Two-vehicle Crashes Research Articles

Issues with using police citations to assign responsibility in quasi-induced exposure

Crash fault determination is one of the most critical issues in applications of quasi-induced exposure. Traditionally, the driver citation issued by the investigating police officer is the primary source to assign responsibility for motor vehicle crashes. Such citations are based on the “evidence” or observation of a moving violation (such as engaged hazardous actions) in combination with non-moving violations (such as suspended driver license) prior to the crash. The objective here is to identify the contributing factors that may lead to driver citations in two-vehicle crashes in addition to the hazardous action. Multivariate binary logistic regression modeling is employed to explore the behavior of the investigating police officer in terms of issuing citation at the crash scene. A series of explanatory parameters including roadway characteristics, environmental factors, and driver and vehicle attributes is assessed. The results show that whether the crash type was a hit-and-run, alcohol and illegal drug use, driver gender, driver age, and injury severity all appear to have significant impacts on the investigating officer’s decision-making. Specific examples are given to demonstrate how two factors hit-and-run and drinking status can skew the exposure estimates in the context of quasi-induced exposure. The findings will help to serve as a basis to select appropriate parameters in assigning crash responsibility in quasi-induced exposure applications; and we make recommendations to modify existing crash database for better safety research in the future.

Motor Vehicle Crashes Associated with Alcohol: Child Passenger Injury and Restraint Use

The role of alcohol in fatal motor vehicle crashes involving children has been well established. However, the nonfatal injury burden of alcohol on child passengers has not been comprehensively assessed. This study sought to determine injury burden and restraint use in child passengers aged 1-15 years in alcohol-related motor vehicle crashes. A retrospective cohort study including all people involved in all crashes with an injury or at least $1000 property damage occurring in Wisconsin in 2007 and involving at least one child passenger aged 1-15 years. A total of 22,464 child passengers were involved in motor vehicle crashes in Wisconsin in 2007; 2.5% (n=570) were in alcohol-related crashes. Child passengers in alcohol-related crashes experienced twice the risk of injury compared to non-alcohol-related crashes (risk ratio [RR]=2.42, 95% CI=2.08, 2.80). Two-vehicle crashes that were alcohol-related were more than two times more likely to result in child injury than those that were not (RR=2.78, 95% CI=2.30, 3.35). In alcohol-related crashes, the risk of injury in children was higher if they were passengers in the alcohol-related vehicle compared to the non-alcohol-related vehicle (RR=1.35, 95% CI=1.01, 1.79). Inappropriate restraint of child passengers was higher in alcohol-related vehicles (34.5% vs 17.1%, p<0.00005), particularly in the group aged 4-7 years (70.8% vs 44.9% inappropriately restrained). Motor vehicle crashes resulting from alcohol-related driving significantly increased child passenger injury and were associated with inappropriate child passenger restraint. Several evidence-based policies are recommended to address this public health problem.

A review of the validity of the underlying assumptions of quasi-induced exposure

In recent years, the quasi-induced exposure technique has been widely implemented in a variety of traffic safety-related settings. One of the primary concerns associated with the applications of quasi-induced exposure is that the underlying assumptions are not explicitly verified or validated before the exposure measurement is adopted. Of principal interest is the assumption that the non-responsible driver/vehicles in two-vehicle crashes are representative of the general driving population on the road at the time of crash occurrence. The objective here is to provide an alternative to test the not-at-fault assumptions with the use of three-or-more-vehicle crashes, which are readily available in many crash databases. With the use of Michigan and Maine crash data as examples, the examination of the validity is developed at two levels: (1) at all locations where crashes took place; (2) at locations where three-or-more-vehicle crashes are prone to occur. Non-responsible drivers are disaggregated by three basic driver–vehicle characteristics (age, gender, and vehicle type) and compared at these two levels for statistical and operational (practical) differences. Examination of the results demonstrates that all of the examined non-responsible driver distributions are consistently similar from both operational and statistical points of view. Compared to other approaches to validation, such as using “exposure truth” (e.g., actual vehicle miles traveled or a trip diary), the proposed validation is much more simplistic, straightforward, and cost-effective.

The Role of Driver Age and Gender in Motor Vehicle Fatal Crashes

This study compares the age and gender of at-fault drivers who were involved in fatal crashes and the corresponding driving errors that contributed to these crashes. This comparison provides insights that may help traffic engineers devise countermeasures to lessen the number of these unnecessary deaths. Data from the Fatality Analysis Reporting System (FARS) for the years 2001 through 2003 were used in this study. The analysis included passenger vehicles (automobiles, utility vehicles, minivans, and pickup trucks) involved in either single- or two-vehicle crashes. The driver responsible in each crash was identified through the driver error variable codes as listed in the FARS databases. Younger drivers (16 through 19 years of age) and the elderly (those 75 and older) were responsible for a disproportionate amount of fatality-related crashes. When combined these two groups accounted for only 6.4% of the total miles driven in 2001, but they were responsible for 83.1% of the fatal crashes attributed to driver-related errors. Driver operating error was listed as the contributing factor in 73% of fatal motor vehicle crashes when the driver was male and 83% of the crashes when the driver was female. The youngest drivers tended to be carrying the highest number of passengers when they were involved in fatal crashes. Failing to stay in the proper lane and driving too fast for road conditions were the two most frequent driver operating errors contributing to fatal crashes for male and female drivers.

Copula-Based Method for Addressing Endogeneity in Models of Severity of Traffic Crash Injuries: Application to Two-Vehicle Crashes

An emerging copula-based methodology is used to address endogeneity in models of crash injury severity. Specifically, two important sources of endogeneity are addressed: (a) endogeneity due to correlations between the injury severity of the two drivers involved in two-vehicle crashes and (b) endogeneity of collision type and injury severity outcomes. Two sets of copula-based joint model systems are formulated and estimated by using data on two-vehicle crashes from the 2007 Generalized Estimates System: a copula-based joint ordered logit–ordered logit model of injury severities of the two drivers involved in two-vehicle crashes and a copula-based joint multinomial logit–ordered logit model of collision type and injury severity outcomes of two-vehicle crashes. The model estimation results and elasticity estimates underscore the importance of accommodating endogeneity in models of crash injury severity. The results shed new light on the determinants of injury severity in two-vehicle accidents.

Variation in crash severity depending on different vehicle types and objects as collision partner

The objective in this study of crashed cars fitted with on-board crash pulse recorders (CPR) was to present differences in average crash severity and distribution of crash severity, depending on collision partner. The investigation included both frontal and rear-end two-vehicle and single-vehicle crashes, into deformable and rigid roadside objects. In total, 544 real-world crashes involving cars fitted with CPRs were included. A difference in average crash severity was found in crashes with different collision partners. Frontal two-vehicle and single-vehicle crashes with rigid roadside objects were shown to generate the highest crash severity. In 22% of crashes with heavy goods vehicles (HGVs) and 2% of car-to-car crashes, change of velocity exceeded 45 km/h. These differences indicate the importance of focusing on compatibility. There was a statistically significant difference between frontal two-vehicle and single-vehicle crashes with deformable objects, and also between single-vehicle crashes with deformable objects and single-vehicle crashes with rigid roadside objects. Of these, the least harmful crash type was single-vehicle crashes into deformable objects. This study provides further insight into how collision partners or objects influence change of velocity and mean acceleration in the studied vehicles. Furthermore, it illustrates the importance of paying attention to compatibility issues, regarding aspects influencing both change of velocity and acceleration.

Evaluation of Safety Ratings of Roads Based on Frontal Crashes with Known Crash Pulse and Injury Outcome

Objective: The objective in this study, using data from crashed cars fitted with on-board crash pulse recorders, was to present differences in average crash severity, distribution of crash severity, and injury outcomes, based on an independent safety rating of roads, also taking road type and speed limit into consideration. Furthermore, the objective was to evaluate differences in injury risk, based on the distribution of crash severity. Methods: The investigation included both frontal two-vehicle crashes and single-vehicle crashes with known injury outcome. In total, 209 real-world crashes involving cars fitted with crash pulse recorders were included. For all crashes, average mean acceleration and change of velocity of the vehicle acceleration pulse were measured and calculated. All crash spots were classified according to an independent road safety rating program (European Road Assessment Programme Road Protection Score), where the safety quality of roads is rated in relation to posted speed limits. The crash severity and injury outcome in crashes that occurred on roads with good safety ratings were compared with crashes on roads with poor safety ratings. The data were also divided into subcategories according to posted speed limit and road type, to evaluate whether there was a difference in crash severity and injury outcome within the categories. Results and Conclusions: In total, crash severity was statistically significantly lower in crashes occurring on roads with good safety ratings than in crashes occurring on roads with poor safety ratings. It was found that crash severity and injury risk were lower on roads with good safety ratings with a speed limit of above 90 km/h compared with roads with poor safety ratings, irrespective of speed limit. On the other hand, crash severity was higher on roads with good safety ratings with speed limit of 70 km/h than on roads with poor safety ratings with the same speed limit. Though it was found that a higher speed limit resulted in higher crash severity on roads with poor safety ratings, the opposite was found on roads with good safety ratings. The main reason for this was that lanes for traffic traveling in opposite directions were more often separated at higher speeds on roads with good safety ratings. On divided roads with good safety ratings, there were no crashes resulting in crash severity above the level corresponding to a 10 percent risk of sustaining serious or fatal injury. This indicates that one of the most important safety measures is divided roads.

A self-organizing feature maps and data mining based decision support system for liability authentications of traffic crashes

This study develops a decision support tool for liability authentications of two-vehicle crashes based on generated self-organizing feature maps (SOM) and data mining (DM) models. Factors critical to liability attributions commonly identified theoretically and practically were first selected. Both SOM and DM models were then generated for frontal, side, and rear collisions of two-vehicle crashes. Appropriateness of all generated models was evaluated and confirmed. Finally, a decision support tool was developed using active server pages. Although with small data size, the decision support system was considered capable of giving reasonably good liability attributions and references on given cases.

Effects of Street Patterns on Injury Risks in Two-Vehicle Crashes

Road crashes not only claim lives and inflict injuries but also create an economic burden on society because of lost productivity. Many studies have identified factors affecting the frequency and severity of crashes. However, few, if any, studies have explored the effect of street pattern on injury risks in urban crashes. In this study, street pattern or urban form is classified into four categories: gridiron, warped parallel, loops and lollipops, and mixed patterns. Their effects on injury risk are examined together with other factors including road features, drivers’ characteristics, crash characteristics, environmental conditions, and vehicle attributes. Calgary, Alberta, Canada, is chosen as the case study, and the logistic regression model is applied with reported crash data from 2003 to 2005 to investigate various factors. The results suggest that current popular patterns, including the loops and lollipops design, are safer than the conventional gridiron pattern from an injury risk perspective in the event of a crash.

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.

Accident severity analysis using ordered probit model

AbstractTo reduce injuries in road crashes, better understanding is needed between the relationship of injury severity and risk factors. This study seeks to identify the contributing factors affecting crash severity with broad considerations of driver characteristics, roadway features, vehicle types, pedestrian characteristics and crash characteristics using an ordered probit model. It also explores how the interaction of these factors will affect accident severity risk. Three types of accidents were investigated: two‐vehicle crashes, single vehicle crashes and pedestrian accidents. The reported crash data in Singapore from 1992 to 2001 were used to illustrate the process of parameter estimation. Several factors such as vehicle type, road type, collision type, location type, pedestrian age, time of day of accident occurrence were found to be significantly associated with injury severity. It was also found that injury severity decreases over time for the three types of accident investigated.

Limits of the quasi-induced exposure method when compared with the standard case–control design: Application to the estimation of risks associated with driving under the influence of cannabis or alcohol

The disparities between the quasi-induced exposure (QIE) method and a standard case–control approach with crash responsibility as disease of interest are studied. The 10,748 drivers who had been given compulsory cannabis and alcohol tests subsequent to involvement in a fatal crash in France between 2001 and 2003 were used to compare the two approaches. Odds ratios were assessed using conditional and unconditional logistic regressions. While both approaches found that drivers under the influence of alcohol or cannabis increased the risk of causing a fatal crash, the two approaches are not equivalent. They differ mainly with regards to the driver sample selected. The QIE method results in splitting the overall road safety issue into two sub-studies: a matched case–control study dealing with two-vehicle crashes and a case–control study dealing with single-vehicle crashes but with a specific control group. Using a specific generic term such as “QIE method” should not hide the real underlying epidemiological design. On the contrary, the standard case–control approach studies drivers involved in all type of crashes whatever the distribution of the responsibility in each crash. This method also known as “responsibility analysis” is the most relevant for assessing the overall road safety implications of a driver characteristic.

Changes in Driver Fatality Rates and Vehicle Incompatibility Concurrent with Changes in the Passenger Vehicle Fleet

With more sport utility vehicles (SUVs) on the road, public concern has been expressed about their influence on traffic safety. The present study examined changes in the mix of passenger vehicles between 1988 and 2004 and concurrent changes in driver fatality rates and vehicle incompatibility. Vehicle registrations and driver deaths per registered vehicle were examined using data from R.L. Polk and Company and the Fatality Analysis Reporting System. Between 1988 and 2004, SUVs comprised an increasingly larger proportion of registered passenger vehicles (5% of one- to three-year-old vehicles in 1988 vs. 22% in 2004), yet driver deaths per registered vehicle decreased 43% to 47% for all passenger vehicle types. Reductions in driver fatality rates were greater for two-vehicle crashes than for single-vehicle crashes and greater for two-vehicle frontal crashes than for two-vehicle side-impact crashes. Driver death rates declined more on rural roads than on urban roads, and this difference was most pronounced for SUVs. Among cars struck by other vehicles, driver death rates in front-to-front and front-to-side impacts decreased more when the striking vehicle was an SUV than a pickup or car. Factors likely contributing to the overall reductions in fatality rates include advances in occupant protection, increases in average vehicle weight, increased availability of SUVs with car-based designs, and reductions in alcohol-impaired driving. Reductions of driver death rates in two-vehicle collisions between 1988 and 2004 are encouraging, but SUVs and pickups continue to pose a substantially higher risk to drivers of cars than when the striking vehicle is another car.

Development of severity models for vehicle accident injuries for signalized intersections in rural areas

The objective of this paper is to establish a statistical relationship correlating crash severity with weather, traffic maneuve rs, and specific roadway geometrics at four-legged signalized intersections in rural areas. In this paper, the probability of the levels of injury severity is examined by applying ordered probit regression models for all crash types, single-vehicle crashes, two-vehicle cras hes, and three or more-vehicle crashes. The study results suggest that in terms of crash severity for all crash records, more vehicl e presence of protected left lane, wider median widths, and higher traffic flows, and more driveways are associated with less injury severity of intersections. By the number of vehicles involved in crashes, the variable shows variations in the models and magni tudes of the estimates.

Relationships of Frontal Offset Crash Test Results to Real-World Driver Fatality Rates

In a study of the relationship between Insurance Institute for Highway Safety frontal offset crash test ratings and real-world fatality rates, there was a clear trend for better-rated vehicles to have lower driver fatality risk, although the correlation was not uniform across all vehicle groups or statistically significant in all cases. For all types of crashes combined, fatality rates per registered vehicle were generally lower for vehicles rated good than for vehicles rated poor, but rates for acceptable and marginal vehicles were not always within this range. A more precise examination of fatality risk was accomplished by comparing driver outcomes in fatal two-vehicle crashes. When a rated vehicle collided with a nonrated vehicle, the fatality risk for the rated vehicle driver was highest for poorly rated vehicles, then progressively smaller for vehicles with marginal, acceptable, or good ratings. For two-vehicle crashes of similar vehicles rated good and poor, the odds of driver fatality was 34 percent lower for the good vehicle than for the poor vehicle, but this estimate was not statistically significant. Finally, in head-on crashes of rated vehicles, the estimated odds of driver fatality was approximately 74 percent lower for the good vehicle than for the poor vehicle, with confidence limits ranging from 28 to 91 percent.

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.

THE RISK OF INJURY AND VEHICLE DAMAGE SEVERITY IN VEHICLE MISMATCHED SIDE IMPACT CRASHES IN BRITISH COLUMBIA

As occupant protection offered by new passenger vehicles has improved, there has been growing concern about the harm that some vehicle designs may inflict on occupants of other vehicles with which they collide. Preceding analyses of crash statistics have clearly demonstrated the incompatibility between passenger sedan cars (PS) and pick-up trucks (PU) involved in side impact crashes in British Columbia. A comparison of light truck and passenger car crashes in previous literature reveals that light truck vehicles inflict greater harm than passenger cars for a number of reasons including their greater weight, stiffer structure, and higher ride height. These features place occupants of passenger cars at a disadvantage should they be involved in a collision with a light truck vehicle. The injury risk for passenger sedan car occupants is greater than the risk for pick-up truck occupants in two-vehicle crashes (Odds Ratio (OR) 1.87; 95% Confidence Interval (CI) 1.38-2.52). In addition, the risk of vehicle damage severity was increased for passenger cars compared with pick-up trucks (write off vehicle-OR 5.35; 95% CI 3.75-7.63, severely damaged vehicles-OR 5.87; 95% CI 4.79–7.19, moderately damaged vehicles-OR 2.86; 95% CI 2.44–3.36). There is strong justification for injury prevention experts and policy makers to step up motor vehicle crash injury prevention advocacy by implementing evidence-based policies to reduce rates of injury as a result of passenger sedan cars and pick-up trucks involved in side impact crashes in the province of British Columbia.

Toward a Better Benchmark: Assessing the Utility of Not-at-Fault Traffic Crash Data in Racial Profiling Research

As studies on racial profiling and biased policing have begun to proliferate, researchers are debating which benchmark is most appropriate for comparison with police traffic stop data. Existing benchmark populations, which include populations estimated from census figures, licensed drivers, arrestees, reported crime suspects, and observed drivers and traffic violators, all have significant limitations. This article offers a new, alternative benchmark for police traffic stops, a benchmark that has not been previously applied or tested in a racial profiling research setting. The analysis presented compares traffic observation data, gathered at selected, high volume intersections during an ongoing racial profiling study in Miami-Dade County, Florida, to not-at-fault driver demographic data from two-vehicle crashes at those same intersections. Findings indicate that non-responsible drivers in two-vehicle crashes appear to represent a reasonably accurate estimate of the racial composition of drivers on the roadways at selected intersections and within areas of varying racial composition. The implications of this finding for racial profiling research are discussed, and suggested areas for future inquiry are identified.

Responsibility of drivers, by age and gender, for motor-vehicle crash deaths

Problem: Motor-vehicle crash rate comparisons by age and gender usually are based on the extent to which drivers in a particular age/gender category are themselves injured or involved in crashes (e.g., the number of 20-year-old females in crashes). Basing comparisons instead on the extent to which drivers in various age/gender groups are responsible for deaths (including themselves) in their crashes is more revealing of their overall contribution to the problem. Methods: Data from the Fatality Analysis Reporting System (FARS, 1996–2000) were used in the analysis, which was based on crashes that involved one or two vehicles only. Drivers in fatal single-vehicle crashes were assumed to have responsibility for the crash. In fatal two-vehicle crashes, driver operator errors reported by police were used to assign crash responsibility. Results: When all crashes were considered, both the youngest and oldest drivers were most likely to be responsible for deaths in their crashes. In two-vehicle crashes, the oldest drivers were more likely than young drivers to be responsible. Young males were more likely than young females to be responsible for crash deaths, whereas females in their 50s and older were more likely than same-age males to be responsible. In terms of responsibility for deaths per licensed driver, young drivers, especially males, had the highest rates because of their high involvement rates and high responsibility rates. The majority of deaths for which young drivers were responsible occurred to people other than themselves, especially passengers in their vehicles, whereas the bulk of the deaths for which older drivers were responsible were their own. Discussion: The results highlight the contribution of young drivers to the motor-vehicle crash problem, the need for measures such as passenger restrictions in graduated licensing systems, and the need for vehicle modifications to better protect older occupants.

Driver injury severity: an application of ordered probit models

This paper describes the use of ordered probit models to examine the risk of different injury levels sustained under all crash types, two-vehicle crashes, and single-vehicle crashes. The results suggest that pickups and sport utility vehicles are less safe than passenger cars under single-vehicle crash conditions. In two-vehicle crashes, however, these vehicle types are associated with less severe injuries for their drivers and more severe injuries for occupants of their collision partners. Other conclusions also are presented; for example, the results indicate that males and younger drivers in newer vehicles at lower speeds sustain less severe injuries.