The Department of Transportation has four offices that conduct automobile crash tests: three within NHTSA and one in the Federal Highway Administration (FHWA). The activities of two programs run by NHTSA are the focus of this report. NHTSA’s Office of Vehicle Safety Compliance performs a compliance testing program of 30-mile-per-hour full-frontal crashes of automobiles, light trucks, and vans into a fixed rigid barrier. This program was created under section 103 of the National Traffic and Motor Vehicle Safety Act of 1966, and it is designed to ensure that vehicles meet minimum safety requirements as specified in Federal Motor Vehicle Safety Standard No. 208 -Occupant Crash Protection (FMVSS 208). Also under the authority of NHTSA is the New Car Assessment Program (NCAP), conducted by the Office of Market Incentives. This program, mandated under title II of the Motor Vehicle Information and Cost Savings Act of 1972, was created to provide information to consumers on the relative crashworthiness, or safety, of automobiles. This charge differs from the compliance test in that vehicles tested in NCAP are not required to meet specified safety standards, while the purpose of compliance tests is to ensure that vehicles meet a level of safety required by law. The NCAP test also differs from the compliance test in two important aspects: NCAP crashes its vehicles at 35 miles per hour, which translates to over one-third more energy than compliance tests, and NCAP engages all manual and automatic restraints, while the compliance test employs only passive restraints. By using all restraint systems, NCAP assesses the maximum crashworthiness of a vehicle in high-speed frontal crashes. In addition to the two programs described above, NHTSA’s Office of Crashworthiness Research conducts a variety of tests to study a wide range of individual safety issues that arise from specific crash configurations. FHWA conducts crash tests to study the interaction between automobiles and roadside obstacles and devices such as guard rails, telephone poles, and bridge abutments. To respond to your request, we examined data from tests conducted for compliance with FMVSS 208 (compliance tests) as well as those conducted under the New Car Assessment Program. We chose to focus on these programs because both conduct tests that are similarly configured, employ standardized procedures, and have been assessing vehicle crashworthiness over a period of years. The two other crash test programs run by DOT are largely research based and, although important, have different purposes from those of our study. Our analysis consisted of three parts: (1) an examination of trends over time in crash test results of both programs, (2) an assessment of the reliability of NCAP results, and (3) a review of the relationship between NCAP results and real-world traffic injuries and fatalities. We first reviewed the background, sample selection, and testing procedures of both NCAP and the compliance program. (See appendix I). We then examined what it is that crash tests measure, as wellas how well measurement devices used in crash tests simulate human biomechanics and physiological response by reviewing biomechanic, human tolerance, and automotive safety literature and by interviewing experts in those fields. (See appendixes II and III.) Next, we analyzed changes in crash test results by year for both the compliance program and NCAP. (See appendix IV.) To address the reliability of crash test results, that is, the degree to which consistent results are obtained through repeated trials, we examined research conducted by NHTSA and compared NCAP results with those obtained in crash tests conducted by manufacturers. (See appendix V.) Finally, we conducted analyses using two national databases that allowed us to relate real-world fatality rates for drivers with the predicted injury risks derived from NCAP results. (See appendix VI). For this analysis, we used Poisson regressions to assess the relationship between fatality rates, derived from the Fatal Accident Reporting System and the R.L. Polk Vehicle Registration System, and the combined injury risk calculated from the NCAP measurements that assess the potential for skeletal injuries to the head and chest. Analyses were conducted for restrained drivers in one- and two-car frontal crashes. We did not include information from the compliance program in the analyses we conducted on either the reliability or the predictive validity of crash test results. In our assessment of the reliability of crash test results, we did not uncover a quantity of data sufficient enough to compare the results of two or more trials of vehicle models. In the case of the predictive validity of crash test results, we did not use compliance test data for two reasons. First, the compliance program had conducted only 145 tests between 1987 and 1992. Second, the variation among compliance results was relatively narrow and scores tended to cluster far below the ceiling values for the compliance tests. These two items resulted in a dataset that was insufficient for conducting detailed statistical analyses. We conducted our review in accordance with generally accepted government auditing standards. In NCAP crashes, nearly all cars now meet the head and chest injury standards of the compliance tests, although they are 36-percent more violent than compliance crashes. The average probability of sustaining a serious injury in a 35 mile-per-hour crash as measured by NCAP has declined from over 0.5 in 1980 to less than 0.2 in 1993. (See figure 1.) Differences among the crashworthiness scores of vehicles tested in this program have experienced similar declines. The introduction of air bags has contributed significantly to this improvement. (For a complete discussion of the trends in crash test results, see appendix IV.) A causal linkage between improved crash test scores and declining highway fatalities cannot be asserted with certainty because of both the many variables involved in a crash and the increased emphasis on traffic accident and injury prevention over the past decade. Nonetheless, it seems reasonable to conclude that manufacturers’ successful efforts to improve their products’ performance in NHTSA crash tests, particularly in NCAP, have contributed to improved occupant protection in real-world crashes, although we were unable to quantify that contribution. These improvements to performance have derived from a variety of efforts, with two examples being modernized manufacturing techniques and an increased emphasis on safety systems and designs. In addition, in recent years, automotive designers have turned more to computer-based simulations to assist in the design of vehicles that meet crash test standards. Although we did not evaluate the state of the art in computer-based crash models, we learned from industry personnel that such modeling appears to accurately predict the results of actual crash tests. Indeed, one computer specialist informed us that the industry uses crash tests in part to validate their computer models. Although simulated crashes are costly as they currently require access to supercomputers, they do allow the manufacturer to assess the crashworthiness of a vehicle in more trials, more quickly, and at impacts points other than the front (or side) of a car. These benefits over actual crash testing permit the identification of crash forces upon an occupant in a time frame that offers immediate redesign implications. To determine whether the result of any test is reliable, consistent results must be obtained through repeated trials of a specified procedure. In the case of crash tests, this means that consistent results of repeated tests of a specific vehicle model are required. This is particularly crucial when comparing the safety ratings of different vehicles. Both the NCAP and compliance programs generally conduct only one trial of a specific vehicle model; thus, insufficient data exist to accurately define the reliability of crash test results. That is, the ability to predict with confidence the likelihood of a tested model’s receiving similar scores if tested again is low. We found only two sources of information on which to assess the reliability of crash test results: a study conducted by NHTSA in 1984, which examined the variations in test results of 12 consecutively manufactured Chevrolet Citations, and our own analysis of the differences between results for vehicle models tested in NCAP and the results for those vehicles in corresponding tests conducted by automobile manufacturers. Our analysis of the data derived from NHTSA’s 1984 study revealed wide variations in the head injury criterion (HIC) results, the measurement taken to assess potential skeletal head injuries. (See appendix V.) Although NHTSA ascribed the variation in results to a number of sources, including the test itself, it failed to discuss the implications of the combined effect of these sources on crash test results; namely, that even within a specific vehicle line, the result of one test may not be indicative of the model’s performance from trial to trial, and large differences in the resultant HIC may occur. We also examined the differences between the results of NCAP and manufacturers’ tests provided to us by NCAP officials. The tests conducted by the manufacturers essentially duplicated the NCAP test procedures. We compared the results of the two tests using the star rating system recently developed by NCAP, hypothesizing that if the manufacturer test were considered a second trial for a model line, its results should be consistent with the NCAP, or first trial. The star rating system ranks cars from 1 to 5 stars, with 5 stars being the best rating, or safest car, and 1 star being the worst rating, or least safe car. These ratings are based on the risks of serious injury for vehicles, which are calculated from the head injury criterion and chest acceleration scores from NCAP tests. (For a discussion of crash test measurements and the star system, see appendix II.) We found that in only about one-half of the paired comparisons would NCAP- and manufacturer-tested vehicles have received the same star rating. In 32 percent of the comparisons, the results of the second trial would have changed by 1 star, while in 8 percent of the cases, the ratings of the vehicles would have changed by 2 or more stars. When we compared the risks of serious injury (the base unit categorized into the five star ratings) derived from the manufacturer and NCAP data, we found that each star category was associated with a wide band in which the resultant risk scores of subsequent tests might fall. For example, the results of a second test of a vehicle rated as 4 stars by its first test could fall between 5 stars and 2 stars. The analyses described above are based on the only two sources of information we could find. The quantity of data in each analysis was not enough for us to fully quantify the reliability of crash test results; however, we were able to determine that NCAP scores, whether reported in raw HIC and chest acceleration scores or as categories of injury probability, have associated levels of imprecision and that seemingly large differences in crash test results may not necessarily reflect true differences in a vehicle’s safety potential. By not properly defining and publishing the degree of reliability, consumers may be misled into purchasing a vehicle purported to be more crashworthy than another when, in fact, it may be no more safe, or even less safe, than the comparison vehicle. Since NCAP crash tests are designed to simulate full-frontal collisions, we restricted our analysis to those types of crashes and found the results of NCAP crash tests are generally reflected in real-world fatality rates. That is, on the whole, a statistically significant relationship exists between real-world highway fatality rates associated with vehicles tested in the NCAP program and their scores in crash tests. However, we concluded that this relationship derives mainly from the high fatality rates of vehicles with the worst NCAP scores. When we divided vehicles into NCAP score quintiles—that is, placed the vehicles into one of five 20-percentile categories based on their location in the distribution of NCAP results—we found that the quintile with the worst NCAP scores (those vehicles in the highest 20-percentile category) had significantly higher fatality rates than the remaining 80 percent of NCAP-tested vehicles. The remaining four quintile categories, however, had associated fatality rates that were not significantly different from one another. (See figure 2 and appendix VI.) Over time, the mean risk of injury in frontal crashes, as measured by NHTSA crash tests, has declined and indeed has mirrored a similar trend in the annual number of highway fatalities. While we cannot state with certainty that NHTSA crash tests are a causal factor in improved crashworthiness, we believe that efforts on the part of automobile manufacturers to produce vehicles that score well on these tests have contributed to the improvement of the overall safety of vehicles. At the very least, the results of NCAP and compliance tests provide indications that the vehicle fleet, on the whole, has become safer over the past 15 years. These trends in the mean score of crash tests, however, do not necessarily suggest that individual vehicles have well-defined levels of safety, nor do they suggest that the relative rankings of two vehicles would be the same if subsequent trials were conducted. They also do not suggest that differing test results are reflected in data derived from real-world traffic collisions. Indeed, only the poorest performers in NCAP had associated fatality rates that were significantly different than other NCAP vehicles. On the basis of our findings, we make two recommendations to the Administrator of NHTSA. First, we recommend that information on NCAP reliability be updated and made available, in clear language, to the general public. Such an effort would require an update of the repeatability study the agency conducted in 1984 and could result not only in a better understanding of the reliability of crash tests for predicting injury risk, but also in discovering ways in which NHTSA can limit the error that derives from sources under its control. We also recommend that NHTSA explore the feasibility of alternative means of testing the crashworthiness of new vehicles. Computer simulations may provide one such alternative. It may be possible to better assess the safety potential of a vehicle through computer-based modeling as this allows more trials, more quickly, and modeling is capable of simulating impacts at all points of a vehicle. In addition, this rapidly emerging technology has the added capability of providing immediate insights into redesigning vehicles in which the crashworthiness may not yet be optimal. We received written comments on a draft of this report from the Department of Transportation. The Department concurred with our recommendation that it update its information on NCAP reliability. We are concerned, however, that the agency might believe it has already complied with this recommendation by developing the star rating format. As noted above and explained in detail in appendix V, this new format does not resolve our questions concerning NCAP reliability. The Department interpreted our second recommendation as a recommendation to augment or replace “live” crash tests with computer simulations and did not concur with us. The Department cited concerns about the costs and predictive limitations of such simulations. We share these concerns, but we believe the Agency has misinterpreted the recommendation. We avoided recommending the adoption of any particular substitute for the current crash test procedures at this time. Rather, we urged the Agency to explore all possible means of reliably defining vehicle crashworthiness. Computer modeling is a potential alternative that deserves exploration and monitoring as the technology matures. Other alternatives could include extending testing programs to include side, rear, and frontal-offset impacts to gain a better understanding of the total safety of a vehicle or seeking greater sharing of crash test data developed by automotive manufacturers either through crash tests replicating NHTSA’s or through their individual component testing programs. The Department provided a number of other specific comments. They are reproduced in appendix VII, together with our response. We have also made modifications to the report as we deemed appropriate on the basis of these comments. After responding to our draft report, the Department also provided us with additional data relevant to NCAP reliability. The results of our analysis of these data can be found in appendix V. We are sending copies of this report to the Secretary of Transportation, the Administrator of the National Highway Traffic Safety Administration, and to other interested parties. We will also make copies available to others upon request. If you have any questions or would like additional information, please call me at (202) 512-3092. Major contributors to this report are listed in appendix VIII. The Department of Transportation has four offices that conduct automobile crash tests: three within NHTSA and one in the Federal Highway Administration. A compliance test program conducted by NHTSA’s Office of Vehicle Safety Compliance consists of full-frontal crashes of automobiles, light trucks, and vans into a fixed rigid barrier to ensure that vehicles meet certain minimum safety requirements. Also under the authority of NHTSA is the New Car Assessment Program, conducted by the Office of Market Incentives. NCAP tests are similar to compliance tests, but they are performed to provide consumer information on the relative crashworthiness of automobiles. The NHTSA Office of Crashworthiness Research conducts a variety of tests to study a wide range of individual safety issues that arise from specific crash configurations. Finally, FHWA conducts crash tests to study the interaction between automobiles and roadside obstacles and devices such as guard rails, telephone poles, and bridge abutments. In this study, we focused on the crash tests run under the compliance program and the New Car Assessment Program because both tests are similarly configured, employ standardized procedures, and have been assessing vehicle crashworthiness over a period of years. The tests conducted by the Office of Crashworthiness Research and those of FHWA, although important, have different purposes from those of our study and could not provide a quantity of data sufficient for us to assess relationships between test results and real-world performance. “to reduce the number of deaths of vehicle occupants, and the severity of injuries, by specifying vehicle crashworthiness requirements in terms of forces and accelerations measured on anthropomorphic dummies, and by specifying equipment requirements for active and passive systems.” These crash tests are conducted under the guidance of NHTSA’s Office of Vehicle Safety Compliance. The current compliance program relies, for the most part, on a certification process in which the manufacturer of a specific make and model vehicle states that the vehicle meets all safety requirements set forth in FMVSS 208. In addition, each year NHTSA selects a number of vehicles to test to ensure that the manufacturer’s certification is justified. The criteria used to determine which specific makes and models to test are based on whether a vehicle is in its first or second model year, whether safety features have been added or redesigned, and how many units are on the road. In selecting models for testing, NHTSA also includes any evidence of poor crashworthiness derived either from consumer complaints filed about specific models or from other crash test programs (in particular, NCAP). Through these criteria, NHTSA compiles a preliminary list of about 50 candidate vehicles for testing and requests information on crash test performance from the manufacturer of each candidate model to determine the final list of vehicles to be tested. Though they are under no obligation to do so, manufacturers will normally provide one or two sets of results from their tests of the model NHTSA specifies. NHTSA uses these data not only as an input for determining the final list of test vehicles, but also as a baseline with which to compare its own results. The compliance test consists of a full-frontal collision of a vehicle into a fixed rigid barrier at a velocity of 30 miles per hour. Anthropomorphic test dummies, fitted with instrumentation to measure forces and accelerations acting on the head, chest, and both femurs, are placed in the driver and front passenger seats. Only passive restraint systems—those that require no effort on the part of an occupant—are engaged. Examples of these are air bags and automatic seat belts. Seat belts that require active participation by the occupant are not used. The underlying assumption is that if a vehicle meets the standards for those occupants who do not make use of all available safety restraint systems, it will also meet the requirements for those who do. The test conditions further specify the forward placement of the seat, the angle of the seat back, the angle of the steering column (where the vehicle has tilt steering), and a number of other components. Some of these, such as adjustable backs for seats, are placed in the manufacturer’s nominal design riding position—that is, the position the manufacturer says is the proper one for the average adult male (5 feet 9 inches, 167 pounds). A second crash test program we studied is the New Car Assessment Program conducted by NHTSA’s Office of Market Incentives. This program was mandated under title II of the Motor Vehicle Information and Cost Savings Act of 1972 to provide consumers with an understanding of the relative crashworthiness of passenger motor vehicles. Since 1979, NCAP has conducted almost 500 crash tests of passenger cars, light trucks, and vans. From 1979 to 1986, NCAP was considered an indicant test for vehicle compliance with Federal Motor Vehicle Safety Standards 212, Windshield Mounting; 219, Windshield Zone Intrusion; and 301, Fuel System Integrity. That is, if a vehicle performed reasonably well on these tests, which required dynamic testing, then it would likely meet compliance test requirements because the NCAP test involves a more violent crash than the one required for the compliance test. If a vehicle performed poorly, the information would be transmitted to the Office of Vehicle Safety Compliance for testing its compliance with the safety standards. NCAP has not been an indicant program since the implementation of dynamic crash tests in the FMVSS 208 program in 1987; however, poor performance on the NCAP test typically leads to compliance testing of the same model. The NCAP crash test is generally similar to the compliance test. Both are full-frontal collisions into a fixed rigid barrier, and both use roughly the same criteria when determining which vehicles to test. However, three very important differences distinguish the two test programs. First, vehicles in the NCAP test are crashed at 35 miles per hour rather than 30 miles per hour, the velocity in the compliance test. This 5 mile-per-hour difference results in a 36-percent increase in the amount of energy in the system. = 1/2 mv). The additional energy in the NCAP test over the compliance test derives from the square of the velocity when the mass of the vehicle is held constant. Thus (35 miles per hour). Second, all active as well as passive safety belts in the automobile are used in the NCAP test; that is, the test dummies are restrained by any manual seat belt furnished with the vehicle as well as any automatic belt or air bag. In the compliance test, as noted earlier, only passive restraints (automatic belts and air bags) are used. The third and foremost difference between the two programs is the underlying purpose of the tests. NCAP is a market-based program that disseminates information to consumers on the relative safety of passenger vehicles. There are no minimum allowable safety performance criteria that vehicles must meet, although NCAP collects the same measurements as the compliance test. Despite the fact that NCAP is not a compliance program, industry personnel have expressed the opinion that the NCAP test has become the de facto regulation. That is, failure to meet compliance levels on this more stringent test involving a more forceful collision than the official compliance test could imply that a vehicle is unsafe. Currently, nearly all vehicles tested under NCAP meet the safety requirements specified in FMVSS 208. Both the compliance and NCAP tests use anthropomorphic test dummies to collect data related to injury potential by measuring accelerations and forces placed on an occupant’s head, chest, and upper leg. Specific levels for each measure, established under FMVSS 208, represent upper-bound limits for compliance with vehicle safety requirements. These ceilings were designed to correspond to the level at which there is a one-in-six chance of an occupant’s sustaining an injury that poses a serious threat to life. The head injury criterion, the measure used in crash tests to assess potential head injury, was adopted by NHTSA on the basis of research conducted to establish the likelihood of skull fractures under different velocity changes. HIC is measured as a composite of the axial accelerations of the head (in three dimensions). Specifically, HIC is the product of (1) the 2.5 power of the average of the resultant head acceleration over a time interval not more than 36 milliseconds and (2) that time interval. The equation for the function is HIC [1/(tt). A HIC score of 1,000, the highest allowable score for achieving vehicle compliance, is associated with a one-in-six chance of sustaining a serious skull injury. For determining potential injury to the chest region, chest acceleration is measured in gravitational units (g’s). manufacturer of the test vehicle. If the Hybrid III is used in a compliance test and the vehicle exceeds the 3-inch maximum reduction distance allowed (the limit associated with major lacerations to the spleen or kidneys), the vehicle is considered not to be in compliance with FMVSS 208. The final measure taken in both the compliance and NCAP tests is the compressive force transmitted axially through the upper legs (femurs). The femur tolerance level of 2,250 pounds of force is based primarily on experimental impacts to the lower limbs and is associated with a one-in-six chance of sustaining a fracture to that bone. When the results of a compliance test exceed the limit for any of the measures, an investigation is conducted to determine reasons for the failure and is typically accompanied by a recall or remedy campaign. If a determination of noncompliance is made, the model being tested may not be sold in the United States. This differs from NCAP as its tests are not conducted to assess vehicle compliance with federal regulations, and therefore, no punitive actions may be taken by NHTSA should a vehicle exceed any of the limits. Table II.1 lists the four measurements made in both test programs and presents the maximum allowable scores under compliance testing for each measure. In 1978 (for the 1979 model year), NHTSA began testing about 30 vehicles per year through its New Car Assessment Program. While no manufacturer is required to exceed 30 mile-per-hour standards, the program, using a 35 mile-per-hour crash test, is designed to inform customers of the relative crashworthiness of an automobile. Traditionally, NCAP reported the actual HIC, chest acceleration, and femur load scores with a disclaimer that only vehicles within 500 pounds of each other could legitimately be compared. Also, NCAP would cite the compliance ceiling levels (1,000 HIC, 60-g chest acceleration, and 2,250-pound femur load) as representing a one-in-six chance of sustaining a severe injury. Despite NHTSA’s claim of overall success in providing information about how well or how poorly passenger vehicles protect their occupants in crashes, some critics argued that NCAP’s method of reporting test results left consumers confused. In response to fiscal year 1992 Senate Appropriations Committee requirements, NHTSA performed a user study and began implementing new methods of informing consumers of the comparative levels of the safety of passenger vehicles as measured by NCAP. This new method, a star chart rating system, is designed to provide consumers with a quick, simplified, single point of comparison to evaluate vehicles in the NCAP test. Based upon analyses of a variety of accident injury studies, NHTSA developed a scale, known as the “Level of Protection Scale,” that relates the probability of sustaining an injury to the level of protection a vehicle provides its occupants from receiving such an injury. This scale forms the basis of NHTSA’s star chart method for releasing NCAP test results to the public. The star chart, which NHTSA began using in December 1993, reports a range of 1 to 5 stars, with 5 stars indicating the best crash protection for vehicles within the same weight class. The number of stars a vehicle may be rated is derived from the injury probabilities associated with the HIC and chest g scores obtained in the crash tests. These probabilities are calculated using the following formulas: Phead = [1 + exp(5.02 - 0.00351 x HIC)]-1 Pcombined = Phead + Pchest - (Phead x Pchest) A vehicle is then assigned a star rating based on its combined injury risk, with the specific number of stars determined by the range in which the combined injury risk lies. The ranges for each star rating are shown in table II.2. “are intended to describe a measuring tool with sufficient precision to give repetitive and correlative results under similar test conditions and to reflect adequately the protective performance of a vehicle or item of motor vehicle equipment with respect to human occupants.” In this appendix, we discuss the characteristics and instrumentation of the Hybrid II and Hybrid III 50th-percentile anthropomorphic test dummies, under the provisions of the NHTSA standards pertaining to occupant crash protection. We also provide a comparison of the two dummy types’ performance in NCAP and the compliance test programs. Finally, we summarize the 1993 decision to standardize the test dummy, requiring the mandatory use of the Hybrid III in all NHTSA crash test programs beginning in 1997. In both the compliance and NCAP test, the manufacturer of the vehicle being tested has the option to choose which type of dummy will be used. While both dummies are designed to represent the physical characteristics of the average adult male, important differences between them exist. Despite the differences, the requirements for vehicular conformance to FMVSS 208 are not different for the two instruments, with the exception of the chest compression criterion, which applies only when the Hybrid III dummy is used. Part 572 of the Federal Motor Vehicle Safety Standards specifies the types of anthropomorphic dummies to be used in the FMVSS 208 compliance test. Currently, two specific types of anthropomorphic test dummies may be used in a compliance crash test: the Hybrid II and the Hybrid III. As specified in subpart B of 49 C.F.R. part 572, since 1973 the Hybrid II 50th-percentile male test dummy is 5 feet 9 inches tall and weighs approximately 164 pounds, and until 1986, this dummy was used when determining compliance to FMVSS 208. In 1986, 49 C.F.R. parts 571 and 572 were amended to adopt the Hybrid III 50th-percentile dummy as an alternative to the Hybrid II for FMVSS testing. This gave manufacturers the option of using either the Hybrid II or Hybrid III test dummy as the means of determining a vehicle’s conformance to NHTSA’s performance requirements. Like its predecessor, the Hybrid III is 5 feet 9 inches tall but weighs slightly more (167 pounds). Also, like the Hybrid II, each Hybrid III used in a compliance test must meet the specifications and performance criteria of part 572 before and after each vehicle test in order to be an acceptable compliance tool. The Hybrid II and Hybrid III use the same instrumentation in the head, chest, and femurs. (See figure III.1.) However, according to General Motors, developer of the Hybrid III, its 50th-percentile male dummy was designed to improve on Hybrid II technology and biofidelity. Most experts regard the Hybrid III test dummy as more biofidelic than the Hybrid II, having a more human-like seated posture, as well as head, neck, chest, and lumbar spine designs. The Hybrid III’s responses to crash conditions more closely approximate the motions associated with human anatomy in crash situations and, therefore, more accurately evaluate injury risks. For example, the improved flexibility of the Hybrid III’s neck over the Hybrid II allows researchers a greater ability to assess the injury potential of whipping motions. In addition to the greater biofidelity, the experts we interviewed stated that the Hybrid III is more sophisticated technologically than the Hybrid II because it has more instrumentation for measuring potential injuries. Specifically, the Hybrid III is capable of measuring nearly four times as many forces and accelerations throughout the body as the Hybrid II. For example, not only does the Hybrid III measure injury potential to the skeletal structures, but it can also determine injury potential to the soft tissues in the upper thorax through the chest compression measure. Further, the Hybrid III has accelerometers and load cells placed in the neck and lower legs that can measure the potential for injuries caused to those anatomical areas. To date, no criteria have been established for meeting compliance for the additional measures other than chest compression. However, the measures do provide DOT with additional information on the potential physiological responses associated with vehicular crashes. Currently, the determination of which dummy to use in a test is made by the manufacturer of the vehicle being tested. Through 1993, manufacturers chose to use the Hybrid III in 36 of the 133 tests of passenger cars in the compliance program and in 30 of the 86 tests of passenger cars in NCAP since the dummy became available for use in the two programs (1988 and 1990, respectively). One expert hypothesized that the reason so few compliance tests involve Hybrid III dummies is that they tend to receive higher HIC scores, especially in noncontact situations and that there is no guarantee that a car designed around the Hybrid II will pass a test using a Hybrid III. The differences between the dummies used in NHTSA’s tests, described above, led us to compare the driver-side HIC and chest acceleration scores from passenger-car compliance and NCAP tests in an attempt to quantify the potential effects on test reliability such differences could create. In this analysis, we controlled for the presence of a driver-side air bag in the car. In general, we found the Hybrid III dummy scores were lower than the Hybrid II scores, but that the presence of air bags strongly affects the relative performance of the two dummy types. (See tables III.1 and III.2.) Chest acceleration (g’s) For passenger cars from 1990 to 1993, with and without air bags. Specifically, we found that Vehicles tested with Hybrid III dummies had lower HIC and chest acceleration scores than those tested with Hybrid II dummies in both compliance and NCAP tests. In NCAP tests, Hybrid III dummies averaged 156 HIC and 3.6 g’s less than Hybrid II dummies. (See table III.1) Similarly, in compliance tests, the mean head injury criterion score for cars tested with Hybrid III dummies was 97 HIC lower than the score for tests that used the Hybrid II, while the mean chest acceleration score was about 2 g’s less for test cars that used the Hybrid III. (See table III.2)In both the NCAP and compliance tests, Hybrid III had significantly lower HIC scores than Hybrid II dummies in vehicles equipped with air bags. In vehicles without air bags, Hybrid IIIs had significantly higher HIC scores than Hybrid IIs. The difference could occur because of the greater flexibility of the Hybrid III’s neck.In both the NCAP and compliance tests, Hybrid III dummies had significantly lower chest acceleration results than Hybrid II dummies in cars with air bags. There was little difference between the chest scores of Hybrid III and Hybrid II dummies in cars without air bags. Chest acceleration (g’s) For passenger cars from 1988 to 1993, with and without air bags. Manufacturers have been reluctant to use Hybrid III dummies for tests of cars not equipped with air bags because these dummies tend to produce higher HIC results, especially in cases where the dummy’s head did not contact the interior components of the car. (Only 18 percent of compliance tests of cars without air bags from 1988 to 1993 and 18 percent of NCAP tests of cars without air bags from 1990 to 1993 used the Hybrid III.) Industry representatives stated that because HIC was developed to determine potential skull injuries—a condition that will not occur if the head does not contact the vehicle’s interior—it should be applied only to cases in which the head actually makes contact. Although they agree that brain injuries can occur when the head does not contact the interior, they contend that the instrumentation in the dummy’s head does not measure the potential for these types of injuries. Therefore, they conclude that in cases of “noncontact” HICs, the results are meaningless and misleading. Thus, rather than risk a spuriously higher HIC score in either the compliance or NCAP tests, manufacturers have tended to use the Hybrid II for vehicles that do not have air bags. While these complex interactions of dummy type, safety equipment, and test conditions can be explained by biomechanical differences between the Hybrid II and Hybrid III dummies, they may also be explained by differences in the test vehicles themselves. As we noted earlier, the manufacturers specify which dummy type to use in NHTSA crash tests, and one may assume that, in the absence of other motivations, they would choose the dummy they anticipate will yield more favorable results. As noted above, each manufacturer undergoing a compliance test may specify either the Hybrid II or the Hybrid III test device. But in recent years, NHTSA has become more convinced that using the Hybrid III will help ensure that all new vehicles are designed with the benefit of the most human-like test dummy available. NHTSA regards the Hybrid III as more representative of human responses in frontal crashes, and it can monitor more types of potential injuries as well. Further, NHTSA has come to recognize that exclusive use of the Hybrid III for compliance testing under FMVSS 208 would result in greater comparability of test results among vehicles produced by different manufacturers. For these reasons, the agency recently issued a Notice of Final Rule that requires the exclusive use of the Hybrid III for all compliance testing under standard no. 208. The final rule takes effect September 1, 1997, to coincide with the date at which all passenger cars and 80 percent of light trucks must be equipped with air bags and all light trucks must have passive (automatic) restraint systems. NCAP will also switch to exclusive use of the Hybrid III test dummy beginning with the 1996 model year. These modifications to the two programs will create a greater degree of standardization of crash tests, thereby, in NHTSA’s view, increasing the “comparability of test results among vehicles produced by different manufacturers, particularly those that now use different dummy types.” We conducted analyses of the trends in NCAP test scores from 1979 through 1993 and found that scores have both improved and become more uniform during the period. We have expressed NCAP results in terms of the combined injury risk scores to which NCAP now translates its HIC and chest scores to produce its new “star system”. Figure IV.1 shows the mean injury risks for the driver position, by year, for model years 1979 through 1993. The mean combined injury risk decreased significantly from a high of 0.507 in 1980 to a low of 0.190 in 1993. The figure also indicates that the significant reduction in the combined risk derives from a significant and consistent decrease in the mean head injury risk probability. While the mean chest injury risk declined significantly during the period, it has been relatively stable since 1983. The variation between the individual test results has also decreased over the years. For example, NCAP head injury criterion scores for vehicles in 1979 ranged from 521 HIC to 4,513 HIC, whereas in 1993, the range was between 273 HIC and 1,459 HIC. One reason for the decline in the mean combined injury risk and its accompanying variation over time is the increasingly widespread installation of air bags. Cars equipped with air bags had significantly lower head injury risk probabilities than cars without air bags. (See figure IV.2.) Since the first NCAP test of cars equipped with air bags in 1987, these vehicles have scored an average head injury risk of 0.063, while cars without air bags have averaged 0.216. There is little difference, however, between the mean chest injury risks for passenger cars equipped with air bags (0.108) and those that did not employ this type of restraint (0.120). (See figure IV.3.) Given the relatively flat chest injury risk shown in figure IV.1, it appears that this risk factor, regardless of the type of restraint, has contributed little to the declining trend for the combined injury risk. We also conducted similar analyses for passenger cars tested in the compliance program. Despite fluctuations from year to year, the combined injury risk did not change significantly from 1987 to 1993. (See figure IV.4.) For all passenger cars. Does not include light trucks and vans. During the same period a steady, though not statistically significant, decline in the mean head injury risk was offset by a significant increase in the mean chest injury risk. These opposing trends are associated with the increased installation of air bags, which are associated with lower head injury risk probabilities and higher chest injury risk probabilities for compliance tests. (See figures IV.5 and IV.6.) The contrasting chest injury risk results between NCAP and compliance programs may have occurred because of the differences in the configuration of the two tests—largely from the determination of which restraint systems are used. In an NCAP crash that makes use of all available passive and manual restraint systems, the seat belt absorbs the dummy’s kinetic energy over a gradual period (for a crash event) before the dummy contacts the air bag. However, cars with air bags are not required to have automatic seat belts. And since manual seat belts are not engaged in compliance tests, the dummy in the driver position is not likely to be restrained by a safety belt in compliance tests of cars with air bags. The dummy, therefore, is likely to move forward without a reduction in its kinetic energy, resulting in a more forceful collision with the air bag than if a seat belt was also in use. Over time, as more of the vehicles tested in the compliance program came equipped with air bags, the mean compliance chest score increased. This is not to say that an air bag-equipped vehicle is less safe than one that does not have an air bag. Indeed, the chest g results of cars with air bags may not be directly comparable to those without the devices because the distribution of the force loading on the chest is different for air bags than for safety belts. Air bags distribute the load caused by chest contact across a larger surface area than safety belts. Nevertheless, the higher chest g result for an air bag-equipped vehicle is consistent with the view held by many traffic safety experts that safety belts alone (that is, without air bags) are much more effective than airbags alone (that is, without safety belts). The decreasing mean crash test results parallel a similar trend with annual fatalities, and part of that latter trend can rightfully be attributed to NHTSA crash tests. In discussions with industry representatives, we found that automobile manufacturers attempt to design vehicles to meet compliance levels for frontal collisions in the NCAP test, as well as ensure that all other safety criteria are met. In addition to “live” crash tests, manufacturers use computer models of frontal collisions, rear and side impacts, and roof crush to simulate NHTSA crash tests and to ensure that the cars meet NHTSA standards. The types of simulations range from models of specific components of the vehicle to nonlinear finite-element models, which incorporate all specifications of the automobile and can predict interactions between the car and its occupants during a collision. These simulations allow manufacturers to gain insight into the deformation of the vehicle, likely intrusions into the occupant compartment, and the force loads generated by various structural components. Though computer- simulated crashes are expensive because they generally require access to a supercomputer, they do allow manufacturers to gain knowledge of how the car will perform and how to correct problems before building prototypes. They are also much less costly and less time-consuming than building and crashing prototypes. In addition, one simulation expert stated that the results of finite-element simulations generally reflect the results obtained in actual crash tests and that the industry uses crash tests in part to validate its computer-based crash models. Our analyses of the trends in NCAP test results have shown that (1) injury risk probabilities have declined over time and (2) the variation between test results has lessened over time. (See appendix IV.) It would seem that cars have become more crashworthy—at least as measured by NCAP—and that this improved crashworthiness is more uniformly distributed across the passenger car fleet. Indeed, in 1979 the combined injury risk for NCAP-tested vehicles ranged from 0.106 to 1.0 (rounded), whereas in 1993, the ends of the distribution ranged from 0.096 to 0.581. Despite the decreased variation in test results, however, the difference between the highest and lowest risk probabilities is still substantial. This variation is open to two quite different interpretations. It may indicate the sensitivity of crash tests to real differences between vehicle models, or it may reflect the imprecision of the test scores. In classical measurement theory, reliability is defined as the repeatability of test results. The reliability of crash tests would be estimated by comparing the results from repeated crash tests of the same model vehicle. On only one occasion has NHTSA attempted to determine whether NCAP crash test results are, in fact, reproducible by crashing a single model on multiple occasions. In this study, 12 consecutively manufactured 1982 Chevrolet Citations were crash-tested by three test facilities, with each facility testing four vehicles, in an attempt “to quantify the degree of variation, as well as develop generalized statistical conclusions about test repeatability.” The mean HIC score for the 12 tests was 685, with the scores ranging from 495 HIC to 954 HIC. NHTSA identified several sources of variation in results derived from the test procedure, as well as from the testing facilities, the test instrumentation, the test dummy used, and the individual vehicles. NHTSA could not quantify the amount of variation attributable to each of these five areas because of the number of possible sources of error within each. Although the amount of variation that can be attributed to any of the sources of error is incalculable, the confounding interactions of accumulated error lead to questions about the reliability of NCAP results. The variation between different units was artificially constrained by selecting 12 consecutively manufactured Chevrolet Citations, yet the head injury results still had a range of 459 HIC. This variation among the HIC scores implies that two scores with a range of less than 219 are not, in statistical terms, significantly different and that any score between 781 HIC and 1,219 HIC is not significantly different from 1,000. Table V.1 illustrates how this level of reliability could affect the interpretation of other crash test scores. The table displays the mean HIC score from the 12 Citation crash tests and the HIC scores of four other vehicles of similar weight. It also indicates whether the NCAP HIC scores are significantly different from (1) the mean Citation score and (2) the putative ceiling of 1,000. The HIC scores received by all the vehicles except the 1990 Lexus are significantly lower than 1,000. However, there is no statistically significant difference between the mean HIC score received by the Citation and three of the four other vehicles. Curb weight (pounds) From NHTSA’s 12 1982 Chevrolet Citation tests and NCAP results for vehicles of similar weight. Does not apply. After reviewing a draft of this report, NHTSA provided us with a second set of data that could shed additional light on the reliability of NCAP scores. These data represent the results of crash tests of model-year 1991 through 1994 vehicles conducted by automobile manufacturers in tests that essentially duplicate the NCAP test conditions. The data were voluntarily submitted to NHTSA before planned NCAP tests. We compared the manufacturer scores with those obtained from NCAP after translating them into the single injury probability score that serves as the basis for NHTSA’s recently introduced star rating system. (See appendix II.) We found that a statistically significant first-order correlation exists (r = .72) between the two sets of injury risk probabilities. We then compared the distributions of star ratings derived from NCAP and manufacturers’ tests. Table V.2 compares the star ratings for the driver position, and table V.3, for the passenger position. If agreement between the two sets of tests had been perfect, all events in the tables would have fallen on the diagonals from upper left to lower right. In actuality, star ratings are the same for approximately one-half of the vehicle models tested (55 percent for the driver position and 45 percent for the passenger position). Differences of one or more stars exist between manufacturer and NCAP ratings for about one-half of the tests; 8 percent of the vehicle models have differences of two or more stars. As appendix II explains, each of NHTSA’s star ratings represents a range of injury probability. For example, a rating of 4 stars indicates that in a crash situation similar to that tested by NHTSA the probability of serious injury to an individual is between 1 in 10 and 2 in 10. The solid bars in figure V.1 depict these probability ranges for each star rating. The lines attached to the bars represent “confidence intervals” that we estimated from the standard deviation of the absolute difference between the combined injury risks for drivers derived from manufacturer and NCAP tests. These confidence intervals represent the estimated range of injury probability within which a vehicle with a nominal rating could be expected to vary if tested again. For example, a 4-star rating could be associated with a vehicle with a “true” injury probability between zero and 0.363. This range overlaps the confidence intervals associated with the 5- and 2-star ratings. Our estimates of the reliability of NCAP crash tests are based on the only two sources of relevant information we are aware of: the repeated crashes of the 1982 Chevrolet Citation, and a comparison of manufacturer and NCAP test scores from 1991 to 1994. Neither of these sources provides ideal information for precisely quantifying the measurement error associated with NCAP scores. We do not know how well the results of the Citation experiment can be applied to vehicles manufactured and crash-tested 10 years later. While the manufacturer-NCAP comparison applies to a large number of late-model cars, we cannot be sure how well the manufacturers succeeded in replicating NCAP crash test conditions in each case or to what extent the results from other manufacturer tests varied from the ones reported to NHTSA. Nevertheless, both analyses support the same conclusion that NCAP scores, whether reported in raw HIC and chest acceleration scores or as categories of injury probability, have associated levels of imprecision. As a result, substantial differences in scores between two test results (100-200 HIC, or a 1-star—or possibly 2-star—rating difference) may not represent true differences in crashworthiness. The overall purpose of both the compliance and NCAP crash tests is to determine the crashworthiness, or safety, of passenger vehicles. This implies, therefore, that a relationship exists between the results of crash tests and real-world injuries and fatalities. To examine this issue, we conducted two analyses comparing results derived from NCAP tests to those from national accident databases. Specifically, our analysis compared NCAP results with traffic injury and fatality information from the National Accident Sampling System (NASS) and the Fatal Accident Reporting System (FARS). This appendix details the methodologies and results of both analyses. Data from the National Accident Sampling System for 1988 through 1991 were combined to determine whether the results of New Car Assessment Program tests are good predictors of serious injuries and fatalities in real-world automobile crashes. The NASS is a sample of annual police-reported accidents involving passenger cars, light trucks, and vans that had to be towed because they were damaged. The NASS year corresponds to the calendar year rather than the automobile industry’s model year, and emphasis is placed on the most recent 5 model-year vehicles. We chose this data system for two reasons: (1) It is a national database that contains information on all types of automobile collisions, and (2) it is the only national database that reports a vehicle’s change in velocity (delta v)—the best available indicator of accident severity—resulting from the collision. We reduced the NASS data sets to single-vehicle and two-vehicle accidents and then combined them into one data set. This resulted in a total of 14,253 vehicles in the final data set. We then matched the results of the NCAP crash tests to the vehicles in our NASS file. NCAP results from 1983 through 1992 were chosen for the analysis for two reasons: (1) We assumed that crash test results are applicable for a given time (as cars age, their crashworthiness may decrease owing to wear and tear) and (2) NASS data were available for the calendar years 1988 through 1991. Because NASS emphasizes for inclusion collisions involving vehicles from the 5 most recent model years, we chose 5 years as the period of time at which a test score no longer applies; therefore, NCAP scores from 1983 were the earliest we included in the analysis. In addition, each NASS year has a half-year’s data from the following model year, as the model year usually begins in late summer. Therefore, the 1991 NASS had some accidents involving 1992 model-year automobiles. The NCAP results were matched to the NASS data set on the following criteria: the make of the vehicle (that is, the manufacturer), the model, the model year, and the body type (sedan, convertible, and so forth). In cases in which a specific make, model, model year, and body type were tested on more than one occasion, only the first test was used. Results for models with corporate twins (vehicles with platforms identical to one another but sold under different model names—for example, Ford Taurus and Mercury Sable) were projected to the twins. The resultant data set for our analyses contained 1,985 cases. When weighted by NASS sampling weights, these represented more than 9 million accidents. We conducted logistic regression analyses to determine whether a relationship exists between serious injuries and fatalities in actual automobile collisions and results from crash tests conducted for NCAP. We analyzed crashes in which damage to the right front, left front, or full front of the vehicle occurred. Single-car and two-car crashes were examined separately. We conducted two sets of analyses: one on the unweighted sample in our dataset and a second, which incorporated the NASS sampling weights. Our analyses of the relationship between real-world traffic injuries and fatalities and NCAP injury risk probabilities were limited to drivers of passenger cars (two-door and four-door sedans, coupes, hatchbacks, and convertibles). We restricted our analyses to “restrained” drivers—that is, drivers who made proper use of either a manual or an automatic seat belt or whose air bag deployed during the crash. The dependent variable used in the analyses was constructed from NASS injury codes to represent whether the driver of an NCAP passenger car involved in a crash either died or was hospitalized for at least 1 day specifically because of the crash. This was coded as a dichotomous variable, with those who died or were hospitalized receiving a 1 and all other nonmissing values receiving a zero. The independent variable of interest was the combined injury risk score associated with specific vehicle models as derived from the HIC and chest acceleration scores from NCAP tests. (See appendix II.) However, because characteristics of the driver and the vehicle and, most importantly, the severity of the crash (as measured by the total change in velocity, or delta v) are associated with the likelihood of injuries and fatalities, we included occupant characteristics (age, gender), vehicle characteristics (curb weight and, in two-car crashes, the weight of the other vehicle), and crash severity (delta v) in our logistic regression models. Tables VI.1 and VI.2 present the results of our analyses of the unweighted sample for one- and two-car crashes. The predictive power of delta v dominates both models, but the driver’s age and the car’s weight also appear as significant predictors of injury in two-car crashes. In these crashes, older drivers and drivers of lighter cars were more likely to suffer injury or death. In neither model was the NCAP injury risk significantly related to hospitalization or death in either one-or two-car crashes. Injrisk = Driver injury risk Age = Age of driver Gender = Gender of driver Curbwgt = Vehicle’s curb weight Dvtotal = Total change in velocity (mph) Represents 46 restrained drivers. Injrisk = Driver injury risk Age = Age of driver Gender = Gender of driver Curbwgt = Vehicle’s curb weight Othvehwgt = Weight of other vehicle Dvtotal = Total change in velocity (mph) Collisions with vehicles weighing less than 10,000 pounds. Represents 131 restrained drivers. Tables VI.3 and VI.4 present the findings from the weighted sample and show very similar results to the unweighted sample. The strongest predictor remains the crash severity, and in two-car crashes, driver age is related to collision outcomes. The weighted sample presents two different conclusions from the unweighted sample, however. The curb weight of the vehicle falls short of statistical significance by traditional criteria, and more to the point, a significant relationship between NCAP risk scores and death or hospitalization appears. Injrisk = Driver injury risk Age = Age of driver Gender = Gender of driver Curbwgt = Vehicle’s curb weight Dvtotal = Total change in velocity (mph) Represents 8,401 restrained drivers. Injrisk = Driver injury risk Age = Age of driver Gender = Gender of driver Curbwgt = Vehicle’s curb weight Othvehwgt = Weight of other vehicle Dvtotal = Total change in velocity (mph) Collisions with vehicles weighing less than 10,000 pounds. Represents 23,514 restrained drivers. Some degree of doubt must be associated with these findings because of the nature of the sample on which they are based. NASS uses a highly complex stratified sampling design to achieve national representativeness for its relatively small sample of observations. The NASS database we used contained 21,377 observations, which when properly weighted, represent more than 9 million accidents. Unfortunately, we found only 366 instances of NCAP-tested cars that met our criteria of properly restrained drivers, and only about one-third of these could be used because of missing values on one or more variables. This drastic reduction in sample size, when combined with the highly uneven distribution of missing values across sampling strata, makes the sampling weight associated with any observation of doubtful validity. To overcome the statistical limitations of our NASS database, we turned to the Fatal Accident Reporting System (FARS). By using FARS, we looked to substantially increase the number of usable cases in the analysis in that FARS contains information on all accidents in a given year that involve at least one fatality (about 45,000 cases per year), while NASS contains only a sample of all accidents (about 3,000 cases per year). In addition, we reasoned that while FARS lacks the information on crash severity provided by NASS’ estimate of the total change in velocity, its severity of crashes was relatively homogeneous because the database is restricted to fatal—presumably severe—crashes. For this analysis, only passenger cars from the 1982 to 1991 model years were included. In addition to the actual test vehicles, our analysis included vehicles that had no substantial structural changes in model years following the tested model year. That is, if a 1984 model-year vehicle were tested in NCAP and no structural changes were made to the 1985 version of the vehicle and it was not retested, the 1985 model year was assigned the same combined injury risk score as the 1984 vehicle. We then matched the vehicles to the FARS and the R.L. Polk Vehicle Registration System (Polk) databases based on the make (that is, the manufacturer), model, model year, and body type of the vehicle. The FARS database is a compilation of all automobile accidents in the United States in any given calendar year in which at least one fatality occurred. The Polk system is a database that contains information on the types, numbers and weights of vehicles registered in a given calendar year. Data for both systems are for the calendar years 1987 through 1991. As with the analysis of NASS data, we restricted this analysis to one- and two-car frontal collisions in which the driver of the NCAP-tested vehicle was restrained by either a seat belt or an air bag. Having matched the NCAP vehicles to the FARS and Polk systems, we then calculated the fatality rates for the vehicles. This was done simply by dividing the number of fatalities by the number of registered vehicles. The fatality rates in our analysis are expressed in terms of fatalities per 100,000 registered vehicles. We then correlated the driver combined injury risk scores and fatality rates associated with vehicle models in a number of ways. First, we calculated a simple correlation using just information on those elements. Next, we regressed fatality rates on additional characteristics associated with vehicles using a Poisson model, which allows one to compare rates of individual cases, especially when the sample size is moderately large and the probability of an event occurring is either very low or very high. This type of analysis fit our needs in that a large number of cases (884) were included in our analyses while the fatality rates of the vehicles included were low (overall, there were 1,036 deaths for approximately 19 million registered vehicles). The variables added to the model held information on the model year and body style of the vehicles in the dataset. We controlled for the model year as a proxy for certain driver, vehicle, and roadway characteristics that could not be included in the model. We controlled for the body style for two reasons: (1) as a surrogate for the relationships found between specific body styles and certain driver characteristics and (2) as a rough surrogate for the weight of the vehicle. As a final analysis, we divided the NCAP injury risk distribution into quintiles and compared the fatality rates of the different groups. Each quintile represented one-fifth of the passenger cars tested in NCAP from 1982 to 1991. We found that a first-order correlation between NCAP injury risk and fatality rates exists (p = .007). When information on the body style and model year of the vehicle was included in the analysis, the strength of the relationship increased (p = .001). However, the relationship appears to be the result of the high fatality rates associated with the poorest performers in NCAP. Indeed, vehicle models within the highest quintile of injury risk (those in the highest 20 percent of the distribution) had significantly higher fatality rates than all other quintile categories. Further, we found that the worst performers on the NCAP test had injury risk probabilities approximately eight times higher than the best-scoring cars, while their fatality rates were almost 28 percent higher. The remaining four quintile groups, on the other hand, were not significantly different from one another. (See tables VI.5 and VI.6.) Thus, it seems that the relationship between driver fatality rates and predicted injury risk stems from the significantly higher fatality rates associated with vehicles that have very high NCAP injury risk probabilities. Mean combined injury risk (NCAP) Fatality rate (FARS/Polk) Fatality rate calculated by dividing the number of fatalities in a given risk quintile by the total number of registered vehicles in that quintile. Fatality rates are expressed as fatalities per 100,000 registered vehicles. The mean combined injury risk is the average NCAP injury risk for the quintile. Body styles include coupes, sedans, two- and four-door hatchbacks, and station wagons. Mean fatality rates as reported in table VI.5. A z-score of 1.96 or greater shows significant differences between the means at a probability level of at least p = .05. Not applicable. The following are GAO’s comments on the letter from the Department of Transportation dated July 13, 1994. 1. We agree with NHTSA that the terms “reliability” and “validity,” as used in the report, refer to their statistical meanings, test repeatability, and predictive validity, respectively. We share the concern that common usage of the terms “could have damaging effects” on NCAP’s credibility and mislead a casual user to conclude that the tests have not had positive effects on the crashworthiness of the U.S. passenger car fleet. For this reason, we have modified the subtitle of the report. NHTSA is correct in asserting that we use the term reliability in its traditional meaning of reproducibility. We disagree with NHTSA’s implication that this meaning is not relevant to “the relative safety performance of vehicles.” Indeed, as our report indicates, the band of uncertainty that surrounds crash test scores (as it does any test results) can affect the relative ranking of vehicles. 2. We recognize that model lines would have NCAP result variations unique to themselves, and the report clearly states this caveat (see p. 38, footnote 5). After completing the Citation experiment, NHTSA made changes in its test procedures to improve their reliability. Unfortunately, no equivalent test of how effective these changes were in reducing the variability between test scores was subsequently performed. After NHTSA had provided its official comments on our draft report, the agency also provided us with crash test results from automobile manufacturers for model-year 1991 through 1994 vehicles. These data were provided to NHTSA in preparation for tests conducted under NCAP and were results of tests that essentially duplicated the NCAP testing procedure. The agency had previously declined to provide this information because they considered it proprietary. We analyzed these data and have included our findings in the body of the report (see pp. 39-41). Though this information cannot define the boundaries of NCAP reliability, the difference between manufacturer and NCAP results reinforces our conclusion that the reliability of NCAP results is limited. 3. We do not disagree with NHTSA that rigorous protocols for crash testing are followed and that NHTSA verifies the results of the crash test with high-speed film. However, this process merely verifies that the accelerometers placed in the test dummy accurately recorded the data from the specific trial. It does not address the issue of reliability, which in classic statistical theory holds that test data are reliable if consistent results are obtained through repeated trials of an experiment using specific procedures. In the case of NCAP crash testing, a specified procedure exists, but the model of the test vehicle changes. Unless multiple trials of the same model line are conducted, we cannot determine the reliability of test results. We are sensitive to the costs the Agency could incur in addressing our recommendation that it update and publish, in clear language, its knowledge of the reliability of NCAP results. For this reason, we suggest that the Agency explore alternative means for accomplishing this goal, in particular by making use of the knowledge base developed by manufacturers. Regardless of the method the Agency uses to address the recommendation, its purpose will not be, as NHTSA suggests, to “enhance the scientific reliability of its data” or “narrow its standard deviation,” but to assure American consumers that they are provided with accurate information about the relative crashworthiness of vehicles. 4. We agree that NHTSA has found a statistically significant difference between the fatality risk of belted drivers involved in two-car frontal collisions in cars with “good” NCAP performance and those that were “poor” performers. In our analysis of the fatality rates, though using a different methodology, we found similar results. The analyses we performed shared a common weakness with NHTSA’s; namely, they were both limited to a relatively small proportion of real-world crashes. NHTSA’s estimate of reduced fatality risk for better scoring NCAP cars is derived from analyses using only two-car crashes in which both drivers were belted and at least one occupant was killed. These conditions limited their analyses to between 81 and 170 crashes. (NHTSA’s database was drawn from the 1979 through 1991 FARS years, which represent between 40,000 and 50,000 highway fatalities annually.) Our analysis was also limited to NCAP cars involved in fatal accidents with restrained drivers, although we also included single-vehicle crashes and FARS data from 1987 through 1991. These limitations reduced our sample to 884 cars. Both NHTSA and we agree that a statistically significant correlation between NCAP scores and real-world crashes can be found but, to use NHTSA’s words, the correlation is “far from perfect.” Our analyses suggested that this correlation derived from the fatality rates of the worst scoring cars, and not from crashworthiness differences among relatively good NCAP performers. 5. We generally agree with NHTSA’s comment that the improvement in NCAP scores over time has contributed to an improvement in highway safety. However, many other influences unrelated to crash testing, such as safety belt usage laws, and the toughening of drunk driving laws, have also contributed to this trend. 6. Our report does not address the purported ease of interpretation associated with the new star rating system. However, we did incorporate NHTSA’s new reporting system into our analysis of the new data provided us by NHTSA. Our findings provide detail to support the conclusion of our draft report: that a reporting system can be no more reliable than the scoring system on which it is based. We disagree that the new star rating system “eliminates . . . implied precision” of HIC, chest, and femur scores. It is true that some cars with nonsignificant differences in scores would end up in the same category under the new system, and thus correctly be presented to the public as roughly equal in crashworthiness. However, it is also true that other cars with nonsignificant score differences could be placed in different categories, a scoring artifact that incorrectly implies substantial differences in the relative levels of crash protection provided by the vehicles. For example, while a vehicle with a chest g of 40 and a HIC of 550 will receive 5 stars, one with a chest g of 40 and a HIC of 555 will receive 4 stars. We do not believe that this difference in HIC scores implies an actual crashworthiness difference. 7. NHTSA appears to suggest that it has already complied with this recommendation through the adoption of its new reporting system. We disagree. The new system, while seemingly clear, does not communicate to the public the band of uncertainty associated with star ratings. Our analyses of the manufacturers’ NCAP test results suggests that this band is sizable and illustrates its potential effects. However, additional information needs to be collected and analyzed before the precision of crash test results can be adequately defined. 8. The recommendation is to explore alternative methods for determining the crashworthiness of vehicles. We cited computer simulations as one promising avenue to explore. We recognize the limitations of the current capabilities of computer simulations (the high cost of supercomputers, the complexity of programming, and so on), and we agree with NHTSA that this technology could not replace actual crash tests in the near future. However, NHTSA’s comment suggests that it has examined the potential benefits of this rapidly emerging technology and has dismissed them. We believe that it should continue to monitor and periodically reassess them. It appears to us that as the technology develops and becomes less costly, the potential benefits of such a system extending to a much larger set of crashes than NCAP now considers at some point in the future may outweigh its costs. Other possible approaches include ones that NHTSA is already considering, such as extending the range of tests to include both side-impact crashes and frontal-offset crashes. While such tests would expand the applicability of NCAP tests to a larger portion of real-world events, they would also substantially increase the costs of the program. This consideration reinforces our belief that the costs and benefits of alternative approaches such as computer modeling need to be revisited regularly over the next decade. 9. We are aware of the limitations of the NASS database, and we agree with NHTSA that the number of cases that mimic the NCAP configuration are few. Indeed, in the 4 years of NASS data we analyzed for the project, only 46 of over 14,000 cases applied to our model most closely resembled the NCAP configuration. We disagree that the methodology was inappropriate. The models used in the analyses were designed not only to simulate the NCAP conditions, but also to discover the sensitivity of NCAP for predicting other frontal collisions, and thereby maximize the number of frontal crash configurations for which the test was applicable and meaningful. It seems reasonable to expect that, given enough cases, NCAP should predict real-world traffic injuries and fatalities in collisions that essentially duplicate the test conditions; however, given the small number of actual events that apply to this configuration, the meaning of any unweighted statistically significant relationship is questionable. 10. There is no contradiction between these statements. NCAP’s relative rankings of different models may be inaccurate in some cases. Nevertheless, it is unlikely that the parallel improvement in NCAP scores and highway safety statistics over the past 15 years is totally coincidental. 11. We agree with NHTSA’s comment about manufacturer participation in NCAP, and the language has been changed. With respect to the quasi-regulatory nature of NCAP, manufacturers repeatedly stated that they must design automobiles to meet this test as if it were the standard. In oral commentary on our draft report, one NHTSA official pointed out that almost all passenger cars meet compliance standards in the NCAP test, and that “in effect, it’s a de facto standard.” 12. The 220-point reduction in the mean HIC falls short of statistical significance (p = .171). This, we believe, is a function of the low number of cases and high variations in the early years of compliance testing. Although the decline is not statistically significant, we would reiterate that, on average, vehicles tested for compliance with FMVSS 208 tend to have HIC and chest acceleration scores that are far below the maximum allowable levels. 13. Although “it has not been proven,” it seems reasonable to assume that a 1979 vehicle that was involved in an accident in 1991 no longer had the same level of structural integrity as it did when it was new, owing to the rusting of the frame, for example, or the weakening of welds. It also seems reasonable to assume that a 1979 model-year vehicle would not perform at its full original safety potential in a collision that occurred in 1991. 14. As our report states, and NHTSA cites, no statistical analysis can, by itself, establish cause-and-effect linkage, and we do not demand this result of our analyses. 15. We accepted NHTSA’s suggestion and used SUDAAN to perform additional analyses of the NASS data. The results were inconclusive. In one case (two-vehicle collisions), we found a statistically significant relationship between NCAP scores and serious injury. (See table VI.4.) However, this result could easily be spurious since the application of NASS sampling weights (which vary substantially and can be quite large) to the small subset of cases that both fit our criteria and have no missing data can greatly distort the analysis. If, as NHTSA suggests, a subset of NASS data is “insufficient to conduct any type of statistical analyses,” applying sampling weights to a nonrandom selection of variously weighted cases is potentially misleading. 16. We are aware that in some analyses, NHTSA has used the combination of subject vehicle weight and its ratio to the other vehicle weight as predictors of injury instead of simply using the weight of the two vehicles. We did not feel it necessary to reanalyze the data using weight and weight ratio since, as NHTSA has pointed out, they “are mathematically equivalent to the information provided by the two individual vehicle weights.”17. We used the traditional adjustment, the ratio of fatalities to the number of registered vehicles, to correct for the variations in exposure to accident involvement among the NCAP-tested vehicles. We agree with NHTSA that other factors, such as driver age and driving history, are also important predictors of accident involvement and are not captured by this adjustment. Our goal here, however, was to answer the simple question: Are proportionately more drivers killed in poor scoring NCAP cars than in better scoring cars? Our answer is “yes.” 18. Based on NHTSA’s comment, we converted HIC and chest g scores to the combined injury probability, which forms the basis for NHTSA’s new rating system, and used it as a variable in the analyses conducted and presented in this report. 19. The section is no longer in the report. Alem, Nabih M., Guy S. Nusholtz, John W. Melvin. “Head and Neck Response to Axial Impacts.” Proceedings of the Twenty-Eighth Stapp Car Crash Conference (SAE Paper No. 841667). Warrendale, Pa.: Society of Automotive Engineers, 1984. Pp. 275-82. Association for the Advancement of Automotive Medicine and the International Research Council on the Biomechanics of Impact. 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Safety Effectiveness Evaluation of the National Highway Traffic Safety Administration’s Rule-Making Process. Vol. 11: Case History of Federal Motor Vehicle Safety Standard 208: Occupant Crash Protection (NTSB-SEE-79-5). Washington, D.C.: U.S. Government Printing Office, 1979. Unterharnscheidt, F.J. “Translational Versus Rotational Acceleration— Animal Experiments With Measured Input.” Proceedings of the Fifteenth Stapp Car Crash Conference (SAE Paper No. 710880). Warrendale, Pa.: SAE, 1971. Pp. 767-70. Versace, John. “A Review of the Severity Index.” Proceedings of the Fifteenth Stapp Car Crash Conference (SAE Paper No. 710881). Warrendale, Pa.: SAE, 1971. Pp. 771-96. The first copy of each GAO report and testimony is free. Additional copies are $2 each. Orders should be sent to the following address, accompanied by a check or money order made out to the Superintendent of Documents, when necessary. 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Summary: Pursuant to a congressional request, GAO reviewed the National Highway Traffic Safety Administration's (NHTSA) crash test programs, focusing on whether they provide valid and reliable indicators of occupant safety in real world crashes. GAO found that: (1) the probability of sustaining a serious injury has declined since the inception of NHTSA test programs; (2) cars marketed in the United States have become more crashworthy; (3) the consistency of New Car Assessment Program (NCAP) test results is questionable and its unreliable data may lead to misinformed purchasing decisions; (4) NCAP ability to predict a vehicle occupant's protection in real world crashes is limited, since NCAP results can only be applied to frontal collisions; and (5) there is a statistically significant relationship between fatality rates and NCAP-predicted injuries, however, these high fatality rates are associated with the poorest NCAP performers.