Vehicle Model Year Research Articles

Investigating factors affecting injury severity of single-vehicle run-off-road crashes

This study aimed to identify and investigate the contributing factors influencing injury severity in single-vehicle run-off-road (ROR) crashes, which are known for their high severity. The primary objective was to analyze and compare the impact of these factors across three distinct vehicle classes: passenger cars, sport utility vehicles (SUVs), and pickups. A mixed logit model with heterogeneity in mean and variance was developed to analyze the injury severity outcomes in ROR crashes for the three vehicle classes. The model accounted for the potential variations in the impact of contributing factors across different vehicle types. The study revealed several significant variables consistently influencing injury severity across all three vehicle classes. These included driver age, alcohol or drug usage, seatbelt utilization, airbag deployment, higher travel speeds, and the vehicle model year post-2010. Notably, as driver age increased, the impact on changes in injury severity outcomes was more pronounced for pickup drivers compared to those operating passenger cars and SUVs. Among the common findings was the highly effective role of seatbelt usage in mitigating injury severity in ROR crashes. Additionally, passenger cars were associated with increased injury severity, particularly at relatively higher travel speeds exceeding 75 mph when contrasted with SUVs and pickups traveling between 61 and 75 mph. The study highlights the importance of considering vehicle class-specific factors in analyzing injury severity in ROR crashes. Recommendations include further in-depth investigations into distinct factors contributing to injury severity within each vehicle class and utilizing more extensive crash datasets to gain additional insights for enhancing road safety.

Effect of ESC (electronic stability control) on tree and pole impacts with focus on rear impacts

ObjectiveThe effect of ESC (Electronic Stability Control) was investigated for the rate of crash exposure, serious injury and fatality in pole and tree impacts. Field data was analyzed by crash type (front, side, rear and rollover) and model year (MY) before, during and after the implementation of ESC. MethodsThe number of pole and tree impacts was determined for four groups of vehicle model years (MY): 1981–1989 MY and 1990–2002 MY before the introduction of ESC, 2003–2009 during the phase-in of ESC and 2010–2020 MY after essentially all vehicles were equipped with ESC. Collisions were grouped by front, side, rear and rollover. Three databases were analyzed: 1990–2020 FARS, 1990–2015 NASS-CDS and 2017–2020 CISS. Vehicle registration was obtained from IHS Markit to determine the rate of pole and tree impacts per 100,000 registered vehicles. The same vehicle selection criteria was used for vehicle registration and crash data. ResultsFatalities dropped 65.2 % (95 % CI, 63.0–67.4 %), z = 43.7, p < 0.001 into poles and 60.3 % (95 % CI, 59.0–61.5 %), z = 72.4, p < 0.001 into trees in vehicles equipped with ESC comparing 1990–2002 MY to 2010–2020 MY vehicles. Seriously injured occupants in crashes with poles dropped 75.9 % (95 % CI, 75.0–76.9 %), z = 116, p < 0.001 between 1990 and 2002 MY and 2010–2020 MY vehicles. There was a 65.2 % (95 % CI, 64.4–65.9 %), z = 141, p < 0.001 reduction in tree impacts. The crash exposure to pole impacts dropped 36.0 % (95 % CI, 35.8–36.3 %), z = 252, p < 0.001 from 80.77/100,000 registered vehicles in 1990–2002 MY vehicles to 51.69/100,000 in 2010–2020 MY vehicles. There was a 61.0 % (95 % CI, 60.8–61.2 %), z = 434, p < 0.001 reduction in tree impacts. For rear impacts, fatalities dropped 82.9 % (95 % CI, 71.3–94.4 %), z = 9.37, p < 0.001 into poles and 74.8 % (95 % CI, 67.8–81.9 %), z = 14.8, p < 0.001 into trees. Serious-injury in rear impacts with poles and trees were essentially eliminated in 2010–2020 MY vehicle crashes. There were significant drops in fatalities in side and frontals impacts and rollovers in vehicles equipped with ESC. ConclusionESC helps the driver maintain vehicle heading and significantly reduced the rate of serious injury and fatality in off-road impacts with poles and trees. The benefits of ESC may not be realized with impairments when the driver does not appropriately steer the vehicle.

Comprehensive analysis of traumatic rupture of the aorta in road traffic crashes: incorporating epidemiological insights and K-prototype clustering

Objectives The identification of crash characteristics associated with traumatic rupture of the aorta (TRA) can significantly enhance countermeasures against TRA. Conventional epidemiological approaches struggle to adequately handle the substantial variability of traffic crash data. Consequently, this study aims to integrate conventional epidemiological analysis with data-driven cluster analysis to more comprehensively analyze TRA-related crash characteristics. Methods A total of 350 unweighted TRA crashes were extracted from traffic crash databases including comprehensive crash details and injury descriptions. Initially, a selection was made of 11 continuous variables and 9 categorical variables, describing crash characteristics. After correlation analysis and principal component analysis were applied to the dataset, K-prototype clustering was finally conducted using 6retained categorical variables and 6 principal components derived from the continuous variables. Results This study found significant age and gender disparities among TRA victims, with 50% falling within the age range of 25–59 years and an overwhelming majority (62.2%) being males. Side impacts emerged as the primary cause of TRA-related crashes (37.2%), followed by collisions with off-road objects (28.6%) and head-on collisions (24.8%). Cluster analyses revealed 6 distinct clusters within the TRA-related crash dataset. These clusters were characterized by factors such as vehicle model year, curb weight, collision dynamics, and seatbelt usage, providing a deeper understanding of the heterogeneity in TRA incidents and their associated factors. Conclusions Although limitations related to available data sources and factors such as accompanying injuries and vehicle weight warrant further comprehensive investigations in the future, this study contributes valuable insights into TRA analysis to enhance understanding and prevention strategies.

Modification of the association between vehicle model year and crash-related injury by race and ethnicity for North Carolinian passenger vehicle occupants.

Modification of the association between vehicle model year and crash-related injury by race and ethnicity for North Carolinian passenger vehicle occupants.

Trends in scrappage and survival of U.S. light-duty vehicles

The rate at which new vehicles replace the existing stock of used vehicles affects the rate at which the benefits of regulations requiring safety technologies, controls on pollutant emissions, and energy efficiency improvements are fully realized. A review of past estimates of the life expectancies of U.S. light-duty vehicles indicates they have been increasing by 0.5 % to 1.5 % per year for the last half a century. We estimate models of scrappage rates and survival probabilities as a function of vehicle age for U.S. passenger cars, SUVs and vans, and pickup trucks, using population counts of vehicles in operation by vehicle type and model year for calendar years 2002–2020. Our results indicate that life expectancies for all three vehicle types continued to increase over this recent time period, by 2–3 years for passenger cars, 3–4 years for SUVs and Vans, and 5–6 years for pickup trucks. By 2020, median expected lifetimes ranged from about 17 years for passenger cars to 20 years for SUVs and vans, and 25 years for pickup trucks. The content and durability of new vehicles is likely to continue to increase as the market transitions to more electrified and automated vehicles, with important implications for policies aimed at reducing emissions, increasing fuel economy and improving safety.

A comparison of patterns and contributing factors of ADAS and ADS involved crashes

Crashes involving Advanced Driver Assistance Systems (ADAS) and Automated Driving Systems (ADS) have been increasing in recent years. Understanding the characteristics of these crashes can guide the optimization of driving automation systems and the policies improving the safety of mixed traffic. However, due to the limited available data, the crashes of ADS- and ADAS-controlled vehicles are still under-investigated. Thus, utilizing the latest National Highway Traffic Safety Administration crash reports, our study explores the patterns and contributing factors of ADAS- and ADS-involved crashes. The sequences of events leading to crashes were extracted from the reports and then categorized into five clusters. Next, for incomplete records, a non-parametric imputation method was applied based on Random Forest. Finally, logistic regression models were built to explore the factors associated with the crashes. The results show that the automation level, speed limit, and vehicle speed are predictors of crash patterns. At the same time, the crash pattern, combined with incident time, roadway type, roadway surface, and vehicle model year are associated with crash outcomes (i.e. contact area and injury severity). The results indicate that further improvement of the ADS/ADAS control algorithms and driver education may be needed to improve the safety of mixed traffic.

Demographic adjustments to driver death rates by vehicle type and size

Objective Driver death rates per million registered vehicles are often used to compare the real-world crash experiences of vehicles of different types and sizes. However, these rates are affected by the risky behavior of drivers (e.g., speeding, impaired driving, lack of restraint use) that differs by age and gender. This paper presents a method for adjusting driver death rates to account for differences in driver age and gender. Methods Driver death rates per million registered vehicles per year were calculated for passenger vehicles of model year 2020. To account for potential differences in driver exposure by age and gender, which can affect motor vehicle crash and injury experience, an algebraic method was used to standardize these rates to a common distribution of female drivers ages 25–64. The standardization depends upon an independent estimate of the relative fatality risk for female drivers ages 25–64. Results The smallest vehicles tended to have higher driver death rates compared with larger vehicles. However, for sports cars, this trend was reversed; larger sports cars had higher driver death rates. Vehicle types popular with male drivers, such as sports cars and pickups, had standardized death rates that were much lower than the raw rates. Conclusions The adjustment for driver age and gender greatly reduced the variability of driver death rates among vehicle types. The procedure used here to adjust driver death rates for driver age and gender can be extended to any situation where it is desired to compare the crash rates of two or more subgroups of a population.

The effect of seatbelt pre-tensioners and load limiters in the reduction of MAIS 2+, MAIS 3+, and fatal injuries in real-world frontal crashes

Contemporary research has pointed out that while newer cars are contributing to the decrease of AIS2+ and AIS3+ injuries in several body regions, this effect is not shown for thoracic injuries like rib or sternal fractures. The objective of this study is to assess the effectiveness of advanced seat belt systems incorporating pre-tensioners and load limiters in the prevention of fatal, AIS2+ and AIS3+ injuries overall and then focus only on the head-face-neck and thoracic areas. Data from the NASS CDS database between 2000 and 2015 was augmented with specific vehicle information taken from NHTSA’s NCAP tests to identify the characteristics of the seat belt of each vehicle involved in a collision. Multivariate logistic regressions were developed to assess the likelihood of injuries for belted front seat occupants in frontal impacts. The presence of pre-tensioners and load limiters with a low load limiter (<4.5 kN) was significantly associated with a decreased risk of fatal and AIS3+ in the whole body (OR = 0.31 (p < 0.05) and OR = 0.70 (p < 0.1)), while high load limiters were significant in the prevention of fatal injuries (OR = 0.42). These effects should be considered always in combination with the delta-v of the collision, as the interaction term between delta-v and advanced seat belt features was significant. In the crashes considered, the model predicted a higher risk of injury for women compared to men, controlling for other occupant and crash factors. Impacts with a slightly oblique component increased the risk of injury compared to pure frontal impacts. After controlling for the presence of pre-tensioners and load limiters, the vehicle model year variable was found to be insignificant in any of the regression models. This study shows that the real-world effectiveness of advanced seat belts still requires further analysis. Other effects like age or impact direction might be more influential in the injury outcome than these seat belt features.

Unsupervised Machine Learning to Detect Impending Anomalies in Testing of Fuel Economy and Emissions of Light-Duty Vehicles

This work focused on demonstrating the capability of unsupervised machine learning techniques in detecting impending anomalies by extracting hidden trends in the datasets of fuel economy and emissions of light-duty vehicles (LDVs), which consist of cars and light-duty trucks. This case study used the vehicles’ fuel economy and emissions testing datasets for vehicle model years 2015 to 2023 with a total of 34,602 data samples on LDVs of major vehicle manufacturers. Three unsupervised techniques were used: principal components analysis (PCA), K-Means clustering, and self-organizing maps (SOM). Results show that there are clusters of data that exhibit trends not represented by the dataset as a whole. Fuel CO vs. Fuel Economy has a negative correlation in the whole dataset (r = −0.355 for LDVs model year 2022), but it has positive correlations in certain sample clusters (e.g., LDVs model year 2022: r = +0.62 in a K-Means cluster where the slope is around 0.347 g−CO/mi/MPG). A time series analysis of the results of clustering indicates that Test Procedure and Fuel Type, specifically Test Procedure 11 and Fuel Type 26 as defined by the US EPA, could be the contributors to the positive correlation of CO and Fuel Economy. This detected peculiar trend of CO-vs.-Fuel Economy is an impending anomaly, as the use of Fuel 26 in emissions testing with Test Procedure 11 of US-EPA has been increasing through the years. With the finding that the clustered data samples with positive CO-vs.-Fuel Economy correlation all came from vehicle manufacturers that independently conduct the standard testing procedures and not data from US-EPA testing centers, it was concluded that the chemistry of using Fuel 26 in performing Test Procedure 11 should be re-evaluated by US-EPA.

Adult occupant injury risk in rear impact and frontal impact: Effect of impact conditions and occupant-related factors

Objectives The objectives of this study were to compare the adult occupant injury risk on specific body regions in frontal and rear impact and to investigate the effect of those crash conditions and occupant-related factors on the injury risk. Method Data from the NASS-CDS and Crash Investigation Sampling System were studied for crashes during 2000 to 2019 involving model year 2000 to 2020 motor vehicles, including frontal collisions and rear-end collisions. The injury risk by specific body regions were compared by descriptive statistics, and logistic regression models were developed to examine the effects of various factors on injury risk by specific body regions, controlling for crash type (frontal impact and rear impact), vehicle impact speed, vehicle impact location, vehicle model year, and occupant gender, age, belt use, and seating position. Results After controlling for the confounding factors, the occupants in frontal impact had higher overall injury risk than in rear impact (at Maximum Abbreviated Injury Scale [MAIS] 3+; odds ratio [OR] = 6.23; 95% confidence interval [CI] [6.06–6.40]), except for lower neck/spine injury risk at MAIS 1+ (OR = 0.47; 95% CI [0.46–0.47]). The impact speed (at MAIS 3+; OR = 1.10; 95% CI [1.10–1.10]) and aging (at MAIS 3+; OR = 1.05; 95% CI [1.05–1.05]) increase overall injury risk, and the unbelted occupants had higher overall injury risk than belted occupants not only in frontal impact (at MAIS 3+; OR = 4.04; 95% CI [3.98–4.10]), but also in rear impact (at MAIS 3+; OR = 28.4; 95% CI [26.4–30.5]). Females had higher overall injury risk than males in frontal impact (at MAIS 3+; OR = 2.01; 95% CI [1.99–2.04]) but not in rear impact (at MAIS 3+; OR = 0.77; 95% CI [0.73–0.81]). Conclusions Occupants in rear impact had lower injury risk than in frontal impact at MAIS 1+ to MAIS 3+, except for neck/spine at MAIS 1+. The belt restraint was effective not only in frontal impact but also in rear impact. This study provided injury risk references for current vehicles that may provide insight to the potential injury risk of rear-facing occupants in future vehicle configurations.

Influential crash conditions leading to injury differences experienced by female and male drivers

IntroductionRobust occupant protection is critical for the longevity and quality of life of the diverse driving population. Studies have shown that the vehicle crash testing process has greatly assisted in decreasing the severity of injuries experienced by occupants. However, female occupants are not equitably accounted for in the current testing processes while experiencing a significantly increased risk of higher severity injuries compared to male occupants in comparable crash conditions. Given the increased safety concern for female occupants, it is critical to investigate the conditions that result in injuries occurring in specific locations in cases of female occupants compared to male occupants. MethodsIn this study, an investigation is made to uncover potential influential crash conditions that lead to injury location differences experienced by female and male drivers using a novel linked dataset of emergency medical services and crash data. Logistic regression methods were used to develop robust analyses. ResultsThe results revealed that female and male drivers experience injuries in different locations to a significant degree depending upon vehicle model year, airbag deployment, and driver age when considering all crash types. The results included the finding that as vehicle model year increases, neck injury risk decreases for male drivers while it increases for female drivers. ConclusionsThis study highlighted the crash conditions and vehicle components that lead to different injury outcomes for female and male drivers. From a policy perspective, the results emphasize the importance of including both representative female and male anthropometry in vehicle testing and design. From a practitioner and research perspective, this study provides the data needed to understand the components of vehicle design that must be further considered to provide optimal occupant protection for the entire driving population, leading to more equitable, positive long-term health outcomes for all drivers.

Injury risks and crashworthiness benefits for females and males: Which differences are physiological?

Objective Previous research has found elevated injury risk for females relative to males in passenger vehicle crashes but has not accounted for ways the crashes themselves differ between these populations. Vehicle curb weight, ride height, safety rating, airbag deployment, and crash configuration all influence injury outcome and often are not well-represented by delta-V alone. This study evaluated the effect of occupant sex on injury risk in front and side crashes while limiting or controlling for non-physiological crash differences. Additionally, the effects of crashworthiness improvements are compared for females and males. Methods NASS-CDS cases from 1998–2015 calendar years involving a belted driver in a front crash or a struck-side driver or right front passenger in a side crash were analyzed. Case vehicle model years were 1989–2016. Logistic regression was used to estimate the risk of MAIS ≥ 2 and MAIS ≥ 3 injury outcomes for females relative to males as well as the change in risk due to improved crashworthiness. Sex-based differences in occupant age, mass, and stature; crash test rating; delta-V; crash configuration; and vehicle-to-vehicle compatibility were considered either through case selection or the inclusion of additional regression covariates. Results Before controlling for crash and vehicle differences, female drivers in front crashes had higher estimated overall and body-region-specific risks of MAIS ≥ 2 and MAIS ≥ 3 injury, as consistent with previous findings. After accounting for such differences, all ratios of injury odds for females relative to males were reduced. Females remained at higher risk of MAIS ≥ 2 injury (OR, 2.23; 95% CI, 1.42–3.51), especially extremity injury, but had similar odds for MAIS ≥ 3 non-extremity injury (OR, 0.98; 95% CI, 0.56–1.7). While controlling for crash differences in side impacts, none of the estimated injury risk differences by sex were significant at the p ≤ 0.05 level. Estimated benefits of improved crashworthiness were similar or greater for females than for males for most injury outcomes. Conclusions Female-specific crashworthiness improvements may be required to provide additional protection against AIS 2 extremity injury. Much of the remaining discrepancy in sex-based injury risk can be attributed differences between vehicles and crashes, not to physiological differences. Addressing these differences will require other types of countermeasures.

The comparison of vehicle headlamps

The aim of this article is the comparison of vehicle headlamps in terms of pedestrians' visibility at nighttime conditions. The study was designed to gain results, which could serve as a basis for the pedestrian-vehicle accident analysis in terms of visibility during night drive. For this study were used comparable vehicles (same vehicle type and model year) with different headlamps type. Three different headlamps (halogen, xenon and LED headlamps) were used for the analysis. Experiments were carried out under similar conditions (straight road, nighttime, no disturbing factors). During a series of static tests, the vehicle approached at predefined distances to the figurant - pedestrian standing on the right side of the roadway. For the luminance analysis were used Luminance Distribution Analyser LumiDISP - software for analysing the luminance conditions based on evaluation of image data from digital photos.

Characterisation of ammonia emissions from gasoline and gasoline hybrid passenger cars

Recent evidence suggests NH 3 emissions from road vehicles play an important role in the formation of fine particulate matter, especially in urban areas. However, there is little data available for NH 3 emitted from road vehicles under real driving conditions, in part due to its lack of regulation in vehicle emission legislation. In this study, we use 210,000 vehicle emission remote sensing measurements to evaluate the complex mix of factors affecting NH 3 emissions from gasoline and gasoline hybrid passenger cars. The influence of vehicle model year and manufacturer on NH 3 emissions is considered, as well as the effect of vehicle deterioration. It is found that the amount of NH 3 emitted increases as vehicle mileage increases. A comparison of cold start and hot exhaust NH 3 emissions reveals that on average, cold start emissions are a factor of 1.7 times higher. New NH 3 emission factors are developed, in addition to speed-emission curves that are potentially useful for national inventories. A new application of remote sensing data is reported, whereby the proportion of failed CO 2 measurements for hybrid vehicles provides unique insight into the real world battery use of both conventional hybrid electric and plug-in hybrid electric vehicles, which is used to refine the NH 3 emission factors for these vehicles. • Vehicle emission measurements using remote sensing. • New NH 3 emission factors for gasoline and gasoline hybrid cars. • Quantification of NH 3 cold start penalty. • NH 3 increases with increasing vehicle mileage. • Fraction of failed CO 2 measurements gives unique insight into hybrid battery use.

Quantitative characterization of AEB pulses across the modern fleet

Objective Characteristics of specific Automatic Emergency Braking (AEB) pulses can result in increased motion of the occupant, which can lead to the occupant being out-of-position such that when a crash occurs protection may be compromised. Quantifying these variations across the modern fleet is crucial to understand the loading environment to which vehicle occupants are exposed. Therefore, we categorized the AEB pulses based on acceleration pulse features such as deceleration magnitude, jerk, and ramp time. Methods A total of 2278 AEB vehicle tests (years 2013–2019) were extracted from the Insurance Institute for Highway Safety (IIHS) database and analyzed. The following pulse characteristics were extracted: Jerk (g/s), Ramp-time (s), and Maximum deceleration (g). A subset of tests in which the tested vehicle did not contact the foam target (n = 1665) was analyzed further, with the following additional variables extracted: Deceleration time (s), Steady-state deceleration (g), and Duration (s). Other non-pulse related features were also considered: Test speed (20 and 40 km/h), Curb weight (Kg), and Vehicle Model Year. Using machine learning methods, the pulses were categorized into clusters. One-way ANOVAs for continuous variables and X2 for categorical features were used to assess differences between clusters (p ≤ 0.05). Results Using the entirety of the AEB vehicle tests extracted (n = 2278), a total of 3 clusters were selected. The three clusters showed significantly different Jerk, Ramp-time, and Maximum deceleration (p < 0.001). Target contact decreased in AEB tests with more recent vehicle model years (rate of contact 66% in 2014 vs 1.7% in 2019). In one cluster, Jerk and Maximum deceleration increased with vehicle model year. Using the subset of tests in which there was no contact with the foam target (n = 1665), 4 categories of pulses were selected. In both sets of clusters, Ramp-time and Jerk showed moderate inverse correlation (r = –0.7), while all other features showed a low correlation. Conclusions These results show that AEB technology improved over the years in obstacle avoidance. The identification of AEB pulse clusters is important in order to describe distinct approaches to achieving AEB and to be able to reproduce representative AEB pulses in the laboratory and understand the influences of those pulses on occupants’ motion.

Using Crash Outcome Data Evaluation System (CODES) to examine injury in front vs. rear-seated infants and children involved in a motor vehicle crash in New York State

BackgroundIn New York State (NYS), motor vehicle (MV) injury to child passengers is a leading cause of hospitalization and emergency department (ED) visits in children aged 0–12 years. NYS laws require appropriate child restraints for ages 0–7 years and safety belts for ages 8 and up while traveling in a private passenger vehicle, but do not specify a seating position.MethodsFactors associated with injury in front-seated (n = 11,212) compared to rear-seated (n = 93,092) passengers aged 0–12 years were examined by age groups 0–3, 4–7 and 8–12 years using the 2012–2014 NYS Crash Outcome Data Evaluation System (CODES). CODES consists of Department of Motor Vehicle (DMV) crash reports linked to ED visits and hospitalizations. The front seat was row 1 and the rear rows 2–3. Vehicle towed from scene and air bag deployed were proxies for crash severity. Injury was dichotomized based on Maximum Abbreviated Injury Severity (MAIS) scores greater than zero. Multivariable logistic regression (odds ratios (OR) with 95% CI) was used to examine factors predictive of injury for the total population and for each age group.ResultsFront-seated children had more frequent injury than those rear-seated (8.46% vs. 4.92%, p < 0.0001). Children in child restraints experienced fewer medically-treated injuries compared to seat belted or unrestrained children (3.80, 6.50 and 13.62%, p < 0.0001 respectively). A higher proportion of children traveling with an unrestrained vs. restrained driver experienced injury (14.50% vs 5.26%, p < 0.0001). After controlling for crash severity, multivariable adjusted predictors of injury for children aged 0–12 years included riding in the front seat (1.20, 1.10–1.31), being unrestrained vs. child restraint (2.13, 1.73–2.62), being restrained in a seat belt vs. child restraint (1.20, 1.11–1.31), and traveling in a car vs. other vehicle type (1.21, 1.14–1.28). Similarly, protective factors included traveling with a restrained driver (0.61, 0.50–0.75), a driver aged < 25 years (0.91, 0.82–0.99), being an occupant of a later vehicle model year 2005–2008 (0.68, 0.53–0.89) or 2009–2015 (0.55, 0.42–0.71) compared to older model years (1970–1993).ConclusionsCompared to front-seated children, rear-seated children and children in age-appropriate restraints had lower adjusted odds of medically-treated injury.

Child occupant injury risk in rear impact and frontal impact: effect of impact conditions and occupant related factors

The rear-facing seat has become a potential seating configuration for the future autonomous vehicle, therefore the potential injury risk of a rear-facing occupant merits further investigation not only for adults, but also for children. The objectives of this study were to compare the child occupant injury risk on specific body regions in frontal and rear impact, and to investigate the effect of those crash conditions and occupant related factors on the occupant injury risk. Data from the NASS–CDS and CISS were studied for crashes during 2000–2019 involving model year 2000–2020 motor vehicles, including frontal and rear–end collision. The injury risk by specific body regions were compared by descriptive statistics. Logistic regression models were developed to examine the effects of various factors on injury risk, controlling for crash type (frontal impact and rear impact), vehicle impact speed, vehicle impact location, vehicle model year, and occupant gender, age, restraint use, and seating position. After controlling for the confounding factors, the children age 3–17 had higher injury risk than infant and toddler (age 0–2) (at MAIS 2+, OR 8.71, p < 0.001). The child occupant injury risk was higher in frontal impact than in rear impact (at MAIS 2+, OR 4.96, p < 0.001), especially for children age 3–17 with the exception of the MAIS 1+ neck/spine injury risk. This study provided child injury risk references for current vehicle which may provide insight to the potential injury risk of rear-facing child occupant in future vehicle configurations.

An evaluation of occupant dynamics during moderate-to-high speed side impacts.

The present study examined trends in occupant dynamics during side impact testing in vehicle models over the past decade. "Moderate-to-high" speed side impacts (delta-V ≥15 km/h) were analyzed. The Insurance Institute for Highway Safety (IIHS) side impact crash data was examined (N = 126). The test procedure involved a moving deformable barrier (MDB) impacting the sides of stationary vehicles at 50.0 km/h. Instrumented 5th-percentile female SID IIs dummies were positioned in the driver and left rear passenger seats. Occupant head, neck, shoulder, torso, spine, and pelvis/femur responses (times histories, peaks, and time-to-peak values) were evaluated and compared to injury assessment reference values (IARVs). The effects of delta-V, vehicle model year, vehicle body type, and occupant seating position on dynamic responses were examined. The vehicle lateral delta-Vs ranged from 15.9 to 34.5 km/h. The MY2018-2020 demonstrated lower peak dynamics than MY2010-2013, for the driver head acceleration (53.7 ± 11.3g vs 46.4 ± 11.6g), shoulder lateral forces (1.7 ± 0.7 kN vs 1.5 ± 0.2 kN), average rib deflection (29.8 ± 8.3 mm vs 28.4 ± 6.2 mm), spine accelerations at T4 (51.4 ± 23.4g vs 39.6 ± 5.9g) and T12 (56.3 ± 18.5g vs 45.2 ± 9.6g), iliac forces (1.9 ± 1.0 kN vs 1.2 ± 0.9 kN), and acetabular forces (1.9 ± 0.8 kN vs 1.3 ± 0.5 kN). The driver indicated statistically higher dynamic responses than the left rear passenger. Higher wheelbase vehicles generally showed lower occupant loading than the smaller vehicles. In conclusion, a reduction in occupant loading and risks for injury was observed in vehicle models over the past decade. This provides further insight into injury mechanisms, occupant dynamics simulations, and seat/restraint design.

Mortality Benefits and Control Costs of Improving Air Quality in Mexico City: The Case of Heavy Duty Diesel Vehicles.

Diesel vehicles are significant contributors to air pollution in Mexico City. We estimate the costs and mortality benefits of retrofitting heavy‐duty vehicles with particulate filters and oxidation catalysts. The feasibility and cost‐effectiveness of controls differ by vehicle model‐year and type. We evaluate 1985 to 2014 model‐year vehicles from 10 vehicle classes and five model‐year groups. Our analysis shows that retrofitting all vehicles with the control that maximizes expected net benefits for that vehicle type and model‐year group has the potential to reduce emissions of primary fine particles (PM2.5) by 950 metric tons/year; cut the population‐weighted annual mean concentration of PM2.5 in Mexico City by 0.90 µg/m3; reduce the annual number of deaths attributable to air pollution by over 80; and generate expected annual health benefits of close to 250 million US$. These benefits outweigh expected costs of 92 million US$ per year. Diesel retrofits are but one step that should viewed in the context of other efforts––such as development of an integrated public transportation system, promotion of the rational use of cars, reduction of emissions from industrial sources and fires, and redesign of the Mexico City Metropolitan Area to reduce urban sprawl––that must be analyzed and implemented to substantially control air pollution and protect public health. Even if considering other potential public health interventions, which would offer greater benefits at the same or lower costs, only by conducting, promoting, and publishing this sort of analyses, we can make strides to improve public health cost‐effectively.

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.