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 tow- away 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 tow- away 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. Rate of injury for drivers involved in tow-away crashes (injury risk) 2. 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 TAC claims TAC claims Match rate (all types of matched with (%) injured road Police reports users) 1987 30,892 17,509 56.7 1988 28,427 16,672 58.6 1989 25,399 17,494 66.3 1990 19,633 13,886 70.7 1991 19,538 12,774 65.4 1992 19,251 13,118 68.1 1993 18,590 12,618 67.8 1994 19,341 11,927 61.6 1995 20,189 12,452 61.7 1996 19,954 14,034 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 tow- away 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: Large Medium Small Sports Luxury • Four-wheel drive vehicles • Passenger vans • Commercial vehicles (less than 3000 kg GVM)
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 CRS= × .
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:
P log = lnitP ☺=+ββok11XXf ++K βk = X . 1− P
That is, the log of the odds ratio is expressed as a linear function of k associated variables, $ Xii,,,= 1K k. Estimates of the parameter coefficients of the logit function, ie the βi 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:
$$ $ $ Ef X =+ E ββ011 E X ++=++=KK E βkk X βββ011 Xkk X 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 fX$ , in the context of crashworthiness ratings we are only interested in the component of variance due to one factor in fX$ 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 fX$ , considering all factors apart from X i to be fixed, is then given by
Var f$ X= X2 Var β$ ( ()ii) ( 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
$ $ fX()± 196. VarfX( ()i ) .
Point estimates and confidence limits in the logistic space were transformed into probability estimates using the inverse logistic transform given by
fX$ e P$ = . fX$ 1+ e
4.2 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: driver sex (male, female) • age: driver age (≤25 years; 26-59 years; ≥60 years) • speedzone: speed limit at the crash location (≤75 km/h; ≥80 km/h) • nveh: 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, βi,,,i= 1K 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) there were less than 100 involved drivers; or ii) 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, Cj , was therefore calculated as:
CRSjj= × j where
Rj denotes the injury risk for car model or year of manufacture j
Sj 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
eαβj e j R = ,S = jjαβj j 11+ e + e
where α j and β j are the values of the logistic regression function fX$ 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()α jjVar()β Var(logej C ) ≈ + ()11+ eαβjj22()+ e
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
logej (CVar )±⋅196 .( logej (C )) .
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 with Mazda 323 82-88 Telstar 83-87 with Mazda 626 83-86 Telstar 88-91 with Mazda 626 88-91 Telstar 92-96 with Mazda 626 92-96 Falcon EA with Falcon EB Series 1 Falcon ED with Falcon EB Series 2 Corsair 89-92 with Pintara 89-92 Commodore VR/VS with Lexcen 93-95 Commodore VN-VP with Lexcen 89-92 Nova 89-93 with Corolla 89-93 Nova 95-96 with Corolla 95-96 Astra 84-86 with Pulsar/Vector 82-86
Astra 87 with Pulsar/Vector 87 Astra 88-89 with Pulsar/Vector 88-90 Barina 85-88 with Suzuki Swift 85-88 Barina 89-93 with Suzuki Swift 89-94 Apollo JK/JL with Camry 88-92 Apollo JM with Camry 93-96 Ford Maverick 88-96 with Nissan Patrol 88-96 Suzuki Scurry 85-87 with Holden Carry 85-90 Suzuki Sierra 82-96 with Holden Drover 85-87 Nissan XFN Utility with Ford Falcon Utility
4.5 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 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 Total injured 4249 4814 5307 5573 5410 5678 5843 6135 6490 6859
Total involved 3304 3267 3689 4020 3920 3957 4085 4243 4547 5193 9 3 6 8 0 9 9 3 7 1 Injury Rate (%) 12.9 14.7 14.4 13.9 13.8 14.3 14.3 14.5 14.3 15.1
4.6.2 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 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 Total killed or admitted to hospital 1380 1499 1664 1644 1735 1772 2008 2221 2438 2670 Total injured 6165 7126 8047 7697 7724 8215 8401 9344 9923 11119 Injury Severity (%) 22.4 21.0 20.7 21.4 22.5 21.6 23.9 23.8 24.6 24.1
4.6.3 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 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 Injury Rate (%) 12.9 14.7 14.4 13.9 13.8 14.3 14.3 14.5 14.3 15.1 Injury Severity (%) 22.4 21.0 20.7 21.4 22.5 21.6 23.9 23.8 24.6 24.1 Combined Rate (%) 2.89 3.09 2.98 2.97 3.11 3.08 3.38 3.45 3.51 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
7.00
6.00
5.00
4.00 Average = 3.44
3.00 22A 22 10A 2.00 1 crash involvement (%) 2 B, 8, 14, 5 3, 11, 10B, 4B, 2, Probability of severe injury given 1.00 RATINGS ADR 4A NCAP ADR 29 ADR 4C CRASHWORTHINESS ADRs 4, 5A ADRs ADR 69 ADRs 0.00 ADRs ADRs 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)
30.00
25.00
20.00
Average = 15.79 15.00 (%)
10.00
5.00 Pr(Injury given crash involvement)
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
30
25 Average = 21.79
20 (%) 15
10 Pr(Severe injury given any injury) 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 I
23/02198 Page 1 I •
23/02198 Page 2 ..
23/02/98 Page 3 ..
23/02/98 Page 4 ..
23/02198 Page 5 APPENDIX 7: CRASHWORTHINESS ESTIMATES BY YEAR OF MANUFACTURE
ALL VEHICLES 15.79 21.79 3.44 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
1969 19.15 28.12 5.39 32 4.74 6.11 1.37
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
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 AVERAGE 12.47
Holden20.0513.54 7.197.1010.475.6412.0610.4014.0713.1210.1613.22Il.ll18.0810.1710.4217.0222.0822.858.378.5714.3912.5717.3113.6518.464.784.666.843.923.073.992.425.358.654.001.598.7812.8310.6612.2511.3318.0912.0515.577.708.96 VitaraJackarooMaverickLandcruiserSierraPatrolRangePajeroDroverFerozaRocky4RunnerIHiluxRoverF70/75/8082-9690-9684-9688-9682-8782-9085-8782-8989-96 NissanSuzuki I 8.51 ToyotaHoldenMitsubishiDaihatsuToyotaFordNissanSuzuki Range Rover I
Ford 26.3711.99 I 22.5114.3921.7310.5010.6013.0112.1911.0213.4413.2212.2911.379.4321.658.638.9231.6413.6513.9715.5218.0815.0131.4416.434.604.653.153.363.333.983.372.049.911.948.648.9326.7312.1916.9013.7912.9010.4915.6115.3710.71 CarryNavaraBrumbyMightyCommodoreRodeoXFNUteFalconHiace/LiteaceWB720UteScurryShuttleSeriesUtePanelBoy90-9682-8782-8585-8682-9082-9688-9082-9385-8886-96UteVan NissanSuzuki I 10.36
NissanHoldenFordToyotaSubaruSuzuki Holden
MitsubishiFord 10.6210.019.468.65 7.648.4210.6011.37I11.719.638.799.792.152.182.582.08 CamryApolIoJM/LexcenVeradaCommodoreKR/KS91-9693-96JPVR/VS Toyota I FalconEDMagnaApr92-94TR/TS Holden Holden Falcon EB Series II
20/02/98 Page 1 Appendix.xls---PR(RISK) BY MKT GRP CWR for NSW - VIC (87-%)
Falcon EA ALL MODEL12.47 AVERAGE6.566.096.426.656.307.466.9210.7310.0811.2510.7112.2410.247.846.295.1210.3510.1011.398.455.7711.3312.3312.2512.4716.5212.1710.6610.0013.3310.2912.2011.639.2110.499.427.458.1614.499.3112.7911.2812.3011.829.8111.5313.6511.8916.139.804.193.253.520.804.334.194.515.283.572.885.216.163.243.892.440.913.052.557.324.014.172.545.881.181.191.1111.4911.1211.7512.7811.2814.0610.8712.4211.8410.0610.011O.D111.456.937.869.228.048.689.798.448.157.738.6510.68900Fair1aneCrownlCressida3Magna200AccordXJ6FalconLexcenCommodoreCressidaFairlaneStatesman929SkylineSonata700300-6005100SeriesSeriesXD-XFEFTM-TP83-9690-9392-9682-9182-9094-9684-9282-9682-8882-8582-8985-9089-9389-9686-9082-9386-8882-94NZSeries&VNNPVB-LIDLIDOVLF I Toyota Falcon EB Series I 11.25 88-Mar92 Ford HoldenMercedesHyundaiFordBMWMazdaHondaNissanVo1voMitsubishiHoldenSaab Benz Holden JaguarFordToyota Ford
Volvo
2.43 Peugeot11.089.42 7.705.507.8516.3310.3012.369.9311.4711.298.903.774.793.457.4312.139.437.56 LibertyTelstarGalant6261MX6505 92-9682-9388-9189-9689-94 Mazda Mazda I MitsubishiFordSubaru Ford
20/02/98 Page 2 Appendix.xls---PR(RISK) BY MKT GRP CWR for NSW - VIC (87-96)
ALL MODEL12.1513.2213.40 IAVERAGE11.2811.3511.7712.6811.8911.4212.4710.5310.9111.7213.4414.7010.899.7412.5720.2213.9712.9014.9117.5117.8914.1813.3313.0115.4216.2319.866.222.836.542.192.484.518.971.491.441.471.501.538.511.4814.1011.0714.3112.5912.9915.4114.8212.8215.48 NimbusPintaraCoronaPrairieCamryCamiraBluebirdCorsairSigma/ScorpionTelstarApolloJK/JLStanza6261MX6Gazelle1800/Leone82-9582-8389-9282-8683-8782-8784-8683-8682-8984-8888-9284-9186-88 12.47 MazdaToyotaNissan I 11.7014.17 Nissan ToyotaMitsubishiNissanHoldenFordSubaruNissanToyota NissanHolden 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 10.4512.5710.9313.6511.3111.1411.4712.9013.6514.6013.549.5120.1313.449.817.2314.398.728.3215.7214.6013.2216.6215.6218.654.934.036.283.627.357.164.595.285.691.691.971.757.5612.8416.0113.5214.6011.4813.7210.9514.6211.3913.2510.27 CivicApplause323CorollaNovaGeminiRBPulsarLantraNovaTercel 91-9583-8895-9686-8892-9590-9495-9686-8782-8388-9189-9682-8489-94 ToyotaHolden 12.3411.09
HoldenToyotaHondaDaihatsuHyundai MazdaHonda
20/02198 Page 3 Appendix.xls---PR(RISK) BY MKT GRP CWR for NSW - VIC (87-%)
ALL MODEL19.88 AVERAGE18.1813.8614.8016.4311.4320.8513.6510.1712.6823.5223.2711.5511.9211.8212.7915.0113.4414.2812.5715.4212.9017.7015.6215.2125.7920.6721.1225.879.2520.3121.658.0829.1615.9216.5213.6517.1216.2318.5614.0716.3330.0031.9116.4317.3116.9216.1319.402.6410.954.973.6410.244.514.524.602.275.363.682.663.553.145.964.253.471.126.481.831.911.948.098.308.637.4126.6524.7527.3820.2315.9718.4614.7315.3314.8514.3810.4714.9314.2416.9416.9512.7013.8514.0115.2211.9016.29 HatchCharadeHandivanGeminiFestivaLaserKFQuintetAstraSherpalFioriLancerLaser/MeteorPulsarNectorExcelBarinaSwiftCordiaCityColtCivic121Festiva 94-96CACC87-90WA91-9685-8882-9294-9691-9491-9382-8990-9483-8695-9689-9484-8782-8682-9082-8482-8588-9282-8889-9384-8688-93WB/KH/ CBKA - KE 12.47 NissanMazdaSuzuki 21.4415.1915.1312.72 Mazda Holden HoldenHondaFordMitsubishiSuzukiRoverDaihatsuHyundaiHoldenSubaruHolden MitsubishiHondaDaihatsuHyundai I
Honda 10.3310.1410.0110.2611.5813.7621.478.3213.6517.1213.8617.026.697.113.605.443.519.8913.3111.7613.1711.9315.9210.74 PaseoPreludeRX7CelicaCapri 90-9384-9189-9482-8591-90
FordMazdaToyota
20/02/98 Page 4 Appendix.xls---PR(RISK) BY MKT GRP CWR ror NSW - VIC (87-96)
ALL MODEL AVERAGE10.0610.7310.644.6710.7816.6216.7220.2212.0820.9426.648.8515.1117.1210.307.064.347.417.779.499.9221.2314.8813.1715.0712.7612.237.58 ExaSupra33PreludeCRXCelicaIntegra 92-9686-8986-8883-8682-9083-9287-96 12.47
Honda Honda NissanToyotaAlfaRomeoHondaToyota
20/02198 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)
Holden17.108.09 11.5830.064.0316.7713.0013.4816.1410.7412.6111.7613.4910.5115.9013.3513.7317.0316.024.5013.8129.9514.7012.4342.497.3218.1431.4723.7528.6325.2515.6121.0426.418.2721.5326.8420.7221.9724.4521.9921.6819.1517.0519.1916.22 Landcruiser4RunnerIHiluxVitaraPajeroPatrolMaverickFerozaDroverRangeRockySierraJackaroo90-9688-9682-9682-8784-9689-9685-8782-9082-89RoverF70/75/80 SuzukiNissan I 18.66
MitsubishiToyotaFordDaihatsuNissanSuzuki Range Rover ToyotaHoldenDaihatsu I
Ford 22.9715.68 I 17.0515.4612.3816.9413.5710.5012.5126.8411.5523.9014.5118.5616.1714.1615.5215.0119.9413.659.337.1117.435.7015.579.5420.8823.2830.4623.1327.9533.5130.5924.0524.6632.578.2829.7536.4120.1621.1321.7826.1720.8718.8815.3818.80 MightyBrumbyFalconCarryNavaraWBHiace/LiteaceRodeoXFNVteScurryCommodore720VteShuttle90-9685-8682-8582-8782-9682-9088-9085-8886-9682-93SeriesPanelVteBoy VteVan NissanSuzuki I 19.48
FordSubaruHoldenNissanHoldenToyotaSuzuki Holden
FordMitsubishi 20.8516.2517.22 14.4112.926.0217.277.337.6820.4320.2524.95 LexcenCommodoreVerada93-9691-96 KR/KSVR/VS I FalconED Toyota I MagnaApr 92-94TR/TS Holden Falcon EB Series II
20/02198 Page 1 Appendix.xls--PR(SEVERE) BY MKT 'GRP CWR for NSW - VIC (87-96)
Falcon EA ALL MODEL20.88 AVERAGE21.7520.0117.6619.0916.8219.2612.453.5816.257.752.7719.579.313.7119.822.5134.2024.958.7126.8422.3426.1222.9721.3720.9021.0821.3723.5922.7021.0921.0719.47 CannyFalconEFLexcenApolloJM/MagnaTM-TPFalconCommodoreSonataSkyline93-9694-9689-9682-9089-9382-8885-90XD-XFJPVNNPVB- VL I Toyota Falcon EB Series I 21.7220.25 88-Mar92
NissanMitsubishi Holden Ford HyundaiFordHolden FordHolden
Volvo 22.7822.2623.1221.1321.6813.4814.1611.5514.6312.8218.0510.5116.7822.0210.1714.8010.3121.7015.6826.8418.1612.5127.8113.6910.6117.6116.6313.3519.6512.0318.277.1318.839.8016.8714.479.3515.9925.407.8528.6339.6525.1036.7327.5421.869.6629.0341.3424.2027.4031.0939.7524.808.878.7933.1621.6023.3621.2023.7026.6226.7723.8620.0829.3520.6416.6716.8814.1018.3517.4816.1819.4215.8413.43 Crown/CressidaFairlaneCressidaAccordXJ632009007009295300-600Statesman100Series83-9690-9392-9684-9289-9682-8589-9382-8982-9682-9182-9382-9486-8882-8886-90SeriesZNSeries& L TO FD
HondaMercedesToyotaJaguarMazdaBMWFordVolvoHoldenFordSaabBMW BenzBenz
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
20102198 Page 2 Appendix.xls---PR(SEVERE) BY MKT GRP CWR for NSW - VIC (87-96)
16.6118.22 ALL MODEL20.2324.3520.88 I AVERAGE21.4617.1414.1114.3820.5116.7518.2010.2510.5310.7822.816.0317.254.1618.374.6317.5218.5818.503.8119.887.7419.233.744.233.509.8715.048.1122.6622.1824.5024.3531.7222.9726.418.8927.6727.5422.8121.7032.3229.4323.2828.6320.4732.6927.4721.3620.0721.6620.6518.7317.5117.6619.87 TelstarPrairie6261MX6CoronaNimbusCamiraTe1starCamryApolloJK/JLCorsairPintaraSigma/ScorpionBluebirdGazelleStanza1800/Leone82-9582-8382-8692-9688-9189-9284-8683-8782-8784-9182-8986-8888-9284-8883-86 NissanMazdaToyota Mazda 22.0821.0720.2024.58
MitsubishiHoldenToyotaNissanSubaruFordFord Ford NissanHolden FordNissan 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 24.9015.6512.2219.7216.9111.7115.5214.5716.6924.3511.4123.7512.0313.9814.379.1813.0815.184.6814.3137.9727.6727.4021.3731.2225.6925.9834.098.8323.3020.6321.6118.6315.0518.9117.5215.0119.14 CorollaGeminiRBApplausePulsarCivic323NovaTercelLantra95-9691-9583-8895-9690-9492-9582-8386-8782-8489-96 Holden 22.75
HondaHyundaiToyotaDaihatsuHolden Mazda
20/02198 Page 3 Appendix.xls--PR(SEVERE) BY MKT GRP CWR for NSW - VIC (87-96)
19.89 2.695.71 ALL MODEL21.64 AVERAGE25.9622.0511.1318.9217.1116.8211.9713.7511.4410.4619.5614.5711.6820.8510.9921.7017.8620.4120.8822.9719.2814.996.8717.8819.1618.2215.1417.8419.004.544.4919.1117.0914.9719.3819.1718.7918.307.099.4818.6716.6919.8118.5817.709.845.394.709.2916.2125.4045.2429.5625.5427.8125.255.3638.0835.3331.9626.418.5722.5023.1327.5430.8427.408.0227.268.0828.0935.7730.9723.5933.0421.3932.4527.4321.7324.4820.7621.2622.2525.5439.5631.3422.9830.7522.4520.0923.1326.1225.8223.1124.7223.2327.6121.8323.2729.8319.6419.81 NovaFestivaHatchCorollaSwiftSherpalFioriBarinaExcel323CivicHandivanColtLaser/MeteorQuintetLancerAstraLaserKFPulsarNCharadeCityGeminiCordia12191-9687-9090-9495-9685-8882-9283-8691-9382-8689-9482-8494-9682-8991-9489-9382-8582-8888-9182-9086-8888-9284-8684-8788-93CCCAWAWBector/KH/ CBKA - KE 20.88 NissanSuzukiMazda NissanMazda Toyota 22.4421.9421.1123.1023.1725.87
RoverMitsubishiHoldenFordHyundaiDaihatsuHyundaiHoldenToyotaFordMitsubishiDaihatsuHolden Holden HyundaiHonda HondaMitsubishiFordMazdaHondaSubaruSuzuki Daihatsu I
Honda Prelude 84-91 17.26 12.61 23.13 10.51
Toyota Celica 82-85 19.95 14.89 26.27 11.38
20/02/98 Page 4 Appendix.xls---PR(SEVERE) BY MKT GRP CWR for NSW - VIC (87-96)
ALL MODEL AVERAGE23.2424.6020.2721.6727.3936.1126.3313.9519.5818.0230.0827.2619.7031.2210.3013.0843.2715.8714.1218.2514.5614.5116.047.5637.3632.2036.6339.1734.0936.3131.098.4127.5167.3323.8624.8822.8649.1724.5620.5020.6724.8214.8816.58 SupraPreludeCelicaCRXRX7PaseoExa33IntegraCapri90-9391-9082-9083-8692-9683-9286-8987-9686-8889-9482-85 20.88
HondaAlfaRomeoNissan FordHondaToyotaMazda Toyota
20/02/98 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)
0.170.710.791.921.73 2.662.491.691.45 ALL MODEL3.432.601.591.100.972.114.320.213.720.662.320.781.842.121.151.691.481.231.861.801.831.152.584.153.584.943.063.262.714.272.192.202.592.022.795.11110AVERAGE9411154933548965857I 2.462.212.993.082.95 2.50LandcruiserVitam]ackarooMaverick4Runner/HiluxRockyPajeroSierraDroverRangePatrolFeroza 82-9688-9689-9684-9685-8782-8782-90RoverF70/75/80 I NissanSuzuki I 82-8990-9682-96
NissanMitsubishiToyotaDaihatsu+Wt~~l.Drly~ye~i~·Suzuki Holden DaihatsuFordHoldenToyota Range Rover I
0.811.241.56 2.60 Ford 2.596.062.305.044.482.600.952.143.580.862.621.491.891.271.751.781.851.871.591.163.543.583.342.513.622.453.673.343.053.314.39I5.943.578.588.06127129122376273192334706096 2.732.744.643.105.822.231.88 BrumbyMightyCarryFalconHiace/LiteaceRodeoCommodoreXFNUteWB720UteNavaraScurryShuttleSeries85-8682-8782-9082-8590-9685-8882-9382-9688-9086-96UtePanelBoy UteVan NissanSuzuki I 2.02 Nissan Holden HoldenToyotaNissanHoldenSuzuki HoldenFordSubaru
20/02198 Page 1 Appendix.xls--CWR BY MKT GRP CWR ror NSW - VIC (87-96)
ALL MODEL AVERAGE 2.60 2.50 2.71 0.21
FalconVerada EAEHKR/KSSeries II 0.74 1.050.710.430.272.312.071.462.231.012.211.501.521.111.862.532.301.762.662.48 222464184329412761485 2.602.472.342.66 LexcenCommodore89-9693-9689-9382-88 VNIVP 2.082.381.411.971.830.460.320.853.081.062.151.121.552.632.202.404.20I3.132.632.61I 52 2.06 FalconCamryApolloJM/CommodoreMagnaTM-TPSonataSkyline94-9682-9093-9691-9682-8885-90XD-XFEF JPVB-VRNSVL Toyota Toyota FalconEDMagnaFalcon EBTR/TSSeries I Mitsubishi I 2.442.03 Apr88-Mar9292-94 Ford FordNissanMitsubishiHolden Holden I Hyundai FordHolden Holden Ford
Volvo 0.860.530.720.620.560.550.620.732.ll2.442.512.031.071.501.360.811.951.031.441.411.661.311.381.971.091.301.221.621.052.102.622.992.583.533.022.572.772.642.302.122.212.073.33 212016121038282639984632 2.312.042.302.071.751.381.601.591.581.421.371.321.961.90 900FairlaneCrown/Cressida200Accord300-600XJ6Cressida37005Statesman100SeriesSeries83-9690-9382-9689-9382-9184-9282-9486-8882-9386-9082-8589-96NSeries& LID D
HondaMercedesBMWJaguarToyotaHoldenSaabFordVolvoBMW Benz
20/02/98 Page 2 Appendix.xls··-CWR BY MKT GRP CWR for NSW - VIC (87-96)
ALL MODEL AVERAGE 2.60 2.50 2.71 0.21
BMW 3 Series 92-96 2.47 51 1.19 3.74 2.55
Ford Fairlane Z & LID F 82-88 2.48 53 2.00 2.96 0.96
Honda Accord 82-85 2.73 71 1.92 3.54 1.62
Mazda 929 82-89 2.99 87 2.27 3.70 1.44
Peugeot 2.240.682.790.580.632.712.610.562.813.622.130.620.970.550.540.902.782.700.752.372.121.122.292.452.302.401.621.091.381.841.151.711.161.751.172.681.511.822.512.732.974.713.843.123.893.772.855.463.343.273.572.513.413.082.992.953.02 119794059674657938830131777357568505882 4.073.062.162.902.772.402.572.582.672.472.531.821.60 LibertyTelstar626/MX6PintaraCoronaNimbusGazelleCamiraGa1an!Prairie505CamryCorsairBluebirdApolloJK/JLSigma/ScorpionStanza1800/Leone82-9582-8683-8782-9389-9292-9682-8388-9184-8882-8989-9689-9484-8683-8688-9282-8786-8884-91 NissanMazdaToyota I 2.682.992.852.32 Subaru MitsubishiSubaruToyotaHoldenNissanFord NissanFordHolden NissanFordToyota
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 Vans 82-92 3.58 112 2.70 4.46 1.76
20/02198 Page 3 Appendix.xls---CWR BY MKT GRP CWR for NSW - VIC (87-96)
3.510.762.760.380.870.672.390.750.742.082.562.192.510.814.070.912.363.182.660.790.212.112.542.462.012.401.142.060.921.511.941.881.601.691.161.861.541.611.321.191.802.571.871.131.331.413.012.752.293.052.132.402.833.123.391.914.383.693.302.954.673.723.863.673.404.234.324.013.943.354.974.523.904.543.784.083.893.423.333.193.613.523.143.133.983.472.71ALL10610410910810710510310211311111797904745423281838078555672767436318684 3.393.202.892.852.812.523.682.942.392.762.253.123.002.412.732.183.962.372.193.323.293.263.22MODEL2.50ExcelSwiftBarinaLaser/MeteorLancerCordiaPulsarNAstraGeminiCorollaPulsarNectorNovaPulsarCivicColt323LaserKFGeminiRB121FestivaTercelNovaLantraAVERAGE94-9695-9683-8891-9591-9690-9491-9484-8682-8889-9495-9682-8986-8788-9184-8792-9582-9689-9388-9286-8882-8382-8682-8489-96CACCWBector/KH/ CBKA - KE Page2.604 2.953.232.52 QuintetApplausePassenger Vans SuzukiHoldenNissanMazdaToyota 3.322.77 MitsubishiFordToyotaFordHolden Honda RoverHoldenHondaFordToyota HyundaiMitsubishiHondaMazda HyundaiMitsubishiToyotaDaihatsu I 20/02198 Nissan Appendix.xls---CWR BY MKT GRP CWR for NSW - VIC (87-96)
ALL MODEL4.324.264.132.026.013.203.610.211.541.871.504.063.213.704.193.433.482.983.532.223.144.854.649.237.397.697.615.075.832.718.026.07130128126125123124116115121118AVERAGE6.225.865.795.565.063.923.894.03 2.50HatchHandivanFestivaWASwiftBarinaExcelCitySherpalFioriCharade121 87-9094-9682-9282-8691-9385-8883-8682-8582-9082-8988-93 2.60 SuzukiMazda 4.305.55 Suzuki DaihatsuHondaHoldenSubaru HyundaiFord Daihatsu Daihatsu Daihatsu
Honda 4.154.984.682.514.562.013.463.702.972.783.532.130.750.791.351.521.411.361.331.561.281.621.451.601.086.014.872.704.534.113.144.816.583.925.244.494.145.4311412010099259591669244986963 3.163.142.382.724.092.033.092.643.043.732.67 PreludeCelicaPaseoIntegraExa33RX7CRXCapriSupra 82-9090-9392-9683-9287-9691-9083-8686-8982-8584-9189-9486-88
A1faRomeoHonda ToyolaToyotaTOYOlaFordNissanToyolaMazdaHonda
20102198 Page 5 APPENDIX with 90%CI.xls--CWR BY MKT GRP CWR for NSW - VIC (87-96)
0.320.830.942.011.88 2.662.491.691.45 ALL MODEL2.603.43 2.012.181.071.131.521.322.72110AVERAGE9433495415654.644.762.10113.433.0989854.142.6972.732.973.962.452.071.87I0.963.120.563.630.171.551.951.771.241.511.031.561.422.992.953.082.212.461.10 LandcruiserViiaraDroverRocky4Runner/HiluxPajeroSierraJackarooPatrolMaverickRangeFeroza2.52 82-9685-8784-9688-9682-9082-8789-96RoverF70175/80 I NissanSuzuki I 1.59 82-8990-96
NissanDaihatsuToyoiaMitsubishiSuzuki~~¥'l)rj'v~Y~li'~······ Holden FordDaihatsuToyoiaHolden Range Rover
1.351.931.101.68 2.60 Ford 6.062.302.59 I2.702.011.971.663.943.551.331271291227362193760233496703.524.102.412.933.133.222.387.703.503.485.738.174.232.183.760.800.723.001.471.251.591.071.803.102.735.822.744.642.231.88 MightyHiace/LiteaceBrumbyCarryWBFalconCommodoreRodeoNavaraScurry720ShuttleXFNUteVteSeries85-8690-9682-8582-9382-9088-9085-8882-9686-96PanelUteBoy VteVan NissanSuzuki I 2.02 82-87 Nissan Holden HoldenNissanToyoiaHoldenSubaruSuzuki HoldenFord
23/02/98 Page 1 APPENDIX with 9O'IoCI.xls---CWR BY MKT GRP CWR for NSW - VIC (87-96)
FalconVerada EBEAKR/KSSeries 11 0.62 242950.36 82-90 2.082.381.831.971.41I1.112.232.192.162.341.522.261.361.901.621.601.59I 22644118432748612.332.262.452.142.53523.951.712.632.612.462.573.040.602.590.380.890.710.230.850.940.360.272.342.472.662.062.60 LexcenFalconMagnaTM-TPCamryApolloJM/FalconEFCommodoreSonataSkyline91-9693-9689-9694-9689-9382-8885-90XD-XFJPVRNSVNIVPVB- VL Toyota Toyota FalconEDMagnaFalcon EBlRffSSeries I Mitsubishi I 2.442.03 Apr92-9488-Mar92 Ford FordHoldenMitsubishiNissan Holden I Hyundai HoldenFord Holden Ford
Volvo 0.970.740.700.680.830.900.781.151.411.211.731.291.021.332120161210263839282.512.483.332.022.862.883.132.602.47262.0742.4192.0032.012.1881.950.871.262.ll2.051.641.161.711.771.261.101.391.18I.211.141.652.042.302.312.071.591.371.901.751.601.321.381.961.581.42 900AccordFairlaneCrown/Cressida200700300-600XJ65CressidaStatesman3100SeriesSeries83-9690-9382-9486-8882-9384-9282-9689-9382-8582-9186-9089-96NSeries& LID D
MercedesFordVolvoBMWToyotaHondaHoldenJaguarSaabBMWToyota Benz
23/02198 Page 2 APPENDIX with 90%CI.xls---CWR BY MKT GRP CWR for NSW - VIC (87-96)
ALL MODEL AVERAGE 2.60 2.52 2.69 0.17
BMW 3 Series 92-96 2.47 51 1.40 3.54 2.14
Ford Fairlane Z & LID F 82-88 2.48 53 2.08 2.88 0.80
Honda Accord 82-85 2.73 71 2.05 3.41 1.36
Mazda 929 82-89 2.99 87 2.38 3.59 1.21
Peugeot 2.24 0.832.382.742.502.452.422.342.202.831.240.981.381.391.881.831.371.921.642.9011977676846405993173079754.422.992.653588132.885057582.393.67823.563.033.322.902.942.813.232.952.373.305.243.340.530.520.460.492.190.752.340.940.820.972.280.472.363.031.791.361.541.162.772.902.473.064.072.572.672.402.582.532.161.601.82. LibertyCamryCorsairBluebirdApolloJKJJLPrairie626/MX6TelstarCoronaNimbusCamiraGalantPintaraSigma/Scorpion505GazelleStanza1800/Leone82-9592-9682-8682-8383-8688-9289-9283-8788-9186-8882-9382-8784-8889-9684-8684-9182-8989-94 MazdaNissanToyota I 2.852.682.992.32
SubaruMitsubishiFordHoldenNissanToyota NissanFordHolden FordFordNissanToyota
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 Vans 82-92 3.58 112 2.84 4.31 1.47
23/02198 Page 3 APPENDIX with 90%CI.xls--CWR BY MKT GRP CWR for NSW - VIC (87-96)
ALL3.51 MODEL2.452.612.572.532.072.212.142.461.241.361.411.521.121.501.953.072.692.842.443.082.302.972.523.181.531.061.342.133.491081061131091071051041031021111174797313278424576748390844.6586812.83365655723.523.73803.273.143.643.243.494.444.074.184.154.393.793.883.843.133.263.723.963.803.393.433.292.693.483.083.070.640.960.320.970.682.152.010.630.622.312.113.410.660.170.570.732.242.671.741.271.631.841.421.581.351.291.771.563.393.003.962.852.393.262.943.683.202.892.252.812.522.412.763.323.293.123.222.182.192.372.73AVERAGEExcelSwiftLancerAstraBarina323QuintetPulsarNLaserlMeteorCivicPulsarNector2.52PassengerPulsarLaserKFGeminiApplauseCorollaGeminiRBNovaColtCordia121FestivaLantraTercelNova 94-9691-9595-9683-8891-9695-9690-9489-9491-9492-9584-8682-8882-8982-8688-9284-8782-8489-9686-8888-9182-8386-8789-9382-96CCCAWBectorIKHVansI CBKA - KE Page2.604 MazdaNissanHoldenToyotaSuzuki 3.322.953.232.772.52 MitsubishiFordToyotaHolden Honda HondaToyotaFordHoldenRover MitsubishiMazdaHondaHyundai HyundaiMitsubishiToyotaDaihatsuHoldenHonda I 23/02198Nissan APPENDIX with 9O'IoCI.xls---CWR BY MKT GRP CWR for NSW - VIC (87-96)
ALL MODEL4.454.042.514.223.813.263.703.133.773.66126116125123128130118124115121AVERAGE4.704.524.957.137.678.745.547.342.697.285.915.053.583.472.683.633.030.171.691.571.261.296.225.795.863.925.565.063.894.03 HatchSherpa/Fiori2.52CharadeExcelFestivaHandivanSwiftBarinaCity121 87-9082-9294-9691-9385-8883·8682-8688-9382-8582-8982-90WA 2.60 SuzukiMazda 4.305.55
DaihatsuHoldenSuzukiSubaru HyundaiFordHonda Daihatsu Daihatsu Daihatsu
Honda 2.291.461.691.091.611.131.561.792.001.741.821.42100114120442599986366956992914.904.593.024.524.293.895.642.604.193.725.056.183.984.182.113.923.493.822.903.112.962.502.331.691.131.274.092.382.723.162.033.143.093.043.732.642.67 PreludeExaCelicaPaseoRX7IntegraCapriSupra33CRX 92-9682-9091-9090-9382-8584-9183-9286-8987-9686-8889-9483-86
AlfaRomeoHonda ToyotaHondaMazdaNissanToyotaFord
23/02198 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 CAR -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 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 1981 -0.1033 0.0159 14.46 14.08 14.85 0.77 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
AVERAGE CAR22.2021.1020.4321.5720.8521.5121.5821.6421.3321.3021.8027.0915.0316.8815.1617.4317.1520.1318.0518.8820.0720.3920.4620.6820.9120.5920.8722.7023.0123.0023.9025.8220.9921.3221.2023.2729.3918.2619.8422.0522.0322.1822.7422.4822.4523.4522.8824.9525.7025.9327.4126.9623.7726.0227.0228.5615.7119.0219.5919.7119.8919.5723.9930.5431.2318.72-0.1781-0.1794-0.0443-0.0810-0.0131-0.2148-0.3326-0.0915-0.2076-0.1178-0.1673-0.0735-0.0715-0.0350-0.0634-0.0637-0.0283-0.01660.03310.00440.06260.21220.04890.16340.28700.00150.11470.14360.19730.14930.33960.09310.12860.02730.04050.07960.03160.03000.03170.03730.04300.04700.05950.07160.12200.10100.10300.04030.03170.03090.02620.02820.04200.12200.07020.05700.04560.04980.03440.02810.03050.02800.02510.02770.027213.683.102.694.714.222.197.172.992.082.552.152.012.252.933.195.03,5.707.968.371.693.517.361.981.991.641.801.831.871.771.7220.2720.5620.5921.0420.7321.2020.4421.5621.8623.8024.3325.3425.6228.1223.4124.7027.0720.7221.3121.8121.5122.3622.8724.4424.0622.6321.7918.3518.9016.6518.4618.8819.0719.85 -1.2781 19901987197119721993197419681996 --- 198319881986198519821980197919891984198119691991197719731967196519661995199419921978197619751970 1964 APPENDIX 7
CRASHWORTHINESS ESTIMATES BY YEAR OF MANUFACTURE APPENDIX 7: CRASHWORTHINESS ESTIMATES BY YEAR OF MANUFACTURE
ALL VEHICLES 15.79 21.79 3.44 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 1969 19.15 28.12 5.39 32 4.74 6.11 1.37 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 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