Differences in male and female injury severities in sport-utility vehicle, minivan, pickup and passenger car accidents

This research explores differences in injury severity between male and female drivers in single and two-vehicle accidents involving passenger cars, pickups, sport-utility vehicles (SUVs), and minivans. Separate multivariate multinomial logit models of injury severity are estimated for male and female drivers. The models predict the probability of four injury severity outcomes: no injury (property damage only), possible injury, evident injury, and fatal/disabling injury. The models are conditioned on driver gender and the number and type of vehicles involved in the accident. The conditional structure avoids bias caused by men and women's different reporting rates, choices of vehicle type, and their different rates of participation as drivers, which would affect a joint model of all crashes. We found variables that have opposite effects for the genders, such as striking a barrier or a guardrail, and crashing while starting a vehicle. The results suggest there are important behavioral and physiological differences between male and female drivers that must be explored further and addressed in vehicle and roadway design.     

Using the U.S. National Household Travel Survey to estimate the impact of passenger characteristics on young drivers’ relative risk of fatal crash involvement

Motor vehicle crashes are the main cause of morbidity and mortality in teenagers and young adults in the United States. Driving exposure and passenger presence, which can both vary by driver and passenger characteristics, are known to influence crash risk. Some studies have accounted for driving exposure in calculating young driver fatal crash risk in the presence of passengers, but none have estimated crash risk by driver sex and passenger age and sex. One possible reason for this gap is that data collection on driving exposure often precludes appropriate analyses. The purpose of this study was to examine, per 10 million vehicle trips (VT) and vehicle-miles traveled (VMT), the relative risk of fatal crash involvement in 15-20-year-old male and female drivers as a function of their passenger's age and sex, using solo driving as the referent. The Fatality Analysis Reporting System provided fatal motor vehicle crash data from 1999 to 2003 and the 2001 National Household Travel Survey (NHTS) provided VT and VMT. The NHTS collects driving exposure for both household and non-household members (e.g., friends, colleagues), but demographic characteristics only on household members. Missing age and sex of non-household passengers were imputed with hot deck using information from household passengers’ trips with non-household drivers, thereby enabling the calculation of crash rate and relative risk estimates based upon driver and passenger characteristics. Using this approach, the highest risk was found for young male drivers with 16-20-year-old passengers (relative risk [RR] per 10 million VT = 7.99; 95% confidence interval [CI], 7.34-8.69; RR per 10 million VMT = 9.94; 95% CI, 9.13-10.81). Relative risk was also high for 21-34-year-old passengers, again particularly when both drivers and passengers were male. These effects warrant further investigation and underscore the importance of considering driving exposure by passenger characteristics in understanding crash risk. Additionally, as all imputation techniques are imperfect, a more accurate estimation of U.S. fatal crash risk per distance driven would require national surveys to collect data on non-household passenger characteristics.     

Are SUVs dangerous vehicles?

This study was a population cohort study of all licensed passenger vehicles in New Zealand in the years 2005–2006. The objective of the study was to evaluate the effect on road safety of sports utility vehicles (SUVs) compared to other passenger vehicle types. Statistical models were fitted to the population of 2,996,000 vehicles of which 17,245 were involved in an injury crash. Controlling for distance driven, vehicle and owner characteristics, SUVs were found to be relatively safe vehicles in terms of injury crash involvement and in terms of the injury rate of their own occupants or other road users into which they crashed. Current research on SUV safety clearly shows them to be a road safety concern, but only once a collision occurs. The present study shows that SUVs in New Zealand have relatively few collisions compared to other passenger vehicle types, allowing for factors such as distance driven, some allowance for the type of driving exposure (via the owners’ addresses) and for owner age and gender. Overall, the vehicle type implicated most frequently in injury crashes and involving the highest rate of road injuries was sports cars, causing clearly the most harm per licensed vehicle. Instead of concerning themselves primarily with SUVs, the focus of road safety agencies should be on the relatively high crash risk of sports cars, which are clearly a road safety concern. Their high crash involvement rate and injury rate is likely to be largely due to the way they are driven rather than to inherent characteristics of the vehicles themselves.     

Do laboratory frontal crash test programs predict driver fatality risk? Evidence from within vehicle line variation in test ratings

A number of studies have examined whether the National Highway Traffic Safety Administration's (NHTSA) frontal crash test results reliably indicate the risk of fatality or injury in serious crashes. The conclusions of these studies are mixed. Generally, studies that examine crashes in the circumstances as close as possible to those of the laboratory test find that crash test results do predict real-world risk, but studies of crashes outside those specific circumstances find either no support for the predictive validity of crash test results or limited support with important inconsistencies. We provide a new test of the predictive validity of the crash test results using information from multiple crash tests within vehicle lines, thus controlling for systematic differences in driver behavior across vehicle lines. Among drivers of passenger cars, we find large, statistically significant differences in fatality risk for vehicles with one- to four-star NHTSA ratings versus a five-star rating. We also examine the Insurance Institute for Highway Safety's frontal offset crash test, though our sample of vehicle lines tested twice or more is considerably smaller than for NHTSA ratings. Our results also support the predictive validity of the frontal offset crash test results for passenger cars, but not for trucks.     

The effects of electronic stability control (ESC) on crashes--an update

The present study is an update of the meta-analysis by Erke (Erke, A., 2008. Effects of Electronic Stability Control (ESC) on accidents: a review of empirical evidence. Accident Analysis & Prevention, 40 (1), 167–173). Results from 12 studies of the effects of Electronic Stability Control (ESC) on the number of different types of crashes were summarized by means of meta-analysis. The results indicate that ESC prevents about 40% of all crashes involving loss of control. The greatest reductions were found for rollover crashes (−50%), followed by run-off-road (−40%) and single vehicle crashes (−25%). These results are however likely to be somewhat overestimated, especially for non-fatal crashes. Multiple vehicle crashes were found to be largely unchanged. Reductions were found for some types of multiple vehicle crashes. Rear-end collisions are unchanged or may increase. Fatal crashes involving pedestrians, bicycles or animals were found to increase as well. ESC was found to be more effective in preventing fatal crashes than non-fatal crashes. ESC is often found to be more effective in Sports Utility Vehicles (SUVs) than in passenger cars. This may be due to differences between drivers of SUVs and passenger cars. The results from meta-analysis indicate that drivers of ESC-equipped vehicles are likely to be safer drivers than other drivers. All the same, ESC may lead to behavioural adaptation in some cases, but it is not likely that behavioural adaptation offsets the positive safety effects. This may be due to a lack of knowledge about ESC.     

Trends in older driver crash involvement rates and survivability in the United States: An update

Objective

Previous research has shown that fatal crash involvement rates per licensed driver aged 70 and older declined significantly more per year in the United States than rates for middle-aged drivers aged 35–54 during 1997–2008, and per vehicle mile traveled from 1995–1996 to 2001–2002. Analyses of police-reported crash data during 1997–2005 indicated that the greater declines for older drivers were due to decreases in crash involvement and in the risk of dying in the crashes that occurred. The current study examined if trends in crash rates, crash involvements, and survivability persisted into more recent years.

Methods

Trends for drivers 70 and older were compared with trends for drivers aged 35–54 for U.S. national fatal passenger vehicle crash involvements per 100,000 licensed drivers during 1997–2012 and for U.S. national fatal passenger vehicle crash involvements per vehicle miles traveled in 1995–1996, 2001–2002, and 2008. Using police-reported crash data during 1997–2008 from 20 U.S. states, trends in involvement rates in non-fatal crashes of various severities per 100,000 licensed drivers and changes in the odds of death and the odds of death or serious injury in a crash were compared between older and middle-aged drivers.

Results

During 2007–2012, declines in national fatal crash involvement rates per licensed driver were similar for drivers 70 and older and middle-aged drivers (18 percent each). However, when considering the entire study period, fatal crash involvement rates continued to reflect a substantially larger decline for drivers 70 and older than for middle-aged drivers (42 vs. 30 percent per licensed driver during 1997–2012, 39 vs. 26 percent per vehicle mile traveled from 1995–2006 to 2008). When analyses of police-reported crash data were extended through 2008, non-fatal injury crash involvement rates per licensed driver declined more for older than for middle-aged drivers (39 vs. 30 percent), and unlike in prior research, average annual declines were significantly larger for drivers 80 and older. Property damage-only crash involvement rates similarly declined significantly more for older than for middle-aged drivers (15 vs. 3 percent). Drivers 70 and older in 1997 were 3.5 times more likely than middle-aged drivers to die in a crash, and this ratio declined to 3.2 by 2008.

Conclusions

Although declines in fatal crash involvement rates in recent years have not differed between older and middle-aged drivers, this did not undo earlier gains for older drivers. The recent slowing in the relative magnitude of the decline for older drivers may be related to the differential effect of the U.S. recession on fatal crash involvements of drivers in these age groups. The decreased likelihood of being involved in a crash of any severity and increased survivability when a crash occurred held when examining data through 2008, and for drivers 80 and older, significant declines in crash involvement relative to middle-aged drivers extended to non-fatal injury crashes.     

Safety impacts due to the incompatibility of SUVs, minivans, and pickup trucks in two-vehicle collisions

This research sets out to estimate the effects of vehicle incompatibility on the risk of death or major injury to drivers involved in two-vehicle collisions.Based on data for 2,999,395 drivers, logistic regression was used to model the risk of driver death or major injury (defined has being hospitalized). Our analyses show that pickup trucks, minivans and sport utility vehicles (SUVs) are more aggressive than cars for the driver of the other vehicle and more protective for their own drivers. The effect of the pickups is more pronounced in terms of aggressivity. The point estimates are comparable to those in the Toy and Hammitt study [Toy, E.L., Hammitt, J.K., 2003. Safety impacts of SUVs, minivans, and pickup trucks in two-vehicle crashes. Risk Analysis 23, 641–650], but, in contrast to that study, we are now able to establish that a greater number of these effects are statistically significant with a larger sample size.Like vehicle mass and type, other characteristics of drivers and the circumstances of the collision influence the driver’s condition after impact. Male drivers, older drivers, drivers who are not wearing safety belts, collisions occurring in a higher speed zone and head-on collisions significantly increase the risk of death. Except for the driver’s sex, all of these categories are also associated with an increased risk of death or of being hospitalized after being involved in a two-vehicle collision. For this risk, a significant increase is associated with female drivers.     

Analysis of crash parameters and driver characteristics associated with lower limb injury

This study aims to investigate changes in frequency, risk, and patterns of lower limb injuries due to vehicle and occupant parameters as a function of vehicle model year. From the National Automotive Sampling System-Crashworthiness Data System, 10,988 observations were sampled and analyzed, representing 4.7 million belted drivers involved in frontal crashes for the years 1998–2010.A logistic regression model was developed to understand the association of sustaining knee and below knee lower limb injuries of moderate or greater severity with motor vehicle crash characteristics such as vehicle type and model years, toepan and instrument panel intrusions in addition to the occupant’s age, gender, height and weight. Toepan intrusion greater than 2 cm was significantly associated with an increased likelihood of injury (odds ratio: 9.10, 95% confidence interval 1.82–45.42). Females sustained a higher likelihood of distal lower limb injuries (OR: 6.83, 1.56–29.93) as compared to males. Increased mass of the driver was also found to have a positive association with injury (OR: 1.04, 1.02–1.06), while age and height were not associated with injury likelihood. Relative to passenger cars, vans exhibited a protective effect against sustaining lower limb injury (OR: 0.24, 0.07–0.78), whereas no association was shown for light trucks (OR: 1.31, 0.69–2.49) or SUVs (OR: 0.76, 0.28–2.02).To examine whether current crash testing results are representative of real-world NASS-CDS findings, data from frontal offset crash tests performed by the Insurance Institute for Highway Safety (IIHS) were examined. IIHS data indicated a decreasing trend in vehicle foot well and toepan intrusion, foot accelerations, tibia axial forces and tibia index in relation to increasing vehicle model year between the year 1995 and 2013. Over 90% of vehicles received the highest IIHS rating, with steady improvement from the upper and lower tibia index, tibia axial force and the resultant foot acceleration considering both left and right extremities. Passenger cars received the highest rating followed by SUVs and light trucks, while vans attained the lowest rating.These results demonstrate that while there has been steady improvement in vehicle crash test performance, below-knee lower extremity injuries remain the most common AIS 2+ injury in real-world frontal crashes.     

The frequency--severity indeterminacy

Nothing is known about unreported crashes; the information we have is of reported crashes only. Whether a crash gets reported depends on its severity. It follows by logic that, using only data about reported crashes, it is impossible to say whether a change or difference in crash counts reflects a change or difference in crash frequency or in crash severity. This indeterminacy has practical implications. Examples discussed are of the misattribution of over-representation in reported crashes of older drivers and of trucks to causal factors related to the frequency of crash involvement, and of misinterpretation by researchers of findings about the rollover propensity of SUVs.     

Factors influential in making an injury severity difference to older drivers involved in fixed object-passenger car crashes

To identify factors influencing severity of injury to older drivers in fixed object-passenger car crashes, two sets of sequential binary logistic regression models were developed. The dependent variable in one set of models was driver injury severity, whereas for the other it was the crash severity (most severe injury in the crash). For each set of models, crash or injury severity was varied from the least severity level (no injury) to the highest severity level (fatality) and vice versa. The source of data was police crash reports from the state of Florida. The model with the best fitting and highest predictive capability was used to identify the influence of roadway, environmental, vehicle, and driver related factors on severity. Travel speed, restraint device usage, point of impact, use of alcohol and drugs, personal condition, gender, whether the driver is at fault, urban/rural nature and grade/curve existence at the crash location were identified as the important factors for making an injury severity difference to older drivers involved in single vehicle crashes.     

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.     

Relative risk of death from ejection by crash type and crash mode

In virtually all circumstances, the chance of survival in a crash is much greater if the occupant is not ejected from the vehicle. Several estimates of the increased risk of death as a result of ejection (ranging from 2.5 to 25) have been made, but none were specific to the crash mode and most did not control for crash severity. The current study examined the relative risk of fatality due to ejection, by crash type and crash mode, using the Fatal Accident Reporting System data from the years 1982 through 1986. Crash type was defined as either single vehicle or multivehicle and crash mode included rollover, nonrollover, and/or direction of impact. Crash severity was controlled for using a paired comparison method of analysis. Both crash type and crash mode were found to have substantial effects on the relative risk of death due to ejection. In addition, risk differences across seating position exist. Depending on crash mode or type, the risks ranged from about 1.5 to 8. Single-vehicle rollover crashes have the highest increased risk of death due to ejection: about eightfold for the driver and sevenfold for the right front passenger.     

The influence of driver distraction on the severity of injuries sustained by teenage drivers and their passengers

Studies show that teenage drivers are at a higher risk for crashes. Opportunities to engage in technology and non-technology based distractions appear to be a particular concern among this age group. An ordered logit model was developed to predict the likelihood of a severe injury for these drivers and their passenger using a national crash database (the 2003, U.S. DOT-General Estimate System [GES]). As one would expect, speeding substantially increases the likelihood of severe injuries for teenage drivers and their passengers. The results of the analysis also reveal that teenage drivers have an increased likelihood of more severe injuries if distracted by a cell phone or by passengers than if the source of distraction was related to in-vehicle devices or if the driver was inattentive. Additionally, passengers of teenage drivers are more likely to sustain severe injuries when their driver is distracted by devices or passengers than with a non-distracted or inattentive driver. This supports the previous literature on teenage drivers and extends our understanding of injuries for this age group related to distraction-related crashes.     

An examination of the environmental,driver and vehicle factors associated with the serious and fatal crashes of older rural drivers

Motor vehicle crashes involving rural drivers aged 75 years and over are more than twice as likely to result in a serious or fatal injury as those involving their urban counterparts. The current study examined some of the reasons for this using a database of police-reported crashes (2004–2008) to identify the environmental (lighting, road and weather conditions, road layout, road surface, speed limit), driver (driver error, crash type), and vehicle (vehicle age) factors that are associated with the crashes of older rural drivers. It also determined whether these same factors are associated with an increased likelihood of serious or fatal injury in younger drivers for whom frailty does not contribute to the resulting injury severity. A number of environmental (i.e., undivided, unsealed, curved and inclined roads, and areas with a speed limit of 100 km/h or greater) and driver (i.e., collision with a fixed object and rolling over) factors were more frequent in the crashes of older rural drivers and additionally associated with increased injury severity in younger drivers. Moreover, when these environmental factors were entered into a logistic regression model to predict whether older drivers who were involved in crashes did or did not sustain a serious or fatal injury, it was found that each factor independently increased the likelihood of a serious or fatal injury. Changes, such as the provision of divided and sealed roads, greater protection from fixed roadside objects, and reduced speed limits, appear to be indicated in order to improve the safety of the rural driving environment for drivers of all ages. Additionally, older rural drivers should be encouraged to reduce their exposure to these risky circumstances.     

Relationship of head restraint positioning to driver neck injury in rear-end crashes

Insurance claims were examined for evidence of neck injuries to drivers of passenger cars struck in the rear. Neck injury rates were significantly lower for male drivers, elderly drivers, and drivers in less severe crashes. Even after accounting for differences in driver demographics and crash severity, neck injury rates were significantly lower for drivers of cars with head restraints that were more likely to be behind the heads of motorists.     

Investigating driver injury severity patterns in rollover crashes using support vector machine models

Rollover crash is one of the major types of traffic crashes that induce fatal injuries. It is important to investigate the factors that affect rollover crashes and their influence on driver injury severity outcomes. This study employs support vector machine (SVM) models to investigate driver injury severity patterns in rollover crashes based on two-year crash data gathered in New Mexico. The impacts of various explanatory variables are examined in terms of crash and environmental information, vehicle features, and driver demographics and behavior characteristics. A classification and regression tree (CART) model is utilized to identify significant variables and SVM models with polynomial and Gaussian radius basis function (RBF) kernels are used for model performance evaluation. It is shown that the SVM models produce reasonable prediction performance and the polynomial kernel outperforms the Gaussian RBF kernel. Variable impact analysis reveals that factors including comfortable driving environment conditions, driver alcohol or drug involvement, seatbelt use, number of travel lanes, driver demographic features, maximum vehicle damages in crashes, crash time, and crash location are significantly associated with driver incapacitating injuries and fatalities. These findings provide insights for better understanding rollover crash causes and the impacts of various explanatory factors on driver injury severity patterns.     

Quasi-induced exposure method: Evaluation of not-at-fault assumption

Crash rates are used to establish the relative safety of various variables of concern such as driver classes, vehicle types and roadway components. Appropriate exposure data for estimating crash rates is critical but crash databases do not contain information on driver or vehicle exposure. The quasi-induced exposure method, which uses not-at-fault driver/vehicle data as an exposure metric, is a technique used in order to overcome this problem. The basic assumption made here is that not-at-fault drivers represent the total population in question. This paper examines the validity of this assumption using the Kentucky crash database to define two samples of not-at-fault drivers. One sample included only not-at-fault drivers selected from the first two vehicles in a multi-vehicle crash (two or more vehicles involved) while the other included the not-at-fault drivers from multi-vehicle crashes with more than two vehicles involved and excluding the first two drivers. The assumption is that the randomness of the involvement of drivers in the second sample is more reasonable than the drivers in the first two vehicles involved in crashes. The results indicate that these two samples are similar; there is no statistical evidence demonstrating that both samples represent two different populations in the maneuvers and other variables/factors examined here; and they are representative simple random samples of the driver population with respect to the distribution of the driver age when there is no reasonable doubt about investigating officers’ judgments. Thus, estimating relative crash propensities for any given driver type by using the quasi-induced exposure approach will yield reasonable estimates of exposure.     

Relative risk of spinal cord injury in road crashes involving seriously injured occupants of light passenger vehicles

Road crashes involving occupants of light passenger vehicles are the leading cause of traumatic spinal cord injury (SCI). Confirming the results of an earlier study, this study showed that: in single vehicle car crashes in the country, the odds of SCI were nearly five times higher (4.7) for occupants of non-sedan type light passenger vehicles compared with sedans; in single vehicle rollover crashes in the country, the odds of SCI were nearly three times higher (2.8) in non-sedans compared with sedans; the odds of SCI were nearly five times higher (4.8) for sports utility vehicles (SUVs) compared with sedans. When the data from the earlier study was included in order to increase statistical power, it was found that when compared to sedans that did not roll, occupants of all types of light passenger vehicles had a statistically significant substantially higher likelihood of SCI when involved in rollover (sedans 7.5 times, SUVs 5.9 times and others 8.4 times). In addition, SUVs had a higher likelihood of SCI even when not involved in rollover (5.4 times). Vehicle designers and regulators need to give more attention to the prevention of vehicle rollover and the means to improve occupant protection in the event of rollover. This study should be extended nationally to gain a larger case series so that the SCI risk of particular vehicle configurations, considering other crash factors, can be more precisely quantified and characteristics for low occurrence of SCI identified.     

The effects of vehicle model and driver behavior on risk

We study the dependence of risk on vehicle type and especially on vehicle model. Here, risk is measured by the number of driver fatalities per year per million vehicles registered. We analyze both the risk to the drivers of each vehicle model and the risk the vehicle model imposes on drivers of other vehicles with which it crashes. The "combined risk" associated with each vehicle model is simply the sum of the risk-to-drivers in all kinds of crashes and the risk-to-drivers-of-other-vehicles in two-vehicle crashes. We find that most car models are as safe to their drivers as most sport utility vehicles (SUVs); the increased risk of a rollover in a SUV roughly balances the higher risk for cars that collide with SUVs and pickup trucks. We find that SUVs and to a greater extent pickup trucks, impose much greater risks than cars on drivers of other vehicles; and these risks increase with increasing pickup size. The higher aggressivity of SUVs and pickups makes their combined risk higher than that of almost all cars. Effects of light truck design on their risk are revealed by the analysis of specific models: new unibody (or "crossover") SUVs appear, in preliminary analysis, to have much lower risks than the most popular truck-based SUVs. Much has been made in the past about the high risk of low-mass cars in certain kinds of collisions. We find there are other plausible explanations for this pattern of risk, which suggests that mass may not be fundamental to safety. While not conclusive, this is potentially important because improvement in fuel economy is a major goal for designers of new vehicles. We find that accounting for the most risky drivers, young males and the elderly, does not change our general results. Similarly, we find with California data that the high risk of rural driving and the high level of rural driving by pickups does not increase the risk-to-drivers of pickups relative to that for cars. However, other more subtle differences in drivers and the driving environment by vehicle type may affect our results.     

Modeling rear-end collisions including the role of driver's visibility and light truck vehicles using a nested logit structure

This paper presents an analysis of the effect of the geometric incompatibility of light truck vehicles (LTV)--light-duty trucks, vans, and sport utility vehicles--on drivers' visibility of other passenger cars involved in rear-end collisions. The geometric incompatibility arises from the fact that most LTVs ride higher and are wider than regular passenger cars. The objective of this paper is to explore the effect of the lead vehicle's size on the rear-end crash configuration. Four rear-end crash configurations are defined based on the type of the two involved vehicles (lead and following vehicles). Nested logit models were calibrated to estimate the probabilities of the four rear-end crash configurations as a function of driver's age, gender, vehicle type, vehicle maneuver, light conditions, driver's visibility and speed. Results showed that driver's visibility and inattention in the following (striker) vehicle have the largest effect on being involved in a rear-end collision of configuration CarTrk (a regular passenger car striking an LTV). Possibly, indicating a sight distance problem. A driver of a smaller car following an LTV, have a problem seeing the roadway beyond the LTV, and therefore would not be able to adjust his/her speed accordingly, increasing the probability of a rear-end collision. Also, the probability of a CarTrk rear-end crash increases in the case that the lead vehicle stops suddenly.