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MEASURING CRASHWORTHINESS: MAKE/MODEL RATINGS AND THE INFLUENCE OF AUSTRALIAN DESIGN RULES FOR MOTOR VEHICLE SAFETY Max Cameron, Caroline Finch, Stuart Newstead and Tri Le Monash University Accident Research Centre, Victoria, Australia Andrew Graham and Michael Griffiths Roads and Traffic Authority, New South Wales, Australia Maria Pappas and Jack Haley NRMA Ltd., New South Wales, Australia ABSTRACT This paper updates and extends the methods in a previous paper which gave crashworthiness ratings for makes/models of Australian cars manufactured during 1982-90. The new results used logistic regression to take into account a larger number of fa ctors which were found to be strongly related to the injury risk and injury severity of drivers. The data covered 220,000 drivers involved in tow­ away crashes in New South Wales during 1987-92, and a total of 45,000 drivers injured in crashes in Victoria and New South Wales during the same period. The crashworthiness ratings measured the risk of a driver being killed or admitted to hospital when involved in a tow-away crash. The ratings were able to identify 26 makes/models manufactured during 1982-92 which have superior or inferior crashworthiness compared with the average vehicle. The relationship between crashworthiness and year of manufacture was investigated using the same analysis methods and an expanded data set including pre-1982 vehicles. The data covered 424,000 drivers involved in tow­ away crashes and 102,000 injured drivers. The crashworthiness of passenger cars in Australia showed the greatest improvements for those manufactured over the years 1970 to 1979 during which a number of new Australian Design Rules aimed at occupant protection took effect. There was a 47% reduction in the risk of serious injury for drivers involved in tow-away crashes while driving the post-1979 cars compared with those manufactured during the 1960's. -297 - CRASHWORTHINESS is the ability of a vehicle to protect its occupants against injury in the event of a crash. There is considerable interest in the ratings of makes and models of passenger cars which reflect their relative crashworthiness. A previous paper reviewed methods used internationally to rate the safety of cars, based on mass crash data (Cameron, Mach, Neiger, Graham, Ramsay, Pappas and Haley, 1992a). Since that time, there have been a number of methodological advances which are reflected in the internationally published ratings (Folksam 1992, Broughton 1994, Highway Loss Data Institute 1994, lnsurance Institute for Highway Safety 1994, U. K. Department of Transport 1995). In 1992, the first crashworthiness ratings of Australian passenger cars were produced based on crash and injury data from Victoria during 1983-90 and New South Wales (NSW) during 1989-90 (Cameron et al 1992a, 1994). The ratings were based on data for 22,964 drivers injured in crashes in the two States, plus data for 73,399 drivers involved in tow-away crashes in NSW. 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 lnsurance (Gustafsson, Hagg, Krafft, Kullgren, Malmstedt, Nygren and Tingvall 1989). The rating figures were widely distributed throughout Australia in the form of a "Driver Protection Ratings" brochure. Cameron et al (1992b) reported the Australian car manufacturers' and importers' responses to the rating scores in the subsequent advertising of their products. The paper also examined the relationship between the rating score and the mass of individual passenger car models. These ratings took into account the speed zone of the crash and the driver sex. Since these ratings were published, an improved analysis method has been developed to take into account a broader range of factors affecting the risk of severe injury, thereby improving the reliability and sensitivity of the results. Based on a comparison of methods applied to the previous data, the new method produces crashworthiness ratings with proportionately smaller variability. This paper describes the data and analysis methods used to update the previously published crashworthiness ratings. The new ratings cover makes -298 - and models of passenger vehicles manufactured during 1982-92 and crashing in Victoria or NSW during 1987-92. The results, given in the appendix, rate passenger vehicles in terms of the risk of the driver being killed or admitted to hospital when involved in a tow-away crash. This paper also describes an investigation of the relationship between crashworthiness and year of manufacture of passenger cars sold in Australia during 1964 to 1992. These years of manufacture were of interest because a number of Australian Design Rules aimed at car occupant protection came into effect during the 1970's. The results are displayed in Figure 1 given later in this paper. lt should be noted that none of the analysis described in this paper addresses the "aggressivity" of specific models of passenger cars, ie. the threat of injury to pedestrians or occupants of other cars in the event of a collision (Broughton 1994, U. K. Department of Transport 1995). DATA The crash and injury data used for the update of the crashworthiness ratings were identical in tormat to those used and described previously (Cameron et al 1992a, 1994), but also covered crashes during 1991 and 1992. The Victorian data were derived from 13,943 Transport Accident Commission claims for injury compensation by drivers of 1982-92 model cars and station wagons which crashed during 1987-92, and whose claim records could be matched with Victoria Police accident reports. The NSW data covered 221,971 drivers of 1982-92 model light passenger vehicles involved in Police reported crashes during 1987-92 which resulted in death or injury or a vehicle being towed away. As well as cars and station wagons, the files covered four-wheel drive vehicles, passenger vans, and light commercial vehicles. Of the 221 ,971 drivers involved in tow-away crashes, 31, 127 were injured. When the data on the injured drivers from the two States were combined, there were data on 45,070 injured drivers available for analysis. The makes and models of the crashed vehicles manufactured during 1982-92 were derived by processes which involved matching the crash records with the State vehicle register using the registration number, and then decoding information held on the register. The processes were the same as those outlined previously (Cameron et al 1992a, 1994). For the investigation of the relationship between crashworthiness and year of manufacture, cars manufactured prior to 1982 were also considered. For this analysis, the data covered 423,612 drivers of cars, station wagons and taxis manufactured in 1964-92 who were involved in tow-away crashes in NSW during 1987-92. The data also covered 101 ,955 drivers of these vehicles who were injured in crashes in Victoria or NSW during the same years. -299 - ANALYSIS OVERVIEW - 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. This risk can be considered to be the product of two probabilities: i) the probability that a driver involved in a crash is injured (injury risk), denoted by R; ii) the probability that an injured driver is killed or admitted to hospital (injuryseverity), denoted by S. That is R S. c = x To produce the updated crashworthiness ratings, each of the two components of the 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 injuryrisk and injuryseverity. LOGISTIC MODEL - The logistic model of a probability, P, is of the form: logit(P) =In(�)1-P = ß0 + ß,X1+.„+ßi.Xk = f(X). That is, the log of the odds ratio is expressed as a linear function, f, of k associated variables, X1, i 1, . , k. Estimates of the parameter coefficients of the logit function, ie. the = can be obtained by maximum likelihood estimation (Hosmer & Lemeshow, ß119, 89). The extension of this model to include interaction terms is straightforward. LOGISTIC MODELS FOR EACH COMPONENT - To obtain crashworthiness ratings reflecting vehicle factors alone, it was necessary to develop logistic models of each of the crashworthiness components separately to identify possible factors, other than vehicle design, that might have influenced the crash outcomes. This was done initially without considering the type of car in the models as the aim was to determine which other factors were most likely to have an influence across a broad spectrum of crashes. Logistic models were obtained separately for injury risk (R) and injury severity (S) 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) -300 - These variables were available in both the Victorian and NSW crash data. Other variables (eg. whether or not the vehicle collided with a fixed object) were highly correlated with these variables, or 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.

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