Pedestrian fatality risk as a function of car impact speed

Knowledge of the amount of violence tolerated by the human body is essential when developing and implementing pedestrian safety strategies. When estimating the potential benefits of new countermeasures, the pedestrian fatality risk as a function of impact speed is of particular importance. Although this function has been analysed previously, we state that a proper understanding does not exist. Based on the largest in-depth, pedestrian accident study undertaken to date, we derive an improved risk function for adult pedestrians hit by the front of passenger cars. Our results show far lower fatality risks than generally reported in the traffic safety literature. This discrepancy is primarily explained by sample bias towards severe injury accidents in earlier studies. Nevertheless, a strong dependence on impact speed is found, with the fatality risk at 50 km/h being more than twice as high as the risk at 40 km/h and more than five times higher than the risk at 30 km/h. Our findings should have important implications for the development of pedestrian accident countermeasures worldwide. In particular, the scope of future pedestrian safety policies and research should be broadened to include accidents with impact speeds exceeding 50 km/h.     

Literature review of pedestrian fatality risk as a function of car impact speed

The aim of this review was to evaluate all studies of pedestrian fatality risk as a function of car impact speed. Relevant papers were primarily investigated with respect to data sampling procedures and methods for statistical analysis. It was uniformly reported that fatality risk increased monotonically with car impact speed. However, the absolute risk estimates varied considerably. Without exceptions, papers written before 2000 were based on direct analyses of data that had a large bias towards severe and fatal injuries. The consequence was to overestimate the fatality risks. We also found more recent research based on less biased data or adjusted for bias. While still showing a steep increase of risk with impact speed, these later papers provided substantially lower risk estimates than had been previously reported.     

Double pair comparison--a new method to determine how occupant characteristics affect fatality risk in traffic crashes

A new method to determine how occupant characteristics affect fatality risk in traffic crashes is developed. The method, which uses data from the Fatal Accident Reporting System (FARS), focuses on two occupants, a "subject" occupant and an "other" occupant. The probabilities of a fatality to the subject occupant when that occupant has one of two characteristics are compared. The other occupant serves essentially a normalizing, or exposure estimating, role. The method uses only fatality frequency data--no external exposure information is required, and it is relatively free from uncertain assumptions. It has wide applicability; examples of potential applications include investigating car occupant fatality risk as a function of sex, age, alcohol use or motorcyclist fatality risk as a function of helmet use. The first application is to determining the effectiveness of safety belts in preventing car occupant fatalities, as described in the paper following this paper.     

Estimating transport fatality risk from past accident data

This paper examines the statistical properties of estimates of fatal accident rates, mean fatalities per accident, and fatality rates when these estimates are based on past accident data. The statistical properties are illustrated by two long-term transport fatal accident datasets from Great Britain, the principal one for railways and the other for roads, chosen to provide a statistical contrast. In both modes, the accident rates have fallen substantially over the long term. Two statistical estimates of current accident and fatality rates are presented for each dataset, one based only on recent data and the other based on estimates of long-term trends. The trend-based estimate is preferred for train accidents because this makes maximum use of the limited and variable data; the recent data are preferred for road accidents because this avoids unnecessary dependence on modelling the trends. For train accidents, the estimated fatality rate based on past accidents is compared with an estimate produced by the railway industry using a risk model. The statistical estimate is less than half the industry's estimate, and the paper concludes that the statistical estimate is to be preferred.     

Relative fatality risk in different seating positions versus car model year

Fatality risk of drivers compared to right-front passengers is examined vs. car model year (MY) using Fatal Accident Reporting System (FARS) data for 1975 through 1986. Confounding effects are removed by comparing unrestrained occupants matched in sex and age (to within three years). MY ≥ 1968 cars, which complied with Federal Motor Vehicle Standard 203 (impact protection for the driver) and FMVSS 204 (rearward column displacement), are compared to MY ≤ 1966 cars, which did not comply with these standards. It is found that, compared to right-front passengers in the same cars, drivers had higher relative fatality risks in MY ≥ 1968 cars and lower relative fatality risks in MY ≤ 1966 cars. Because there are so few fatal frontal crash data for MY 1966 and MY 1968 cars, definitive conclusions regarding the effectiveness of FMVSS 203 and 204 in reducing driver fatalities are not possible. However, our analysis, together with the assumption that right-front-passenger fatality risk was the same in 1966 and 1968 MY cars, does suggest that a previous 12% effectiveness estimate is more likely to be high than low.     

Crossing county lines: the impact of crash location and driver's residence on motor vehicle crash fatality

INTRODUCTION: Studies have demonstrated that the fatality risk for motor vehicle crashes (MVCs) is higher in rural than urban areas. The purpose of this study was to quantify the risk of a fatal outcome associated with a crash by the urban/rural classification of the driver's county of residence and the county of crash before and after adjusting for potentially confounding factors. METHODS: County of crash and driver's county of residence were classified as urban or rural for 514,648 Utah crash participants. Multivariate regression analysis was used to assess the impact of rural versus urban crash location on fatality outcomes for both urban and rural drivers. RESULTS: Before adjusting for confounding factors the relative risk of fatality in a rural versus urban crash was 9.7 (95% CI: 8.0-11.7) for urban drivers and their passengers compared to 1.8 (95% CI: 1.3-2.6) for rural residents. Adjustment for behavioral, road, and crash characteristics reduced risk estimates to 2.8 (95% CI: 2.2-3.5) and 1.2 (95% CI: 0.8-1.7), respectively. CONCLUSION: Urban and rural drivers may have distinct risk factors for MVC fatality in rural areas. Interventions to reduce the risk of fatality in rural areas should evaluate the needs of both urban and rural drivers.     

Injury risk curves for the skeletal knee-thigh-hip complex for knee-impact loading

Injury risk curves for the skeletal knee-thigh-hip (KTH) relate peak force applied to the anterior aspect of the flexed knee, the primary source of KTH injury in frontal motor-vehicle crashes, to the probability of skeletal KTH injury. Previous KTH injury risk curves have been developed from analyses of peak knee-impact force data from studies where knees of whole cadavers were impacted. However, these risk curves either neglect the effects of occupant gender, stature, and mass on KTH fracture force, or account for them using scaling factors derived from dimensional analysis without empirical support. A large amount of experimental data on the knee-impact forces associated with KTH fracture are now available, making it possible to estimate the effects of subject characteristics on skeletal KTH injury risk by statistically analyzing empirical data.Eleven studies were identified in the biomechanical literature in which the flexed knees of whole cadavers were impacted. From these, peak knee-impact force data and the associated subject characteristics were reanalyzed using survival analysis with a lognormal distribution. Results of this analysis indicate that the relationship between peak knee-impact force and the probability of KTH fracture is a function of age, total body mass, and whether the surface that loads the knee is rigid. Comparisons between injury risk curves for the midsize adult male and small adult female crash test dummies defined in previous studies and new risk curves for these sizes of occupants developed in this study suggest that previous injury risk curves generally overestimate the likelihood of KTH fracture at a given peak knee-impact force. Future work should focus on defining the relationships between impact force at the human knee and peak axial compressive forces measured by load cells in the crash test dummy KTH complex so that these new risk curves can be used with ATDs.     

Using speeding detections and numbers of fatalities to estimate relative risk of a fatality for motorcyclists and car drivers

Precise estimation of the relative risk of motorcyclists being involved in a fatal accident compared to car drivers is difficult. Simple estimates based on the proportions of licenced drivers or riders that are killed in a fatal accident are biased as they do not take into account the exposure to risk. However, exposure is difficult to quantify. Here we adapt the ideas behind the well known induced exposure methods and use available summary data on speeding detections and fatalities for motorcycle riders and car drivers to estimate the relative risk of a fatality for motorcyclists compared to car drivers under mild assumptions. The method is applied to data on motorcycle riders and car drivers in Victoria, Australia in 2010 and a small simulation study is conducted.     

Estimating the effects of crash phase injury countermeasures—II : The fatality trend and its modification by countermeasures

The trend of automobile occupant fatalities from 1950 to 1968 was studied. The influence of such factors as vehicle age, improved doorlocks, small cars, speed, seat belt use, driver age, and the Interstate Highway System was estimated on the basis of past studies. The relation of 20 other factors to this trend was explored by regression analyses. No satisfactory representation of the trend could be achieved without including either new automobile registration data or the Index of Industrial Production in the independent variables. A hypothesis explaining this was proposed. The number of automobiles, by model year groups corresponding to the availability of crash phase countermeasures, involved in potentially fatal accidents, was projected to 1968. Applying the reduction in fatality risk to these figures, fatality trends with countermeasures are projected to 1980 and compared with a projection assuming no countermeasures.     

The estimated effect of mass or footprint reduction in recent light-duty vehicles on U.S. societal fatality risk per vehicle mile traveled

The National Highway Traffic Safety Administration (NHTSA) recently updated its 2003 and 2010 logistic regression analyses of the effect of a reduction in light-duty vehicle mass on US societal fatality risk per vehicle mile traveled (VMT; Kahane, 2012). Societal fatality risk includes the risk to both the occupants of the case vehicle as well as any crash partner or pedestrians. The current analysis is the most thorough investigation of this issue to date. This paper replicates the Kahane analysis and extends it by testing the sensitivity of his results to changes in the definition of risk, and the data and control variables used in the regression models. An assessment by Lawrence Berkeley National Laboratory (LBNL) indicates that the estimated effect of mass reduction on risk is smaller than in Kahane's previous studies, and is statistically non-significant for all but the lightest cars (Wenzel, 2012a). The estimated effects of a reduction in mass or footprint (i.e. wheelbase times track width) are small relative to other vehicle, driver, and crash variables used in the regression models. The recent historical correlation between mass and footprint is not so large to prohibit including both variables in the same regression model; excluding footprint from the model, i.e. allowing footprint to decrease with mass, increases the estimated detrimental effect of mass reduction on risk in cars and crossover utility vehicles (CUVs)/minivans, but has virtually no effect on light trucks. Analysis by footprint deciles indicates that risk does not consistently increase with reduced mass for vehicles of similar footprint. Finally, the estimated effects of mass and footprint reduction are sensitive to the measure of exposure used (fatalities per induced exposure crash, rather than per VMT), as well as other changes in the data or control variables used. It appears that the safety penalty from lower mass can be mitigated with careful vehicle design, and that manufacturers can reduce mass as a strategy to increase their vehicles’ fuel economy and reduce greenhouse gas emissions without necessarily compromising societal safety.     

The effect of recent trends in vehicle design on U.S. societal fatality risk per vehicle mile traveled,and their projected future relationship with vehicle mass

The National Highway Traffic Safety Administration (NHTSA) recently updated its 2003 and 2010 logistic regression analyses of the effect of a reduction in light-duty vehicle mass on US fatality risk per vehicle mile traveled (VMT). The current NHTSA analysis is the most thorough investigation of this issue to date. LBNL's assessment of the analysis indicates that the estimated effect of mass reduction on risk is smaller than in the previous studies, and statistically non-significant for all but the lightest cars.     

Latent risk and trend models for the evolution of annual fatality numbers in 30 European countries

In this paper a unified methodology is presented for the modelling of the evolution of road safety in 30 European countries. For each country, annual data of the best available exposure indicator and of the number of fatalities were simultaneously analysed with the bivariate latent risk time series model. This model is based on the assumption that the amount of exposure and the number of fatalities are intrinsically related. It captures the dynamic evolution in the fatalities as the product of the dynamic evolution in two latent trends: the trend in the fatality risk and the trend in the exposure to that risk. Before applying the latent risk model to the different countries it was first investigated and tested whether the exposure indicator at hand and the fatalities in each country were in fact related at all. If they were, the latent risk model was applied to that country; if not, a univariate local linear trend model was applied to the fatalities series only, unless the latent risk time series model was found to yield better forecasts than the univariate local linear trend model. In either case, the temporal structure of the unobserved components of the optimal model was established, and structural breaks in the trends related to external events were identified and captured by adding intervention variables to the appropriate components of the model. As a final step, for each country the optimally modelled developments were projected into the future, thus yielding forecasts for the number of fatalities up to and including 2020.     

Narrative text analysis of Kentucky tractor fatality reports

Narrative information in fatality investigation reports contains data elements not routinely analyzed with coded occupational injury surveillance data. A narrative text analysis of 69 Kentucky Fatality Assessment and Control Evaluation (FACE) agricultural tractor fatality reports from 1994 to 2004 was performed. The FACE reports were developed using the National Institute for Occupational Safety and Health, Division of Safety Research-recommended FACE report format that incorporates Haddon's matrix. Haddon's matrix separates the fatal incident into three event phases and is used to develop points of intervention based on human, organizational, and environmental factors. A multivariate logistic regression analysis for association between identified exposure variables and the outcomes of interest was undertaken. The operation of a tractor with an attached bucket, muddy terrain, and being thrown from the tractor were independent risk factors for being declared "dead at the scene". A tractor rollover and operation of a tractor on a slope were independent risk factors for being "crushed" by a tractor. Narrative text analysis of FACE fatality investigation reports is a valuable tool for the identification of additional factors contributing to tractor fatalities that can inform farm safety training, identify new areas for agricultural interventions, and support the development of new agricultural engineering strategies.     

Simple models of fatality trends revisited seven years later.

The author's original paper presented simple linear models of fatalities based on data through 1982 and appeared in this journal in 1984. The earlier paper reported good fits through 22 years of fatality counts using population and employment data, after adjusting for the short-term effect of the oil shortage (in 1974) and the long-term effect of the 55 mph speed limit (beginning in 1974). Attempts (reported here) to refit the model through seven additional years were less successful. It may be that the relationships originally reported have changed, that important new factors have been introduced, or that the original fits were partly luck. The recent emphasis on behavioral solutions to safety problems (including programs to decrease alcohol use and increase safety belt use) is one important change, so the effect of the benefits of these programs on the model fits is explored. The original model began to overpredict fatalities just as safety benefits were beginning to accrue from increased safety belt use and decreased driver-alcohol involvement, and both the model overprediction and the benefits of these programs increased over the seven years of data added to the original model. Thus, previous government estimates of the number of lives saved by these behavioral programs are supported by the observed change in the statistical relationship between fatality counts and economic factors.     

Firearms in US homes as a risk factor for unintentional gunshot fatality

This study used national data and a matched case-control design to estimate the relative risk of death by an unintentional gunshot associated with having firearms in the home. A sample of adults who died in the United States in 1993 from unintentional gunshot injuries was drawn from the National Mortality Followback Survey (NMFS) (n=84). Twenty controls were sought for each case from the 1994 National Health Interview Survey (NHIS) and matched to the cases by sex, age group, race, and region of residence (n=1451). Subjects were classified as having or not having guns in the home based interview responses. The relative risk of death by an unintentional gunshot injury, comparing subjects living in homes with and without guns, was 3.7 (95% confidence interval (CI)=1.9-7.2). Adjustment for covariates resulted in little change in the effect estimates. There was evidence of a dose-response effect: compared to subjects living in homes with no guns, the relative risk was 3.4 (95% CI=1.5-7.6) among subjects with one gun and 3.9 (95% CI=2.0-7.8) among subjects with multiple guns in the home. Having handguns in the home was associated with the largest effect estimates. Tests of homogeneity showed that the effect estimates did not vary significantly across categories of the matching variables. Firearms in the home appear to be a risk factor for unintentional gunshot fatality among adults. The magnitude of the observed effect estimates should be compared with those from additional studies.     

Traffic accident statistics and risk perceptions in Japan and the United States

Several recent studies have concluded that Japan and the US have different risk cultures. This study examines the actual risk environments faced by citizens in the two countries, in the domain of traffic safety, as a possible source of differences in risk perceptions. The study contrasts traffic-accident risks from several points of view (e.g. car drivers, motorcyclists, bicyclists and pedestrians) and risk statistics (e.g. death rates, relative fatality risks, and accident lethality). Results clarify the traffic risks in the two countries and confirm their potential for explaining cross-national differences in risk perceptions.     

Fatality risk in motorcycle collisions with roadside objects in the United States

Motorcycle crashes with roadside objects often involve more than one impact event: typically involving a collision with the ground and another object. The objective of this study was to determine the fatality risk in these roadside object collisions when compared with crashes only involving a collision with the ground. The roadside objects analyzed included guardrails, concrete barriers, signs, utility poles, and trees. The Fatality Analysis Reporting System (FARS) database was used in conjunction with the General Estimates System (GES) to analyze fatality risk for motorcycle crashes from 2004 to 2008. The analysis was based upon over 3600 fatal motorcycle crashes with roadside objects. Collisions with roadside objects were found to have a higher fatality risk than collisions with either the ground or another motor vehicle. Based on the most harmful event reported in the crash, motorcycle collisions with guardrail were 7 times more likely to be fatal than collisions with the ground, and collisions with trees were almost 15 times more likely to be fatal than collisions with the ground. Additionally, the roadside object was reported as the most harmful event in the majority of the crashes in fatal two-event crashes involving a roadside object and a collision with the ground, with the exception of collisions with signage. From these analyses it was concluded that collisions with fixed objects are more harmful to motorcyclists than collisions with the ground.     

Car occupant safety in frontal crashes: a parameter study of vehicle mass, impact speed, and inherent vehicle protection

A new mathematical model was developed to estimate average injury and fatality rates in frontal car-to-car crashes for changes in vehicle fleet mass, impact speed distribution, and inherent vehicle protection. The estimates were calculated from injury/fatality risk data, delta-V distribution and collision probability of two vehicles, where delta-V depends on impact speed and mass of the colliding vehicles. The impact speed distribution was assumed to be unaffected by a change in fleet mass distribution.

The results showed that safety in frontal crashes would improve 27–35% by a 10% increase in fatality risk parameters, which reflected substantial improvement in inherent vehicle protection. A 40% safety improvement was attained by a 10% impact speed reduction. Consequences of vehicle fleet mass were not as strong, but depended on the average mass ratio of the fleet. A reduction in mass range would be the most beneficial, while a uniform mass reduction of 20% would increase the fatality rate by 5.4%. The model estimates trends in traffic safety and may help to identify priorities in active and passive safety.     

The fatality and injury risk of light truck impacts with pedestrians in the United States

In the United States, passenger vehicles are shifting from a fleet populated primarily by cars to a fleet dominated by light trucks and vans (LTVs). Because light trucks are heavier, stiffer, and geometrically more blunt than passenger cars, they pose a dramatically different type of threat to pedestrians. This paper investigates the effect of striking vehicle type on pedestrian fatalities and injuries. The analysis incorporates three major sources of data, the Fatality Analysis Reporting System (FARS), the General Estimates System (GES), and the Pedestrian Crash Data Study (PCDS). The paper presents and compares pedestrian impact risk factors for sport utility vehicles, pickup trucks, vans, and cars as developed from analyses of US accident statistics. Pedestrians are found to have a two to three times greater likelihood of dying when struck by an LTV than when struck by a car. Examination of pedestrian injury distributions reveals that, given an impact speed, the probability of serious head and thoracic injury is substantially greater when the striking vehicle is an LTV rather than a car.     

Limits for survivability in frontal collisions: theory and real-life data combined

The limits for survivability in vehicle frontal collisions are unknown. This paper proposes a new hypothesis that occupant risk in frontal collisions is due to both inertial and crushing injuries and that the limits of survivability in frontal collisions are principally due to the complete crushing of vehicles at high DeltaV's. Analysis of the NASS data for the period 1982-1991 for AIS3+ injury and fatality to belted and unbelted drivers shows that the real world distributions of risk with DeltaV are asymptotic to 1.0 over similar DeltaV ranges and over a lower speed range than that predicted from intrusion/complete car crush alone. This is consistent with the proposed hypothesis as human biomechanical loading also influences survivability. While the hypothesis is supported by the presently available limited high-speed collision data, further in-depth investigations should be undertaken to confirm the ultimate limits of survivability.