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Motor vehicle crashes involving child Vulnerable Road Users (VRUs) remain a critical public health concern in the United States. While previous studies successfully utilized the crash scenario typology to examine traffic crashes, these studies focus on all types of motor vehicle crashes thus the method might not apply to VRU crashes. Therefore, to better understand the context and causes of child VRU crashes on the U.S. road, this paper proposes a multi-step framework to define crash scenario typology based on the Fatality Analysis Reporting System (FARS) and the Crash Report Sampling System (CRSS). A comprehensive examination of the data elements in FARS and CRSS was first conducted to determine elements that could facilitate crash scenario identification from a systematic perspective. A follow-up context description depicts the typical behavioral, environmental, and vehicular conditions associated with an identified crash scenario.

The Lane Change Task (LCT) provides a simple, scorable simulation of driving, and serves as a primary task in studies of driver distraction. It is widely accepted, but somewhat limited in functionality, a problem this project partially overcomes. In the Lane Change Task, subjects drive along a road with 3 lanes in the same direction. Periodically, signs appear, indicating in which of the 3 lanes the subject should drive, which changes from sign to sign. The software is plug-and-play for a current Windows computer with a Logitech steering/pedal assembly, even though the software was written 18 years ago. For each timestamp in a trial, the software records the steering wheel angle, speed, and x and y coordinates of the subject. A limitation of the LCT is that few characteristics of this useful software can be readily modified as only the executable code is available (on the ISO 26022 website), not the source code.

The automotive industry widely accepted the launch of electric vehicles in the global market, resulting in the emergence of many new areas, including battery health, inverter design, and motor dynamics. Maintaining the desired thermal stress is required to achieve augmented performance along with the optimal design of these components. The HVAC system controls the coolant and refrigerant fluid pressures to maintain the temperatures of [Battery, Inverter, Motor] in a definite range. However, identifying the prominent factors affecting the thermal stress of electric vehicle components and their effect on temperature variation was not investigated in real-time. Therefore, this article defines the vector electric vehicle thermal operating point (EVTHOP) as the first step with three elements [instantaneous battery temperature, instantaneous inverter temperature, instantaneous stator temperature].

Engaging in visual-manual tasks such as selecting a radio station, adjusting the interior temperature, or setting an automation function can be distracting to drivers. Additionally, if setting the automation fails, driver takeover can be delayed. Traditionally, assessing the usability of driver interfaces and determining if they are unacceptably distracting (per the NHTSA driver distraction guidelines and SAE J2364) involves human subject testing, which is expensive and time-consuming. However, most vehicle engineering decisions are based on computational analyses, such as the task time predictions in SAE J2365. Unfortunately, J2365 was developed before touch screens were common in motor vehicles.

With the evolution of telemetry technology in vehicles, Advanced Automatic Collision Notification (AACN), which detects occupants at risk of serious injury in the event of a crash and triages them to the trauma center quickly, may greatly improve their treatment. An Injury Severity Prediction (ISP) algorithm for AACN was developed using a logistic regression model to predict the probability of sustaining an Injury Severity Score (ISS) 15+ injury. National Automotive Sampling System Crashworthiness Data System (NASS-CDS: 1999-2015) and model year 2000 or later were filtered for new case selection criteria, based on vehicle body type, to match Subaru vehicle category. This new proposed algorithm uses crash direction, change in velocity, multiple impacts, seat belt use, vehicle type, presence of any older occupant, and presence of any female occupant.

Tanker trucks are commonly used for transporting liquid material including chemical and petroleum products. On the one hand, tanker trucks are susceptible to rollover accidents due to the high center of gravity when they are loaded and due to the liquid sloshing effects when the tank is partially filled. On the other hand, tanker truck rollover accidents are among the most dangerous vehicle crashes, frequently resulting in serious to fatal driver injuries and significant property damage, because the liquid cargo is often hazardous and flammable. Therefore, effective schemes for tanker truck rollover avoidance are highly desirable and can bring a considerable amount of societal benefit. Yet, the development of such schemes is challenging, as tanker trucks can operate in various environments and be affected by manufacturing variability, aging, degradation, etc. This paper considers the use of Learning Reference Governor (LRG) for tanker truck rollover avoidance.

Knee airbags (KABs) are one countermeasure in newer vehicles that could influence lower extremity (LEX) injury, the most frequently injured body region in frontal crashes. To determine the effect of KABs on LEX injury for drivers in frontal crashes, the analysis examined moderate or greater LEX injury (AIS 2+) in two datasets. Logistic regression considered six main effect factors (KAB deployment, BMI, age, sex, belt status, driver compartment intrusion). Eighty-five cases with KAB deployment from the Crash Injury Research and Engineering Network (CIREN) database were supplemented with 8 cases from the International Center for Automotive Medicine (ICAM) database and compared to 289 CIREN non-KAB cases. All cases evaluated drivers in frontal impacts (11 to 1 o’clock Principal Direction of Force) with known belt use in 2004 and newer model year vehicles. Results of the CIREN/ICAM dataset were compared to analysis of a similar dataset from NASS-CDS (5441 total cases, 418 KAB-deployed).

The current study presents the results of an experiment on driver performance including reaction time, eye-attention movement, mental workload, and subjective preference when different features of Advanced Driver Assistance Systems (ADAS) warnings (Forward Collision Warning) are displayed, including different locations (HDD (Head-Down Display) vs HUD (Head-Up Display)), modality of warning (text vs. pictographic), and a new concept that provides a dynamic bird’s eye view for warnings. Sixteen drivers drove a high-fidelity driving simulator integrated with display prototypes of the features. Independent variables were displayed as modality, location, and dynamics of the warnings with driver performance as the dependent variable including driver reaction time to the warning, EORT (Eyes-Off-Road-Time) during braking after receiving the warning, workload and subject preference.

Previous study suggested that female, thin, obese, and older occupants had a higher risk of death and serious injury in motor vehicle crashes. Human body finite element models were a valuable tool in the study of injury biomechanics. The mesh deformation method based on radial basis function(RBF) was an attractive alternative for morphing baseline model to target models. Generally, when a complex model contained many elements and nodes, it was impossible to use all surface nodes as landmarks in RBF interpolation process, due to its prohibitive computational cost. To improve the efficiency, the current technique was to averagely select a set of nodes as landmarks from all surface nodes. In fact, the location and the number of selected landmarks had an important effect on the accuracy of mesh deformation. Hence, how to select important nodes as landmarks was a significant issue. In the paper, an efficient peak point-selection RBF mesh deformation method was used to select landmarks.

In recent years the U.S. Army Tank-Automotive Research, Development, and Engineering Center (TARDEC) has been investigating the survivability and injury mechanisms of underbody blast and crash, and their effects on personnel, with the use of Anthropomorphic Test Devices (ATD), or crash test dummies. Injury Assessment Reference Values (IARV) for crash have been researched for decades, and the US Army Research Laboratory (ARL), some years ago, also developed IARVs for underbody blast for the Hybrid III 50th percentile ATD. More recently, TARDEC extended these IARVs for the 5th and 95th percentile. With the advent of TARDEC’s Occupant Protection Laboratory large amounts of data were accumulated, which brought an interest in automating the analysis, and so a software tool was developed. The interactive in-house written software, called ICalc, allows the user to open test data files acquired from blast testing, drop tower testing, and crash testing.

Crash safety researchers have an increased concern regarding the decreased thoracic deflection and the contributing injury causation factors among the elderly population. Sternum fractures are categorized as moderate severity injuries, but can have long term effects depending on the fragility and frailty of the occupant. Current research has provided detail on rib morphology, but very little information on sternum morphology, sternum fracture locations, and mechanisms of injury. The objective of this study is two-fold (1) quantify sternum morphology and (2) document sternum fracture locations using computed tomography (CT) scans and crash data. Thoracic CT scans from the University of Michigan Hospital database were used to measure thoracic depth, manubriosternal joint, sternum thickness and bone density. The sternum fracture locations and descriptions were extracted from 63 International Center for Automotive Medicine (ICAM) crash cases, of which 22 cases had corresponding CT scans.

Natural fiber-reinforced composites are currently gaining increasing attention as potential substitutes to pervasive synthetic fiber-reinforced composites, particularly glass fiber-reinforced plastics (GFRP). The advantages of the former category of composites include (a) being conducive to occupational health and safety during fabrication of parts as well as handling as compared to GFRP, (b) economy especially when compared to carbon fiber-reinforced composites (CFRC), (c) biodegradability of fibers, and (d) aesthetic appeal. Jute fibers are especially relevant in this context as jute fabric has a consistent supply base with reliable mechanical properties. Recent studies have shown that components such as tubes and plates made of jute-polyester (JP) composites can have competitive performance under impact loading when compared with similar GFRP-based structures.

The purpose of this study was to use detailed medical information to evaluate thoracic injuries in elderly patients in real world frontal crashes. In this study, we used analytic morphomics to predict the effect of torso geometry on rib fracture, a major source of injury for the elderly. Analytic morphomics extracts body features from computed tomography (CT) scans of patients in a semi-automated fashion. Thoracic injuries were examined in front row occupants involved in frontal crashes from the International Center for Automotive Medicine (ICAM) database. Among these occupants, two age groups (age < 60 yr. [Nonelderly] and age ≥ 60 yr. [Elderly]) who suffered severe thoracic injury were analyzed. Regression analyses were conducted to investigate injury outcomes using variables for vehicle, demographics, and morphomics. Compared to the nonelderly group, the elderly group sustained more rib fractures.

In order to improve the comprehensive protection for children with variable shapes and sizes, this paper conducted studies on the impact injury for obese children based on a 10-YO finite element model. Some specific geometrics on the body surface were firstly acquired by the combination of pediatric anthropometric database and generator of body (GEBOD). A Radial Basis Function (RBF) based mesh morphing technique was then used to modify the original standard size FE model using the obtained geometrics. The morphed FE model was validated based on the experimental data of frontal sled test and chest-abdomen impact test. The effects of obesity on injury performances were analyzed through simplified high-speed and low-speed crash simulations.

In order to provide an improved countermeasure for occupant protection, a new type of active reversible preload seatbelt (ARPS) is presented in this paper. The ARPS is capable of protecting occupants by reducing injuries during frontal collisions. ARPS retracts seatbelt webbing by activating an electric motor attached to the seatbelt retractor. FCW (Forward Collision Warning) and LDW (Lane Departure Warning) provide signals as a trigger to activate the electric motor to retract the seatbelt webbing, thus making the occupant restraint system work more effectively in a crash. It also helps reduce occupant’s forward movement during impact process via braking. Four important factors such as preload force, preload velocity and the length and timing of webbing retraction play influential roles in performance of the ARPS. This paper focuses on studying preload performance of ARPS under various test conditions to investigate effects of the aforementioned factors.

Computational human body models, especially detailed finite element models are suitable for investigation of human body kinematic responses and injury mechanism. A real-world lateral vehicle-tree impact accident was reconstructed by using finite element method according to the accident description in the CIREN database. At first, a baseline vehicle FE model was modified and validated according to the NCAP lateral impact test. The interaction between the car and the tree in the accident was simulated using LS-Dyna software. Parameters that affect the simulation results, such as the initial pre-crash speed, impact direction, and the initial impact location on the vehicle, were analyzed. The parameters were determined by matching the simulated vehicle body deformations and kinematics to the accident reports.

We have recently obtained experimental data and used them to develop computational models to quantify occupant impact responses and injury risks for military vehicles during frontal crashes. The number of experimental tests and model runs are however, relatively small due to their high cost. While this is true across the auto industry, it is particularly critical for the Army and other government agencies operating under tight budget constraints. In this study we investigate through statistical simulations how the injury risk varies if a large number of experimental tests were conducted. We show that the injury risk distribution is skewed to the right implying that, although most physical tests result in a small injury risk, there are occasional physical tests for which the injury risk is extremely large. We compute the probabilities of such events and use them to identify optimum design conditions to minimize such probabilities.

Periprosthetic fractures refer to the fractures that occur in the vicinity of the implants of joint replacement arthroplasty. Most of the fractures during an automotive frontal collision involve the long bones of the lower limbs (femur and tibia). Since the prevalence of persons living with lower limb joint prostheses is increasing, periprosthetic fractures that occur during vehicular accidents are likely to become a considerable burden on health care systems. It is estimated that approximately 4.0 million adults in the U.S. currently live with Total Knee Replacement (TKR) implants. Therefore, it is essential to study the injury patterns that occur in the long bone of a lower limb containing a total knee prosthesis. The aim of the present study is to develop an advanced finite element model that simulates the possible fracture patterns that are likely during vehicular accidents involving occupants who have knee joint prostheses in situ.

Numerical models of Hybrid III had been widely used to study the effect of underbody blast loading on lower extremities. These models had been primarily validated for automotive loading conditions of shorter magnitude in longer time span which are different than typical blast loading conditions of higher magnitude of shorter duration. Therefore, additional strain rate dependent material models were used to validate lower extremity of LSTC Hybrid III model for such loading conditions. Current study focuses on analyzing the mitigating effect of combat boots in injury responses with the help of validated LSTC Hybrid III model. Numerical simulations were run for various impactor speeds using validated LSTC Hybrid III model without any boot (bare foot) and with combat boot.

In the elderly population, rib fracture is one of the most common injuries sustained in motor vehicle crashes. The current study was conducted to predict the biomechanical fracture responses of ribs with respect to age, gender, height, weight and percentage of ash content. Three-point bending experiments were conducted on 278 isolated rib samples extracted from 82 cadaver specimens (53 males and 29 females between the ages of 21 and 87 years) for 6th and 7th levels of ribs. Statistical analyses were carried out to identify differences based on age and gender. It was found that, in comparison to males, females had significantly lower values for maximum bending moments, slopes of bending moment-angle curves, and average cortical-bone thickness (p < 0.05). Samples of ribs taken from elderly specimens failed at lower values of fracture moments than those from younger specimens, and had lower slopes of bending moment-angle curves, both in males and females (p < 0.05).