts back to a probability of 0.75. This 

leads to the concept of odds ratios, a widely 

used measure of relationship between two 

dichotomous variables.

It is implicit in much of the literature on 

categorical data analysis that odds ratios are less 

sensitive to changes in marginal frequencies (e.g., 

the total number of rollovers and non-rollovers) 

than other measures of association. They are 

generally regarded as fundamental descriptions 

of the relationship between the variables of 

interest. Importantly, odds ratios are directly 

related to the parameters in the logit model.

3.3 Logistic Regression Analysis
Analysis of Crashes Involving 15-Passenger Vans 23

The Logit Model

The binary response model for rollovers states 

that the probability of rollover, conditional on 

a single-vehicle crash having occurred, is a 

function of selected explanatory variables. It 

Y denotes the dependent variable in a binaryresponse model for rollovers, Y is equal to 1 if 

there is a rollover and 0 otherwise. The goal is 

to statistically estimate the probability that Y=1, 

considered as a function of explanatory variables. 

The logit model, which is a widely used binaryresponse model for rollover is:

This model can be rewritten, after taking the 

natural logarithm of both sides as:

where � is the intercept and � is the vector of 

coefficients and x is the vector of explanatory 

variables. The logistic regression analysis has 

been performed in two ways – independently 

for each vehicle type to assess the effect of 

various factors in predicting rollover as well as 

a model for the vehicle population as a whole

with design variables accounting for differences 

between the vehicle types.
24 National Center for Statistics and Analysis - Technical Report

The explanatory variables used to model rollover as an outcome are shown in Table 19. The model 

uses metrics to represent various crash and driver-related characteristics and more importantly, the 

number of occupants in the vehicle. That is, for each vehicle type:

Logit (Pr(Rollover)) = OCCUPANCY STORM FAST HILL CURVE BADSURF MALE YOUNG OLD DRINK 

DUMMYFL DUMMYMD DUMMYNC DUMMYPA DUMMYUT.

The factors used in the model mirror those used in NHTSA’s National Car Assessment Program 

(NCAP) studies.

Also included in the regression model were five variables DummyFL, DummyMD, DummyNC, 

DummyPA and DummyUT. The variables DUMMY<state> represent the change in Logit(Pr(Rollover)) 

due to the crash’s taking place in that state as compared to an otherwise similar crash in Florida. 

They are included to control for differences in traffic patterns and reporting practices that effect 

rollover rates between the states. The roadway function class, i.e., if the site of the crash was a rural 

or urban area, was not used in the regression due to the unavailability of the data. However, it may 

be assumed that speed limit, curve and roadway surface conditions are reasonable explanatory 

variables to account for the rural/urban dichotomy. For each value of occupancy, the proportion of 

rollovers predicted by the model is computed by summing the predicted probabilities of rollover for 

all of the cases with that occupancy and dividing by the number of cases with that occupancy. 

 Table 16 presents the results of the logit model in terms of odds-ratios and significance parameters 

(p-values). The regression was done within each vehicle type in order to assess the effect of the 

various covariates on rollover outcome. Table 20 presents the odds ratios for the regression analysis 

on single vehicle crashes involving 15-passenger vans only. 

3.3.1 Logistic Regression Analysis Performed 

Independently for Each Type of Vehicle

Variable Description Levels

Occ Number of Occupants 1 to 15+

Dark Light Condition 1 if dark; 0 if not dark

Storm Stormy Weather 1 if stormy; 0 if not

Fast Speed (Speed Limit as Proxy) 1 if 50+ mph else 0

Hill Hilly Gradient 1 if yes else 0

Curve Road Curves 1 if yes else 0

Badsurf Adverse Roadway Surface Conditions 1 if yes else 0

Male Male Driver 1 if yes else 0

Young Young Driver 1 if yes else 0

Drink Driver Impairment 1 if yes else 0

Table 19 - Explanatory (Independent) Variables in Logistic Regression Model
Analysis of Crashes Involving 15-Passenger Vans 25

Odds ratios can be interpreted as tools for 

multiplicative comparisons with respect to a 

reference value. For example, an odds ratio of 5 

for fast indicates that the odds of a rollover on a 

road with a high speed limit (50 mph or above) is 

about five times as high as that in a lower speed 

road (under 50 mph), conditional on being in a 

single vehicle crash.

The joint estimation using the logistic regression 

model reveals that the variables with the most 

significant impact on rollover outcome, as 

indicated by their p-values, are:

• Fast (high-speed road)

• Occupancy (number of occupants in 

the vehicle)

• Curve (curved geometry at site)

The effect of these factors on rollover outcome 

is also statistically significant as indicated by the 

low p-values.

As seen in Table 20, each unit increase in 

occupancy increases the odds of a rollover by 

close to 12 percent (from 1 to 1.120 or 12 percent), 

conditional on being in a single-vehicle crash.

Also, the odds of a rollover on a road with a high 

speed limit (FAST: 50 mph or above) is about 

five times as high as that in a lower speed road, 

conditional on being in a single vehicle crash.

The odds of a rollover on a curved road (CURVE) 

increase by 99 percent over the odds of rolling 

over on a straight road.

A comparison of the odds-ratio estimates of 

the three statistically significant factors (Speed, 

occupancy, adverse weather and road geometry) 

for 15-passenger vans with the corresponding 

odds-ratios for other vehicle types is illustrated 

in Table 21.

As seen in Table 21, the three factors that were 

significant in predicting rollover of 15-passenger 

Interpretation of Odds Ratios

Variable Odds Ratio Coefficient P-value (Chi Sq.)

Intercept NA -2.1178 < 0.0001

Occupancy 1.120 0.1135 <0.0001

Dark 1.200 0.1821 0.2944

Storm 1.351 0.3011 0.1468

Fast 5.022 1.6138 <0.0001

Hill 1.087 0.0836 0.6368

Curve 1.989 0.6874 0.0001

badsurf 0.980 -0.0207 0.9237

Male 1.036 0.0349 0.8486

Young 1.222 0.2005 0.2819

Old 0.845 -0.1687 0.7613

Drink 0.811 -0.2091 0.5205

p-value for entire model: <0.0001

Source: NHTSA State Data Reporting System (SDRS) FL, MD, NC, PA and UT data.

Table 20 - Logistic Regression Predicting Rollover in Single-Vehicle Crashes, 15-Passenger Vans
26 National Center for Statistics and Analysis - Technical Report

vans in single vehicle crashes were also significant 

for other types of vehicles. For 15-Passenger 

vans, a unit increase in occupancy, controlling 

for other factors, contributes to a 12 percent (odds 

ratio of 1.120) increase in the predicted odds of 

rollover, conditional on being in a single vehicle 

crash. An odds-ratio of 1.12 for occupancy 

implies that for every unit increase in occupancy, 

the odds of a rollover are increased 1.12 times 

– an increase of 12 percent. In order to determine 

the effect of increasing occupancy on rollover, 

it is helpful to understand the multiplicative 

nature of odds ratios for different increments 

of occupancy. If O is the odds ratio for a unit 

occupancy, then the odds ratio for k occupants is 

Ok. Correspondingly, when loaded to the design 

capacity of 15 occupants, the odds ratio would be 

5.47 [1.1215]. Correspondingly, when passenger 

cars are loaded to their capacity, the odds ratio 

increases to 1.27 (1.0614), or, just a 27 percent 

increase. Table 22 depicts these comparisons 

by vehicle type. The odds ratio at the designed 

seating capacity show the most pronounced effect 

for 15-passenger vans followed by Minivans, 

SUVs, Pickup Trucks and Passenger Cars.

In terms of change in the odds of rollover per 

unit increase in occupancy, 15-passenger vans 

compare on the same scale as other types of 

vehicles. However, the large multiplicative 

factor in terms of the number of occupants 

correspondingly predict much higher odds of 

rollover at designed seating capacity as compared 

to other types of vehicles. In fact, they have about 

2.7 [5.41/2.01] times the odds ratio of rollover as 

Vehicle Type Variable Odds Ratio P-value (Chi Sq.)

15-Passenger Vans

Occupancy 1.120 <0.0001

Fast 5.022 <0.0001

Curve 1.989 0.0001

Passenger Cars

Occupancy 1.061 <0.0001

Fast 2.454 <0.0001

Curve 1.889 <0.0001

SUVs

Occupancy 1.211 <0.0001

Fast 2.626 <0.0001

Curve 1.605 <0.0001

Pickup Trucks

Occupancy 1.134 <0.0001

Fast 2.669 <0.0001

Curve 1.827 <0.0001

Minivans

Occupancy 1.123 <0.0001

Fast 3.213 <0.0001

Curve 1.664 <0.0001

Source: NHTSA State Data Reporting System (SDRS) FL, MD, NC, PA and UT data.

Table 21 - Odds-Ratio Estimates of Occupancy, Road Curvature and Speed in Logit Model Predicting 

Rollover in Single-Vehicle Crashes, by Vehicle Type

15-Passenger Vans (15+) 5.47

Passenger Cars (4+) 1.27

SUVs (4+) 2.15

Pickup Trucks (4+) 1.65

Minivans (7+) 2.01

Source: Logistic Regression on FL, MD,NC, PA and 

UT Data.

Table 22 - Odds-Ratio Estimates at Full 

Occupancy, by Vehicle Type
Analysis of Crashes Involving 15-Passenger Vans 27

compared to minivans at full occupancy, which 

is about half the capacity of 15-passenger vans. 

Also, 15-passenger vans have an estimated odds 

ratio of 4.3 times [5.47/1.27] that of passenger cars 

and pickup trucks when loaded to the designed 

seating capacity. The corresponding ratio when 

compared with SUVs is about 2.54 [5.47/2.15].

For the sake of comparison with Minivans, 

at occupancy level of 7, the odds-ratio for 15-

passenger vans is 2.21 [1.127] – pointing to a twofold increase in the odds of rollover. Similarly, 

at an occupancy level of 4, the odds-ratio for 15-

passenger vans is 1.57 [1.124] – pointing to a 57 

percent increase in the odds of rollover.

The explanatory variables used to model rollover 

as an outcome are shown in Table 23. The model 

uses metrics to represent various crash and driverrelated characteristics and more importantly, the 

number of occupants in the vehicle. 

Logit (Pr(Rollover)) = OCCUPANCY STORM 

FAST HILL CURVE BADSURF MALE YOUNG 

OLD DRINK DUMMYMD DUMMYNC 

DUMMYPA DUMMYUT D_CAR D_SUV D_

PICKUP D_MINIVAN

3.3.2 Logistic Regression Analysis Performed for the 

Vehicle Population as a Whole

This model will facilitate a comparison between 

the different vehicle types after adjusting for all 

other factors, including occupancy. The design 

variables D_CAR D_SUV D_PICKUP and D_

MINIVAN will account for overall differences 

in the geometry and features by the type of the 

vehicle. It is to be noted that the design variables 

average out the differences that might exist within 

a vehicle type, for example a compact sedan 

versus a large passenger car. This type of analysis 

is meant to provide insight into differences that 

might exist between different vehicle types in 

an overall sense and should not be interpreted 

for individual vehicle models within a vehicle 

category.
28 National Center for Statistics and Analysis - Technical Report

The logistic regression yields the parameter estimates and odds ratios for the various factors as 

shown in Table 24.

Variable Description Levels

Occ Number of Occupants 1 to 15+

Dark Light Condition 1 if dark; 0 if not dark

Storm Stormy Weather 1 if stormy; 0 if not

Fast Speed (Speed Limit as Proxy) 1 if 50+ mph else 0

Hill Hilly Gradient 1 if yes else 0

Curve Road Curves 1 if yes else 0

Badsurf Adverse Roadway Surface Conditions 1 if yes else 0

Male Male Driver 1 if yes else 0

Young Young Driver 1 if yes else 0

Drink Driver Impairment 1 if yes else 0

D_CAR Design Variable for Cars 1 is Passenger Car else 0

D_SUV Design Variable for SUVs 1 is SUV else 0

D_PICKUP Design Variable for Pickups 1 is Pickup else 0

D_MINIVAN Design Variable for Minivans 1 is Minivan else 0

Variable Odds Ratio Coefficient P-value (Chi Sq.)

Intercept NA -1.8774 < 0.0001

Occupancy 1.095 0.0905 <0.0001

Dark 0.967 -0.0335 <0.0001

Storm 0.861 -0.1500 <0.0001

Fast 2.605 0.9574 <0.0001

Hill 1.141 0.1319 <0.0001

Curve 1.844 0.6119 <0.0001

badsurf 0.877 -0.1318 <0.0001

Male 0.995 -0.00534 0.4986

Young 1.344 0.2957 <0.0001

Old 0.667 -0.4056 <0.0001

Drink 1.266 0.2362 <0.0001

D_CAR 0.654 -0.4239 <0.0001

D_SUV 2.405 0.8777 <0.0001

D_PICKUP 1.261 0.2322 <0.0001

D_MINIVAN 0.817 -0.2016 <0.0001

p-value for entire model: <0.0001

Source: Logistic Regression on FL, MD, NC,PA and UT Data.

Table 23 - Explanatory (Independent) Variables in Logistic Regression Model

Table 24 - Logistic Regression Predicting Rollover in Single-Vehicle Crashes, All Vehicles
Analysis of Crashes Involving 15-Passenger Vans 29

Plugging the coefficients, the logistic regression model yields predicted probability of rollover as 

shown in Figure 8. Figure 8 represents the probability distribution of rollover, conditional on a single 

vehicle crash, for what can be considered as a “best-case” scenario in terms of factors that affect 

rollover as an outcome. The “favorable” scenario is a combination of favorable driving conditions 

and factors for the terms included in the logistic regression model. This includes good light and 

weather conditions, low-speed road (under 50 mph), flat terrain, straight and good road conditions 

and no driver impairment.

Figure 9 depicts the distribution of the probability of rollover for what can be considered as a 

“adverse” scenario to affect rollover. The adverse scenario includes statistically significant variables, 

fast and curve. The probabilities depicted in Figure 9 are for crashes occurring on curved areas on 

high-speed roads.

As seen in Figures 8 and 9, the probability of rollover as indicated by the logistic regression model 
30 National Center for Statistics and Analysis - Technical Report

indicates a progressively worsening risk of rollover with increasing occupancy for all vehicle types 

including 15-passenger vans. The probability of rollover with just the driver in the vehicle ranges 

from under 0.20 in favorable conditions to above 0.4 in adverse conditions. However, when the 

van is loaded to or above its designed seating capacity, the corresponding probabilities increase to 

an estimated 0.40 and 0.80, respectively. This trend, while observed for all types of vehicles, is most 

pronounced for 15-passenger vans because of the sheer multiplicative effect of the larger seating 

capacity for 15-passenger vans. Figure 10 depicts various regression curves that depict how the 

probability of rollover in single vehicle crashes involving 15-passenger vans change upon the addition 

of various adverse factors that can be considered to affect rollover as an outcome.

Figure 10 depicts the relative shifts in the estimated probabilities of rollover of a 15-passenger van by 

occupancy, conditional on being in a single vehicle crash, for various combinations of scenarios that 

could affect rollover outcome. As expected, the probability curves have higher starting values (at 

Occupancy=1) for more adverse scenarios but follow a more or less progressively worsening rollover 

rate with increasing 
Analysis of Crashes Involving 15-Passenger Vans 31

The purpose of this report was to analyze the 

circumstances in crashes that resulted in the 

rollover of a 15-passenger van. State crash data 

from five states in the period from 1994 to 2001 

were used to identify vehicle, environmental 

and driver related factors that were significant 

in affecting rollovers in single vehicle crashes 

involving these vans. Of particular interest 

was the effect on increasing occupancy on the 

rollover propensity of 15-passenger vans. For 

comparison, similar analyses were performed 

for other types of passenger vehicles (SUVs, 

Pickup Trucks, Minivans and Passenger Cars). 

Also, NHTSA’s FARS data from 1990 to 2002 

were used to examine the circumstances in 

fatal, rollover crashes involving 15-passenger 

vans. The extent of seat belt use among fatally 

injured occupants of 15-passenger vans was 

compared with that of occupants of other types 

of vehicles. While comparisons can be made of 

restraint use among fatally injured occupants 

of different vehicle types, the true extent of belt 

usage can only be assessed by analyzing data 

that is representative of all crashes – data that is 

not presently available.

The overall rate of rollover in single vehicle 

crashes, as observed from NHTSA’s State Data, 

for 15-passenger van is in fact lower than that for 

SUVs and Pickup Trucks. However, the effect of 

occupancy is observed to have a wider disparity 

in rollover rates in 15-passenger vans between 

conditions when the vehicle was loaded above or 

below half its designed seating capacity. In fact, 

when loaded to above half their seating capacity, 

15-passenger vans were observed to have 2.2 

times the rollover rate as compared to when 

they were loaded to or below half their designed 

seating capacity. This compares to lower ratios 

for SUVs (1.4), Pickup Trucks (1.3), Passenger 

Cars (1.3) and Minivans (1.7).

A majority of the high occupancy level rollovers 

involving 15-passenger vans were in high-speed 

roads (50+ mph). However, conditional on a 

crash having occurred on a high-speed road, the 

disparity in the rollover rates between scenarios 

when they were loaded to or below half their 

seating capacity and when they were loaded 

above half the designed seating capacity was 

most pronounced for 15-passenger vans. The 

rollover rate under the heavily-loaded scenario 

was again more than 2 times the rate under the 

lightly loaded scenario. This compares to lower 

ratios for SUVs (1.23), Pickup Trucks (1.20), 

Passenger Cars (1.16) and Minivans (1.32).

The overall rate of rollover, expressed as the 

proportion of single vehicle crashes that resulted 

in a rollover, for 15-passenger vans is, if not 

lower, comparable with that of other passenger 

vehicles. However, statistical analysis based on 

state crash data shows that 15-passenger vans 

exhibit much higher risk, measured in terms of 

odds, of rollover when the vans were traveling 

at their full capacity as compared to when the 

driver was the only occupant in the van. While 

the increment in the risk of rollover with every 

unit increase in occupancy for 15-passenger vans 

was comparable to other passenger vehicles, 15-

passenger vans exhibited a much higher risk of 

rollover when they were loaded at or above their 

designed seating capacity. In fact, the odds of 

rollover for 15-passenger vans with 15 or more 

occupants was more than five times the risk of 

rollover when the driver was the only occupant 

in the van. This increase in the risk of rollover at 

or above the designed seating capacity is much 

less for SUVs and Pickup Trucks (about 2 times), 

Minivans (1.7 times) and Passenger Cars (1.3 

times). In summary, while the overall rollover 

rate for 15-passenger vans are comparable to 

other passenger vehicles, the disparity in the 

risk of rollover under fully and lightly loaded 

conditions is most pronounced for 15-passenger 

vans because they can carry a larger number of 

occupants.

7. Conclusions
32 National Center for Statistics and Analysis - Technical Report

The analysis also showed speed and the geometry 

of the road to be factors significant in affecting 

rollover outcome in all types of vehicles. The 

posted speed limit, used as an explanatory 

variable for travel speed, was determined to 

have a significant effect on the risk of rollover 

for 15-passenger vans as compared to other 

types of vehicles. In fact, the risk of rollover, as 

measured by the odds, for a 15-passenger van 

that is traveling on a high-speed road (50+ mph) 

is about five times the risk of rollover for a van 

that is traveling on a low-speed road (under 50 

mph).

The geometry of the road, as in if the road is curved 

or not, also was found to have a significant role in 

affecting rollover outcome in 15-passenger vans. 

The risk of rollover, measured by the odds, for a 

15-passenger van traveling on a curved road is 

about twice the risk of rollover for a van that is 

traveling on a straight road.

Analysis of FARS data showed that in the period 

from 1990 to 2002, there were 1,111 fatally 

injured occupants of 15-passenger vans. Of 

these fatalities, 684, or about 60 percent of all 

15-passenger van occupant fatalities, occurred 

in single vehicle crashes. Slightly more than 80 

percent of all fatalities in single vehicle crashes 

involving 15-passenger vans occurred when the 

vans rolled over.

The observed safety belt usage rate is very low 

among fatally injured occupants of 15-passenger 

vans involved in single-vehicle crashes. More 

than three-fourths of 15-passenger van occupants 

killed in single-vehicle crashes were not properly 

restrained. Also, a majority (92 percent) of 

those who were properly restrained survived 

the crash. An unrestrained 15-passenger van 

occupant involved in a fatal, single vehicle crash 

is about three times as likely to have been killed 

as compared to a properly restrained occupant.

Proper restraint use greatly reduces the chances 

of ejection from a 15-passenger van. About 60 

percent of the 15-passenger van occupants killed 

in single-vehicle crashes were ejected from 

the vehicle. An unrestrained occupant of a 15-

passenger van is about four times as likely to be 

ejected from the van as compared to a properly 

restrained occupant. 

Outreach efforts on this topic should emphasize 

the significant disparity between the risks of 

rollover of a 15-passenger van between lightly 

loaded (driver only) and fully loaded (15+ 

occupants) conditions. Drivers of 15-passenger 

vans ought to be cognizant of this change in risk 

when they are driving a van that is fully loaded. 

They also should be driven with utmost care 

while driving on high-speed roads as well as 

while negotiating a turn – conditions shown to 

have a significant impact in increasing the risk 

of rollover in any vehicle. Also, all occupants 

should be properly restrained when the vehicle is 

in motion to reduce the risk of occupant ejection 

in rollover events. Also, driver training on safe 

operation of these vans, especially of fullyloaded ones traveling on high-speed roads, is 

recommended.
Analysis of Crashes Involving 15-Passenger Vans 33

1. Garrott, R.W., (2001) The Rollover Propensity of Fifteen-Passenger Vans, 

National Highway Traffic Safety Administration, Department of Transportation

2. Winnicki, J., (1996) Estimating the Injury-Reducing Benefits of Ejection-Mitigating 

Glazing, DOT HS 808-369, National Highway Traffic Safety Administration, 

Department of Transportation

8. References
34 National Center for Statistics and Analysis - Technical Report
Analysis of Crashes Involving 15-Passenger Vans 35

9. Glossary

15-Passenger Van: Vans that have seating 

positions for a driver plus fourteen passengers 

are typically called 15-passenger vans. Also, 

these vehicles are actually classified as buses 

under 49 CFR 571.3.

Commercial Drivers License (CDL): As of 

April 1, 1992, a CDL is required by all states for 

driving a commercial motor vehicle in excess of 

26,000 pounds; or for transporting hazardous 

materials in sufficient amounts to be placarded; 

or for transporting 16 or more passengers, 

including the driver.

Crash BAC: The highest BAC among all the 

actively-involved persons in the crash. For 

example, in a crash involving a vehicle and a 

pedestrian, if the driver of the vehicle had a BAC 

of 0.01 g/dl and the pedestrian had a BAC of 

0.11 g/dl, the Crash BAC is 0.11 g/dl.

Driver BAC: The BAC of any driver involved in 

a crash.

Fatal Crashes: A motor vehicle traffic crash 

where there was at least one fatality to a vehicle 

occupant(s) or nonoccupant(s) involved in the 

crash.

FSVC: Fatal Single-Vehicle Crash (FSVC) is a 

single-vehicle crash that resulted in a fatality 

to the occupants of the vehicle and (or) a 

nonoccupant that was hit by the vehicle.

Impaired: A person is said to be impaired if 

their BAC is between 0.01 and 0.07 g/dl (0.01-

0.07).

Intoxicated: A person is said to be intoxicated if 

their BAC is 0.08 g/dl or greater (0.08+).

Light Trucks: A Pickup truck or a Sport Utility 

Vehicle (SUV).

Multiple-Vehicle Crash: A motor vehicle traffic 

crash is said to be a multiple-vehicle crash if 

more than one vehicle-level Police Accident 

Reports (PARs) are submitted for the crash. A 

multiple-vehicle crash may also involve more 

than one vehicle involved with one or more 

nonoccupants.

Nonoccupant: Any person involved in a crash 

who is not the occupant of a motor vehicle. 

Pedestrians, pedalcyclists, persons on rollerblades, skateboards, etc. are nonoccupants.

Passenger Vehicle: A passenger car, lighttruck or van.

Restraint Usage: Restraints can be in the form 

of safety belts, child safety seats or helmets. 

Safety-belts are present in every seating position 

in a 15-Passenger Van. Restraint-Use would be 

coded as ‘Yes’ for occupants of a 15-passenger 

van if the use of safety belts or child safety seats 

is observed.

Rollover: A rollover is defined as any vehicle 

rotation of 90 degrees or more, about any true 

longitudinal or lateral axis. Rollover can occur 

at any time during the unstable situation. 

Rollover can occur as a First or Subsequent 

event. Subsequent event refers to a rollover that 

occurs after the first harmful event.

Single Vehicle Crash: A motor vehicle traffic 

crash is said to be a single-vehicle crash if only 

one vehicle-level Police Accident Report (PAR) 

is submitted for the crash. A single-vehicle 

crash can also be a crash where one vehicle was 

involved with one or more nonoccupants.
36 National Center for Statistics and Analysis - Technical Report
Analysis of Crashes Involving 15-Passenger Vans 37

Appendix A: VIN Pattern to Identify 

15-Passenger Vans

The vans identified for inclusion in this study 

are the extended versions, where identifiable, of 

their series. Only the extended versions of the 

series can be configured to carry 15 passengers. 

However, it is conceivable that some unknown 

number of these vehicles left the manufacturer 

with seating for fewer than 15 persons as the 

seating configuration/capacity is not reported 

in FARS and also cannot be deciphered from the 

VIN. Also, there is flexibility to alter the seating 

capacity in such vans post-production for the 

purpose of carrying cargo etc. 

Only the first eleven positions in the VIN are 

needed to identify these vans as shown in Table 

A-1. Wildcards (*) in any of these positions 

indicate any character while ranges of numbers 

indicate all acceptable numbers for that position 

(e.g., 1-5 indicates 1,2,3,4,5). Character choices 

such as ‘B/D’ indicate that either ‘B’ or ‘D’ is 

acceptable for that position.

Manufacturer Position in the Vehicle Identification Number (VIN)

1 2 3 4 5 6 7 8 9 10 11

Ford 1-5 B/F B/D * S 3 1 * * * *

Chrysler 1-3/J B 5-6 * B 3 * * * * *

Chevrolet 1-4/J C/G A/B * G 3/8 9 * * * *

GMC 1-4/J C/G J/D * G 3/8 9 * * * *

Source: NCSA

Table A-1 - VIN-Pattern to Identify Vans Used in This Study
38 National Center for Statistics and Analysis - Technical Report
Analysis of Crashes Involving 15-Passenger Vans 39

Appendix B: SAS® Code to Identify 

15-Passenger Vans in FARS

DATA VANS;

SET FARS.VEHICLE;

/* EXTRACT FORD VEHICLES */

IF SUBSTR(VIN,1,1) IN (‘1’,’2’,’3’,’4’,’5’) AND 

SUBSTR(VIN,2,1) IN (‘B’,’F’) THEN DO;

 IF SUBSTR(VIN,5,3) IN (‘S31’) THEN DO;

 IF SUBSTR(VIN,3,1) IN (‘B’,’D’) THEN DO;

 VTYPE=1;

 MODL=’FORD’;

 OUTPUT;

 END;

 END;

END;

/* EXTRACT DODGE VEHICLES */

IF SUBSTR(VIN,1,1) IN (‘1’,’2’,’3’,’J’) AND SUBSTR(VIN,2,1) IN (‘B’) THEN DO;

IF SUBSTR(VIN,5,2) IN (‘B3’) AND SUBSTR(VIN,3,1) IN (‘5’,’6’) THEN DO;

 VTYPE=1;MODL=’DODG’;OUTPUT;

END;

END;

/* EXTRACT GM VEHICLES */

IF SUBSTR(VIN,1,1) IN (‘1’,’2’,’3’,’J’,’4’) AND SUBSTR(VIN,2,1) IN (‘C’,’G’) THEN DO;

IF SUBSTR(VIN,3,1) IN (‘A’,’B’) AND SUBSTR(VIN,5,3) IN (‘G39’,’G89’) THEN DO;

 VTYPE=1;MODL=’CHEV’;OUTPUT;

 END;

END;

IF SUBSTR(VIN,1,1) IN (‘1’,’2’,’3’,’J’,’4’) AND SUBSTR(VIN,2,1) IN (‘C’,’G’) THEN DO;

IF SUBSTR(VIN,3,1) IN (‘J’,’D’) AND SUBSTR(VIN,5,3) IN (‘G39’,’G89’) THEN DO;

 VTYPE=1;MODL=’GMC ‘;OUTPUT;

 END;

END;

RUN;
40 National Center for Statistics and Analysis - Technical Report
Analysis of Crashes Involving 15-Passenger Vans 41

Appendix C: Useful Resources

1. NHTSA Reports and Research Notes

• Garrott, R.W. et al., (2001) The Rollover Propensity of Fifteen-Passenger Vans, 

National Highway Traffic Safety Administration, Department of Transportation.

• Subramanian, R. (2004), Analysis of Crashes Involving 15-Passenger Vans, National 

Highway Traffic Safety Administration, Department of Transportation.

2. Safety Flyers and Hangtags

• Safety Flyer: Reducing the Risk of Rollover Crashes in Fifteen Passenger Vans, 

National Highway Traffic Safety Administration, Department of Transportation.

http://www.nhtsa.dot.gov/cars/problems/studies/15PassVans/Index.htm

• Hangtag: Reducing the Risk of Rollover Crashes in Fifteen Passenger Vans, National 

Highway Traffic Safety Administration, Department of Transportation.

http://www.nhtsa.dot.gov/cars/problems/studies/15PassVans/ROLLOVER_

HANGTAG_LaserRes.pdf

 NHTSA Contact:

 Mark Krawczyk

 Consumer Programs Analyst, Consumer Information Division

 NHTSA

 Mark.Krawczyk@nhtsa.dot.gov

 (202) 366-6330

3. Training and Instructional Materials (NHTSA does not endorse this product but is 

merely providing information of its existence).

• Coaching the Van Driver, Training Video:

National Safety Council FLI Learning Systems

(800) 621-7619 (609) 466-9000

http://www.nsc.org/ http://www.flilearning.com/

4. Federal Law Prohibiting Sale/Lease of 12/15-Passenger Vans for Significant Transport 

of Kids from School/Day Care

• NHTSA Interpretation Letter: 

http://www.nhtsa.dot.gov/cars/rules/interps/files/17730.drn.htm

DOT HS 809 729

May 2004