National Automotive Sampling System Crashworthiness Research Articles

Sex-based differences in odds of motor vehicle crash injury outcomes

ObjectiveSeveral studies have documented the relative risk or odds of injury and fatality for females versus males in motor vehicle crashes (Parenteau et al. 2013, Forman et al. 2019, Brumbelow and Jermakian, 2022; Noh et al. 2022). Though, none combined National Automotive Sampling System–Crashworthiness Data System (NASS-CDS) and Crash Investigation Sampling System (CISS). The aim of this study was to document the relative odds of various injury outcomes for females versus males while considering a broad range of crash types, pre-crash and crash variables, and occupant characteristics. MethodsMultivariable logistic regression was carried out to study the odds of injury for females versus males. A select imputation method (Hot Deck, Approximate Bayesian Bootstrap) was applied as part of efforts to create multivariable logistic regression models for 25 different injury outcomes associated with occupants (age 13 years and older) involved in passenger vehicle crashes published in NASS-CDS (2000 to 2015) and CISS (2017–2021). Both pre-crash (n=7) and crashworthiness (n=22) predictor variables were considered, but only significant variables at p≤0.10 level were retained in final models. Six crash-type models were produced for each injury outcome; one that included all crashes, one for each of four different planar crash types (frontal, near-side, far-side, rear), and one for crashes involving rollover. These six sets of crash-type models were expanded further to include a model version that included both pre-crash/environment and crashworthiness predictor variables and one model limited to crashworthiness predictors only. Different than other recent studies, all crash types, occupant restraint conditions, and seating positions were considered. Occupant sex was retained in all models to facilitate female versus male injury outcome odds ratio (OR) assessments. ResultsFemale versus male injury OR estimates for 300 unique models are presented. Females had significantly higher odds of injury than males in 36 models (OR>1.0, p-value ≤0.05). This contrasts with 43 models where females had significantly lower odds (OR<1.0, p≤0.05). For the remaining 221 models, there was a near even split in how often the odds of injury were non-significantly higher (n=103) and non-significantly lower (n=114) for females as compared to males (p>0.05). In four cases, the OR estimate was 1.00. Amongst the results, there was a trend for females to have higher odds of AIS 2+ injuries (MAIS 2+ OR=1.75 and 1.69 for Full and Crashworthiness models, respectively for the All Crashes dataset). These increases included higher estimates for lower extremity injuries in frontal crashes, consistent with earlier studies (e.g., Forman et al. 2019). However, for certain AIS 2+ (neck, thorax) and AIS 3+ injuries (head, neck, thorax), females had significantly lower odds of injury (p≤0.05). The trends for reduced odds of injury for females were most prevalent in non-frontal crash models.

Exploring the temporal variability of the factors affecting driver injury severity by body region employing a hybrid econometric approach

The current study contributes to safety literature by incorporating the influence of temporal factors (observed and unobserved) within a multivariate model system for medical professional generated body region specific injury severity score. For this purpose, we adopt a hybrid econometric modeling approach that accommodates for the unobserved factors using two mechanisms. First, we parameterize unobserved temporal factor variation through the customization of the variance by time cohort (heteroscedasticity). Second, the common unobserved factors affecting severity across various body regions is accommodated through traditional random parameter consideration process. The proposed model system is estimated using data drawn from the National Automotive Sampling System-Crashworthiness Data System (NASS-CDS) database for the time cohorts 2003, 2006, 2009, 2012, and 2015. For the current analysis, we consider 6-point Abbreviated Injury Scale (AIS) for eight body regions (head, face, neck, abdomen, thorax, spine, lower extremity, and upper extremity). The proposed model system offers interesting insights on body region severity evolution over time. The model estimation is augmented with post-estimation exercises including hold-out sample validation analysis, illustrative policy analysis and extensive elasticity effect computation.

Comparison of Vehicle-Based Crash Severity Metrics for Predicting Occupant Injury in Real-World Oblique Crashes

The flail space model (FSM) is currently used in U.S. roadside hardware crash testing as a means of assessing occupant injury risk using observed vehicle kinematics data. European roadside hardware crash tests use an FSM variant along with a variant of the acceleration severity index (ASI). Although the FSM and ASI are currently used in roadside hardware testing, other vehicle-based crash severity metrics exist. Previous research has focused on examining the ability of these metrics to predict injury in frontal crashes. Despite the Manual for Assessing Safety Hardware prescribing a significant number of oblique crash tests, there has been little research on how well these metrics predict real-world oblique crash injury. This study compared the ability of six different vehicle-based metrics to predict occupant injury in oblique crashes: maximum delta-v, occupant impact velocity, ridedown acceleration, ASI, occupant load criterion, and vehicle pulse index. The crash severity metrics were calculated from real-world crash pulse data recorded by event data recorders. Oblique crashes from the National Automotive Sampling System Crashworthiness Data System were used to train logistic regression models that predict moderate to fatal injuries. The models were then compared on a dataset of oblique crashes from the Crash Investigation Sampling System. The results of this study confirmed that vehicle-based metrics provide a reasonable means of predicting real-world occupant injury risk in oblique crashes and suggest little difference between the investigated metrics. In addition to the vehicle-based metrics, belt use and vehicle damage location were found to influence injury risk.

Identifying Pedal Misapplication Behavior Using Event Data Recorders

&lt;div class="section abstract"&gt;&lt;div class="htmlview paragraph"&gt;Pedal misapplication (PM) crashes, i.e., crashes caused by a driver pressing one pedal while intending to press another pedal, have historically been identified by searching unstructured crash narratives for keywords and verified via labor-intensive manual inspection. This study proposes an alternative method to identify PM crashes using event data recorders (EDRs). Since drivers in emergency braking situations are motivated to hit the brake hard, it follows that drivers in emergency braking situations that commit a PM would likewise hit the accelerator hard, likely harder than accelerator pedal application during normal driving. Thus, the time-series accelerator pedal position and the derived accelerator pedal application rate were used to isolate accelerator misapplications. Additional strategic filters were applied based on characteristics observed from previous PM analyses to reduce false positive PM identifications. These include a crash type filter, since PM crashes have been shown to manifest as majority road departure, end departure, rear-end, and forward impact crash types. After analyzing pre-crash EDR data from the National Automotive Sampling System Crashworthiness Data System (NASS/CDS) case years 1997 to 2015, evidence of PM was observed in 4.3% of weighted events. This result was substantially higher than the previously estimated 0.2% PM frequency [&lt;span class="xref"&gt;1&lt;/span&gt;,&lt;span class="xref"&gt;2&lt;/span&gt;]. The time-to-collision (TTC) at the point of PM was calculated for each case, and over 50% of cases had a TTC of less than 2.0 seconds. Over one-third of these drivers engaged the accelerator to 99% of pedal stroke or above and over one-eighth of drivers engaged both the brake and the accelerator pedals simultaneously during the recorded pre-crash period.&lt;/div&gt;&lt;/div&gt;

Real-Time Regression Analysis of Streaming Clustered Data With Possible Abnormal Data Batches

This article develops an incremental learning algorithm based on quadratic inference function (QIF) to analyze streaming datasets with correlated outcomes such as longitudinal data and clustered data. We propose a renewable QIF (RenewQIF) method within a paradigm of renewable estimation and incremental inference, in which parameter estimates are recursively renewed with current data and summary statistics of historical data, but with no use of any historical subject-level raw data. We compare our renewable estimation method with both offline QIF and offline generalized estimating equations (GEE) approach that process the entire cumulative subject-level data all together, and show theoretically and numerically that our renewable procedure enjoys statistical and computational efficiency. We also propose an approach to diagnose the homogeneity assumption of regression coefficients via a sequential goodness-of-fit test as a screening procedure on occurrences of abnormal data batches. We implement the proposed methodology by expanding existing Spark’s Lambda architecture for the operation of statistical inference and data quality diagnosis. We illustrate the proposed methodology by extensive simulation studies and an analysis of streaming car crash datasets from the National Automotive Sampling System-Crashworthiness Data System (NASS CDS). Supplementary materials for this article are available online.

Parallelized optimization design of bumper systems under multiple low-speed impact loads

Majority of existing design optimization of bumper systems has focused on one single impact loading case in literature, which may not offer proper performance under other loading cases. This study aims to address this issue by developing a multiobjective optimization approach, in which multiple impact loading scenarios are considered to optimize the intrusion and energy absorption of the bumper system. Modeling of real-life impact scenarios is first validated by comparing the numerical results with the experimental data. Based upon the Latin hypercube design (LHD) and Kriging surrogate approaches, energy absorption (EA) and maximum intrusion (MI) are formulated in terms of design variables to consider the structural crashworthiness and repair/maintenance cost, respectively. In order to generate Pareto solution in the multiobjective optimization effectively, the recently developed Kriging Believer based parallelized efficient global optimization (EGO) algorithm is adopted to optimize the bumper system subject to three impact loads, namely the low-speed sled crash, dynamic three-point bending and 40% offset impact, respectively. These different load cases are considered through a weighted average scheme. The optimization results indicate that the Pareto solutions largely depend on the assignment of weight factors to different load cases. In order to generate more reasonable results, the National Automotive Sampling System-Crashworthiness Data System (NASS-CDS) database is also used to determine the weighting factors for each loading case. It is found that for the intrusion objective, the design under the multiple impact loads offers an intrusion reduction of 20.27% in the sled crash, 5.84% in the 40% offset impact, in comparison with the baseline design. The intrusion of three-point bending is the same as that of baseline design to compromise other more frequently occurring load cases. For the energy absorption objective, although the design leads to increase in EA by 3.01% in the sled crash and 1.79% in 40%-offset impact, the performance in the three-point bending is actually sacrificed to compromise the other more frequently occurring load cases. The study help gain insights into the design optimization of a bumper system for real-life automotive engineering.

Injury risk curves in far-side lateral motor vehicle crashes by AIS level, body region and injury code

Objective The objective of this study was to develop injury risk curves as a function of change in vehicle velocity for occupants in far-side lateral motor vehicle crashes (MVCs) by AIS level, body region, and specific AIS codes that commonly occur in this crash mode. Methods The National Automotive Sampling System-Crashworthiness Data System (NASS-CDS) years 2000–2015 database was queried, resulting in 4,495 non-weighted far-side crashes. For each case, occupant age, sex, and the following metadata were collected: vehicle model year, vehicle body type, lateral delta-v, normalized PDOF, multiple impacts, belt use, seat position, object contacted, striking vehicle body type, maximum crush extent and side airbag deployment. Multivariable logistic regression was used to develop risk curves for AIS 2+ through 5+ injuries, AIS 2+ injuries by body region (head, thorax, lower extremity), and for each of the 10 most frequent far-side AIS 2+ injuries. Significant covariates were determined by backwards elimination (p < 0.05). The full dataset and a subsampled dataset of only cases with side airbag deployment were used to develop risk curves. Results For AIS 2+ through 5+ injury, greater delta-V was associated with greater injury risk (OR’s: 2.48–3.66 per 11.9 kph increase) and belt use was associated with lower risk (OR’s: 0.04–0.36 compared to unbelted). Multiple impacts were significant predictors of increased AIS 3+, 4+ and 5+ injury risk (OR’s: 2.56, 2.27 and 2.83 compared to single impact). For AIS 2+ body region injuries, lateral delta-V and maximum CDC extent were positively associated with increased head, thorax and lower extremity injury risk while belt use was associated with lower risk. Increased lateral delta-v, unbelted status, and greater maximum CDC extent frequently increased injury risk for the most common far-side injuries. Side airbag deployment was not a significant covariate for the injury risk models. Conclusions The resulting risk models expand upon previous literature gaps to provide a more comprehensive view of contributors to injury risk for occupants in far-side MVCs. This study yields risk curves based on the latest available NASS-CDS data.

An examination of the performance of damaged energy-absorbing end terminals

ObjectivesGuardrail end terminals are designed to gradually decelerate vehicles during impact and protect vehicle occupants from severe injuries. It has been observed that some in-service end terminals are damaged, and it is unclear if their safety performance is still acceptable. The objectives of this study were to examine the conditions of in-service end terminals, and to evaluate the performance of damaged relative to undamaged end terminals in simulated impacts. MethodsCommon damage patterns of guardrail end terminals were investigated by using post-crash pictures collected from the National Automotive Sampling System-Crashworthiness Data System (NASS-CDS). Conditions of in-service end terminals mounted along roads in portions of six U.S. states were examined by using a sample from the second Strategic Highway Research Program-Roadway Information Database (SHRP2-RID). Finite Element (FE) models of two minorly and three severely damaged ET-Plus systems, a commonly used energy-absorbing guardrail end terminal along U.S. roads, were developed. To evaluate the performance of the damaged ET-Plus systems, we performed impact simulations with vehicle-to-damaged ET-Plus models according to the National Cooperative Highway Research Program (NCHRP) 350, test conditions 3–30. ResultsOf the 1000 in-service end terminal cases we investigated, 73% were undamaged, 18% had minor damage, and 8% had major damage. Increases in the average vehicle deceleration rates, maximum vehicle yaw angles, and vehicle local deformations were observed in simulated impacts with damaged ET-Plus end terminals relative to impacts with undamaged ET-Plus end terminals. For one damaged ET-Plus, a secondary collision was observed. Overall, we found that the damaged end terminals usually increased collision severity when compared with undamaged end terminals. ConclusionsThe findings of this study point out the need for in-service performance evaluations and proper maintenance and repair practices of end terminals. The simulation models developed in this study could be further employed to investigate device performance in crash situations that are physically impractical to test and investigate the effects of site characteristics on device performance. The simulation models could also supplement crash tests to certify new hardware designs.

Expansion of NASS/CDS for characterizing run-off-road crashes

Objective Run-off-road (ROR) crashes account for one-third of all annual crash fatalities in the US. The National Automotive Sampling System Crashworthiness Data System (NASS/CDS) is a dataset which may be used to understand the nature of ROR crashes. Despite the wealth of coded data available in NASS/CDS, this dataset lacks coded information about the roadside environment and the off-road trajectory of the vehicle. This information would be useful for determining lane departure warning (LDW) benefits, residual safety problems, performance of current safety hardware, lane marking inventory, LDW test procedure development, radius of curvature characterization, and effectiveness of ESC. The purpose of this paper is to demonstrate a methodology for expanding the data available in NASS/CDS to form and validate a specialized road departure database. Methods Observed, measured, and reconstructed data elements were extracted from NASS/CDS and compiled into the National Cooperative Highway Research Program (NCHRP) 17-43 database. Observed variables were primarily coded from the scene photographs and included information such as the lane markings, and geometry of the roadside cross-section. Additional variables were measured from the scaled scene diagrams including the path of the vehicle, road dimensions, and roadside object positions. The vehicle impact speed and departure speed were reconstructed using the WinSMASH delta-v, roadside object characteristics, and vehicle path. Two studies were conducted to demonstrate the usefulness of the NCHRP 17-43 database in evaluating both vehicle-based and infrastructure-based ROR countermeasures. Results The resulting NCHRP 17-43 database includes 1,581 NASS/CDS cases representing 510,154 ROR crashes. Analysis of the database found that drivers which crashed following an overcorrection were younger than drivers which did not overcorrect. This may indicate that inexperienced drivers are more likely to overcorrect when departing the roadway. The 85th percentile impact severity of ROR crashes, which occur on roads with a speed limit greater than 65 mph, is higher than the practical worst-case test conditions for roadside barriers. Conclusions The NCHRP 17-43 database contains information extracted from NASS/CDS cases to better understand the nature of ROR crashes, driver behavior in these crashes, and the potential benefits of both vehicle-based and infrastructure-based ROR countermeasures.

Estimating the number of traffic crash-related cervical spine injuries in the United States; An analysis and comparison of national crash and hospital data

BackgroundCervical spine injury is a common result of traffic crashes, and such injuries range in severity from minor (i.e. sprain/strain) to moderate (intervertebral disk derangement) to serious and greater (fractures, dislocations, and spinal cord injuries). There are currently no reliable estimates of the number of crash-related spine injuries occurring in the US annually, although several publications have used national crash injury samples as a basis for estimating the frequency of both cervical and lumbar spinal disk injuries occurring in lower speed rear impact crashes. PurposeTo develop a reliable estimate of the number of various types of cervical spine injuries occurring in the US by comparing data from national crash injury to national hospital ED and inpatient samples. Study DesignComparative cross-sectional MethodsCervical spine injury data were accessed, analyzed, and compared from 3 national databases; the National Automotive Sampling System-Crashworthiness Data System (NASS-CDS), Nationwide Emergency Department Sample (NEDS), and the Nationwide Inpatient Sample (NIS). ResultsIt is estimated that there are approximately 869,000 traffic crash-related cervical spine injuries seen in hospitals in the US annually, including around 841,000 sprain/strain (whiplash) injuries, 2800 spinal disk injuries, 23,500 fractures, 2800 spinal cord injuries, and 1500 dislocations. Because of a highly restrictive inclusion criteria for both crash and injury types, as well as a very small sample size, the NASS-CDS underestimated all types of crash-related cervical spine injuries seen in US hospital emergency departments by 84 %. The injury type with the largest degree of underestimation in the NASS-CDS was cervical disk injuries, which were estimated at an 88 % lower frequency than in the NEDS. National insurance claim data, which include cases of cervical disk injury diagnosed both in and outside of the ED, indicate that the NEDS likely undercounts cervical disk injuries by 92 %, and thus the NASS-CDS correspondingly undercounts such injuries by 99 % or more. ConclusionsBecause of a limited sample size and restrictive criteria for both crash and injury inclusion, the NASS-CDS cannot be used to estimate the number of crash-related spinal injuries of any type or severity in the US. The most inappropriate use of the database is for estimating the number of spinal injuries resulting from low speed rear impact collisions, as the NASS-CDS samples fewer than 1 in 100,000 of the cervical spine injuries of any type occurring in low speed rear impact collisions.

Crash Telemetry-Based Injury Severity Prediction is Equivalent to or Out-Performs Field Protocols in Triage of Planar Vehicle Collisions.

With the increasing availability of vehicle telemetry technology, there is great potential for Advanced Automatic Collision Notification (AACN) systems to improve trauma outcomes by detecting patients at-risk for severe injury and facilitating early transport to trauma centers. National Automotive Sampling System Crashworthiness Data System (NASS-CDS) data from 1999-2013 were used to construct a logistic regression model (injury severity prediction [ISP] model) predicting the probability that one or more occupants in planar, non-rollover motor vehicle collisions (MVCs) would have Injury Severity Score (ISS) 15+ injuries. Variables included principal direction of force (PDOF), change in velocity (Delta-V), multiple impacts, presence of any older occupant (≥55 years old), presence of any female occupant, presence of right-sided passenger, belt use, and vehicle type. The model was validated using medical records and 2008-2011 crash data from AACN-enabled Michigan (USA) vehicles identified from OnStar (OnStar Corporation; General Motors; Detroit, Michigan USA) records. To compare the ISP to previously established protocols, a literature search was performed to determine the sensitivity and specificity of first responder identification of ISS 15+ for MVC occupants. The study population included 924 occupants in 836 crash events. The ISP model had a sensitivity of 72.7% (95% Confidence Interval [CI] 41%-91%) and specificity of 93% (95% CI 92%-95%) for identifying ISS 15+ occupants injured in planar MVCs. The current standard 2006 Field Triage Decision Scheme (FTDS) was 56%-66% sensitive and 75%-88% specific in identifying ISS 15+ patients. The ISP algorithm comparably is more sensitive and more specific than current field triage in identifying MVC patients at-risk for ISS 15+ injuries. This real-world field study shows telemetry data transmitted before dispatch of emergency medical systems can be helpful to quickly identify patients who require urgent transfer to trauma centers.

Residual road departure crashes after full deployment of LDW and LDP systems

Objective: Road departures are one of the most severe crash modes in the United States. To help reduce this risk, vehicles are being introduced in the United States with lane departure warning (LDW) systems, which warn the driver of a departure, and lane departure prevention (LDP) systems, which assist the driver in steering back to the roadway. Previous studies have estimated that LDW/LDP systems may prevent one third of drift-out-of-lane road departure crashes. This study investigates the crashes that were not prevented, to potentially set research priorities for next-generation road departure prevention systems.Methods: The event data recorder (EDR) data from 128 road departure crashes in the National Automotive Sampling System Crashworthiness Data System (NASS-CDS) from 2011 to 2015 were mapped onto the vehicle trajectory and simulated with LDW/LDP to assess the potential for crash avoidance. The model predicted that 63–83% of single-vehicle road departure crashes may not be prevented by an LDW system and 49% may not be prevented by an LDP system.Results and Conclusions: For LDP systems, which were assumed to have zero latency, no crashes were avoided if the time-to-collision (TTC) from lane crossing to impact was less than 0.55 s. Obstacles such as guardrails and traffic barriers, which tend to be very close to the road, were more common among the remaining crashes. The study shows that LDW/LDP systems are limited by two factors, driver reaction time and TTC to the roadside object. Thus, earlier driver response and longer TTC may help in these situations.

Factors contributing to serious and fatal injuries in belted rear seat occupants in frontal crashes

Objectives: Earlier research has shown that the rear row is safer for occupants in crashes than the front row, but there is evidence that improvements in front seat occupant protection in more recent vehicle model years have reduced the safety advantage of the rear seat versus the front seat. The study objective was to identify factors that contribute to serious and fatal injuries in belted rear seat occupants in frontal crashes in newer model year vehicles.Methods: A case series review of belted rear seat occupants who were seriously injured or killed in frontal crashes was conducted. Occupants in frontal crashes were eligible for inclusion if they were 6 years old or older and belted in the rear of a 2000 or newer model year passenger vehicle within 10 model years of the crash year. Crashes were identified using the 2004–2015 National Automotive Sampling System Crashworthiness Data System (NASS-CDS) and included all eligible occupants with at least one Abbreviated Injury Scale (AIS) 3 or greater injury. Using these same inclusion criteria but split into younger (6 to 12 years) and older (55+ years) cohorts, fatal crashes were identified in the 2014–2015 Fatality Analysis Reporting System (FARS) and then local police jurisdictions were contacted for complete crash records.Results: Detailed case series review was completed for 117 rear seat occupants: 36 with Maximum Abbreviated Injury Scale (MAIS) 3+ injuries in NASS-CDS and 81 fatalities identified in FARS. More than half of the injured and killed rear occupants were more severely injured than front seat occupants in the same crash. Serious chest injury, primarily caused by seat belt loading, was present in 22 of the injured occupants and 17 of the 37 fatalities with documented injuries. Nine injured occupants and 18 fatalities sustained serious head injury, primarily from contact with the vehicle interior or severe intrusion. For fatal cases, 12 crashes were considered unsurvivable due to a complete loss of occupant space. For cases considered survivable, intrusion was not a large contributor to fatality.Discussion: Rear seat occupants sustained serious and fatal injuries due to belt loading in crashes in which front seat occupants survived, suggesting a discrepancy in restraint performance between the front and rear rows. Restraint strategies that reduce loading to the chest should be considered, but there may be potential tradeoffs with increased head excursion, particularly in the absence of rear seat airbags. Any new restraint designs should consider the unique needs of the rear seat environment.

Intersection characteristics that influence collision severity and cost

Introduction: Traffic engineers require robust tools to assist with their day-to-day decision making, and there is no better example of this than traffic signal warrants. North American traffic signal warrant systems are lacking in how they incorporate motor-vehicle collisions from both a severity and prediction perspective. The objective of this study was to produce reliable collision costs for the development of improved traffic signal warrants that accounted for the variations in severity that practitioners should expect based on the characteristics of the intersection being studied. Method: The primary data used for this analysis were from the National Automotive Sampling System (NASS) Crashworthiness Data System, with adjustments from the NASS General Estimates System and Fatality Accident Reporting System. Generalized ordered logit models were used to identify the most significant intersection characteristics, which were then used to segregate the data to determine expected the collision severity profiles and average costs of both casualty and total collisions at intersections. Results: The average collision at a signalized intersection was found have a lower severity than the average collision at a stop-controlled intersection. A combination of posted speed limit, urban/rural, and divided/undivided were identified as the most significant intersection characteristics in most cases and were used to delineate the data for developing collision cost estimates. Conclusions: Posted speed limit, rural/urban land use, and the presence of divided approaches are intersection characteristics that traffic engineers can readily determine and/or control for that have significant effects on intersection collision severity. Practical applications: The collision costs produced through this process give traffic engineers a reliable estimate that can provide a more substantial foundation for justifying a proposed change in intersection traffic control.

“Robust-Squared” Imputation Models Using Bart

AbstractExamples of “doubly robust” estimators for missing data include augmented inverse probability weighting (AIPWT) and penalized splines of propensity prediction (PSPP). Doubly robust estimators have the property that, if either the response propensity or the mean is modeled correctly, a consistent estimator of the population mean is obtained. However, doubly robust estimators can perform poorly when modest misspecification is present in both models. Here we consider extensions of the AIPWT and PSPP that use Bayesian additive regression trees (BART) to provide highly robust propensity and mean model estimation. We term these “robust-squared” in the sense that the propensity score, the means, or both can be estimated with minimal model misspecification, and applied to the doubly robust estimator. We consider their behavior via simulations where propensities and/or mean models are misspecified. We apply our proposed method to impute missing instantaneous velocity (delta-v) values from the 2014 National Automotive Sampling System Crashworthiness Data System dataset and missing Blood Alcohol Concentration values from the 2015 Fatality Analysis Reporting System dataset. We found that BART, applied to PSPP and AIPWT, provides a more robust estimate compared with PSPP and AIPWT.

Age effects on injury pattern of rear-seat child occupants in frontal crashes

This paper presents a study using 1997-2015 National Automotive Sampling System (NASS) Crashworthiness Data System (CDS) data to estimate the risk and body region distribution of injury for rear-seated children aged 4-18 using vehicle seat belts in frontal crashes and evaluate specific cut-off points for age as effect modifiers of the association between use of vehicle seat belts and their respectively significant injury. Logistic regression analyses were conducted to evaluate the factors affecting the injury risk for children aged 4-18. Results showed that seatbelt was the most common form of restraint for children older than four years of age seated in the rear seat. Children 8-12 years of age were at the highest risk of significant injury among children 4-18 years old. The risks of significant injury by body regions varied among children 4-18 years old due to the differences in anthropometry. Children 4-8 years of age appeared to be at increased risk of injury from using seat belts, whereas children 9-18 years of age experienced protective effects of using seat belts.

Age effects on injury pattern of rear-seat child occupants in frontal crashes

This paper presents a study using 1997-2015 National Automotive Sampling System (NASS) Crashworthiness Data System (CDS) data to estimate the risk and body region distribution of injury for rear-seated children aged 4-18 using vehicle seat belts in frontal crashes and evaluate specific cut-off points for age as effect modifiers of the association between use of vehicle seat belts and their respectively significant injury. Logistic regression analyses were conducted to evaluate the factors affecting the injury risk for children aged 4-18. Results showed that seatbelt was the most common form of restraint for children older than four years of age seated in the rear seat. Children 8-12 years of age were at the highest risk of significant injury among children 4-18 years old. The risks of significant injury by body regions varied among children 4-18 years old due to the differences in anthropometry. Children 4-8 years of age appeared to be at increased risk of injury from using seat belts, whereas children 9-18 years of age experienced protective effects of using seat belts.

Retraction: Car safety seats for children: rear facing for best protection

Henary B, Sherwood CP, Crandall JR, et al . Car safety seats for children: rear facing for best protection. Injury Prev 2007;13:398-402. DOI: 10.1136/ip.2006.015115 The manuscript ‘ Car safety seats...

Rear-facing versus forward-facing child restraints: an updated assessment

ObjectivesThe National Highway Traffic Safety Administration and the American Academy of Pediatrics recommend children be placed in rear-facing child restraint systems (RFCRS) until at least age 2. These recommendations are...

Identification of characteristics and frequent scenarios of single-vehicle rollover crashes during pre-ballistic phase; part 1 – A descriptive study

This study aimed to identify common patterns of pre-ballistic vehicle kinematics and roadway characteristics of real-world rollover crashes. Rollover crashes that were enrolled in the National Automotive Sampling System-Crashworthiness Data System (NASS-CDS) between the years 2000 and 2010 were analyzed. A descriptive analysis was performed to understand the characteristics of the pre-ballistic phase. Also, a frequency based pattern analysis was performed using a selection of NASS-CDS variables describing the pre-ballistic vehicle kinematics and roadway characteristics to rank common pathways of rollover crashes. Most case vehicles departed the road due to a loss of control/traction (LOC) (61%). The road departure with LOC was found to be 13.4 times more likely to occur with slippery road conditions compared to dry conditions. The vehicle was typically laterally skidding with yawing prior to a rollover (66%). Most case vehicles tripped over (82%) mostly at roadside/median (69%). The tripping force was applied to the wheels/tires (82%) from the ground (79%). The combination of these six most frequent attributes resulted in the most common scenario, which accounted for 26% of the entire cases. Large proportion of road departure with LOC (61%) implies electronic stability control (ESC) systems being an effective countermeasure for preventing single-vehicle rollover crashes. Furthermore, the correlation between the road departure with LOC and the reduced friction limit suggests the necessity of the performance evaluation of ESC under compromised road surface condition.