Crash Cases Research Articles

Drugs and Alcohol: Their Relative Crash Risk

The purpose of this study was to determine (a) whether among sober (blood alcohol concentration [BAC] = .00%) drivers, being drug positive increases the drivers' risk of being killed in a fatal crash; (b) whether among drinking (BAC > .00%) drivers, being drug positive increases the drivers' risk of being killed in a fatal crash; and (c) whether alcohol and other drugs interact in increasing crash risk. We compared BACs for the 2006, 2007, and 2008 crash cases drawn from the U.S. Fatality Analysis Reporting System (FARS) with control drug and blood alcohol data from participants in the 2007 U.S. National Roadside Survey. Only FARS drivers from states with drug information on 80% or more of the drivers who also participated in the 2007 National Roadside Survey were selected. For both sober and drinking drivers, being positive for a drug was found to increase the risk of being fatally injured. When the drug-positive variable was separated into marijuana and other drugs, only the latter was found to contribute significantly to crash risk. In all cases, the contribution of drugs other than alcohol to crash risk was significantly lower than that produced by alcohol. Although overall, drugs contribute to crash risk regardless of the presence of alcohol, such a contribution is much lower than that by alcohol. The lower contribution of drugs other than alcohol to crash risk relative to that of alcohol suggests caution in focusing too much on drugged driving, potentially diverting scarce resources from curbing drunk driving.

Evaluation of an Autonomous Braking System in Real-World PTW Crashes

Objectives: Powered 2-wheelers (PTWs) are becoming increasingly popular in Europe. They have the ability to get around traffic queues, thus lowering fuel consumption and increasing mobility. The risk of rider injury in a traffic crash is however much higher than that associated with car users. The European project, Powered Two Wheeler Integrated Safety (PISa), identified an autonomous braking system (AB) as a priority to reduce the injury consequences of a PTW crash. The aim of this study was to assess the potential effectiveness of the AB system developed in PISa, taking into account the specific system characteristics that emerged during the design, development and testing phases. Methods: Fifty-eight PTW cases representing European crash configurations were examined, in which 43 percent of riders sustained a Maximum Abbreviated Injury Scale (MAIS) 2+ injury. Two of the most common crash types were a PTW impacting a stationary object (car following scenario) 16% and an object pulling across the PTW path (crossing scenario) 54%. An expert team analysed the in-depth material of the sample crashes and determined a posteriori to what extent the AB would have affected the crash. For those cases where the AB was evaluated as applicable, a further quantitative evaluation of the benefits was conducted by considering a set of different possible rider reactions in addition to that exhibited in the actual crash. Results: In 67 percent of cases, the application of AB could have mitigated the crash outcome. Analysis of those real crash cases showed the potential for an expert rider to avoid the collision. An early reaction of the rider, associated with a correct application of the brakes would have avoided 18 of the 37 car following/crossing scenarios. Conversely, according to the analysis, an expert rider would not have been able to avoid 19 of the 37 cases. In 14 of those 19 cases, the AB would have contributed to mitigating the crash outcome. Conclusions: This study demonstrated significant potential for application of the autonomous braking system in car following and crossing scenarios. In addition, the theoretical benefit curves for the AB globally, were able to provide good quantitative indications of its benefits in real cases where the AB was considered applicable. Further analysis with larger databases is suggested in order to confirm the magnitude of benefits in the PTW crash population. Supplemental materials are available for this article. Go to the publisher's online edition of Traffic Injury Prevention to view the supplemental file.

Car Accident Reconstruction and Head Injury Correlation

Estimation of brain damage remains an elusive issue and controlled tests leading to brain damage cannot be carried out on volunteers. This study reconstructs real-world car accidents to estimate the kinematics of the head impact. This data is to be used to estimate the head injury measures through computer simulations and then correlate reported skull as well as brain damage to impact measures; whence validating the head FE model (Willinger, IJCrash 8:605–617, 2003). In this study, two crash cases were reconstructed. Injury correlation was successful in one of these cases in that the injuries to the brain of one of the car drivers could be correlated in terms of type, location and severity when compared with the tolerance limits of relevant injury parameters (Willinger, IJCrash 8:605–617, 2003).

Graph and heuristic based topology optimization of crash loaded structures

For the efficient development of new structural concepts, it is necessary to perform an optimization of the mechanical properties of profile cross-sections taking into account all relevant load cases. Especially for crash load cases, there currently exists no established method for the conceptual design and topology optimization. The main problems are the complicated deformation conditions in the crash, the huge number of design variables, the existence of simulative and physical bifurcation points and the costly determination of sensitivity information. For the application area of developing profile cross-sections, the method presented in this paper attempts to overcome these shortfalls. It has been developed for the combined topology, shape and sizing optimization taking into account all relevant crash load cases. For this a flexible description of the structure's profile cross-section via mathematical graphs is used. Modifications of the structure's topology are performed with heuristics (rules), which are based on expert knowledge, whereas the automatically generated shape und sizing parameters of the structure are optimized with mathematic optimization algorithms.

Pattern of non-fatal injuries in road traffic crashes in a hilly area: A study from Shimla, North India

Research Question:What are the various injuries in road traffic crash cases?Objectives:To study various non-fatal injuries in road traffic crash cases.Study Design:Hospital based Descriptive study.Study Population:The study population comprised of 401 consecutive cases of non- fatal injuries involved in road traffic crashes and reported at Indira Gandhi Medical College hospital, Shimla.Study Period:1st June 2005 to 31st May 2006.Study Variables:Demographic characteristics of the victims, pattern of injuries and hospital stay of the victims. Types of crashes, time, day and month of crashes, vehicles involved in crashes, use of protective gear etc.Statistical Analysis:Percentages, Proportions.Results:73% of the injured victims were young between 20-49yrs, male to female ratio being 5.3:1. Employees (34.7%) and occupants of transport vehicles (45.9%) constituted the maximum number of the victims. Major injuries (fractures and abd. injuries) were reported in 53.4% of the victims and fractures of lower limb were the commonest of the injuries (26.3%). Use of seat-belt was found to be alarmingly low (14.3%) amongst the four- wheeler users and its non-use was found to be significantly associated with the major injuries. Helmet was used by 36 cases (66.7%) out of total of 54 users of motorized two-wheelers at the time of crash. Human error was the most reported cause of crash (82%) and the most common mode of crash was skidding and/rolling down (55%).23.1% of the drivers were reported to have consumed alcohol at the time of crash.

Application of Stochastic Gradient Boosting Technique to Enhance Reliability of Real-Time Risk Assessment

This study proposes a new and promising machine learning technique to enhance the reliability of real-time risk assessment on freeways. Stochastic gradient boosting (SGB) is used to identify hazardous conditions on the basis of traffic data collected from multiple detection systems such as automatic vehicle identification (AVI), remote traffic microwave sensors (RTMS), real-time weather stations, and roadway geometry. SGB's key strengths lie in its capability to fit complex nonlinear relationships; it handles different types of predictors and accommodates missing values with no need for prior transformation of the predictor variables or elimination of outliers, as with real-time applications. Boosting multiple simple trees together overcomes the poor prediction accuracy of singletree models and provides fast and superior predictive performance. Three models are calibrated: a full model that augments all available data and another two models to compare explicitly the prediction performance of traffic data collected from different sources (AVI and RTMS) at the same location. The results from the preliminary analysis as well as the calibrated models indicate that crash prediction by AVI is comparable to that by RTMS data. Moreover, the full model achieves superior classification accuracy by identifying about 89% of crash cases in the validation data set with only a 6.5% false positive rate. Because of its superior classification performance and its minimal required data preparation, SGB is recommended as a promising technique for real-time risk assessment.

Fatal drowning as a result of an airplane crash—Case report

An ULM (Ultra Light Motorized) plane Aeroprakt 22-L with two men on board dived unexpectedly into the Dworackie lake near the town of Olecko in Warmia and Mazury district, Northeastern Poland. The pilot and the passenger had multiorgan blunt injuries, including subdural and subarachnoid hemorrhage, fractured ribs, fractured thigh (in one of the deceased) and pulmonary contusions as a result of the impact with the lake. The multiorgan injuries and unconsciousness resulting from head trauma prevented the casualties from saving themselves. The underlying cause of the death was the crash into the lake, however drowning was assessed as the proximate cause of death. The accident was analyzed together with an account prepared by State Commission on Aircraft Accident Investigation and with the Human Factor Analysis and Classification System – HFACS (the standardized method of analysis of flight accidents, the tool originally developed and tested within the U.S. military).

Glass Intact Assures Safe Cervical Spine Protocol

BackgroundSelective cervical spine immobilization performed by Emergency Medical Services (EMS) is being utilized with increasing frequency. These protocols, although very sensitive, still include subjective data such as “mild cervical discomfort.” The aim of this study is to create an objective clinical decision rule that would enhance the selective approach for cervical spine immobilization in patients aged 16–60 years. Study ObjectiveIt is hypothesized that, in a motor vehicle crash, the integrity of the involved vehicle’s glass window and airbag status is an excellent objective measure for the amount of energy a vehicle occupant has experienced during the crash. GLass intact Assures Safe Spine (GLASS) is an easy and objective method for evaluation of the need for prehospital cervical spine immobilization. MethodsA retrospective cohort study was performed with sample motor vehicle crash cases to evaluate the performance of the GLASS rule. The National Accident Sampling System-Crashworthiness Data System (NASS-CDS) was utilized to investigate tow-away motor vehicle crashes, including their glass damage characteristics and occupant injury outcomes, over an 11-year period (1998–2008). Sample occupant cases selected for this study were patients aged 16–60 years, who were belt-restrained front seat occupants involved in a crash with no airbag deployment, and no glass damage before the crash. ResultsA total of 14,191 occupants involved in motor vehicle crashes were evaluated in this analysis. The results showed that the sensitivity of the GLASS rule was 95.20% (95% confidence interval [CI] 91.45–98.95%), the specificity was 54.27% (95% CI 53.44–55.09%), and the negative predictive value was 99.92% (95% CI 99.86–99.98%). ConclusionThe GLASS rule presents the possibility of a novel, more objective tool for cervical spine clearance. Prospective evaluation is required to further evaluate the validity of this clinical decision rule.

Global sensitivity analysis for the efficient solution of optimization problem in design process

AbstractApplication of the methods of global sensitivity analysis in design process arises due to the complexity associated with structural optimization, e. g., in the automobile industry for an optimal vehicle structure for crash load cases. Usually, thousands of variants are considered for a vehicle design project and each variant represents a combination of a number of model parameters. The computation time for a single variant ranges from several hours to days. To reduce the complexity of the optimization problem, the significant parameters should be identified but possibly with a very few sample points. Since most of the available global sensitivity methods require a good approximation of the model response, a relatively large number of sample points is usually required for the surrogate model. In this contribution, an overview of state‐of‐the‐art methods of global sensitivity analysis is given and an alternative idea is proposed to avoid full approximation of the model response. Instead, only the approximation of the level sets of the model response is used to derive sensitivity measures. (© 2012 Wiley‐VCH Verlag GmbH & Co. KGaA, Weinheim)

Suicide by Motor Vehicle “Accident” in Queensland

Objective: Around the world, a substantial proportion of motor vehicle crash deaths are recognized as “hidden” suicides. This project sought to progress understandings of drivers who used a motor vehicle to die by suicide in Queensland, Australia, during the period 1990 to 2007. Methods: Data for this study were derived from the Queensland Suicide Register and forensic crash investigation case records. Analysis focused on life circumstances and events preceding the death, physical and mental illnesses, past suicidality, and indication of suicide intent (e.g., suicide notes or statements). Results: Compared to cases using other methods, confirmed driver suicides were more likely to be males aged between 25 and 44 years who were employed at the time of death. A large proportion of driver suicides had consumed alcohol immediately prior to the crash and experienced a number of life events, including relationship conflict, legal or criminal issues, and financial problems. Conclusion: These exploratory results indicate the need to educate crash investigators about the characteristics of those who use a motor vehicle to die. Improving the information available on the mental and physical health and background life-related factors of crash victims can help coroners and researchers determine whether these deaths were intentional. Further investigation is needed in order to formulate intervention strategies for those who may be vulnerable to driver suicide.

A two-stage mining framework to explore key risk conditions on one-vehicle crash severity

This paper proposes a two-stage mining framework to explore the key risk conditions that may have contributed to the one-vehicle crash severity in Taiwan's freeways. In the first stage, a genetic mining rule (GMR) model is developed, using a novel stepwise rule-mining algorithm, to identify the potential risk conditions that best elucidate the one-vehicle crash severity. In the second stage, a mixed logit model is estimated, using the antecedent part of the mined-rules as explanatory variables, to test the significance of the risk conditions. A total of 5563 one-vehicle crash cases (226 fatalities, 1593 injuries and 3744 property losses) occurred in Taiwan's freeways over 2003–2007 are analyzed. The GMR model has mined 29 rules for use. By incorporating these 29 mined-rules into a mixed logit model, we further identify one key safe condition and four key risk conditions leading to serious crashes (i.e., fatalities and injuries). Each key risk condition is discussed and compared with its adjacent rules. Based on the findings, some countermeasures to rectify the freeway's serious one-vehicle crashes are proposed.

Alcohol-related risk of driver fatalities: an update using 2007 data.

The purpose of this study was to determine whether the relative risk of being involved in an alcohol-related crash has changed over the decade from 1996 to 2007, a period during which there has been little evidence of a reduction in the percentage of all fatal crashes involving alcohol. We compared blood-alcohol information for the 2006 and 2007 crash cases (N = 6,863, 22.8% of them women) drawn from the U.S. Fatality Analysis Reporting System (FARS) with control blood-alcohol data from participants in the 2007 U.S. National Roadside Survey (N = 6,823). Risk estimates were computed and compared with those previously obtained from the 1996 FARS and roadside survey data. Although the adult relative risk of being involved in a fatal alcohol-related crash apparently did not change from 1996 to 2007, the risk for involvement in an alcohol-related crash for underage women has increased to the point where it has become the same as that for underage men. Further, the risk that sober underage men will become involved in a fatal crash has doubled over the 1996-2007 period. Compared with estimates obtained from a decade earlier, young women in this study are at an increased risk of involvement in alcohol-related crashes. Similarly, underage sober drivers in this study are more at risk of involvement in a crash than they were a decade earlier.

Impact reconstruction from damage to pedal and motorcycle helmets

Pedal and motorcycle helmets offer a high level of protection to the wearer’s head. There is a need to review and assess the performance offered by helmets, so that helmet design and test standards can be optimized. One input into this process is crash reconstruction. Helmeted crash cases can be collected and examined, leading to insights into impact severity, helmet performance and injury outcomes. However, it is unclear to what extent residual helmet damage reflects the impact characteristics. This paper addresses this issue using controlled laboratory impact tests. Two pedal cycle and three motorcycle helmet models were tested with an ‘M’ size headform in impact energy attenuation tests from 1 m, 2 m and 2.5 m. Headform acceleration, impact force and post-impact deformation were measured. The dynamic deformations were measured with three methods: video, kinetic energy and an analytical approach using impact force and liner yield stress. All five models offered highly repeatable performance in terms of impact energy attenuation and acceleration management in radial impacts across the impact severities. The results showed that the Standards Australia certified helmets provided impact protection to the head in impacts that greatly exceeded the impact energy attenuation performance requirements of those standards. The residual and dynamic deformation measurements were correlated with drop height and headform acceleration for pedal cycle helmets. The results indicate that the residual deformation observed in a pedal cycle helmet collected from a crash can be used to estimate the impact severity and, after undertaking exemplar impact tests on the same model helmet, the head impact acceleration. However, the residual deformation measured on the three motorcycle helmets was not correlated with the drop height, which indicated that, within the limits of this study, estimating crash severity from motorcycle helmet damage is not reliable.

Integration of a crashworthy battery in a fully electric city bus

This paper focuses on a novel concept for a fully electric city bus and the crashworthy integration of a changeable battery system. The changeable battery had to be located in an accessible and safe position. By careful analysis, an acceptable battery location was found under the floor of the vehicle. Due to the absence of design drawings of the real bus, an existing finite element model of a full size van was taken as a substitute. This model has less weight than the actual bus. Therefore, the battery was downsized based on range calculations. All parts of the vehicle concerning the combustion engine were removed and the battery was implemented in the model. This vehicle model was tested virtually using different crash load cases to demonstrate the feasibility of a crashworthy integration. Additional testing was carried out to evaluate the stability of the real bus lithium-ion cells under crash conditions.

Methodology for estimating the dependence between force and deplacement: A vehicle crash case

Accident reconstruction software analyzed impact of vehicles considers usage of coefficient of restitution as a known quantity. In practice it is common that numerical value of coefficient of restitution is determined on basis of experience. Presence of error in its evaluation causes an essential error in output results. Thus, it is of exceptional importance to determine more precisely its numerical value. Improved solution of vehicle accident reconstruction software is presented in this paper. To archive that, in this paper was developed methodology which provides such analysis of impact process in which the coefficient of restitution becomes the result, and not input data. We have suggested new methodology for mathematical modeling of function dependence between force and displacement in a collision of vehicles. The compression process was approximated with piecewise linear function. The restitution process was approximated with linear curves. During process of restitution stiffness depends on maximum value of displacements during process of compression. The quality of the coherence between experimental data and mathematical function is quantified by residual sum of squares. Numerical examples are performed by usage of the obtained methodology.

An improved critical constraint method for structural optimization of product families

This paper discusses important improvements in the efficient Critical Constraint Method (CCM) for the optimization of structural product families subjected to multiple crash load cases. The method was first presented by Oman and Nilsson (Struct Multidisc Optim 41(5):797---815, 2010). However, the algorithm often converged towards an infeasible solution, which considerably limited the applicability of the method. Therefore, improvements are presented here to make the method more robust regarding feasible solutions, resulting in only a minor decrease in efficiency compared to the original method. The improvements include; a penalty approach to control the feasibility of the method by continuously pushing the solution out of the infeasible region, a dynamic contraction algorithm to increase the accuracy and robustness of the method by considering the optimization progress and variable history in the reduction of the step size, and the implementation of a parallel approach to further increase the efficiency of the method by enabling the full potential of large-scale computer clusters. Finally, the potential of the improved CCM algorithm is demonstrated on a large-scale industrial family optimization problem and it is concluded that the high efficiency of the method enables the usage of large product family optimization in the design process.

Computational methodology to predict injury risk for motor vehicle crash victims: A framework for improving Advanced Automatic Crash Notification systems

Advanced Automatic Crash Notification (AACN) systems, capable of predicting post-crash injury severity and subsequent automatic transfer of injury assessment data to emergency medical services, may significantly improve the timeliness, appropriateness, and efficacy of care provided. The estimation of injury severity based on statistical field data, as incorporated in current AACN systems, lack specificity and accuracy to identify the risk of life-threatening conditions. To enhance the existing AACN framework, the goal of the current study was to develop a computational methodology to predict risk of injury in specific body regions based on specific characteristics of the crash, occupant and vehicle. The computational technique involved multibody models of the vehicle and the occupant to simulate the case-specific occupant dynamics and subsequently predict the injury risk using established physical metrics. To demonstrate the computational-based injury prediction methodology, three frontal crash cases involving adult drivers in passenger cars were extracted from the US National Automotive Sampling System Crashworthiness Data System. The representative vehicle model, anthropometrically scaled model of the occupant and kinematic information related to the crash cases, selected at different severities, were used for the blinded verification of injury risk estimations in five different body regions. When compared to existing statistical algorithms, the current computational methodology is a significant improvement toward post-crash injury prediction specifically tailored to individual attributes of the crash. Variations in the initial posture of the driver, analyzed as a pre-crash variable, were shown to have a significant effect on the injury risk.

Validity of using linked hospital and police traffic crash records to analyse motorcycle injury crash characteristics

Linking hospital discharge and police traffic crash records has been used to provide information on causes and outcomes for hospitalised traffic crash cases. Motorcyclists are particularly vulnerable to injury in a traffic crash, but no published linkage studies have reported in detail on this road user group. The present study examined motorcycle traffic crash injury cases in New Zealand in 2000–2004 by probabilistically linking national hospital discharge records with police traffic crash reports. Injury cases had to have spent at least one night in hospital before being discharged and were defined as serious or moderate based on their International Classification of Disease Injury Severity Scores (ICISS). Despite a robust linkage process, only 46% of cases could be linked to a police record; 60% of the serious injuries and 41% of the moderate. The low linkage was most likely due to under-reporting of crashes to or by the police. While moderate injury cases were expected to be under-reported, the level of under-reporting of cases with serious threat-to-life injuries is concerning. To assess whether the linked dataset could provide valid information on the crash circumstances and injury outcomes of hospitalised motorcycle crash cases, the characteristics of the linked and unlinked hospital discharge cases were compared using chi-square tests and multivariate logistic regression. Serious injury cases were less likely to be linked if only one vehicle was involved, or the injured riders and passengers were younger than 20 years or spent less than one week in hospital. For moderate injury cases, there were also differences in linkage by injured body region and crash month. While these discrepancies need to taken into consideration when interpreting results, the linked hospital-police dataset has the potential to provide insights into motorcycle crash circumstances and outcomes not otherwise obtainable.

A classification tree based modeling approach for segment related crashes on multilane highways

Introduction This study presents a classification tree based alternative to crash frequency analysis for analyzing crashes on mid-block segments of multilane arterials. Method The traditional approach of modeling counts of crashes that occur over a period of time works well for intersection crashes where each intersection itself provides a well-defined unit over which to aggregate the crash data. However, in the case of mid-block segments the crash frequency based approach requires segmentation of the arterial corridor into segments of arbitrary lengths. In this study we have used random samples of time, day of week, and location (i.e., milepost) combinations and compared them with the sample of crashes from the same arterial corridor. For crash and non-crash cases, geometric design/roadside and traffic characteristics were derived based on their milepost locations. The variables used in the analysis are non-event specific and therefore more relevant for roadway safety feature improvement programs. First classification tree model is a model comparing all crashes with the non-crash data and then four groups of crashes (rear-end, lane-change related, pedestrian, and single-vehicle/off-road crashes) are separately compared to the non-crash cases. The classification tree models provide a list of significant variables as well as a measure to classify crash from non-crash cases. ADT along with time of day/day of week are significantly related to all crash types with different groups of crashes being more likely to occur at different times. Conclusions From the classification performance of different models it was apparent that using non-event specific information may not be suitable for single vehicle/off-road crashes. Impact on Industry The study provides the safety analysis community an additional tool to assess safety without having to aggregate the corridor crash data over arbitrary segment lengths.

The Additive Effects of Alcohol and Benzodiazepines on Driving

To examine the relationship between the combination of alcohol and benzodiazepines and the risk of committing an unsafe driver action. We used data from the Fatality Analysis Reporting System (1993-2006) on drivers aged 20 or older who were tested for both alcohol and drugs. Using a case-control design, we compared drivers who had at least one unsafe driver action (UDA; e.g., weaving) recorded in relation to the crash (cases) to drivers who did not (controls). Drivers who tested positive for intermediate- and long-acting benzodiazepines in combination with alcohol had significantly greater odds of a UDA compared to those under the influence of alcohol alone, up to blood alcohol concentrations (BACs) of 0.08 and 0.05 g/100 ml, respectively. The odds of a UDA with short-acting benzodiazepines combined with alcohol were no different than for alcohol alone. This study demonstrates that the combination of alcohol and benzodiazepines can have detrimental effects on driving beyond those of alcohol alone. By describing these combined effects in terms of BAC equivalencies, this study also allows for the extrapolation of simple, concrete concepts that communicate risk to the average benzodiazepine user.