VEHICLE CRASHWORTHINESS RATINGS AND
CRASHWORTHINESS BY YEAR OF VEHICLE
MANUFACTURE:
VICTORIA AND NSW CRASHES DURING 1987-96
by
Stuart Newstead
Max Cameron
Chau My Le
Report No. 128
March 1998
MONASH UNIVERSITY ACCIDENT RESEARCH CENTRE
ii
MONASH UNIVERSITY ACCIDENT RESEARCH CENTRE
REPORT DOCUMENTATION PAGE
________________________________________________________________________________
Report No.
Report Date
ISBN
Pages
128
March 1998
0 7326 0708 6
25 + Appendices
________________________________________________________________________________
Title and sub-title:
Vehicle Crashworthiness Ratings and Crashworthiness by Year of Vehicle Manufacture :
Victoria and NSW Crashes During 1987-96
________________________________________________________________________________
Author(s)
Type of Report & Period Covered
Newstead, S.V., Cameron, M.H.
Summary Report, 1982-96
Le, C.M.
________________________________________________________________________________
Sponsoring Organisations - This project was funded as contract research by the following organisations:
Road Traffic Authority of NSW
Royal Automobile Club of Victoria Ltd.
NRMA Ltd.
Federal Office of Road Safety
VicRoads
________________________________________________________________________________
Abstract:
Crashworthiness is the relative safety of vehicles in preventing severe injury in crashes. Crashworthiness
ratings for 1982-96 model vehicles were developed based on data on crashes in Victoria and New South
Wales during 1987-96. Crashworthiness was measured by a combination of injury severity (of injured
drivers) and injury risk (of drivers involved in crashes). Injury severity was based on 85,585 drivers injured
in crashes in the two States. Injury risk was based on 431,690 drivers involved in crashes in New South
Wales where a vehicle was towed away. The ratings were adjusted for the driver sex and age, the speed limit
at the crash location, and the number of vehicles involved, factors which were found to be strongly related to
injury risk and/or severity. They estimate the risk of a driver being killed or admitted to hospital when
involved in a tow-away crash, to a degree of accuracy represented by the confidence limits of the rating in
each case. The estimates and their associated confidence limits were sufficiently sensitive that they were able
to identify 44 models of passenger cars, four-wheel drive vehicles, passenger vans and light commercial
vehicles which have superior or inferior crashworthiness characteristics compared with the average vehicle.
Also investigated is the relationship between vehicle crashworthiness and the year of manufacture of
Australian vehicles manufactured from 1964 to 1996. The data covered 1,077,352 drivers involved in towaway crashes in New South Wales during 1987-96, and 263,000 drivers injured in crashes in Victoria or New
South Wales during the same period. Cars, station wagons and taxis manufactured during the years 1964 to
1996 were considered.
The results of this report are based on a number of assumptions and warrant a number of qualifications which
should be noted.
________________________________________________________________________________
Key Words: (IRRD except when marked*)
Injury, Vehicle Occupant, Collision, Passenger Car Unit, Passive Safety System, Statistics
Disclaimer:
This Report is produced for the purposes of providing information concerning the safety of vehicles
involved in crashes. It is based upon information provided to the Monash University Accident
Research Centre by VicRoads, the Transport Accident Commission, the New South Wales Roads and
Traffic Authority, and NRMA Ltd. Any republication of the findings of the Report whether by way of
summary or reproduction of the tables or otherwise is prohibited unless prior written consent is
obtained from the Monash University Accident Research Centre and any conditions attached to that
consent are satisfied. A brochure based on this report is available from the sponsoring organisations
and may be freely quoted.
________________________________________________________________________________
VEHICLE CRASHWORTHINESS RATINGS AND CRASHWORTHINESS BY YEAR OF VEHICLE MANUFACTURE
iii
MONASH UNIVERSITY ACCIDENT RESEARCH CENTRE
iv
EXECUTIVE SUMMARY
This report describes the development of further updated crashworthiness ratings (the
relative safety of vehicles in preventing severe injury in crashes) for 1982-96 model
vehicles based on crash data from Victoria and New South Wales. Crashworthiness was
measured by a combination of injury severity (of injured drivers) and injury risk (of drivers
involved in crashes). Injury severity was based on 85,585 drivers injured in crashes in the
two States during 1987-96. Injury risk was based on 431,690 drivers involved in crashes in
New South Wales where a vehicle was towed away.
The crashworthiness ratings were adjusted for the driver sex and age, the speed limit at the
crash location, and the number of vehicles involved, factors which were found to be
strongly related to injury risk and/or severity. These adjustments were made with the aim
of measuring the effects of vehicle factors alone, uncontaminated by other factors available
in the data which affected crash severity and injury susceptibility.
The rating scores estimate the risk of a driver being killed or admitted to hospital when
involved in a tow-away crash, to a degree of accuracy represented by the confidence limits
of the rating in each case. The estimates and their associated confidence limits were
sufficiently sensitive that they were able to identify 44 models of passenger cars, four-wheel
drive vehicles, passenger vans and light commercial vehicles which have superior or
inferior crashworthiness characteristics compared with the average vehicle.
It is concluded that the additional crash data has enabled the crashworthiness ratings to be
obtained for a larger range of car models than previously. The new data set has been able to
produce more up-to-date and reliable estimates of the crashworthiness of individual car
models than those published previously. However the results and conclusions are based on
a number of assumptions and warrant a number of qualifications which should be noted.
A second stage of the project investigated the relationship between vehicle crashworthiness
and the year of manufacture of vehicles for the years of manufacture 1964 to 1996. This
study updated an earlier one which studied vehicles manufactured in the years 1964 to
1995.
The crashworthiness of passenger vehicles (cars, station wagons and taxis), measured by the
risk of the driver being killed or admitted to hospital as the result of involvement in a towaway crash, has been estimated for the years of manufacture from 1964 to 1996. This study
showed similar patterns of improvements in crashworthiness over the period of study to the
original study with the greatest gains over the years 1970 to 1979 during which a number of
new Australian Design Rules aimed at occupant protection took effect. Gains in
crashworthiness have also been observed over the years 1989 to 1996.
VEHICLE CRASHWORTHINESS RATINGS AND CRASHWORTHINESS BY YEAR OF VEHICLE MANUFACTURE
v
ACKNOWLEDGMENTS
A project as large and complex as this could not have been carried out without the help and support of a
number of people. The authors particularly wish to acknowledge:
•
Professor Peter Vulcan and Professor Brian Fildes of the Monash University Accident Research Centre
(MUARC) for their constructive advice throughout the project
•
Mr David Attwood of the Transport Accident Commission (TAC) for the provision of TAC claims data
•
Mr David Farrow and Mr Geoff Elston of VicRoads Business Services Division for the provision of data
from Victorian Police crash reports
•
Mr Michael Griffiths of the New South Wales Roads and Traffic Authority (RTA) for his support for the
project and the release of data from NSW Police crash reports
•
Mr Jack Haley of NRMA for his support for the project and for providing procedures to determine the
models of vehicles crashing in NSW and Victoria
•
Ms Maria Pappas of NRMA who developed and applied the procedures to determine the models of
vehicles recorded on NSW and Victoria Police crash reports
•
Mr Michael Adams of the NSW RTA who prepared and provided data files from NSW Police crash
reports
•
Mr John Goldsworthy, Mr Ken Smith and Mr Keith Seyer of the Federal Office of Road Safety for their
support for the project and advice on vehicle model details
•
Mr Bob Gardner and Dr Gray Scott of VicRoads for their support for the project and advice on vehicle
model details
•
Mr Michael Case, Mr Richard Stolinski and Mr Matthew Dickie of the RACV, for their support in the
project, for the provision of logic to determine the models of vehicles from information obtained from the
Victorian vehicle register by the TAC, and for advice on substantive changes in designs of specific
models over the years
•
Mr David Kenny of MUARC for updating and refining the RACV logic to determine the models of
vehicles recorded in TAC claims records
•
Ms Cheryl Hamill, formerly of VicRoads, and Mr Foong Chee Wai and Mr Terry Mach, formerly of
MUARC, for developing and implementing the procedures for merging TAC claims records and
Victorian Police crash report data
•
Dr Caroline Finch, Mr Tri Minh Le, and Mr Michael Skalova, all formerly of MUARC, for the
development of the analysis methods in earlier years which formed the basis of the methods used in this
report.
•
Dr Alan Miller, formerly of the CSIRO Division of Mathematics and Statistics for suggesting analysis
methods used in this report to improve the sensitivity of the results and to determine the confidence limits
of the estimates.
•
Officers of the Victorian and NSW Police Forces and of the Transport Accident Commission who
diligently recorded the information on crashes and injuries which formed the basis of this report.
MONASH UNIVERSITY ACCIDENT RESEARCH CENTRE
vi
VEHICLE CRASHWORTHINESS RATINGS:
VICTORIA AND NSW CRASHES DURING 1987-96
CONTENTS
Page No.
1. INTRODUCTION ......................................................................................................................................... 1
1.1 BACKGROUND ............................................................................................................................................ 1
1.2 PROJECT AIMS ............................................................................................................................................ 2
2. CRASH DATA............................................................................................................................................... 3
2.1 VICTORIAN CRASHES.................................................................................................................................. 3
2.2 NEW SOUTH WALES CRASHES.................................................................................................................... 4
2.3 COMBINED DATA FROM THE TWO STATES.................................................................................................. 4
3. MODELS OF VEHICLES............................................................................................................................ 5
4. ANALYSIS ..................................................................................................................................................... 6
4.1 OVERVIEW OF THE ANALYSIS METHODS .................................................................................................... 6
4.1.1 The Logistic Model ............................................................................................................................. 7
4.1.2 Logistic Confidence Limits for the Vehicle Models or Year of Manufacture ..................................... 7
4.2 LOGISTIC MODELS FOR EACH COMPONENT ................................................................................................ 8
4.2.1 Obtaining the Covariate Models......................................................................................................... 8
4.2.2 Assessing Car Model or Year of Manufacture Differences ................................................................ 9
4.2.3 Assessing Market Group Averages ................................................................................................... 10
4.3 COMBINING THE INJURY RISK AND INJURY SEVERITY COMPONENTS ....................................................... 10
4.4 INDIVIDUAL CAR MODELS ........................................................................................................................ 11
4.5 MARKET GROUP ANALYSES ..................................................................................................................... 12
4.6 TRENDS IN THE RATING CRITERIA DURING 1987-96 ................................................................................ 12
4.6.1 Trends in Driver Injury Rate in NSW ............................................................................................... 12
4.6.2 Trends in Driver Injury Severity in Victoria and NSW Combined ................................................... 13
4.6.3 Trends in the Combined Rate............................................................................................................ 13
5. RESULTS ..................................................................................................................................................... 13
5.1 VEHICLE CRASHWORTHINESS RATINGS .................................................................................................... 13
5.1.1 Injury Risk......................................................................................................................................... 13
5.1.2 Injury Severity................................................................................................................................... 14
5.1.3 Crashworthiness Ratings .................................................................................................................. 15
5.1.4 Comparisons with the All Model Average Rating............................................................................. 15
5.2 CRASHWORTHINESS BY YEAR OF MANUFACTURE .................................................................................... 17
5.2.1 Injury Risk......................................................................................................................................... 17
5.2.2 Injury Severity................................................................................................................................... 17
5.2.3 Crashworthiness by Year of Manufacture ........................................................................................ 18
5.2.4 Discussion on the Analysis of Crashworthiness by Year of Manufacture ........................................ 20
6. CONCLUSIONS .......................................................................................................................................... 23
7. ASSUMPTIONS AND QUALIFICATIONS............................................................................................. 23
7.1 ASSUMPTIONS........................................................................................................................................... 23
7.2 QUALIFICATIONS ...................................................................................................................................... 24
REFERENCES ................................................................................................................................................ 24
VEHICLE CRASHWORTHINESS RATINGS AND CRASHWORTHINESS BY YEAR OF VEHICLE MANUFACTURE
vii
APPENDICES
APPENDIX 1. Makes and models of cars involved in Victorian and NSW crashes during
1987-96
APPENDIX 2. Logistic regression estimates of injury risk by model and market group
APPENDIX 3. Logistic regression estimates of injury severity by model and market
group
APPENDIX 4. Crashworthiness ratings of 1982-96 models of cars involved in crashes
during 1987-96
APPENDIX 5. Logistic regression estimates of injury risk by year of manufacture
APPENDIX 6. Logistic regression estimates of injury severity year of manufacture
APPENDIX 7. Crashworthiness estimates by year of manufacture
MONASH UNIVERSITY ACCIDENT RESEARCH CENTRE
viii
VEHICLE CRASHWORTHINESS RATINGS:
VICTORIA AND NSW CRASHES DURING 1987-96
1.
INTRODUCTION
1.1
Background
In 1990, the NSW Roads and Traffic Authority (RTA) and the NRMA set out on a joint project
to develop a ‘car safety rating’ system based on Police records of crash and injury involvement.
The objective was to use vehicle crash records and injury data to develop ratings for the relative
safety of vehicles. The NRMA and RTA entered into discussions with the CSIRO to conduct the
necessary analysis, and by early 1991 had produced some relative ranking of vehicles.
Also during 1990, the Victorian Parliamentary Social Development Committee (SDC) in its
report on its inquiry into vehicle occupant protection recommended ways should be investigated
for Victorian consumers to give high priority to motor vehicle occupant protection in the
vehicles they purchase (SDC 1990).
In the second half of 1990, the Monash University Accident Research Centre (MUARC)
commenced a project to develop consumer advice on vehicle safety performance from mass
accident data. The development of crashworthiness ratings (the relative safety of vehicles in
preventing severe injuries in crashes) was given priority in the project because of their potential
to find significant differences between makes and models.
In mid 1991, the NSW and Victorian groups became aware of each others activities and,
following discussions, agreed to proceed jointly rather than have two competing vehicle safety
rating systems, one based on Victorian data and the other on NSW data. Later, the NSW RTA
and NRMA agreed that MUARC should undertake the analysis of the joint NSW/Victorian data
sets. The NSW RTA and NRMA perform preliminary work on the NSW data base to, as far as
possible, provide a clean set of data with accurately inscribed models for each vehicle. The data
are then handed over to MUARC for analysis.
Crashworthiness ratings rate the relative safety of vehicles by examining injury outcomes to
drivers in real crashes. The crashworthiness rating of a vehicle is a measure of the risk of serious
injury to a driver of that vehicle when it is involved in a crash. This risk is estimated from large
numbers of records of injury to drivers of that vehicle type involved in real crashes on the road.
In 1994, MUARC produced vehicle crashworthiness ratings based on crash data from Victoria
and New South Wales during 1987-92 (Cameron et al, 1994a,b). These ratings updated an earlier
MUARC set produced by Cameron et al (1992). Crashworthiness was measured in two
components:
1.
2.
Rate of injury for drivers involved in tow-away crashes (injury risk)
Rate of serious injury (death or hospital admission) for injured drivers (injury severity).
The crashworthiness rating was formed by multiplying these two rates together; it then measured
the risk of serious injury for drivers involved in crashes. Measuring crashworthiness in this way
was first developed by Folksam Insurance who publish the well-known Swedish ratings
(Gustafsson et al 1989).
The results of these ratings are summarised in Cameron et al (1994a) with a full technical
description of the analysis methods appearing in Cameron et al (1994b). These ratings use an
analysis method which was developed to maximise the reliability and sensitivity of the results
from the available data. In addition to the speed zone and driver sex, the method of analysis
adjusts for the effects of driver age and the number of vehicles involved, to produce results with
all those factors taken into account.
Subsequent to the ratings of Cameron et al (1994a,b), two further updated sets of ratings were
produced during 1996 and 1997 (Newstead et al 1996, Newstead et al 1997) covering vehicles
manufactured over the period 1982-94 and 1982-1995 respectively and crashing during 1987-94
and 1987-95 respectively incorporating some enhancements to the methods of statistical
analysis. The 1997 crashworthiness ratings covered 120 individual models of sedans, station
wagons, four wheel drives, passenger vans and light commercial vehicles and were given as
estimates of risk of severe injury for each model along with 95% confidence limits on each
estimate. These rating figures were widely distributed in the form of a "Used Car Ratings"
brochure, based on similar brochures produced from the earlier ratings.
Another focus of the vehicle crashworthiness ratings study has been to track historical
improvements in the average crashworthiness of the vehicle fleet since 1964. In 1994, the Royal
Automobile Club of Victoria (RACV) commissioned a study to investigate the effects of the
year of manufacture of vehicles (vehicle year) on their road safety (Cameron et al 1994c). This
project focused on investigating the relationship between crashworthiness and vehicle year of
manufacture for the years 1964 to 1992. The aim of the original study of Cameron et al (1994c)
was, to the extent possible, to measure the crashworthiness of vehicles of different years of
manufacture, after eliminating the influence of other key factors affecting the risk of injury
which might also be associated with vehicle year (eg. driver age and sex, use on high speed
roads, etc.).
The original study of Cameron et al (1994c) showed that the crashworthiness of passenger
vehicles in Australia has improved over the years of manufacture 1964 to 1992 with rapid
improvement over the years from about 1970 to 1979. Drivers of vehicles manufactured during
1970 to 1979 could be expected to have benefited from the implementation of a number of
Australian Design Rules (ADRs) for motor vehicle safety which previous research has shown to
be effective in providing occupant protection.
1.2
Project Aims
The aim of this project was to update the previously published crashworthiness ratings of
Newstead et al (1997) by inclusion of additional crash data from the year 1996. The updated
ratings cover the drivers of cars, station wagons, four-wheel drive vehicles, passenger vans, and
light commercial vehicles manufactured during 1982-96 and crashing in Victoria or NSW during
1987-96.
This project also aims to update the results of the study of crashworthiness by vehicle year of
manufacture to include vehicles manufactured over the years 1964 to 1996. This component of
this project also used the same methods and data sources as the crashworthiness ratings project
(Newstead et al 1997), the exception being that pre-1982 vehicles were also included.
2.
CRASH DATA
Data from Victoria and NSW used to produce the crashworthiness ratings of Newstead et al
(1997) covering vehicles manufactured over the period 1982-95 and crashing during the years
1987-95 was again used here. In addition, data for 1996 for both states were obtained and
integrated bringing the total period of crash data covered to 1987-96 for vehicles manufactured
in the years 1982-96.
2.1
Victorian Crashes
Detailed injury data have been collected by the Transport Accident Commission (TAC) and its
predecessor, the Motor Accidents Board, as part of their responsibilities to provide road
transport injury compensation. For each claimant, a description of the injuries was recorded, as
well as whether the person was admitted to hospital. Some details of the occupied vehicle (but
not its model) were obtained by TAC from the VicRoads registration system. When the TAC
was established in 1987, it introduced a requirement that the crashes resulting in an injury claim
should be reported to the Police, and started adding Police accident numbers (if and when
available) to the claims records.
TAC injury claims from all types of road users who were involved in crashes in the period 1987
to 1995 had been merged with Police crash reports for the previous crashworthiness ratings (see
Cameron et al (1994a,b) for a description of the method of matching). The Police reports were
for all persons involved in crashes, no matter whether the Police officer recorded the person as
injured or uninjured (this procedure was followed because it was possible for an injury claim to
be made in circumstances where injury was not apparent at the time of the crash). Crashes are
reported to the Police in Victoria if a person is killed or injured, if property is damaged but
names and addresses are not exchanged, or if a possible breach of the Road Traffic Regulations
has occurred (Green 1990).
The levels of matching of TAC claims with persons recorded on Police reports for each year
during 1987-95, achieved by Newstead et al (1997) for the last crashworthiness ratings, are
shown in Table 1. To update the ratings, files on TAC claims during 1996 were obtained. These
were merged with the Police reports on crashes in Victoria during 1996, achieving the match
rates also shown in Table 1. The methods of matching for the 1996 data were the same as used
previously and are detailed in Cameron et al (1994b).
The merged files of TAC claims with Police reports for 1996 was added to the earlier data on
crashes during 1987-95, which then represented 142,484 TAC claims for injury during 1987-96.
The resulting file covered 19,860 injured drivers of 1982-96 model cars who had accepted TAC
claims. The information on these drivers was combined with data on drivers injured in NSW
(see Section 2.3) to produce the updated crashworthiness ratings.
Table 1:
TAC claims for injury compensation from crashes during 1987-96
Year
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
TAC claims
(all types of
injured road
users)
30,892
28,427
25,399
19,633
19,538
19,251
18,590
19,341
20,189
19,954
TAC claims
matched with
Police reports
Match rate
(%)
17,509
16,672
17,494
13,886
12,774
13,118
12,618
11,927
12,452
14,034
56.7
58.6
66.3
70.7
65.4
68.1
67.8
61.6
61.7
70.3
For the study of crashworthiness by year of vehicle manufacture, of the 142,484 merged TAC
claims for injury during 1987-96, 63,339 were injured drivers of cars, station wagons or taxis
manufactured over the years 1964-96. Again, the information on these drivers was combined
with data on drivers injured in NSW (see Section 2.2).
2.2
New South Wales Crashes
NRMA supplied files covering 431,690 light passenger vehicles involved in Police reported
crashes during 1987-96 which resulted in death or injury or a vehicle being towed away.
NRMA had added the model and year of manufacture to these vehicles after matching with the
NSW vehicle register via registration number and vehicle make. The files supplied covered only
vehicles manufactured during 1982-96, but covered four-wheel drive vehicles, passenger vans,
and light commercial vehicles as well as cars and station wagons. The method of assembly of
this data is given in Cameron et al (1994b).
The vehicle files (which also contained driver age and sex) were merged with files supplied by
NSW RTA covering details of the person casualties (killed and injured persons) and the reported
crashes for the same years. Each vehicle/driver matched uniquely with the corresponding crash
information, but only injured drivers could match with persons in the casualty files. A driver
who did not match was considered to be uninjured. Out of the 431,690 drivers involved in towaway crashes, 66,582 were injured.
For the study of crashworthiness by vehicle year of manufacture, the NSW data represented
1,077,352 drivers of cars, station wagons or taxis manufactured from 1964 to 1996 who were
involved in tow-away crashes. Of these drivers, 179,811 were injured.
The presence of uninjured drivers in the merged data file meant that it was suitable for
measuring the risk of driver injury (in cars sufficiently damaged to require towing). This
contrasted with the Victorian data file, which could not be used to measure injury risk directly
because not all uninjured drivers were included.
2.3
Combined Data from the Two States
When the data on the injured drivers was combined for analysis, it covered 84,035 drivers of
1982-96 model vehicles who were injured in crashes in Victoria or NSW during 1987-96. This
information was used to assess the injury severity of the injured drivers of the different makes
and models.
The information on the 431,690 drivers involved in tow-away crashes in NSW was used to
assess the injury rate of drivers of the different makes and models.
For the study of crashworthiness by year of vehicle manufacture, the combined data on the
injured drivers covered 262,975 drivers of vehicles manufactured between 1964 and 1996 who
were injured in crashes in Victoria or NSW during 1987-96 and 1,077,352 drivers involved in
tow-away crashes in NSW.
3.
MODELS OF VEHICLES
NRMA located the crashed vehicles in NSW vehicle registration records after matching by
registration number and vehicle make. The Vehicle Identification Number (VIN) or chassis
number obtained from the register was decided to determine the models of light passenger
vehicles. The decoding identified some light truck and unusual commercial models which were
not considered further. Of the vehicles manufactured during 1982-96, all but around 4% had
their model identified. Further details are given by Pappas (1993).
The Victorian vehicle register provided the make and year of manufacture of the crashed vehicle
but not the model. Models were initially derived for cars manufactured during 1982-88 using
logic developed and supplied by the Royal Automobile Club of Victoria (RACV) based on the
make, year and power-mass units. Power-mass units (PMU) are the sum of RAC horsepower
units (PU) and the vehicle mass in units of 50 kg (MU). Refined logic was developed by
MUARC based on make, year, PMU, PU, MU and body type, and extended to cover 1989-93
models. The MUARC logic was applied to the combined Victorian data in conjunction with the
RACV logic to derive passenger car models for the model years 1982-93.
For vehicles crashing in 1994, 1995 or 1996, where available, the Victorian vehicle register
provided the VIN of each crashed vehicle along with the information described above. VINs are
recorded on the Victorian vehicle register for most vehicles from 1989 year of manufacture
onwards. Where a VIN was available for a vehicle appearing in the 1994, 1995 or 1996 crash
data, the model information was decoded from the VIN using the methods of Pappas (1993).
Where the VIN was not available, the RACV and MUARC logic, described above, was used to
obtain model details.
RACV, NRMA and the Federal Office of Road Safety (FORS) provided advice on the particular
models which had experienced substantial changes in design (and hence potential
crashworthiness) during model years 1982-96 and in which years the design was relatively
constant. This resulted in certain models being split into ranges of years of manufacture. Where
the new model was introduced near the beginning or end of a year (up to two months either
way), this process was relatively straightforward (accepting a small mis-classification in some
circumstances); however when the model changed near the middle of the year, the model for that
year was kept separate and potentially treated as a "mixed" model (eg. the Daihatsu Charade
1987 models).
Advice had previously been provided by VicRoads regarding models (sometimes only for
specific years) which were essentially the same design or construction, though registered as
having different manufacturers, which could be combined with each other. This information
was used in the analysis to combine some models, otherwise one or both members of each such
pair of models would have been excluded and a crashworthiness rating figure would not have
been produced (Section 4.2).
As in previous crashworthiness ratings, models were excluded with fewer than 20 injured drivers
and/or fewer than 100 involved drivers appearing in the crash data. These selection criteria were
used to ensure stability in fitting the logistic regression models along with suitably small
confidence limits on the estimated crashworthiness ratings.
For the purpose of publication, the models were also categorised in market groups as follows:
•
Passenger cars and station wagons:
•
•
•
Four-wheel drive vehicles
Passenger vans
Commercial vehicles (less than 3000 kg GVM)
Large
Medium
Small
Sports
Luxury
It should be noted that some of the vehicle models identified in the Victorian and NSW crash
data have optional safety equipment, such as air bags, which could significantly alter the
crashworthiness rating of the vehicle model when fitted. Notable examples in local manufacture
include the Holden Commodore VR/VS, Toyota Camry 1993-96 and Mitsubishi Magna TR/TS,
all of which have optional air bag fitment. It is, however, generally not possible to identify
which particular vehicles of a model series do and do not have such optional safety equipment
installed using the model decoding procedures described above. Consequently, for those vehicle
models with optional safety equipment, the estimated crashworthiness rating represents an
average of the safety performance for vehicles with and without the optional safety equipment
weighted by the number of each in the crash data.
In future updates of crashworthiness ratings, it is planned to investigate the feasibility of rating
separately vehicles of certain model series with and without air bags in order to judge the safety
benefits of this device. To achieve this, it will be necessary to seek the cooperation of vehicle
manufacturers to advise on which particular vehicles in the crash data were fitted with air bags
by checking the crashed vehicle VINs against the manufacturer’s build schedules.
4.
ANALYSIS
4.1
Overview of the Analysis Methods
The crashworthiness rating (C) is a measure of the risk of serious injury to a driver of a car when
it is involved in a crash. It is defined to be the product of two probabilities (Cameron et al,
1992):
i)
the probability that a driver involved in a crash is injured (injury risk), denoted by R;
and
ii)
the probability that an injured driver is hospitalised or killed (injury severity), denoted by
S.
That is
C = R × S.
Measuring crashworthiness in this way was first developed by Folksam Insurance who publish
the well-known Swedish ratings (Gustafsson et al, 1989).
In the present report, each of the two components of the crashworthiness rating were obtained by
logistic regression modelling techniques. Such techniques are able to simultaneously adjust for
the effect of a number of factors (such as driver age and sex, number of vehicles involved, etc.)
on probabilities such as the injury risk and injury severity.
4.1.1
The Logistic Model
The logistic model of a probability, P, is of the form:
log it P = ln
☺
P
= βo + β1X1 +K + βk Xk = f X .
1− P
That is, the log of the odds ratio is expressed as a linear function of k associated variables,
Xi , i = 1,K, k . Estimates of the parameter coefficients of the logit function, ie the β$ i can be
obtained by maximum likelihood estimation (Hosmer & Lemeshow, 1989). The extension of
this model to include interaction terms is straightforward.
The expected value of the logit function can be calculated from the estimated coefficients and
the mean level of each factor:
E f X = E β0 + E β1 X1 +K +E βk Xk = β$ 0 + β$ 1X1 +K β$ k Xk = f$ X .
4.1.2
Logistic Confidence Limits for the Vehicle Models or Year of Manufacture
Whilst it is possible to calculate the variance of f$ X , in the context of crashworthiness ratings
we are only interested in the component of variance due to one factor in f$ X with the variance
due to the other factors in the model being of no interest. In practice, the component of variance
due to the factor representing the vehicle model or year of manufacture is of interest, whilst the
variance due to the remaining factors such as driver age and sex is common to all vehicle models
or years of manufacture and hence of no interest.
To isolate the component of variance in the logistic model due to only one factor, say factor X i ,
the remaining factors were fixed at a predetermined level (their mean value). The variance of
f$ X , considering all factors apart from X i to be fixed, is then given by
(
( )
)
Var f$ ( X i ) = X i2Var β$ i
In the logistic models of injury risk or injury severity, X i was a [0,1] indicator function of either
a particular vehicle model or market group or year of manufacture, depending on the analysis
being performed. Hence the variance function given above equalled the variance of the
coefficient β$ i .
A 95% confidence interval for the logit function with respect to component X i is given by
(
)
f$ ( X ) ± 196
.
Var f$ ( X i ) .
Point estimates and confidence limits in the logistic space were transformed into probability
estimates using the inverse logistic transform given by
P$ =
4.2
e
f$ X
1+ e
f$ X
.
Logistic Models for Each Component
4.2.1
Obtaining the Covariate Models
Before adjusted crashworthiness ratings could be obtained it was necessary to consider logistic
models of each of the crashworthiness components separately to identify possible factors, other
than vehicle design, that might have influenced the crash outcomes. A stepwise procedure was
used to identify which factors had an important influence. This was done without considering
the type of car or year of manufacture in the model as the aim was to determine which other
factors were most likely to have an influence across a broad spectrum of crashes. Furthermore,
the car model variable had to be excluded from the logistic modelling process at this stage
because of analysis convergence problems when the car model was competing against the other
factors in the stepwise procedure.
Logistic models were obtained separately for injury risk and injury severity because it was likely
that the various factors would have different levels of influence on these two probabilities.
The factors considered during this stage of the analysis for both injury risk and injury severity
were
•
•
•
•
sex:
age:
speedzone:
nveh:
driver sex (male, female)
driver age (≤25 years; 26-59 years; ≥60 years)
speed limit at the crash location (≤75 km/h; ≥80 km/h)
the number of vehicles involved (one vehicle; ≥1 vehicle)
These variables were chosen for consideration because they were part of both the Victorian and
New South Wales databases. Other variables were only available from one source and their
inclusion would have drastically reduced the number of cases that could have been included in
the analysis.
All data was analysed using the LR procedure of the BMDP statistical package (BMDP, 1988).
Estimates of the coefficients of the logit function, β$ i , i = 1,K, k , together with their associated
standard errors, were obtained by maximum likelihood estimation. In the modelling process,
design variables for the various factors were chosen in such a way that the estimated coefficients
represented deviations of each of the variable levels from the mean (ie. the BMDP LR marginal
method for forming design variables was used).
For both injury risk and injury severity, a stepwise procedure was used to identify which factors
and their interactions made a significant contribution to these probabilities. All possible first
order interactions were considered. A hierarchal structure was imposed so that if an interaction
between two variables was included in the model then the corresponding main effects would
also be included. The resultant logistic regression models were referred to as the "covariate"
models or equations.
The average value of the injury risk or injury severity, and estimated 95% confidence intervals,
were obtained directly from the "covariate" models by substituting mean values of each of the
factors and their interactions into the regression equations.
4.2.2
Assessing Car Model or Year of Manufacture Differences
Injury risk and injury severity for individual cars were estimated after adding a variable
representing car model or year of manufacture to the respective logistic "covariate" models. The
car model or year of manufacture variable was forced into the logistic equation and individual
car model or year of manufacture coefficients were computed to represent deviations of that car
or year from the average. As mentioned earlier, this was to avoid non-convergence problems in
the analysis when car model or year of manufacture was allowed to compete with the other
factors in the stepwise selection process.
It was important to ensure that the logistic model adequately described the data and did not yield
individual car model coefficients that were imprecise or unstable. For this reason, individual car
models with small frequencies were pooled with similar car models, if appropriate (see Section
4.4) or they were excluded from the analysis. Car models were excluded if, after pooling
models, either:
i)
ii)
there were less than 100 involved drivers; or
there were less than 20 injured drivers.
After exclusion, the regression analyses were performed on 130 individual car models (or pooled
similar models). The variable representing car model was therefore categorical with 130
nominal levels. The choice of the design for the logistic model allowed the injury risk and
injury severity estimates for each individual car model to be compared with the overall (average)
rating for all cars. No such criteria was necessary for the year of manufacture analysis.
For each car model or year of manufacture, a 95% confidence interval for the logit functions of
injury risk and injury severity was obtained after first adjusting for the average value of the
"covariate" model and then allowing for the deviation from average for that particular car model.
Estimates of injury risk and injury severity were obtained by de-transforming the logit functions
as described in Section 4.1.2. A 95% confidence interval was determined after adjusting for the
average values of the significant factors and their interactions. The precision of the estimates of
injury risk and injury severity is measured by the width of these 95% confidence intervals.
4.2.3
Assessing Market Group Averages
A similar approach to that for individual car models was used to assess car market group
averages. A variable with 8 levels representing the different market groups (large, medium,
small, luxury, sports, 4-wheel drive, passenger vans and commercial vehicles with GVM < 3000
kg) was added to each of the "covariate" models of Section 4.2.1. Deviations of each market
group, from the average, was also assessed. Ninety-five percent confidence intervals for the
estimates of both injury severity and injury risk were also obtained for each of the market
groups.
4.3
Combining the Injury Risk and Injury Severity Components
The final combined ratings of vehicle crashworthiness are given by:
Crashworthiness Rating = Injury risk x Injury severity.
For a given model of car or year of manufacture, j, the crashworthiness rating, C j , was therefore
calculated as:
C j = Rj × Sj
where
Rj
Sj
denotes the injury risk for car model or year of manufacture j
denotes the injury severity for car model or year of manufacture j
Noting the form of the logistic inverse transformation in section 4.1.2 above, we have
Rj =
e
αj
1+ e
αj
,
Sj =
e
βj
1+ e
βj
where α j and β j are the values of the logistic regression function f$ X for injury risk and
injury severity respectively for vehicle model or year of manufacture j.
Taking the natural log of the crashworthiness rating and using asymptotic statistical theory, the
asymptotic variance of the log of the crashworthiness rating is
Var (log e C j ) ≈
Var (α j )
αj
(1 + e )
2
+
Var ( β j )
β
(1 + e j ) 2
where the variances of α j and β j are as given in section 4.1.2 and the estimates of α j and β j
are considered independent.
The 95% confidence interval for the natural log of the crashworthiness rating is then
(
)
log e ( C j ) ± 1.96 ⋅ Var log e ( C j ) .
The 95% confidence limit for the crashworthiness rating is obtained by taking the exponent of
the confidence limit of the logged crashworthiness rating shown above.
Because each of the two estimated crashworthiness components have been adjusted for the effect
of other factors by logistic regression prior to their incorporation into the combined ratings, the
resultant crashworthiness rating is also adjusted for the influence of these factors. It should be
noted that the confidence interval for the combined rate reflects the variability in the car model
only and not the variability in the other factors included in the logistic models.
The same procedure was used to obtain crashworthiness ratings of each distinct market group
and for each year of vehicle manufacture.
4.4
Individual Car Models
Injury risk and injury severity for individual cars was estimated after adding the car model to the
logistic model described in Section 4.1.
In order to ensure that the logistic model adequately described the data and did not yield
crashworthiness estimates which were imprecise, individual car models with small frequencies
were pooled with similar models (Table 2) or excluded from the analysis. The car models which
were excluded from the analyses are indicated in Appendix 1.
Table 2:
Pooled Models of Cars
Laser 82-89
Telstar 83-87
Telstar 88-91
Telstar 92-96
Falcon EA
Falcon ED
Corsair 89-92
Commodore VR/VS
Commodore VN-VP
Nova 89-93
Nova 95-96
Astra 84-86
with
with
with
with
with
with
with
with
with
with
with
with
Mazda 323 82-88
Mazda 626 83-86
Mazda 626 88-91
Mazda 626 92-96
Falcon EB Series 1
Falcon EB Series 2
Pintara 89-92
Lexcen 93-95
Lexcen 89-92
Corolla 89-93
Corolla 95-96
Pulsar/Vector 82-86
Astra 87
Astra 88-89
Barina 85-88
Barina 89-93
Apollo JK/JL
Apollo JM
Ford Maverick 88-96
Suzuki Scurry 85-87
Suzuki Sierra 82-96
Nissan XFN Utility
4.5
with
with
with
with
with
with
with
with
with
with
Pulsar/Vector 87
Pulsar/Vector 88-90
Suzuki Swift 85-88
Suzuki Swift 89-94
Camry 88-92
Camry 93-96
Nissan Patrol 88-96
Holden Carry 85-90
Holden Drover 85-87
Ford Falcon Utility
Market Group Analyses
In addition to the individual car model analyses, logistic regression analyses were performed
based on broad market groups as defined in Section 3. The market group analyses provided
reference ratings for models in each group.
4.6
Trends in the Rating Criteria During 1987-96
In both Victoria and New South Wales there have been major increases in road safety during the
1990s and this may have produced a general reduction in the risk of serious injury in crashes as
well as reductions in the number of crashes occurring. There was therefore some concern that
there may have been a bias in the crashworthiness ratings which would have tended to produce a
more favourable score for the most recent model cars. This was because the later model cars
(post-1987) have crashed during the later years in 1987-96. If so, the crashworthiness rating of
the later model cars would tend to be lower, irrespective of design improvements, than would be
expected if the general improvements in road safety had not occurred.
This concern led to a need to investigate whether there were in fact, general reductions in the
risk of driver injury in NSW, and/or driver injury severity in Victoria and NSW, and whether
these changes if present needed to be taken into account in the crashworthiness ratings of
specific years of the same models.
4.6.1
Trends in Driver Injury Rate in NSW
The file of drivers involved in crashes in NSW used to measure the driver injury rate, the first
component of the crashworthiness rating, was analysed by the year in which the crash occurred
to assess any trends. There was no evidence of a consistent trend over the period (Table 3).
The generally increasing number of drivers during each year was due to the increasing pool of
1982-96 manufactured vehicles on the road (and hence involved in crashes) during the period
1987 to 1996, off-set by the general reduction in crash involvement.
Table 3: Numbers of drivers of light passenger vehicles manufactured in 1982-96 and involved
in tow-away crashes in NSW during each of the years 1987-96.
Year of Crash
Total injured
1987
4249
1988
4814
1989
5307
1990
5573
1991
5410
1992
5678
1993
5843
1994
6135
1995
6490
1996
6859
Total involved
Injury Rate (%)
4.6.2
3304
9
12.9
3267
3
14.7
3689
6
14.4
4020
8
13.9
3920
0
13.8
3957
9
14.3
4085
9
14.3
4243
3
14.5
4547
7
14.3
5193
1
15.1
Trends in Driver Injury Severity in Victoria and NSW Combined
The file of drivers injured in crashes in the two States combined was used to assess the trend in
driver injury severity, the second component of the crashworthiness rating. Again there was no
evidence of a consistent trend over the period (Table 4).
Table 4: Numbers of drivers of light passenger vehicles manufactured in 1982-96 and injured in
crashes in Victoria and NSW during each of the years 1987-96.
Year of Crash
Total killed or
admitted to hospital
Total injured
Injury Severity (%)
4.6.3
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1380
6165
22.4
1499
7126
21.0
1664
8047
20.7
1644
7697
21.4
1735
7724
22.5
1772
8215
21.6
2008
8401
23.9
2221
9344
23.8
2438
9923
24.6
2670
11119
24.1
Trends in the Combined Rate
The driver injury rate (Table 3) and driver injury severity (Table 4), for each crash year during
1987-96, were multiplied to form a Combined Rate (Table 5). The Combined Rate measures
essentially the same risk (ie. of death or hospital admission for drivers involved in tow-away
crashes) as the crashworthiness rating. However it should be noted that it has not been adjusted
for the effect of various factors (eg. driver age and sex, speed zone of the crash, etc.) in the same
way as the rating scores.
Table 5: Combined Rate for drivers of light passenger vehicles manufactured in 1982-96 and
involved in tow-away crashes during each of the years 1987-96.
Year of Crash
Injury Rate (%)
Injury Severity (%)
Combined Rate (%)
1987
12.9
22.4
2.89
1988
14.7
21.0
3.09
1989
14.4
20.7
2.98
1990
13.9
21.4
2.97
1991
13.8
22.5
3.11
1992
14.3
21.6
3.08
1993
14.3
23.9
3.38
1994
14.5
23.8
3.45
1995
14.3
24.6
3.51
1996
15.1
24.1
3.64
It was concluded that since there was no evidence of clear and consistent trends in the injury risk
and injury severity ratios, upon which the crashworthiness analysis is based, over the crash years
considered that there was no need to take account in the analysis the fact that later model cars
have crashed in the later years.
5.
RESULTS
5.1
Vehicle Crashworthiness Ratings
5.1.1
Injury Risk
Injury risk was estimated from the data on 431,690 drivers involved in tow-away crashes in
NSW (as described in Section 2.2). This data set is referred to as the "involved drivers". Because
of missing values in one or more of the covariates driver sex and age, speedzone and number of
vehicles involved in crash amongst the 431,690 involved drivers, the final file used for analysis
consisted of the 382,027 drivers for which all the covariate data was complete. The "covariate"
model for injury risk was determined from the variables described in Section 4.2.1.
All of driver sex and age, speedzone and number of vehicles, along with first order interactions
between speedzone and number of vehicles, sex and number of vehicles, age and sex, speedzone
and age and speedzone and sex and second order interactions between sex, speedzone and
number of vehicles and sex, speedzone and age were significantly associated with injury risk
and were included in the logistic model. No other interaction term significantly improved the fit
of the logistic model.
The overall (average) injury risk for involved drivers in tow-away crashes in NSW, after
adjusting for differences in the factors in the “covariate” model given above, was 12.47 per 100
drivers. In other words, the probability that a driver involved in a tow-away crash in NSW was
injured was 12.47%, after adjusting for other significant factors.
Appendix 2 gives the estimates of injury risk derived by logistic regression for 130 individual
car models, or sets of car models. Injury risk ranged from 6.93 % for the Mercedes Benz 200
series to 27.38% for the Subaru Sherpa/Fiori.
An estimate of the variability in the injury risk estimates was calculated from the width of the
corresponding 90% confidence intervals. Individual confidence interval widths ranged from
0.80% (Falcon XD-XF) to 10.95% for the Rover Quintet. The small variability for the Falcon X
series Sedan is not surprising since there were more cars of this model than any other in the data
set and precision is known to improve with increasing sample size.
The estimated injury risk for each market group is also given in Appendix 2. The luxury vehicles
had the lowest injury risk (10.18%) and the passenger van market group had the highest
(16.27%).
5.1.2
Injury Severity
The data on "injured drivers" covered 85,585 drivers of 1982-96 model vehicles who were
injured in crashes in Victoria or NSW during 1987-96 (as described in Section 2.3). Because of
missing values in one or more of the covariates amongst the 85,585 injured drivers, the final file
used for analysis consisted of the 84,142 drivers for which all the covariate data was complete.
The "covariate" model for injury severity was determined from the variables described in
Section 4.2.1.
The analysis identified a number of significant base covariate effects - driver sex, driver age,
speedzone and number of vehicles in crash. In addition, significant first order interactions were
found between sex and age, speedzone and number of vehicles in crash, speedzone and age and
age and number of vehicles in crash. No other interaction term significantly improved the fit of
the logistic model.
The overall (average) injury severity for injured drivers, after adjusting for differences in the
associated factors, was 20.88 per 100 drivers. In other words, the probability that a driver
injured in a crash was severely injured was 20.88 %, after adjusting for other significant factors.
Appendix 3 gives the estimates of injury severity derived by logistic regression for 130
individual car models, or sets of combined models. Injury severity ranged from 8.09% for the
Holden Jackaroo (1984-1996) to 49.17% for the Honda Prelude (1992-1996).
An estimate of the variability in the estimates of injury severity was calculated from the width of
the corresponding 90% confidence intervals. Individual confidence interval widths ranged from
2.51% Ford Falcon XD-XF (82-88) to 36.11% for the Honda Prelude (1992-1996).
The estimated injury severity for each market group is also given in Appendix 3. Four wheel
drive vehicles performed best with respect to injury severity (ie they had the lowest injury
severity - 18.89%). The Sports car market group had the highest injury severity (22.18%).
5.1.3
Crashworthiness Ratings
The crashworthiness ratings for each car model and market group were obtained by multiplying
the individual injury risk and injury severity estimates. Because each of the two components
have been adjusted for the confounding factors, the resultant crashworthiness rating is also
adjusted for the influence of them.
Crashworthiness ratings were able to be obtained for the "average" car as well as for each
individual model and market group after adjusting for the confounding factors.
Appendix 4 gives the crashworthiness ratings and the associated 95% confidence intervals for
each of the 130 car models included in the analyses. Appendix 4 also gives the crashworthiness
ratings with 90% confidence limits for each of the 130 vehicle models. Each rating is expressed
as a percentage, representing the number of drivers killed or admitted to hospital per 100 drivers
involved in a tow-away crash. Overall ratings for the market groups are also given. The table
indicates the overall ranking of the crashworthiness ratings from 1 (lowest or best
crashworthiness rating) to 130 (highest or worst crashworthiness rating).
Each crashworthiness rating is an estimate of the true risk of a driver being killed or admitted to
hospital in a tow-away crash, and as such each estimate has a level of uncertainty about it. This
uncertainty is indicated by the confidence limits in Appendix 4. There is 95% probability that
the confidence interval will cover the true risk of serious injury (death or hospital admission) to
the driver of the particular model of vehicle.
The ratings in Appendix 4 exclude those models where:
•
the width of the confidence interval exceeded 7, or
•
the ratio of the confidence interval width to the rating score exceeded 1.6 (this criterion was
also necessary because smaller confidence intervals tended to occur for the lower rating
scores, but the confidence intervals were relatively wide in proportionate terms). This
exclusion criterion is more stringent than that used by Cameron et al (1994a,b) reflecting the
greater accuracy afforded in the current ratings as a result of larger quantities of data.
5.1.4
Comparisons with the All Model Average Rating
The confidence limits can be used to judge whether the true risk of death or hospitalisation for a
driver of a specific model car involved in a tow-away crash is really different from the overall
average for all models, ie. 2.60 per 100 involved drivers. An upper limit below the average is
indicative of superior crashworthiness, whereas a lower limit above the average suggests inferior
crashworthiness. Other models also have crashworthiness ratings at the low or high end of the
scale, but their confidence limits overlap the all model average. Although such models may also
have superior or inferior crashworthiness characteristics, the data base did not contain sufficient
numbers of these models for the data to represent scientific evidence that this is the case.
Twenty one models had ratings representing evidence of superior crashworthiness because their
upper confidence limits were less than the average rating. Six of these were large cars and a
further seven were luxury models. Two were classified as medium cars, four were four wheel
drives whilst the last two were passenger car based commercial vehicles. The specific models
were (in order of estimated risk of serious driver injury in a crash, from lowest to highest):
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
Holden Jackaroo (1984-96)
Volvo 700 Series (1984-92)
Toyota Cressida (1989-1993)
BMW 5 Series (1982-96)
Mitsubishi Magna TR/TS and Verada KR/KS (1991-96)
Honda Accord (1986-90)
Toyota Landcruiser (1990-96)
Mercedes Benz 300-600 Series (1982-95)
Volvo 200 Series (1982-93)
Ford Maverick (1988-96) / Nissan Patrol (1988-1996)
Toyota Crown/Cressida (1982-85)
Peugeot 505 (1982-93)
Range Rover (1982-96)
Subaru Liberty (1989-94)
Holden Commodore VR/VS (1993-96)/Toyota Lexen (1993-96)
Ford Panel Van (1982-1996)
Ford Falcon Ute (1982-96) / Nissan XFN UTE (1988-90)
Holden Apollo JM/JP (1993-96) / Toyota Camry (1993-96)
Ford Falcon EA/EB Series I (1988-March 1992)
Ford Falcon ED/EB Series II (April 1992-94)
Ford Falcon XD-XF (1982-88)
Twenty three models had ratings representing evidence of inferior crashworthiness
because their lower confidence limits were greater than the average rating. Fourteen were small
cars, four were light commercial vehicles, two were families of passenger vans, three were
medium cars. The specific models were (in order of estimated risk of serious driver injury in a
crash, from highest to lowest):
•
•
•
•
•
•
•
•
•
Honda City (1983-86)
Holden Scurry (1985-86) / Suzuki Carry (1982-90)
Subaru Sherpa/Fiori (1982-92)
Suzuki Mighty Boy (1985-88)
Suzuki Hatch (1982-85)
Daihatsu Handivan (1982-90)
Ford Festiva WA (1991-93) / Mazda 121 (1987-90)
Daihatsu Charade (1982-86)
Subaru Brumby (1982-93)
•
•
•
•
•
•
•
•
•
•
•
•
•
•
Holden Barina (1985-88) / Suzuki Swift (1985-88)
Nissan Gazelle (1984-88)
Mitsubishi Passenger Vans (1982-96)
Hyundai Excel (1982-89)
Daihatsu Charade (1988-93)
Honda Civic (1984-87)
Nissan Passenger Vans (1982-92)
Holden Astra (1984-86) / Nissan Pulsar/Vector (1984-86)
Mitsubishi Colt (1982-88)
Holden Barina (1989-93) / Suzuki Swift (1989-94)
Mazda 323 (1982-88) / Ford Laser/Meteor (1982-89)
Toyota Hiace/Liteace (1982-93)
Holden Camira (1982-89)
Ford Telstar (1983-87) / Mazda 626/MX6 (1983-87)
5.2 Crashworthiness by Year of Manufacture
5.2.1
Injury Risk
Injury risk was estimated from the data on 1,077,332 drivers involved in tow-away crashes in
NSW (as described in Section 2.2). This data set is referred to as the "involved drivers".
Because of missing values of some of the factors to be included in the logistic regression, and
the exclusion of pre-1964 vehicles and unknown years, analysis was performed on data relating
to 668,637 involved drivers, 101,555 of whom were injured.
The "covariate" model for injury risk was determined from the variables described in Section
4.2.1 The covariates driver sex, driver age, speedzone and number of vehicles (nveh) were
significantly associated with injury risk and were included in the logistic regression as main
effects. In addition, significant first order interactions were found between sex and speedzone,
sex and age group, sex and nveh, speedzone and age group and speedzone and nveh as well as
second order interactions between sex, speedzone and nveh and sex, speedzone and agegroup.
No other variable or interaction term significantly improved the fit of the logistic model.
The overall (average) injury risk for involved drivers in tow-away crashes in NSW, after
adjusting for the significant main effects and interactions described above, was 15.79%. In other
words, the estimated probability that a driver involved in a tow-away crash in NSW was injured
was 15.79%, after adjusting for other significant factors.
Appendix 5 gives the estimates of injury risk derived by logistic regression for the individual
years of manufacture. The variability in the injury risk estimates relative to the year of
manufacture can be seen from the width of the corresponding 95% confidence intervals.
5.2.2
Injury Severity
The data on "injured drivers" covered 263,000 drivers who were injured in crashes in Victoria
or NSW during 1987-96 (as described in Sections 2.1 and 2.2). Because of missing values of
some of the associated crash factors, and the exclusion of pre-1964 vehicles and unknown years,
logistic regression was performed on data relating to 161,984 injured drivers, 37,816 of whom
were severely injured (killed or admitted to hospital).
The "covariate" model for injury risk was determined from the variables described in Section
4.2.1. The analysis identified a number of significant based covariate effects - driver sex, driver
age, speedzone and number of vehicles (nveh). In addition, significant interactions were found
between sex and age, speedzone and age, speedzone and nveh and age and nveh. No other
variable or interaction term significantly improved the fit of the logistic model.
The overall (average) injury severity for injured drivers, after adjusting for differences in the
associated factors, was 21.79%. In other words, the estimated probability that a driver injured in
a crash was severely injured was 21.79%, after adjusting for the significant factors described
above.
Appendix 6 gives the estimates of injury severity derived by logistic regression for the
individual years of manufacture. The variability in the estimates of injury severity relative to
year of manufacture can be seen from the width of the corresponding 95% confidence intervals.
5.2.3
Crashworthiness by Year of Manufacture
The crashworthiness estimates for each year of manufacture were obtained by multiplying the
individual injury risk and injury severity estimates. Because each of the two components have
been adjusted for the confounding factors, the resultant crashworthiness estimate is also adjusted
for the influence of them.
Appendix 7 gives the crashworthiness estimates and the associated 95% confidence intervals for
each of the 32 years of manufacture included in the analysis. Each estimate is expressed as a
percentage, representing the number of drivers killed or admitted to hospital per 100 drivers
involved in a tow-away crash.
The true risk of a driver being killed or admitted to hospital in a tow-away crash is only
estimated by each figure, and as such each estimate has a level of uncertainty about it. This
uncertainty is indicated by the confidence limits in Appendix 7. There is 95% probability that
the confidence interval will cover the true risk of serious injury (death or hospital admission) to
the driver of a vehicle of the particular year of manufacture.
The crashworthiness estimates and their confidence limits are plotted for each year of
manufacture in Figure 1. The relatively wide confidence intervals observed on the estimates of
crashworthiness for years of manufacture 1964 to 1969 and 1996 are a reflection of the smaller
numbers of crashes involving vehicles manufactured in these years appearing in the data.
Figure 1 shows general and significant improvement in vehicle crashworthiness with increasing
year of manufacture over the years considered. Specifically, little improvement can be seen in
the years 1964 to 1969 followed by rapid improvement over the period 1970 to 1979 with a
plateau from 1980 to 1985. There is visual evidence of a decreasing trend in the period after
1985 with vehicles manufactured after 1991 being statistically significantly safer on average
than those manufactured before 1986.
To summarise the magnitude of the improvement in crashworthiness seen in vehicles during the
1970's, the average crashworthiness estimate for the 1980-85 year vehicles was compared with
the average for those manufactured during 1964-69. This showed a reduction of approximately
42% in the risk of serious injury for drivers involved in tow-away crashes between these two
time periods. Further statistically significant improvements in crashworthiness have also been
observed over the period 1986 to 1996.
The injury risk component of the crashworthiness estimate, together with its 95% confidence
limits, is plotted in Figure 2. In a similar way, the injury severity component is plotted in Figure
3. Examination of these figures together shows the improvements in crashworthiness with year
of manufacture observed in Figure 1 are due largely to a decrease in the probability of any injury
given crash involvement (injury risk) with year of manufacture shown in Figure 2. There was a
strong downward trend in injury risk with vehicle year of manufacture whilst Figure 3 shows a
much weaker effect of vehicle year of manufacture on injury severity.
FIGURE 1
Crashworthiness by year of manufacture
(with 95% confidence limits)
8.00
6.00
5.00
4.00
Average = 3.44
ADR 69
NCAP
CRASHWORTHINESS
RATINGS
ADR 29
ADR 4C
ADR 4A
ADRs 4B, 5B, 22A
0.00
ADRs 11, 14, 22
1.00
ADRs 10B, 21
2.00
ADRs 2, 3, 8, 10A
3.00
ADRs 4, 5A
Probability of severe injury given
crash involvement (%)
7.00
64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96
Year of manufacture
FIGURE 2
Injury risk by year of manufacture
(with 95% confidence limits)
Pr(Injury given crash involvement)
(%)
30.00
25.00
20.00
Average = 15.79
15.00
10.00
5.00
0.00
64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96
Year of Manufacture
FIGURE 3
Injury severity by year of manufacture
(with 95% confidence limits)
35
Pr(Severe injury given any injury)
(%)
30
25
Average = 21.79
20
15
10
5
0
64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96
Year of Manufacture
5.2.4
Discussion on the Analysis of Crashworthiness by Year of Manufacture
The findings of this research are closely consistent with those of the original study by Cameron
et al (1994a). This is as expected given that the data used in the analysis here is an extension of
that used in Cameron et al’s study with the addition of crashes occurring in Victoria and NSW
during 1993 to 1996. As shown by Cameron et al, after a period of little change during the late
1960's, there was rapid improvement over the years from about 1970 to 1979. Drivers of
vehicles manufactured during these years could be expected to have benefited from the
implementation of a number of Australian Design Rules (ADRs) for motor vehicle safety which
previous research has shown to be effective in providing occupant protection (Cameron 1987),
namely:
•
•
•
•
•
•
•
•
ADR 4 (seat belts fitted in front seats) from January 1969
ADR 2 ("anti-burst" door latches and hinges) from January 1971
ADR 10A ("energy-absorbing" steering columns) also from January 1971
ADR 22 (head restraints) from January 1972
ADR 10B (steering columns with limited rearward displacement) from January 1973
ADR 4B (inertia reel seat belts fitted in front seats) from January 1975
ADR 22A (minimum-height adjustable head restraints) from January 1975
ADR 29 (side door strength) from January 1977.
In addition, the following ADRs introduced over the same period could also be expected to have
provided increased injury protection for drivers:
•
•
•
•
•
•
•
•
•
ADR 5A (seat belt anchorage points for front seats) from January 1969
ADR 3 (strengthened seat anchorages) from January 1971
ADR 8 (safety glass in windscreens and side windows) from July 1971
ADR 11 ("padded" sun visors) from January 1972
ADR 14 ("breakaway" rear vision mirrors) from January 1972
ADR 21 ("padded" instrument panels) from January 1973
ADR 4A (improved seat belt buckles), effective from April 1974
ADR 5B (improved location of seat belt anchorages) from January 1975
ADR 4C (dual-sensing locking retractor inertia reel seat belts) from January 1976.
The years of implementation of these ADRs are shown on Figure 1 for comparison with the
crashworthiness estimates for the vehicles manufactured during the 1970's.
This study extends previous work to provide estimates of the relative crashworthiness of
vehicles manufactured in 1996. For a number of reasons, it may have been expected that these
years of manufacture have shown an improvement in crashworthiness. Improvement may have
stemmed from vehicle manufacturer reaction to two areas of activity in vehicle safety which
have emerged during the 1990’s, namely;
• The introduction of programs to advise consumers of relative vehicle safety. Vehicle
crashworthiness ratings ranking vehicles’ relative driver protection based on real crash data
were first published in 1992 and updated in 1994 and 1996 (Cameron, Newstead and Skalova
(1996)). The Australian New Car Assessment Program, which rates relative driver and front
left passenger protection based on controlled laboratory impact testing of vehicles, first
published test results in April 1993 for 9 popular vehicle models and to date has published
relative safety ratings for over 35 vehicle models (see Figure 1).
• Drafting of Australian Design Rule (ADR) 69 specifying standards for frontal impact
occupant protection in passenger cars as part of the Motor Vehicle Standards Act. ADR 69
was approved as a national standard by the Minister for Land Transport on 16th December
1992, coming into effect for all newly released car models on 1st July 1995 and for all new
passenger cars sold from 1st January 1996.
It might be expected that consumer vehicle safety advice such as crashworthiness ratings and
NCAP, which rate a vehicle’s relative occupant protection, may encourage vehicle
manufacturers to consider safety as a top priority in vehicle design so as to have their product
perform well in these safety ratings. Whilst the implementation of ADR 69 occurred at the
beginning of the last year of vehicle manufacture on which this study focuses, it is possible that
manufacturers worked towards meeting this standard in their new vehicles from its approval in
December 1992, hence showing benefits over the period 1993 to 1996.
Figure 1 shows general and significant improvement in vehicle crashworthiness with increasing
year of manufacture over the years considered. It should be noted that whilst the trend in
crashworthiness during the 1990s was not statistically significant, vehicles manufactured over
the period 1990 to 1995 have an average crashworthiness statistically significantly better than
those manufactured before 1986 whilst. Whilst the estimate of crashworthiness for vehicles
manufactured during 1996 appears to be following an upwards trend from of those manufactured
in 1994 and 1995, the confidence limits, particularly on the 1996 year of manufacture
crashworthiness estimate, are too wide at this point to make a definitive assessment of trends
over these three years.
Further updates of the study planned for the future and adding additional years’ crash data will
also improve the statistical accuracy of estimated crashworthiness for the years 1992 onwards. In
this study, these years estimates have relatively wide confidence limits reflecting the smaller
quantities of crash data for vehicles manufactured in these years, particularly 1996.
Analysis by Age of Vehicle
Subsequent to the year of vehicle manufacture analysis, for which the results are presented here,
an additional analysis was attempted. The purpose of the additional analysis was to assess the
relationship between the age of a vehicle at the time of crash and crashworthiness to determine
whether a vehicle becomes less crashworthy as its condition deteriorates with age. The method
of this analysis was identical to that used for the crashworthiness by year of vehicle manufacture
assessment, apart from the addition of an extra covariate to the logistic regression model
representing the age of the vehicle at time of crash. When run, however, the analysis proved
unsuccessful, with the regression models failing to converge to stable parameter estimates.
Failure of the regression model to converge when including age of vehicle at crash is indicative
of a problem with the analysis design. In this case the design problem stems from the fact that
the analysis focuses on years of vehicle manufacture from 1964 to 1996 but the data available
for analysis covers only the period 1987 to 1996. Consequently, the vehicles which are older at
time of crash are generally those of early years of manufacture whilst the vehicles which are
younger at time of crash are generally later years of manufacture. Hence the effect of age of
vehicle at crash is confounded with the effect of vehicle year of manufacture in the analysis
attempted here with neither effect able to be estimated independently.
There are a number of possible ways which could be suggested to attempt to overcome the
problem of the confounding between the effects of year of manufacture and vehicle age at crash.
One would be to only consider vehicles manufactured over the same period for which data are
available, that is 1987 to 1996. This would only partially eliminate the problem though, as
vehicles of earlier year of manufacture would still be the only ones capable of being observed
crashing at an older age. Presently, such an analysis would also only be able to look at vehicles
up to 10 years old at time of crash which may not be the time period in which deterioration
effects were able to substantially effect crashworthiness. A second potential solution would be to
examine the crashworthiness at different ages of a cohort of vehicles at a selected single year of
manufacture, presuming vehicles manufactured in this year could be observed crashing in all the
years for which data are available. Unfortunately, in this design, the effect of vehicle age of
crash would be confounded with any change in overall crash severity which may be observed
from year to year in the crash data. Again, this analysis would also be confined to examination
of vehicle deterioration effects over a 10 year period.
In summary, the outcome of this extra analysis examining age of vehicle at time of crash suggest
the results of estimating crashworthiness by year of manufacture presented above also
encompass the effects of any deterioration of a vehicle over time on crashworthiness due to the
confounded nature of both effects in the analysis design used.
6.
CONCLUSIONS
Additional crash data has enabled the crashworthiness ratings to be obtained for a larger range of
car models than previously now covering 130 different vehicle models. The new data set has
been able to produce more up-to-date and reliable estimates of the crashworthiness of individual
car models than those published previously.
The rating scores estimate the risk of a driver being killed or admitted to hospital when involved
in a tow-away crash, to a degree of accuracy represented by the confidence limits of the rating in
each case. The estimates and their associated confidence limits are sufficiently sensitive that
they are able to identify 44 models of passenger cars, four-wheel drive vehicles, passenger vans
and light commercial vehicles which have superior or inferior crashworthiness characteristics
compared with the average vehicle.
The crashworthiness of passenger vehicles (cars, station wagons and taxis), measured by the risk
of the driver being killed or admitted to hospital as the result of involvement in a tow-away
crash, has been estimated for the years of manufacture from 1964 to 1996. This study futher
updates the original one by Cameron et al (1994a) for years of manufacture 1964 to 1992 and
showed similar patterns of improvements in crashworthiness with the greatest gains over the
years 1970 to 1979 during which a number of new Australian Design Rules aimed at occupant
protection took effect. Further gains in crashworthiness have also been observed over the years
1986 to 1996.
7.
ASSUMPTIONS AND QUALIFICATIONS
The results and conclusions presented in this report are based on a number of assumptions and
warrant a number of qualifications which the reader should note. These are listed in the
following sections.
7.1
Assumptions
It has been assumed that:
•
TAC claims records and NSW Police crash reports accurately recorded driver injury,
hospitalisation and death.
•
There was no bias in the merging of TAC claims and Victorian Police crash reports related
to the model of car and factors affecting the severity of the crash.
•
Crashed vehicle registration numbers were recorded accurately on Police crash reports and
that they correctly identified the crashed vehicles in the Victorian and NSW vehicle
registers.
•
The adjustments for driver sex, age, speed zone and the number of vehicles involved
removed the influences of the main factors available in the data which affected crash severity
and injury susceptibility.
•
The form of the logistic models used to relate injury risk and injury severity with the
available factors influencing these outcomes (including the car models) was correct.
7.2
Qualifications
The results and conclusions warrant at least the following qualifications:
•
Only driver crash involvements and injuries have been considered. Passengers occupying
the same model cars may have had different injury outcomes.
•
Some models with the same name through the 1982-96 years of manufacture may have
varied substantially in their construction and mass. Although there should be few such
models in these updated results, the rating score calculated for these models may give a
misleading impression and should be interpreted with caution.
•
Other factors not collected in the data (eg. crash speed) may differ between the models and
may affect the results. However, earlier analysis has suggested that the different rating
scores are predominantly due to vehicle factors alone (Cameron et al 1992).
REFERENCES
BMDP Inc. (1988), BMDP statistical software manual. Chief Ed: WJ Dixon. University of
California Press, Berkeley.
CAMERON, M. H. (1997); “The effectiveness of Australian Design Rules aimed at occupant
protection”. Proceedings, seminar on Structural Crashworthiness and Property Damage
Accidents. Department of Civil Engineering, Monash University.
CAMERON, M.H., FINCH, C.F., and LE, T. (1994a), “Vehicle Crashworthiness Ratings:
Victoria and NSW Crashes During 1987-92 - Summary Report”. Report No. 55, Monash
University Accident Research Centre,
CAMERON, M.H., FINCH, C.F., and LE, T. (1994b), "Vehicle Crashworthiness Ratings:
Victoria and NSW Crashes During 1987-92 - Technical Report". Report No. 58, Monash
University Accident Research Centre.
CAMERON, M.H., NEWSTEAD, S.V., LE, T. and FINCH, C. (1994c) “ Relationship between
vehicle crashworthiness and year of manufacture”. Report No. 94/6 Royal Automobile Club of
Victoria Ltd.
CAMERON, M.H., MACH, T., and NEIGER, D. (1992), "Vehicle Crashworthiness Ratings:
Victoria 1983-90 and NSW 1989-90 Crashes - Summary Report". Report No. 28, Monash
University Accident Research Centre.
CAMERON, M.H., NEWSTEAD, S.V. and SKALOVA, M. (1996), “The development of
vehicle crashworthiness ratings in Australia” Paper 96-S9-O-14, Proceedings 15th International
Technical Conference on the Enhanced Safety of Vehicles, Melbourne, May 1996.
GREEN, P. (1990), "Victorian Road Accident Database: Frequency Tables for Accident Data
Fields: 1988". Accident Studies Section, VIC ROADS.
GUSTAFSSON, H., HAGG, A., KRAFFT, M., KULLGREN, A., MALMSTEDT, B.,
NYGREN, A., and TINGVALL, C. (1989), "Folksam Car Model Safety Rating 1989-90".
Folksam, Stockholm.
HOSMER, D.W., and LEMESHOW, S. (1989), "Applied Logistic Regression". Wiley, New
York.
NEWSTEAD, S., CAMERON, M. and SKALOVA, M. (1996), “Vehicle Crashworthiness
Ratings : Victoria and NSW Crashes During 1987-94” Report No. 92, Monash University
Accident Research Centre.
NEWSTEAD, S., CAMERON, M. and LE, C.M. (1997), “Vehicle Crashworthiness Ratings and
Crashworthiness by Year of Manufacture: Victoria and NSW crashes during 1987-95. Report
No. 107, Monash University Accident Research Centre.
PAPPAS, M. (1993), "NSW Vehicle Occupant Protection Ratings Documentation". Report to
NRMA Ltd. and Road Safety Bureau, Roads and Traffic Authority, NSW.
SOCIAL DEVELOPMENT COMMITTEE (1990), "Inquiry into Vehicle Occupant Protection".
Parliament of Victoria.
APPENDIX 1
MAKES AND MODELS OF CARS INVOLVED IN
VICTORIAN AND NSW CRASHES DURING 1987-96
I
23/02198
I
Page 1
I
23/02198
•
Page 2
..
23/02/98
Page 3
..
23/02/98
Page 4
..
23/02198
Page 5
APPENDIX
CRASHWORTHINESS
ALL VEHICLES
ESTIMATES
7:
BY YEAR OF MANUFACTURE
0.00
0.08
0.08
4.68
7.22
2.54
3.89
6.53
2.64
4.10
6.33
2.23
4.43
6.21
1.78
24
3.98
5.40
1.42
5.39
32
4.74
6.11
1.37
5.17
30
4.68
5.71
1.03
25.34
4.87
27
4.45
5.34
0.89
24.44
4.73
25
4.34
5.15
0.81
15.79
21.79
3.44
1964
21.47
27.07
5.81
1965
22.27
22.63
5.04
28
1966
20.61
24.70
5.09
29
1967
21.80
24.06
5.25
31
1968
19.81
23.41
4.64
1969
19.15
28.12
1970
20.19
25.62
1971
19.24
1972
19.36
AVERAGE
33
1973
19.59
24.33
4.77
26
4.40
5.16
0.76
1974
18.64
22.87
4.26
23
3.99
4.56
0.57
1975
17.17
23.80
4.09
22
3.82
4.37
0.55
1976
16.76
21.86
3.66
21
3.44
3.91
0.47
1977
16.16
22.36
3.61
20
3.38
3.86
0.49
1978
15.86
21.51
3.41
19
3.21
3.62
0.41
1979
14.52
21.81
3.17
18
2.99
3.36
0.37
1980
15.00
20.44
3.06
15
2.89
3.25
0.36
1981
14.46
21.56
3.12
17
2.94
3.30
0.36
1982
14.50
21.31
3.09
16
2.92
3.27
0.34
1983
14.70
20.73
3.05
13
2.87
3.23
0.36
1984
13.71
20.72
2.84
12
2.69
3.00
0.32
1985
14.41
21.20
3.05
14
2.90
3.22
0.33
1986
13.54
20.59
2.79
11
2.63
2.96
0.33
1987
13.03
21.04
2.74
10
2.57
2.93
0.36
1988
13.17
20.56
2.71
9
2.54
2.89
0.36
1989
12.60
19.85
2.50
7
2.34
2.67
0.34
1990
12.74
19.07
2.43
6
2.26
2.61
0.36
1991
12.88
20.27
2.61
8
2.40
2.84
0.45
1992
12.64
18.46
2.33
3
2.12
2.57
0.45
1993
12.60
18.88
2.38
4
2.14
2.64
0.50
1994
12.13
16.65
2.02
1.79
2.28
0.49
1995
11.52
18.90
2.18
2
1.87
2.53
0.65
1996
13.21
18.35
2.42
5
1.87
3.15
1.28
APPENDIX 2
LOGISTIC REGRESSION ESTIMATES OF
INJURY RISK BY MODEL AND MARKET GROUP
Appendix.xls--PR(RISK)
BY MKT GRP
CWR for NSW - VIC (87-96)
ALL MODEL
13.54
Holden20.05
12.47
AVERAGE
I
12.57
Sierra
82-96
10.16
1.59
11.33
Landcruiser
82-89
18.08
22.08
5.64
10.42
8.37
22.85
18.46
5.35
8.78
Drover
85-87
84-96
10.17
88-96
13.65
4RunnerIHilux
4.00
10.40
14.07
13.12
17.02
8.57
14.39
4.78
3.99
8.65
12.25
12.05
18.09
15.57
7.70
Feroza
82-87
82-90
89-96
7.19
7.10
Il.ll
6.84
2.42
90-96
Patrol
12.06
12.83
13.22
4.66
10.66
10.47
17.31
3.92
8.96 Vitara
Maverick
Jackaroo
3.07
Range
Rover
Pajero
Rocky
F70/75/80
8.51
I
11.99
Ford 26.37
8.65
10.62
10.01
9.46
16.43
Panel
Van
21.73
31.64
9.91
82-90
21.65
13.65
15.01
3.15
3.98
8.64
12.90
720Ute
82-85
82-96
13.97
12.19
Navara
13.22
10.71 Carry
Hiace/Liteace
90-96
85-86
82-93
85-88
10.50
13.01
11.02
15.52
3.33
13.79
16.90
Falcon
Shuttle
Ute
82-87
10.60
3.36
86-96Ute
11.37
9.43
8.63
1.94
15.37
XFNUte
88-90
22.51
12.29
18.08
31.44
4.65
3.37
8.93
26.73
15.61
2.04
12.19
II 14.39
Rodeo
13.44
8.92
10.49
WB
Series
4.60
Commodore
Scurry
Brumby
Mighty
Boy
10.36
II
7.64
9.79
2.15
11.37
11.71
8.42
10.60
9.63
8.79
2.18
2.58
2.08
Lexcen
91-96
93-96JP
Commodore
VR/VS
Verada
KR/KS
ApolIoJM/
Camry
FalconED
Magna Apr92-94
TR/TS
Holden
n EB Series II
20/02/98
Page 1
Appendix.xls---PR(RISK)
BY MKT GRP
CWR for NSW - VIC (87-%)
12.47
ALL MODEL
Falcon EA
7.46
7.84
12.17
9.21
5.77
5.88
Fairlane
N
CrownlCressida
10.00
200
82-93
7.45
6.30
8.16
4.17
9.80
82-96
5100
6.65
4.33
8.44
Cressida
10.24
16.52
7.32
12.42
700
Series
84-92
89-96
Lexcen
10.71
89-93
6.42
6.92
10.08
5.12
12.47
11.63
9.42
9.31
13.65
5.28
5.21
8.68
3Accord
Series
90-93
10.10
8.45
12.24
11.25
16.13
3.89
3.24
929
82-85
82-89
6.56
&VBLIDO
82-88
10.35
10.29
4.51
82-94
86-88
2.54
8.65
13.33
12.33
10.49
4.19
10.06
86-90
6.29
3.52
7.86
300-600
83-96
Series
10.66
4.01
2.55
9.79
Sonata
82-90
11.39
11.82
11.89
1.19
1.11
VNNP
6.09
12.25
12.20
4.19
6.16
3.57
3.05
10.87
6.93
9.22
XJ6
Statesman
92-96
82-91
85-90
11.33
11.28
2.88
1.18
14.49
14.06
12.78
9.81
3.25
8.04
Fair1ane
Z
10.73
11.53
0.80
11.12
XD-XF
12.79
2.44
11.49
LID
F
94-96
1O.D1
7.73
10.01
8.15
11.45
12.30
0.91
Commodore
VL
11.28
11.75
10.68900
Falcon
EF
11.84
AVERAGE
Skyline
Magna
TM-TP
11.25
88-Mar92
9.42
Peugeot11.08
5.50
505
10.30
11.47
3.77
7.56 Liberty
82-93
9.93
7.85
8.90
7.4312.13
89-96
88-91
4.79
12.36
6261MX688-91
16.33
11.29
3.45
9.43
Galant
89-94
92-96
6261MX692-96
Telstar
I 7.70
I
Ford
20/02/98
2.43
Page 2
Appendix.xls---PR(RISK)
BY MKT GRP
CWR for NSW - VIC (87-96)
ALL MODEL
13.22
13.40
12.15
14.18
14.70
13.44
10.89
16.23
1.53
82-89
11.72
Prairie
84-86
11.89
13.33
11.35
13.97
17.89
10.53
Stanza
12.68
12.47
1.49
14.91
19.86
8.97
1.47
15.41
Camira
6261MX683-87
82-86
20.22
8.51
Telstar
83-87
1.44
Gazelle
84-88
11.77
6.54
2.19
Corona
1800/Leone
82-95
82-87
13.01
Corsair
89-92
82-83
10.91
15.42
1.50
83-86
11.42
12.90
Bluebird
88-92
12.57
9.74
17.51
6.22
86-88
14.82
15.48 Nimbus
12.59
12.82
2.48
14.31
4.51
12.99
1.48
11.28
2.83
Pintara
84-91
14.10
11.07
IIAVERAGE
Camry
Sigma/Scorpion
ApolloJK/JL
14.17
11.70
12.47
I
Toyota
Tarago
91-96
10.32
7.70
13.76
6.05
Toyota
Tarago
83-90
14.92
13.54
16.43
2.88
Nissan
Passenger
Vans
82-92
16.52
14.80
18.46
3.66
Mitsubishi
Passenger
Vans
82-96
17.18
16.03
18.37
2.34
Nissan
20/02198
11.47
89-94
Nova
95-96
8.32
14.39
12.90
14.60
9.81
13.22
Nova
15.62
Corolla
11.14
14.60
6.28
323
90-94
10.45
15.72
12.57
20.13
7.23
7.16
7.56
Tercel 91-95
83-88
95-96
16.62
9.51
1.69
86-88
13.44
3.62
1.75
88-91
13.65
1.97
82-84
4.59
10.27 Civic
10.93
13.65
8.72
4.93
5.69
82-83
89-96
86-87
11.31
13.54
18.65
4.03
7.35
14.62
Lantra
Pulsar
92-95
13.72
11.48
14.60
13.25
5.28
12.84
13.52
10.95
16.01
GeminiRB
11.39
11.09 Applause
12.34
Page 3
Appendix.xls---PR(RISK)
BY MKT GRP
CWR for NSW - VIC (87-%)
ALL MODEL
19.88
15.21
9.25
95-96
82-89
82-92
31.91
11.55
16.52
4.97
13.85
Festiva 94-96
WB
13.86
15.01
14.28
13.44
16.23
17.12
16.92
5.96
1.12
1.91
15.97
11.90
Barina
Excel
121
91-96
90-94
89-94
88-92
84-86
89-93
82-88
3.55
84-87
14.80
8.08
19.40
4.60
16.95
CC
16.43
20.67
4.25
Charade
85-88
82-86
12.79
15.42
12.90
20.31
18.56
17.31
14.93
Cordia
94-96
20.85
17.70
25.79
29.16
8.09
8.30
24.75
Handivan82-90
87-90
11.82
13.65
2.64
82-84
10.17
21.12
10.95
Astra
23.52
30.00
82-85
23.27
83-86
12.68
16.33
3.64
2.66
3.68
1.94
15.33
14.38
15.22
Lancer
Laser/Meteor
Swift
Colt
CA
/ CB
KA - KE
12.57
16.13
14.24
Civic
11.92
16.43
10.47
18.18
21.65
3.47
18.46
4.52
3.14
7.41
16.94
16.29 Hatch
88-93
13.65
11.43
15.92
14.07
2.27
14.73
Gemini
LaserKF
91-94
/KH
14.85
PulsarNector
6.48
26.65
91-93
27.38
15.62
25.87
10.24
8.63
20.23
4.51
5.36
14.01
AVERAGE
12.70
Festiva
WA
1.83
Quintet
SherpalFiori
City
15.19
15.13
21.44
12.72
12.47
I
Honda
20/02/98
21.47
91-90
10.33
17.02
13.31
89-94
10.01
11.58
8.32
17.12
9.89
13.17
15.92
Celica
RX7
90-93
82-85
10.14
10.26
3.51
11.76
11.93
Prelude
84-91
6.69
13.76
7.11
5.44
10.74 Paseo
13.65
13.86
3.60
Capri
Page 4
Appendix.xls---PR(RISK)
BY MKT GRP
CWR ror NSW - VIC (87-96)
ALL MODEL
20/02198
16.72
26.64
9.92
AVERAGE
10.73
8.85
10.06
10.78
15.11
17.12
Celica
83-86
4.67
7.41
16.62
20.22
7.77
9.49
12.23
86-88
10.64
20.94
10.30
7.06
4.34
21.23
13.17
12.76
33
86-89
83-92
12.08
7.58 Exa
82-90
15.07
CRX
87-96
14.88
Prelude
Integra 92-96
Supra
12.47
Page 5
APPENDIX 3
LOGISTIC REGRESSION ESTIMATES OF
INJURY SEVERITY BY MODEL AND MARKET GROUP
Appendiuls--PR(SEVERE)
BY MKT GRP
CWR for NSW - VIC (87-96)
8.09
Holden17.10
I
28.63
13.49
30.06
12.61
17.03
16.02
4.50
42.49
12.43
21.53
13.48
13.35
26.84
29.95
13.81
11.76
10.51
15.90
25.25
26.41
13.00
10.74
23.75
13.73
7.32
21.04
11.58
18.14
8.27
21.68
19.19
16.14
20.72
17.05
16.77
14.70
31.47
4.03
15.61
21.99
24.45
19.15
21.97
16.22
18.66
4RunnerIHilux
Drover
85-87
82-96
Feroza
89-96
82-90
Patrol
82-87
Sierra
82-89Rover
Vitara
88-96
84-96
Maverick
Jackaroo
Landcruiser
90-96
Rocky
F70/75/80
Range
Pajero
II
5.70
24.66
14.16
17.43
23.13
20.16
18.88
30.46
12.38
26.84
11.55
14.51
18.56
16.17
13.65
9.33
7.11
15.57
30.59
27.95
8.28
17.05
15.52
32.57
12.51
23.90
36.41
15.46
15.01
21.78
10.50
16.94
13.57
19.94
9.54
20.88
23.28
24.05
33.51
21.13
20.87
15.38
18.80
29.75
26.17
19.48
Navara
Hiace/Liteace
86-96
82-90
85-86
85-88
WB
XFNVte
720Vte
82-87
88-90
Series
Vte
Falcon
82-96
Panel
Van
Rodeo
Commodore
Shuttle
90-96
82-85
82-93
Scurry
Brumby
Carry
Mighty
Boy Vte
II
12.92
14.41
7.33
20.25
20.43
17.27
7.68
24.95
6.02
93-96
Lexcen
91-96 KR/KSVR/VS
Commodore
Verada
FalconED
Magna
TR/TS
Apr 92-94
I
15.68
Ford 22.97
20.85
16.25
17.22
EB Series II
20/02198
Page 1
Appendix.xls--PR(SEVERE)
BY MKT 'GRP
CWR for NSW - VIC (87-96)
20.88
ALL MODEL
Volvo
20102198
19.57
2.77
22.34
21.75
12.45
7.75
34.20
26.84
20.01
23.59
17.66
19.26
3.71
22.97
21.37
19.09
20.90
21.37
3.58
16.82
16.25
9.31
8.71
24.95
26.12
21.09
21.07
19.47
19.82
2.51
22.70
21.08
AVERAGE
21.72
20.25
Falcon EA
82-90
Lexcen
Sonata
Commodore
89-96
82-88
VB- VL
85-90XD-XF
89-93
FalconEF
93-96
94-96
Falcon
VNNP
MagnaTM-TP
Canny
Skyline
ApolloJM/
JP
88-Mar92
10.17
24.80
27.40
10.51
13.69
24.20
8.79
33.16
18.35
14.63
21.70
15.68
13.35
8.87
16.18
13.48
17.61
31.09
14.16
7.85
14.80
10.31
25.10
19.42
22.78
22.26
16.63
16.87
14.47
39.65
21.86
41.34
39.75
9.80
28.63
16.78
10.61
21.13
18.05
26.84
12.03
20.64
12.82
18.16
27.81
9.66
29.03
20.08
14.10
23.70
22.02
13.43
18.27
7.13
25.40
23.12
21.68
11.55
12.51
19.65
15.99
9.35
36.73
26.62
26.77
23.86
18.83
23.36
17.48
16.88
15.84
21.60
27.54
21.20
29.35
16.67
Cressida
82-89
N
200
82-93
86-88
5300-600
89-93
86-90
Crown/Cressida
82-85
& LLTO
TO FD
929
XJ6
3900
Statesman
Series
90-93
82-96
82-94
Series
89-96
700
100
83-96
84-92
SeriesZ
Accord
82-88
&
Fairlane
92-96
82-91
I
Peugeot
505
82-93
21.13
13.35
31.72
18.36
Subaru
Liberty
89-94
19.25
13.94
25.98
12.04
Mitsubishi
Galant
89-96
17.79
9.91
29.82
19.90
Page 2
Appendix.xls---PR(SEVERE)
BY MKT GRP
CWR for NSW - VIC (87-96)
I
ALL MODEL
20.88
20.23
24.35
4.63
19.88
15.04
17.51
24.50
29.43
21.36
10.53
17.25
4.16
17.52
18.50
32.32
20.47
20.07
7.74
18.58
22.81
20.65
20.51
19.23
3.74
22.97
28.63
18.37
3.81
10.25
22.81
9.87
27.47
14.38
17.14
14.11
16.75
10.78
6.03
22.66
8.89
26.41
27.67
27.54
23.28
21.66
17.66
24.35
4.23
8.11
22.18
21.46
18.20
3.50
31.72
21.70
32.69
18.73
19.87
AVERAGE
21.07
24.58
22.08
20.20
16.61
18.22
Corsair
83-86
Corona
82-95
84-91
82-87
88-92
92-96
Te1star
89-92
83-87
Gazelle
84-88
Nimbus
1800/Leone
82-83
86-88
Bluebird
6261MX6
Pintara
Telstar
88-91
Prairie
Camira
84-86
82-89
Stanza
82-86
Camry
ApolloJK/JL
Sigma/Scorpion
I
I
Toyota
Tarago
91-96
15.73
7.90
28.90
21.00
Toyota
Tarago
83-90
21.21
17.54
25.40
7.86
Nissan
Passenger
Vans
82-92
21.65
17.27
26.84
9.57
Mitsubishi
Passenger
Vans
82-96
23.08
20.11
26.41
6.30
Nissan
20/02198
16.69
12.03
13.08
8.83
21.37
18.91
19.72
14.37
15.18
27.40
34.09
20.63
15.65
27.67
18.63
16.91
9.18
14.31
37.97
31.22
23.30
21.61
11.41
25.98
17.52
11.71
15.52
24.35
13.98
15.01
19.14
4.68
12.22
24.90
14.57
23.75
15.05
25.69
22.75
Corolla
91-95
82-84
323
Nova
95-96
95-96
90-94
Civic
82-83
Tercel
83-88
92-95
89-96
Lantra
GeminiRB
86-87
Pulsar
Applause
Page 3
Appendix.xls--PR(SEVERE)
BY MKT GRP
CWR for NSW - VIC (87-96)
ALL MODEL
21.64
11.97
16.82
15.14
31.96
22.45
5.36
14.57
19.28
14.99
18.30
7.09
16.69
18.58
5.39
25.40
29.56
27.81
21.39
21.73
30.75
18.22
35.33
27.43
19.38
21.70
17.86
20.41
14.97
39.56
20.09
29.83
18.92
19.16
38.08
27.61
10.46
20.88
17.84
19.11
19.17
18.79
18.67
19.81
9.29
25.54
8.57
26.41
22.50
8.08
28.09
23.11
24.72
21.83
17.09
23.23
23.27
19.00
25.25
24.48
25.96
11.13
4.54
45.24
23.13
20.76
19.64
AVERAGE
17.11
22.97
9.48
32.45
8.02
27.40
23.13
22.05
11.44
10.99
33.04
26.12
19.81
19.56
20.85
6.87
4.49
4.70
16.21
27.26
35.77
23.59
21.26
25.54
31.34
22.98
25.82
13.75
11.68
17.88
17.70
9.84
27.54
30.84
22.25
30.97
23.17
21.94
21.11
22.44
25.87
23.10
19.89
Handivan
82-90
121
83-86
82-92
82-86
95-96
Excel
323
Colt
Laser/Meteor
89-93
82-88
KA - KE
91-96
Civic
88-91
Hatch
Gemini
890-94
82-84
82-85
7-90 CC
Nova
Swift
85-88
91-94
Lancer
Cordia
91-93
82-89
ector
Barina
Astra
PulsarN
Charade
89-94
84-86
84-87
88-93
94-96
88-92
WB
Corolla
86-88
LaserKF
/KH
Festiva
WA
CA
/ CB
Quintet
SherpalFiori
City
2.69
5.71
20.88
I
20/02/98
Honda
Prelude
84-91
17.26
12.61
23.13
10.51
Toyota
Celica
82-85
19.95
14.89
26.27
11.38
Page 4
Appendix.xls---PR(SEVERE)
CWR
ALL MODEL
20/02/98
23.24
14.12
23.86
31.22
37.36
26.33
19.70
27.26
18.25
7.56
14.88
36.11
8.41
67.33
49.17
20.27
14.51
34.09
22.86
27.39
15.87
13.08
13.95
10.30
32.20
36.63
24.56
20.50
14.56
24.88
21.67
30.08
16.58
19.58
16.04
36.31
24.82
43.27
27.51
18.02
31.09
20.67
AVERAGE
24.60
39.17
BY MKT GRP
for NSW - VIC (87-96)
CRX
Exa
33
892-96
83-92
3-86
86-88
Prelude
82-90
RX7
Celica
86-89
7-96
Paseo
91-90
90-93
89-94
82-85
Supra
Capri
Integra
20.88
Page 5
APPENDIX 4
CRASHWORTHINESS RATINGS OF
1982-96 MODELS OF CARS INVOLVED IN
CRASHES DURING 1987-96
with
(1) 95 % CONFIDENCE LIMITS
(2) 90 % CONFIDENCE LIMITS
Appendix.xls---CWR
BY MKT GRP
CWR for NSW - VIC (87-96)
I
I I
1.92
2.49
0.71
0.79
1.69
1.45
1.73
2.66
0.17
1.15
3.06
0.78
5.11 110
85
89-96
0.21
2.71
2.50
1.69
1.23
2.58
4.27
11
Sierra
1.84
88-96
1.48
2.19
1.80
2.59
2.11
1.15
3.26
33
2.21
82-87
0.66
2.12
2.79
49
Drover
85-87
4.32
2.32
1.83
4.15
94
89
3.08
2.95
Vitam
Feroza 82-96
0.97
2.20
2.02
Landcruiser
Maverick
Patrol
4Runner/Hilux
3.72
1.86
3.58
4.94
2.99
]ackaroo
2.60
ALL MODEL
1.10
AVERAGE
84-96
3.43
1.59
Range
Rover
7 2.46
54
65
Pajero
15
Rocky
F70/75/80
82-90
82-96
82-89
90-96
Holden
Ford
20/02198
I
II
1.56
1.24
0.81
2.60
1.78
2.60
73
2.74
129
60
1.27
0.95
2.62
1.75
1.87
3.34
3.62
3.57
5.94
122
96 2.73
4.64
3.54
3.58
1.85
3.58
3.34
5.82
1.88
2.51
1.49
3.05
2.14
0.86
1.16
2.45
3.31
23
34
2.23
3.10
5.04
1.89
3.67
8.58
4.48
4.39
8.06 127
1.59
2.59
70
2.30
62
6.06
19
37
2.02
85-86
82-90
Hiace/Liteace
WB
Series
82-85
82-93
Shuttle
85-88
Falcon
Panel
Van
Rodeo
82-96
XFNUte
Commodore
90-96
88-90
720Ute
Navara
Ute
Scurry
82-85
Carry
Brumby
Mighty
Boy Ute
82-96
86-96
82-87
Page 1
Appendix.xls--CWR
BY MKT GRP
CWR ror NSW - VIC (87-96)
ALL MODEL
AVERAGE
II I
64
29
2.31
1.01
1.52
1.50
2.53
24
27
2.07
1.11
61
2.60
2.66
0.43
0.27
2.21
1.86
2.30
2.48
41
2.34
2.23
2.66
48
1.05
0.71
1.46
1.76
18
5 2.47
43
0.32
2.63
52
2.06
3.08
1.06
4.20
3.13
0.85
1.55
2.20
2.40
0.46
2.15
2.61 22
1.12
2.63
1.41
1.83
2.08
1.97
2.38
2.44
2.03
Mitsubishi
I
Ford
Holden
Volvo
20/02/98
0.55
0.62
984632 2.31
1.60
1.58
0.56
1.90
0.81
28
1.38
0.86
0.53
0.73
2.03
1.07
1.95
1.03
1.44
2.57
2.30
16
12
10
1.75
0.62
1.37
2.07
1.32
1.42
1.36
1.31
1.09
1.30
1.22
2.62
3.53
2.58
20
39
1.96
26
2.07
1.62
2.99
38
2.30
2.ll
2.10
2.77
2.64
1.59
1.50
1.66
2.21
2.44
0.72
1.41
2.12
1.97
1.05
3.02
2.04
1.38
2.51
3.33 21
2.60
Falcon
EH
Series II
Verada EA
KR/KS
93-96
Lexcen
Commodore
89-93
VNIVP
Falcon
94-96
EF JP
Sonata
82-90
XD-XF
91-96
82-88
VBVL
VRNS
Skyline89-96
ApolloJM/
Camry
MagnaTM-TP
85-90
88-Mar92
Apr
92-94
0.74
5Statesman
Series
900
Fairlane
Crown/Cressida
100
86-88
N
9-93
700
300-600
Series
XJ6
82-85
89-96
& LID D
90-93
3Cressida
884-92
2-96
200
Series
83-96
82-94
82-93
Accord
86-90
82-96
2-91
Page 2
2.50
2.71
0.21
Appendix.xls··-CWR
BY MKT GRP
CWR for NSW - VIC (87-96)
ALL MODEL AVERAGE
2.50
2.71
0.21
92-96
2.47
51
1.19
3.74
2.55
82-88
2.48
53
2.00
2.96
0.96
Accord
82-85
2.73
71
1.92
3.54
1.62
929
82-89
2.99
87
2.27
3.70
1.44
BMW
3 Series
Ford
Fairlane Z
Honda
Mazda
I
20/02198
2.60
& LID
F
1.84
2.45
75
2.30
57
2.53
2.51
13
1.60
2.78
0.63
2.13
2.37
1.71
3.84
3.08
77
68
2.77
2.71
0.55
0.54
0.90
2.40
1.17
3.89
2.85
59
67
58
2.58
2.67
0.97
2.29
1.15
1.75
1.82
2.73
3.41
79
46
35
2.40
0.58
2.79
0.56
3.62
2.70
1.09
2.68
4.71
3.27
3.34
88
93
82 3.06
4.07
2.90
1.16
1.51
40
50
2.47
1.12
1.38
2.51
17
1.82
0.75
30
2.16
0.62
2.99
2.12
2.95
3.02 119
2.57
2.97
2.61
1.62
3.12
3.77
2.81
3.57
5.46
Peugeot 2.240.68
2.68
2.85
2.99
2.32
505
82-93
83-86
Corona
Stanza
82-86
82-83
Pintara
89-92
86-88
Camira
Gazelle84-88
82-89
84-86
88-91
89-96
Bluebird
888-92
2-86
1800/Leone
82-95
82-87
Corsair89-92
Nimbus84-91
Prairie
83-87
92-96
626/MX6
89-94
Telstar
Ga1an!
Liberty
Camry
ApolloJK/JL
Sigma/Scorpion
Toyota
Tarago
91-96
1.62
14
0.44
2.81
2.38
Toyota
Tarago
83-90
3.16
101
2.51
3.82
1.31
Nissan
Passenger
82-92
3.58
112
2.70
4.46
1.76
Vans
Page 3
Appendix.xls---CWR
BY MKT GRP
CWR for NSW - VIC (87-96)
3.18
3.98
45
0.81
86
2.51
97
84 3.39
2.41
83
78
74
2.85
2.76
106
3.29
1.51
2.57
4.08
108
0.76
2.11
3.30
36
2.25
89-96
2.08
0.92
1.54
1.33
1.41
2.95
3.47
42
32
31
2.39
2.18
2.19
Lantra91-95
82-96
92-95
0.21
2.71
2.54
3.35
Astra
0.79
1.69
2.83
3.12
4.52
3.90
113
111
3.68
PulsarNector
84-87
PulsarN
ector
1.87
4.38
3.12
0.91
1.13
3.69
4.97
47
2.94
86-87
82-86
0.87
0.67
2.39
0.74
2.36
2.66
2.46
2.01
2.06
1.88
1.60
1.16
1.86
1.32
1.80
1.19
3.72
3.67
3.86
3.94
3.33
3.61
3.19
3.52
3.13
90
81
80
55
72
56
76
2.89
2.81
2.52
3.00
Corolla
Gemini
Corolla95-96
Nova
LaserKF
Nova
91-94
90-94
88-91
86-88
82-84
/KH
0.38
3.05
3.42
104
1.61
2.40
4.01
102
3.20
2.19
2.13
4.32
103
3.22
94-96
1.94
4.23
105
91-96
2.76
1.91
4.67
95-96
2.75
107
3.32
Excel
89-94
3.01
3.78
109
Colt
82-88
2.56
3.39
3.40
117
3.96
2.37
Pulsar
Tercel83-88
4.07
GeminiRB
0.75
2.40
3.14
2.73
Corolla90-94
95-96
82-89
82-83
CC
88-92
Laser/Meteor
323
Festiva
WB
KA - KE
2.29
3.26
121
1.14
3.89
Swift
Barina
89-93
84-86
4.54
Civic
ALL
MODEL2.50
AVERAGE
Cordia
Lancer
CA
/ CB
3.51
Quintet
Applause
Passenger
Vans
2.95
2.52
3.23
2.77
3.32
I
2.60
Page
4
Appendix.xls---CWR
BY MKT GRP
CWR for NSW - VIC (87-96)
FestivaWA
91-93
4.19
5.79
0.21
2.71
2.50
1.87
3.21
2.98
3.14
115
3.92
83-86
82-89
4.13
3.20
3.70
3.43
3.48
7.39
7.61
126
125
124
5.56
Handivan
121 87-90
82-85
121
6.01
1.50
4.85
4.64
9.23
116
6.22
3.89
Excel
88-93
4.32
4.26
7.69
8.02
128
5.86
Hatch
Swift
82-92
85-88
82-90
3.61
4.06
3.53
2.22
5.07
5.83
123
5.06
4.03
Barina
94-96
ALL MODEL
AVERAGE
2.02
1.54
6.07 130
118
Charade
82-86
City
SherpalFiori
5.55
4.30
Honda
20102198
95
1.41
99
69
0.79
1.62
44
4.68
0.75
5.43 114
3.09
4.15
2.01
2.13
1.08
4.87
5.24
4.14
100
1.28
4.81
92
4.98
1.60
6.58
4.09
2.78
1.56
1.33
4.11
2.72
3.92
66
4.49
63 3.16
1.35
1.36
2.70
25
3.14
2.38
3.46
98
3.53
4.56
1.45
6.01
120
3.73
2.97
4.53
91
3.04
2.51
2.67
3.70
2.64
2.03
1.52
3.14
2.60
Exa
83-86
RX7
82-85
CRX
87-96
33
83-92
86-88
90-93
Paseo
91-90
Prelude84-91
Celica
86-89
89-94
Prelude92-96
Integra
Supra 82-90
Capri
Page 5
APPENDIX
with 90%CI.xls--CWR
BY MKT GRP
CWR for NSW - VIC (87-96)
I I
Drover
85-87
Feroza
89-96
2.52 82-96
4Runner/Hilux
82-87
84-96
Sierra
Landcruiser
Patrol
Viiara
88-96
Jackaroo
Maverick
Range
Rover
Rocky
F70175/80
Pajero
82-90
82-96
90-96
82-89
II
85-86
82-90
82-93
85-88
720
Vte
XFNUte
882-96
8-90
Rodeo
82-85
Navara
Falcon
Commodore
90-96
Ute
Hiace/Liteace
WB
Series
Panel
Van
Shuttle
Scurry
Carry
Brumby
82-96
Mighty
Boy Vte
86-96
82-87
2.01
0.83
0.94
2.49
1.88110
1.69
1.45
2.66
2.724.14
2.18
49
0.56
2.46
1.134.76
1.10
0.17
1.03
1.55
2.73
1.24
1.51
1.524.64
94
3.12
3.08
0.96
2.01
89
85
3.63
1.56
2.95
1.42
1.87
1.07
11
2.45
2.07
1.323.09
33
1.77
2.21
2.97
3.43
3.96
1.95
2.99
2.10
2.60
ALL MODEL
3.430.32
AVERAGE
65
15
72.69
54
1.59
I
Holden
Ford
23/02/98
1.68
1.35
1.10
2.60
1.93
2.73
0.80
3.948.17
1.662.38
1.333.13
3.94
3.55
5.73
2.18
5.82
4.64
1.88
1.973.22
129
60
3.52
4.23
3.00
1.25
1.59
23
34
0.72
1.07
2.23
2.01
73
96
2.93
1.47
3.10
127
122
7.70
3.76
4.10
2.41
70
3.50
3.48
2.74
1.80
6.06
2.30 2.70
2.59
19
62
37
2.02
Page 1
APPENDIX
with 9O'IoCI.xls---CWR
BY MKT GRP
CWR for NSW - VIC (87-96)
II I
Falcon
EA
Series 11
Verada EB
KR/KS
82-90
93-96
89-93
82-88
Falcon
XD-XF
FalconEF
94-96
Sonata
89-96
VNIVP
VB- VL
Lexcen
Commodore
VRNS
Camry
Skyline91-96
MagnaTM-TP
ApolloJM/
JP
85-90
88-Mar92
Apr92-94
81.95
2.ll
20
28
2.07
0.68
1.26
1.39
1.38
0.97
6242.07
2.18
1.18
I.21
1.58
0.70
2.47
932.00
1.77
1.59
10
1.412.51
1.732.88
1.293.33
1.023.13
1.332.48
21
26
39
2.05
1.16
1.10
1.14
1.65
2.04
1.90
1.96
0.90
16
12
1.64
1.60
0.74
1.26
1.37
0.83
2.01
1.42
1.32
1.15
2.02
0.87
1.212.86
38
2.30
2.31
0.78
2.60
2.41
1.71
1.75
82-96
882-85
9-93
300-600
86-90
Series
700
84-92
83-96
XJ6
3Statesman
90-93
89-96
900
82-94
5Cressida
Series
Accord
100
200
Series
82-93
82-91
& LID D
Fairlane
86-88
N
Crown/Cressida
24
29
53.04
0.36
27
0.94
1.602.45
0.85
1.902.26
1.71
0.60
2.16
43
48
61
52
2.57
0.89
0.27
2.47
2.66
2.60
1.522.14
1.622.33
22
18
0.71
41
2.46
0.23
2.34
1.592.53
2.06
2.19
2.34
2.26
64
2.63
2.61
0.38
2.59
2.23
1.363.95
2.08
1.83
1.97
1.41 1.11
2.38
2.44
2.03
Mitsubishi
I
ord
Holden
Volvo
23/02198
0.62
Page 2
APPENDIX
with 90%CI.xls---CWR
BY MKT GRP
CWR for NSW - VIC (87-96)
ALL MODEL AVERAGE
2.60
2.69
0.17
92-96
2.47
51
1.40
3.54
2.14
82-88
2.48
53
2.08
2.88
0.80
Accord
82-85
2.73
71
2.05
3.41
1.36
929
82-89
2.99
87
2.38
3.59
1.21
BMW
3 Series
Ford
Fairlane Z
Honda
Mazda
I
2.52
& LID
F
13
1.642.99
40
2.37
1.54
1.60
1.373.56
2.16
2.34
1.883.67
59
88
0.49
1.384.42
82
3.03
1.36
1.832.65
35
0.82
50
1.24
0.98
17
30
3.34
2.36
1.16
2.20
1.393.67
77
57
58
2.19
0.75
2.58
2.53
68
0.52
2.38
2.74
2.50
2.45
67
79
75
3.03
3.32
3.23
0.53
0.46
0.94
1.79
2.90
2.83
93
0.47
3.06
1.922.88
46
0.97
2.47
2.40
2.39
1.82.
2.95
2.28
2.57
2.42
2.94
2.90
2.81
2.77
2.67
2.905.24
119
3.30
2.34
4.07
Peugeot 2.24 0.83
2.32
2.68
2.85
2.99
505
89-96
82-87
82-89
92-96
82-93
86-88
Galant
Corona
Stanza
82-95
83-86
89-92
Prairie
Telstar
83-87
84-86
Camira
626/MX6
Nimbus84-91
88-91
89-94
1800/Leone
82-83
Bluebird
82-86
88-92
Pintara
Gazelle84-88
Corsair
Camry
ApolloJKJJL
Liberty
Sigma/Scorpion
Toyota
Tarago
91-96
1.62
14
0.63
2.62
1.99
Toyota
Tarago
83-90
3.16
101
2.61
3.71
1.10
Nissan
Passenger
82-92
3.58
112
2.84
4.31
1.47
23/02198
Vans
Page 3
APPENDIX
with 90%CI.xls--CWR
BY MKT GRP
CWR for NSW - VIC (87-96)
2.67
3.183.84
0.97
1.84
3.22
86
1.63
1.123.27
32
1.74
2.19
84
90
1.58
89-94
1.063.73
45
2.39
1.343.49
47
84-86
55
2.01
2.73
90-94
78
81
2.89
111
0.66
PulsarNector
103
83
3.43
0.32
1.35
3.20
Festiva
WB
2.974.39
3.68
84-87
2.69
0.17
2.52
2.61
0.68
2.444.07
105
3.26
121
91-96
82-89
1.503.24
42
2.15
2.37
Lantra91-95
2.21
1.244.65
3.79
3.41
3.00
2.94
Cordia
82-86
88-92
2.84
107
3.80
0.96
2.31
3.29
Swift
Barina
89-93
Tercel83-88
2.07
97
4.18
2.11
2.69
3.96
1.27
3.32
2.41
86-87
3.72
0.64
3.39
Astra
82-88
1.523.52
2.52
82-83
1.413.64
1.953.52
72
0.62
2.24
1.56
2.76
Corolla95-96
Nova
95-96
2.14
76
3.08
0.63
2.81
Corolla90-94
88-91
2.53
80
3.26
0.57
0.73
Gemini
82-84
86-88
2.45
2.304.15
2.523.88
113
102
1.42
Civic
91-94
IKH
I CB
3.29
104
323
LaserlMeteor
KA - KE
3.494.44
117
36
1.77
3.96
2.25
89-96
82-96
PulsarN
ector
2.134.44
106
95-96
1.532.83
31
1.29
2.18
92-95
3.12
Lancer
CC
CA
108
Excel
GeminiRB
3.07
109
Colt
74
56
3.07
Nova 94-96
2.46
3.48
2.57
3.13
2.85
Corolla
LaserKF
ALL
AVERAGE
3.08
3.39
1.363.14
Pulsar
3.51 MODEL
Quintet
Applause
Passenger
Vans
3.23
2.95
3.32
2.52
2.77
I
Page
2.604
APPENDIX
with 9O'IoCI.xls---CWR
BY MKT GRP
CWR for NSW - VIC (87-96)
124
3.47
125
4.04
128
3.63
2.51
3.264.52
118
115
3.03
0.17
1.26
4.03
3.134.70
116
3.664.95
3.81
7.28
3.777.34
3.58
5.56
4.22
123
1.69
5.06
4.45
7.67
2.68
5.86
130
5.05
5.54
2.69
3.89
1.57
3.92
121
1.29
5.91
126
7.13
5.79
3.708.74
6.22
ALL MODEL
AVERAGE
5.55
4.30
Honda
23/02198
1.094.19
63
91
3.11
1.424.90
100
98
3.49
1.69
99
114
3.82
1.462.60
25
1.13
1.794.29
1.563.89
44
66
69
2.50
2.33
1.27
2.64
2.67
2.29
1.135.05
95
92
3.98
3.92
2.96
3.16
1.694.59
2.00
1.825.64
120
4.18
3.73
2.03
1.613.72
1.743.02
2.11
2.38
2.72
1.564.52
3.09
3.04
2.90
6.18
4.09
3.14
94-96
82-90
88-93
82-89
91-93
82-86
82-92
83·86
2.52
Charade
Excel
Festiva
121 87-90
85-88
WA
Handivan
82-85
Barina
Swift
Hatch
Sherpa/Fiori
City
2.60
91-90
Paseo
86-88
89-94
86-89
83-86
83-92
90-93
82-85
87-96
33
Celica
RX7
CRX 82-90
Exa
Prelude92-96
Prelude84-91
Integra
Capri
Supra
Page 5
APPENDIX 5
LOGISTIC REGRESSION ESTIMATES OF
INJURY RISK BY
YEAR OF MANUFACTURE
---
APPENDIX 5:
LOGISTIC REGRESSION ESTIMATES OF INJURY RISK BY YEAR OF MANUFACTURE
AVERAGE
-1.6741
0.0148
15.79
12.87
19.22
6.34
1964
0.3772
0.0683
21.47
19.30
23.81
4.51
1965
0.4241
0.0784
22.27
19.72
25.04
5.32
1966
0.3258
0.0705
20.61
18.44
22.97
4.52
1967
0.3970
0.0521
21.80
20.11
23.59
3.48
CAR
1968
0.2759
0.0462
19.81
18.41
21.29
2.88
1969
0.2341
0.0414
19.15
17.93
20.44
2.51
1970
0.2999
0.0308
20.19
19.24
21.18
1.95
1971
0.2397
0.0279
19.24
18.41
20.10
1.70
1972
0.2474
0.0256
19.36
18.59
20.16
1.57
1973
0.2618
0.0240
19.59
18.86
20.34
1.48
1974
0.2008
0.0192
18.64
18.08
19.22
1.14
1975
0.1003
0.0200
17.17
16.62
17.73
1.11
1976
0.0715
0.0181
16.76
16.27
17.26
0.99
1977
0.0274
0.0192
16.16
15.65
16.67
1.02
1978
0.0052
0.0166
15.86
15.43
16.30
0.87
1979
-0.0987
0.0162
14.52
14.13
14.92
0.79
1980
-0.0609
0.0159
15.00
14.60
15.40
0.79
14.08
14.85
0.77
1981
-0.1033
0.0159
14.46
1982
-0.0999
0.0152
14.50
14.14
14.88
0.74
1983
-0.0845
0.0164
14.70
14.30
15.10
0.81
1984
-0.1658
0.0151
13.71
13.36
14.06
0.70
1985
-0.1076
0.0144
14.41
14.06
14.76
0.70
1986
-0.1799
0.0159
13.54
13.18
13.91
0.73
1987
-0.2238
0.0173
13.03
12.65
13.42
0.77
1988
-0.2120
0.0173
13.17
12.79
13.56
0.78
1989
-0.2630
0.0175
12.60
12.22
12.98
0.76
1990
-0.2500
0.0188
12.74
12.34
13.16
0.82
1991
-0.2371
0.0223
12.88
12.40
13.38
0.98
1992
-0.2592
0.0243
12.64
12.12
13.17
1.05
1993
-0.2631
0.0272
12.60
12.02
13.19
1.17
1994
-0.3062
0.0300
12.13
11.52
12.77
1.25
1995
-0.3646
0.0386
11.52
10.77
12.31
1.54
1996
-0.2084
0.0692
13.21
11.73
14.84
3.11
APPENDIX 6
LOGISTIC REGRESSION ESTIMATES OF
INJURY SEVERITY BY
YEAR OF MANUFACTURE
---
APPENDIX 6:
LOGISTIC REGRESSION ESTIMATES OF INJURY SEVERITY BY YEAR OF MANUFACTURE
21.641.80
21.331.77
21.30
21.80
15.03
17.15
18.05
18.88
20.07
20.91
20.87
23.01
23.77
19.71
19.84
19.57
-0.2076
0.0331
0.0626
0.0316
0.0317
0.0281
20.59
21.04
20.44
21.31
21.51
22.87
18.35
18.46
18.88
19.07
23.27
0.0931
22.207.17
21.104.22
20.432.99
21.572.55
21.571.98
20.851.98
21.511.80
21.581.69
16.88
15.16
17.43
20.132.08
20.39
20.46
20.68
20.59
22.70
23.00
23.90
25.82
19.842.69
22.051.99
22.031.64
22.181.72
22.481.80
22.741.83
22.451.87
23.452.15
22.882.01
24.952.25
25.702.69
26.963.19
27.413.51
19.02
19.59
19.89
23.992.19
-0.1781
-0.1794
-0.0443
-0.0810
-0.0131
-0.2148
-0.3326
-0.1178
-0.0735
-0.1673
-0.0715
-0.0634
-0.0350
-0.0637
-0.0283
-0.0166
0.2122
0.0015
0.1147
0.1436
0.1493
0.1973
0.3396
0.0273
0.0405
0.0373
0.0430
0.0262
0.0282
0.1220
0.0702
0.0498
0.0456
0.0305
0.0280
0.0251
0.0277
20.27
20.73
21.20
21.56
21.86
23.80
24.33
25.34
28.12
20.72
21.81
22.36
24.44
18.90
16.65
19.85
AVERAGE CAR
27.098.37
20.99
21.32
21.20
26.02
15.71
31.237.96
18.72
0.1634
0.0489
0.2870
0.1286
0.0796
0.0716
0.1220
23.41
24.70
27.07
21.79
18.263.10
25.932.93
30.54
-0.0915
0.0044
0.0300
0.0470
0.0595
0.0403
0.0317
0.0309
0.0570
0.0344
0.0272
20.56
25.62
29.39
27.025.70
28.567.36
0.1010
0.1030
0.0420
14.71
3.68
24.06
22.63
5.03,
-1.2781
APPENDIX 7
CRASHWORTHINESS ESTIMATES BY
YEAR OF MANUFACTURE
APPENDIX
CRASHWORTHINESS
ALL VEHICLES
15.79
ESTIMATES
21.79
3.44
7:
BY YEAR OF MANUFACTURE
0.00
0.08
0.08
AVERAGE
1964
21.47
27.07
5.81
33
4.68
7.22
2.54
1965
22.27
22.63
5.04
28
3.89
6.53
2.64
1966
20.61
24.70
5.09
29
4.10
6.33
2.23
1967
21.80
24.06
5.25
31
4.43
6.21
1.78
1968
19.81
23.41
4.64
24
3.98
5.40
1.42
19.15
28.12
5.39
32
4.74
6.11
1.37
1969
1970
20.19
25.62
5.17
30
4.68
5.71
1.03
1971
19.24
25.34
4.87
27
4.45
5.34
0.89
1972
19.36
24.44
4.73
25
4.34
5.15
0.81
19.59
24.33
4.77
26
4.40
5.16
0.76
1973
1974
18.64
22.87
4.26
23
3.99
4.56
0.57
1975
17.17
23.80
4.09
22
3.82
4.37
0.55
1976
16.76
21.86
3.66
21
3.44
3.91
0.47
1977
16.16
22.36
3.61
20
3.38
3.86
0.49
1978
15.86
21.51
3.41
19
3.21
3.62
0.41
1979
14.52
21.81
3.17
18
2.99
3.36
0.37
1980
15.00
20.44
3.06
15
2.89
3.25
0.36
1981
14.46
21.56
3.12
17
2.94
3.30
0.36
1982
14.50
21.31
3.09
16
2.92
3.27
0.34
1983
14.70
20.73
3.05
13
2.87
3.23
0.36
1984
13.71
20.72
2.84
12
2.69
3.00
0.32
1985
14.41
21.20
3.05
14
2.90
3.22
0.33
13.54
20.59
2.79
11
2.63
2.96
0.33
1986
1987
13.03
21.04
2.74
10
2.57
2.93
0.36
1988
13.17
20.56
2.71
9
2.54
2.89
0.36
1989
12.60
19.85
2.50
7
2.34
2.67
0.34
1990
12.74
19.07
2.43
6
2.26
2.61
0.36
1991
12.88
20.27
2.61
8
2.40
2.84
0.45
1992
12.64
18.46
2.33
3
2.12
2.57
0.45
1993
12.60
18.88
2.38
4
2.14
2.64
0.50
1994
12.13
16.65
2.02
1.79
2.28
0.49
1995
11.52
18.90
2.18
2
1.87
2.53
0.65
1996
13.21
18.35
2.42
5
1.87
3.15
1.28