Differences in Long-term Medical Consequences Depending on Impact Direction Involving Passenger Cars

Objective: There is limited knowledge of the long-term medical consequences for occupants injured in car crashes in various impact directions. Thus, the objective was to evaluate whether injuries leading to permanent medical impairment differ depending on impact direction.

Methods: In total, 36,743 injured occupants in car crashes that occurred between 1995 and 2011 were included. All initial injuries (n = 61,440) were classified according to the Abbreviated Injury Scale (AIS) 2005. Injured car occupants were followed for at least 3 years to assess permanent medical impairment. The data were divided into different groups according to impact direction and levels of permanent impairment. The risk of permanent medical impairment was established for different body regions and injury severity levels, according to AIS.

Results: It was found that almost 12% of all car occupants sustained a permanent medical impairment. Given an injury, car occupants involved in rollover crashes had the highest overall risk to sustain a permanent medical impairment. Half of the head injuries leading to long-term consequences occurred in frontal impacts. Far-side occupants had almost the same risk as near-side occupants. Occupants who sustained a permanent medical impairment from cervical spine injuries had similar risk in all impact directions (13%) except from rollover (17%). However, these injuries occurred more often in rear crashes. Most of the injuries leading to long-term consequences were classified as minor injuries by AIS for all impact directions.

Conclusions: Studying crash data from a perspective of medical impairment is important to identify injuries that might not be prioritized only considering the AIS but might lead to lower quality of life for the occupant and also costs for society. These results can be used for road transport system strategies and for making priority decisions in vehicle design.     

Driver Injury Risk Variability in Finite Element Reconstructions of Crash Injury Research and Engineering Network (CIREN) Frontal Motor Vehicle Crashes

Objective: A 3-phase real-world motor vehicle crash (MVC) reconstruction method was developed to analyze injury variability as a function of precrash occupant position for 2 full-frontal Crash Injury Research and Engineering Network (CIREN) cases.

Method: Phase I: A finite element (FE) simplified vehicle model (SVM) was developed and tuned to mimic the frontal crash characteristics of the CIREN case vehicle (Camry or Cobalt) using frontal New Car Assessment Program (NCAP) crash test data. Phase II: The Toyota HUman Model for Safety (THUMS) v4.01 was positioned in 120 precrash configurations per case within the SVM. Five occupant positioning variables were varied using a Latin hypercube design of experiments: seat track position, seat back angle, D-ring height, steering column angle, and steering column telescoping position. An additional baseline simulation was performed that aimed to match the precrash occupant position documented in CIREN for each case. Phase III: FE simulations were then performed using kinematic boundary conditions from each vehicle's event data recorder (EDR). HIC15, combined thoracic index (CTI), femur forces, and strain-based injury metrics in the lung and lumbar vertebrae were evaluated to predict injury.

Results: Tuning the SVM to specific vehicle models resulted in close matches between simulated and test injury metric data, allowing the tuned SVM to be used in each case reconstruction with EDR-derived boundary conditions. Simulations with the most rearward seats and reclined seat backs had the greatest HIC15, head injury risk, CTI, and chest injury risk. Calculated injury risks for the head, chest, and femur closely correlated to the CIREN occupant injury patterns. CTI in the Camry case yielded a 54% probability of Abbreviated Injury Scale (AIS) 2+ chest injury in the baseline case simulation and ranged from 34 to 88% (mean = 61%) risk in the least and most dangerous occupant positions. The greater than 50% probability was consistent with the case occupant's AIS 2 hemomediastinum. Stress-based metrics were used to predict injury to the lower leg of the Camry case occupant. The regional-level injury metrics evaluated for the Cobalt case occupant indicated a low risk of injury; however, strain-based injury metrics better predicted pulmonary contusion. Approximately 49% of the Cobalt occupant's left lung was contused, though the baseline simulation predicted 40.5% of the lung to be injured.

Conclusions: A method to compute injury metrics and risks as functions of precrash occupant position was developed and applied to 2 CIREN MVC FE reconstructions. The reconstruction process allows for quantification of the sensitivity and uncertainty of the injury risk predictions based on occupant position to further understand important factors that lead to more severe MVC injuries.     

Estimated Injury Risk for Specific Injuries and Body Regions in Frontal Motor Vehicle Crashes

Objective: Injury risk curves estimate motor vehicle crash (MVC) occupant injury risk from vehicle, crash, and/or occupant factors. Many vehicles are equipped with event data recorders (EDRs) that collect data including the crash speed and restraint status during a MVC. This study's goal was to use regulation-required data elements for EDRs to compute occupant injury risk for (1) specific injuries and (2) specific body regions in frontal MVCs from weighted NASS-CDS data.

Methods: Logistic regression analysis of NASS-CDS single-impact frontal MVCs involving front seat occupants with frontal airbag deployment was used to produce 23 risk curves for specific injuries and 17 risk curves for Abbreviated Injury Scale (AIS) 2+ to 5+ body region injuries. Risk curves were produced for the following body regions: head and thorax (AIS 2+, 3+, 4+, 5+), face (AIS 2+), abdomen, spine, upper extremity, and lower extremity (AIS 2+, 3+). Injury risk with 95% confidence intervals was estimated for 15–105 km/h longitudinal delta-Vs and belt status was adjusted for as a covariate.

Results: Overall, belted occupants had lower estimated risks compared to unbelted occupants and the risk of injury increased as longitudinal delta-V increased. Belt status was a significant predictor for 13 specific injuries and all body region injuries with the exception of AIS 2+ and 3+ spine injuries. Specific injuries and body region injuries that occurred more frequently in NASS-CDS also tended to carry higher risks when evaluated at a 56 km/h longitudinal delta-V. In the belted population, injury risks that ranked in the top 33% included 4 upper extremity fractures (ulna, radius, clavicle, carpus/metacarpus), 2 lower extremity fractures (fibula, metatarsal/tarsal), and a knee sprain (2.4–4.6% risk). Unbelted injury risks ranked in the top 33% included 4 lower extremity fractures (femur, fibula, metatarsal/tarsal, patella), 2 head injuries with less than one hour or unspecified prior unconsciousness, and a lung contusion (4.6–9.9% risk). The 6 body region curves with the highest risks were for AIS 2+ lower extremity, upper extremity, thorax, and head injury and AIS 3+ lower extremity and thorax injury (15.9–43.8% risk).

Conclusions: These injury risk curves can be implemented into advanced automatic crash notification (AACN) algorithms that utilize vehicle EDR measurements to predict occupant injury immediately following a MVC. Through integration with AACN, these injury risk curves can provide emergency medical services (EMS) and other patient care providers with information on suspected occupant injuries to improve injury detection and patient triage.     

Evaluation of Vehicle-Based Crash Severity Metrics

Objective: Vehicle change in velocity (delta-v) is a widely used crash severity metric used to estimate occupant injury risk. Despite its widespread use, delta-v has several limitations. Of most concern, delta-v is a vehicle-based metric which does not consider the crash pulse or the performance of occupant restraints, e.g. seatbelts and airbags. Such criticisms have prompted the search for alternative impact severity metrics based upon vehicle kinematics. The purpose of this study was to assess the ability of the occupant impact velocity (OIV), acceleration severity index (ASI), vehicle pulse index (VPI), and maximum delta-v (delta-v) to predict serious injury in real world crashes.

Methods: The study was based on the analysis of event data recorders (EDRs) downloaded from the National Automotive Sampling System / Crashworthiness Data System (NASS-CDS) 2000–2013 cases. All vehicles in the sample were GM passenger cars and light trucks involved in a frontal collision. Rollover crashes were excluded. Vehicles were restricted to single-event crashes that caused an airbag deployment. All EDR data were checked for a successful, completed recording of the event and that the crash pulse was complete. The maximum abbreviated injury scale (MAIS) was used to describe occupant injury outcome. Drivers were categorized into either non-seriously injured group (MAIS2?) or seriously injured group (MAIS3+), based on the severity of any injuries to the thorax, abdomen, and spine. ASI and OIV were calculated according to the Manual for Assessing Safety Hardware. VPI was calculated according to ISO/TR 12353-3, with vehicle-specific parameters determined from U.S. New Car Assessment Program crash tests. Using binary logistic regression, the cumulative probability of injury risk was determined for each metric and assessed for statistical significance, goodness-of-fit, and prediction accuracy.

Results: The dataset included 102,744 vehicles. A Wald chi-square test showed each vehicle-based crash severity metric estimate to be a significant predictor in the model (p < 0.05). For the belted drivers, both OIV and VPI were significantly better predictors of serious injury than delta-v (p < 0.05). For the unbelted drivers, there was no statistically significant difference between delta-v, OIV, VPI, and ASI.

Conclusions: The broad findings of this study suggest it is feasible to improve injury prediction if we consider adding restraint performance to classic measures, e.g. delta-v. Applications, such as advanced automatic crash notification, should consider the use of different metrics for belted versus unbelted occupants.     

Serious road injuries in The Netherlands dissected

Objective: This article discusses the characteristics and injury patterns of serious road injuries (Maximum Abbreviated Injury Scale [MAIS] 2+ inpatients) in The Netherlands.

Methods: In The Netherlands, the actual number of serious injuries is estimated by linking police data to hospital data. The distribution of serious road injuries over (1) travel mode and gender and (2) crash type and age are compared for the years 2000 and 2011. Moreover, the distribution of the injuries over the body regions is illustrated using colored injury body profiles.

Results: The number of serious injuries is higher for men than for women and increased from 16,500 in 2000 to 19,700 in 2011. In 2011, about half (51%) of the serious road injuries were due to a bicycle crash not involving a motor vehicle. The share of casualties aged 60 years and older is relatively high (43% in 2011) in these crashes. The injury body profiles show that head injuries (31%) and injuries to the lower extremities (37%) are most prevalent. Compared to other travel modes, pedestrians and riders of powered 2-wheelers relatively often sustain lower-leg injuries compared to other travel modes. Head injuries are most prevalent in cyclists who are injured in a crash with a motorized vehicle. Cyclists who are injured in a crash not involving a motor vehicle and casualties of 60 years and older relatively often include hip or upper-leg injuries.

Conclusion: The characteristics of serious road injuries differ from those of fatalities and the distribution of injuries over the body differs by travel mode, gender, and age.     

Health burden of serious road injuries in the Netherlands

Background: The consequences of injuries in terms of disabilities and health burden are relevant for policy making. This article provides an overview of the current knowledge on this topic and discusses the health burden of serious road injuries in The Netherlands.

Methods: The overview of current knowledge on disabilities following a road crash is based on a literature review. The health burden of serious road injuries is quantified in terms of years lived with disability (YLD), by combining incidence data from the Dutch hospital discharge register with information about temporary and lifelong disability.

Results: Literature shows that road traffic injuries can have a major impact on victims' physical and psychological well-being and functioning. Reported proportions of people with disability vary between 11 and 80% depending on the type of casualties, time elapsed since the crash, and the health impacts considered. Together, all casualties involving serious injuries in The Netherlands in 2009 account for about 38,000 YLD, compared to 25,000 years of life lost (YLL) of fatalities. Ninety percent of the burden of injury is due to lifelong consequences that are experienced by 20% of all those seriously injured in road accidents. Lower leg injuries and head injuries represent a high share in the total burden of injury as have cyclists that are injured in a crash without a motorized vehicle. Pedestrians and powered 2-wheeler users show the highest burden of injury per casualty.

Conclusion: Given their major impacts and contribution to health burden, road policy making should also be aimed at reducing the number of serious road injuries and limiting the resulting health impacts.     

Injury Outcome in Crashes with Guardrail End Terminals

Objective: The goal of this study is to evaluate the crash performance of guardrail end terminals in real-world crashes. Guardrail end terminals are installed at the ends of guardrail systems to prevent the rail from spearing through the car in an end-on collision. Recently, there has been a great deal of controversy as to the safety of certain widely used end terminal designs, partly because there is surprisingly little real-world crash data for end terminals. Most existing studies of end terminal crashes used data from prior to the mid-1990s. Since then, there have been large improvements to vehicle crashworthiness and seat belt usage rates, as well as new roadside safety hardware compliant with National Cooperative Highway Research Program (NCHRP) Report 350, “Recommended Procedures for the Safety Performance Evaluation of Highway Features.” Additionally, most existing studies of injury in end terminal crashes do not account for factors such as the occurrence of rollover. This analysis uses more recent crash data that represent post-1990s vehicle fleet changes and account for a number of factors that may affect driver injury outcome and rollover occurrence.

Methods: Passenger vehicle crashes coded as involving guardrail end terminals were identified in the set of police-reported crashes in Michigan in 2011 and 2012. End terminal performance was expected to be a function of end terminal system design. State crash databases generally do not identify specific end terminal systems. In this study, the coded crash location was used to obtain photographs of the crash site prior to the crash from Google Street View. These site photographs were manually inspected to identify the particular end terminal system involved in the crash. Multiple logistic regression was used to test for significant differences in the odds of driver injury and rollover between different terminal types while accounting for other factors.

Results: A total of 1,001 end terminal crashes from the 2011–2012 Michigan State crash data were manually inspected to identify the terminal that had been struck. Four hundred fifty-one crashes were found to be suitable for analysis. Serious to fatal driver injury occurred in 3.8% of end terminal crashes, moderate to fatal driver injury occurred in 11.8%, and 72.3% involved property damage only. No significant difference in moderate to fatal driver injury odds was observed between NCHRP 350 compliant end terminals and noncompliant terminals. Car drivers showed odds of moderate to fatal injury 3.6 times greater than LTV drivers in end terminal crashes. Rollover occurrence was not significantly associated with end terminal type.

Conclusions: Car drivers have greater potential for injury in end terminal crashes than light truck/van/sport utility vehicle drivers. End terminal designs compliant with NCHRP 350 did not appear to carry different odds of moderate driver injury than noncompliant end terminals. The findings account for driver seat belt use, rollover occurrence, terminal orientation (leading/trailing), control loss, and the number of impact events. Rollover and nonuse of seat belts carried much larger increases in injury potential than end terminal type. Rollover did not appear to be associated with NCHRP 350 compliance.     

Census Study of Real-Life Near-Side Crashes with Modern Side Airbag-Equipped Vehicles in the United States

Objective: This study aimed to investigate the crash characteristics, injury distribution, and injury mechanisms for Maximum Abbreviated Injury Score (MAIS) 2+ injured belted, near-side occupants in airbag-equipped modern vehicles. Furthermore, differences in injury distribution for senior occupants compared to non-senior occupants was investigated, as well as whether the near-side occupant injury risk to the head and thorax increases or decreases with a neighboring occupant.

Method: National Automotive Sampling System's Crashworthiness Data System (NASS-CDS) data from 2000 to 2012 were searched for all side impacts (GAD L&R, all principal direction of force) for belted occupants in modern vehicles (model year > 1999). Rollovers were excluded, and only front seat occupants over the age of 10 were included. Twelve thousand three hundred fifty-four MAIS 2+ injured occupants seated adjacent to the intruding structure (near-side) and protected by at least one deployed side airbag were studied. To evaluate the injury risk influenced by the neighboring occupant, odds ratio with an induced exposure approach was used.

Result: The most typical crash occurred either at an intersection or in a left turn where the striking vehicle impacted the target vehicle at a 60 to 70° angle, resulting in a moderate change of velocity (delta-V) and intrusion at the B-pillar. The head, thorax, and pelvis were the most frequent body regions with rib fracture the most frequent specific injury. A majority of the head injuries included brain injuries without skull fracture, and non-senior rather than senior occupants had a higher frequency of head injuries on the whole. In approximately 50% of the cases there was a neighboring occupant influencing injury outcome.

Conclusion: Compared to non-senior occupants, the senior occupants sustained a considerably higher rate of thoracic and pelvis injuries, which should be addressed by improved thorax side airbag protection. The influence on near-side occupant injury risk by the neighboring occupant should also be further evaluated. Furthermore, side airbag performance and injury assessments in intersection crashes, especially those involving senior occupants in lower severities, should be further investigated and side impact dummy biofidelity and injury criteria must be determined for these crash scenarios.     

Development of injury risk models to guide CT evaluation in the emergency department after motor vehicle collisions

Abstract

Objective: The clinical evaluation of motor vehicle collision (MVC) victims is challenging and commonly relies on computed tomography (CT) to detect internal injuries. CT scans are financially expensive and each scan exposes the patient to additional ionizing radiation with an associated, albeit low, risk of cancer. Injury risk prediction based on regression modeling has been to be shown to be successful in estimating Injury Severity Scores (ISSs). The objective of this study was to (1) create risk models for internal injuries of occupants involved in MVCs based on CT body regions (head, neck, chest, abdomen/pelvis, cervical spine, thoracic spine, and lumbar spine) and (2) evaluate the performance of these risk prediction models to predict internal injury.

Methods: All Abbreviated Injury Scale (AIS) 2008 injury codes were classified based on which CT body region would be necessary to scan in order to make the diagnosis. Cases were identified from the NASS-CDS. The NASS-CDS data set was queried for cases of adult occupants who sought medical care and for which key crash characteristics were all present. Forward stepwise logistic regression was performed on data from 2010–2014 to create models predicting risk of internal injury for each CT body region. Injury risk for each region was grouped into 5 levels: very low (<2%), low (2–5%), medium (5–10%), high (10–20%), and very high (20%). The models were then tested using weighted data from 2015 in order to determine whether injury rates fell within the predicted risk level.

Results: The inclusion and exclusion criteria identified 5,477 cases in the NASS-CDS database. Cases from 2010–2014 were used for risk modeling (n?=?4,826). Seven internal injury risk models were created based on the CT body regions using data from 2010–2014. These models were tested against data from 2015 (n?=?651). In all CT body regions, the majority of occupants fell in the very low or low predicted injury rate groups, except for the head. On average, 57% of patients were classified as very low risk and 15% as low risk for each body region. In most cases the actual rate of injury was within the predicted injury risk range. The 95% confidence interval overlapped with predicting injury risk range in all cases.

Conclusion: This study successfully demonstrated the ability for internal injury risk models to accurately identify occupants at low risk for internal injury in individual body regions. This represents a step towards incorporating telemetry data into a clinical tool to guide physicians in the use of CT for the evaluation of MVC victims.     

Role of age and injury mechanism on cervical spine injury tolerance from head contact loading

Objective: The objective of this study was to determine the influence of age and injury mechanism on cervical spine tolerance to injury from head contact loading using survival analysis.

Methods: This study analyzed data from previously conducted experiments using post mortem human subjects (PMHS). Group A tests used the upright intact head–cervical column experimental model. The inferior end of the specimen was fixed, the head was balanced by a mechanical system, and natural lordosis was removed. Specimens were placed on a testing device via a load cell. The piston applied loading at the vertex region. Spinal injuries were identified using medical images. Group B tests used the inverted head–cervical column experimental model. In one study, head–T1 specimens were fixed distally, and C7–T1 joints were oriented anteriorly, preserving lordosis. Torso mass of 16 kg was added to the specimen. In another inverted head–cervical column study, occiput–T2 columns were obtained, an artificial head was attached, T1–T2 was fixed, C4–C5 disc was maintained horizontal in the lordosis posture, and C7–T1 was unconstrained. The specimens were attached to the drop test carriage carrying a torso mass of 15 kg. A load cell at the inferior end measured neck loads in both studies. Axial neck force and age were used as the primary response variable and covariate to derive injury probability curves using survival analysis.

Results: Group A tests showed that age is a significant (P < .05) and negative covariate; that is, increasing age resulted in decreasing force for the same risk. Injuries were mainly vertebral body fractures and concentrated at one level, mid-to-lower cervical spine, and were attributed to compression-related mechanisms. However, age was not a significant covariate for the combined data from group B tests. Both group B tests produced many soft tissue injuries, at all levels, from C1 to T1. The injury mechanism was attributed to mainly extension. Multiple and noncontiguous injuries occurred. Injury probability curves, ±95% confidence intervals, and normalized confidence interval sizes representing the quality of the mean curve are given for different data sets.

Conclusions: For compression-related injuries, specimen age should be used as a covariate or individual specimen data may be prescaled to derive risk curves. For distraction- or extension-related injuries, however, specimen age need not be used as a covariate in the statistical analysis. The findings from these tests and survival analysis indicate that the age factor modulates human cervical spine tolerance to impact injury.     

Analysis of rider and child pillion passenger kinematics along with injury mechanisms during motorcycle crash

Abstract

Objective: Traffic fatalities among motorcycle users are intolerably high in Thailand. They account for 73% of the total number of road fatalities. Children are also among these victims. To improve countermeasures and design of protection equipment, understanding the biomechanics of motorcycle users under impact conditions is necessary. The objective of this work is to analyze the overall kinematics and injuries sustained by riders and child pillion passengers in various accident configurations.

Methods: Motorcycle accident data were analyzed. Common accident scenarios and impact parameters were identified. Two numerical approaches were employed. The multibody model was validated with a motorcycle crash test and used to generate possible accident cases for various impact conditions specified to cover all common accident scenarios. Specific impact conditions were selected for detailed finite element analysis. The finite element simulations of motorcycle-to-car collisions were conducted to provide insight into kinematics and injury mechanisms.

Results: Global kinematics found when the motorcycle’s front wheel impacts a car (config-MC) highlighted the translation motion of both the rider and passenger toward the impact position. The rider’s trunk impacted the handlebar and the head either impacted the car or missed. The hood constituted the highest head impact occurrence for this configuration. The child mostly impacted the rider’s back. Different kinematics were found when car impacted the lateral side of the motorcycle (config-CM). Upper bodies of both rider and child were laterally projected toward the car front. The windshield constituted the highest proportion of head impacts. The hood and A-pillar recorded a moderate proportion. The rider in finite element simulations with config-MC experienced high rib stress, lung strain, and pressure beyond the injury limit. A high head injury criterion was observed when the head hit the car. However, the simulation with config-CM exhibited high lower extremities stress and lung pressure in both occupants. Hyperextension of the rider’s neck was observed. The cumulative strain damage measure of the child’s brain was higher than the threshold for diffuse axonal injury (DAI).

Conclusions: This study revealed 2 kinematics patterns and injury mechanisms. Simulations with config-MC manifested a high risk of head and thorax injury to the rider but a low risk of severe injury to the child. Thorax injury to the rider due to handlebar impact was only found in simulations with config-MC. However, a high risk of skull, lower extremity, brain, and neck injuries were more pronounced for cases with config-CM. A high risk of DAI was also noticed for the child. In simulations with config-CM the child exhibited a higher risk of severe injury.     

Development and Validation of the Total HUman Model for Safety (THUMS) Toward Further Understanding of Occupant Injury Mechanisms in Precrash and During Crash

Objective: Active safety devices such as automatic emergency brake (AEB) and precrash seat belt have the potential to accomplish further reduction in the number of the fatalities due to automotive accidents. However, their effectiveness should be investigated by more accurate estimations of their interaction with human bodies. Computational human body models are suitable for investigation, especially considering muscular tone effects on occupant motions and injury outcomes. However, the conventional modeling approaches such as multibody models and detailed finite element (FE) models have advantages and disadvantages in computational costs and injury predictions considering muscular tone effects. The objective of this study is to develop and validate a human body FE model with whole body muscles, which can be used for the detailed investigation of interaction between human bodies and vehicular structures including some safety devices precrash and during a crash with relatively low computational costs.

Methods: In this study, we developed a human body FE model called THUMS (Total HUman Model for Safety) with a body size of 50th percentile adult male (AM50) and a sitting posture. The model has anatomical structures of bones, ligaments, muscles, brain, and internal organs. The total number of elements is 281,260, which would realize relatively low computational costs. Deformable material models were assigned to all body parts. The muscle–tendon complexes were modeled by truss elements with Hill-type muscle material and seat belt elements with tension-only material. The THUMS was validated against 35 series of cadaver or volunteer test data on frontal, lateral, and rear impacts. Model validations for 15 series of cadaver test data associated with frontal impacts are presented in this article. The THUMS with a vehicle sled model was applied to investigate effects of muscle activations on occupant kinematics and injury outcomes in specific frontal impact situations with AEB.

Results and Conclusions: In the validations using 5 series of cadaver test data, force–time curves predicted by the THUMS were quantitatively evaluated using correlation and analysis (CORA), which showed good or acceptable agreement with cadaver test data in most cases. The investigation of muscular effects showed that muscle activation levels and timing had significant effects on occupant kinematics and injury outcomes. Although further studies on accident injury reconstruction are needed, the THUMS has the potential for predictions of occupant kinematics and injury outcomes considering muscular tone effects with relatively low computational costs.     

Cervical and thoracic spine injury in pediatric motor vehicle crash passengers

Objective: Motor vehicle occupants aged 8 to 12 years are in transition, in terms of both restraint use (booster seat or vehicle belt) and anatomical development. Rear-seated occupants in this age group are more likely to be inappropriately restrained than other age groups, increasing their vulnerability to spinal injury. The skeletal anatomy of an 8- to 12-year-old child is also in developmental transition, resulting in spinal injury patterns that are unique to this age group. The objective of this study is to identify the upper spine injuries commonly experienced in the 8- to 12-year-old age group so that anthropomorphic test devices (ATDs) representing this size of occupant can be optimized to predict the risk of these injuries.

Methods: Motor vehicle crash cases from the National Trauma Data Bank (NTDB) were analyzed to characterize the location and nature of cervical and thoracic spine injuries in 8- to 12-year-old crash occupants compared to younger (age 0–7) and older age groups (age 13–19, 20–39).

Results: Spinal injuries in this trauma center data set tended to occur at more inferior vertebral levels with older age, with patients in the 8- to 12-year-old group diagnosed with thoracic injury more frequently than cervical injury, in contrast to younger occupants, for whom the proportion of cases with cervical injury outnumbered the proportion of cases with thoracic injury. With the cervical spine, a higher proportion of 8- to 12-year-olds had upper spine injury than adults, but a substantially lower proportion of 8- to 12-year-olds had upper spine injury than younger children. In terms of injury type, the 8- to 12-year-old group’s injury patterns were more similar to those of teens and adults, with a higher relative proportion of fracture than younger children, who were particularly vulnerable to dislocation and soft tissue injuries. However, unlike for adults and teens, catastrophic atlanto-occipital dislocations were still more common than any other type of dislocation for 8- to 12-year-olds and vertebral body fractures were particularly frequent in this age group.

Conclusions: Spinal injury location in the cervical and thoracic spine moved downward with age in this trauma center data set. This shift in injury pattern supports the need for measurement of thoracic and lower cervical spine loading in ATDs representing the 8- to 12-year-old age group.     

Overview of a combined computational–experimental evaluation for the assessment of panoramic sunroof impact characteristics for ejection mitigation

Abstract

Objective: To meet increasing customer demand, many vehicle manufacturers are now offering a panoramic sunroof option in their vehicle lineup. Currently, there is no regulatory or consumer test aimed at assessing the potential for ejection mitigation of roof glazing, which leaves manufacturers to develop internal performance standards to guide designs. The goal of this study was to characterize the variety of occupant-to-roof impacts involving unbelted occupants in rollover crashes to determine the ranges of possible effective masses and impact velocities. This information can be used to define occupant retention requirements and performance criteria for roof glazing in occupant ejection protection.

Methods: This study combined computational (MADYMO and LS-Dyna) simulations of occupant kinematics in rollover crashes with laboratory rollover crash tests using the dynamic rollover test system (DRoTS) and linked them through controlled anthropomorphic test device (ATD)-to-roof (“drop”) impact tests. The DRoTS and the ATD drop tests were performed to explore impact scenarios and estimate dummy-to-roof impact impulses. Next, 13 sets of vehicle kinematics and deformation data were extracted from a combination of vehicle dynamics and finite element model simulations that reconstructed variations of rollover crash cases from the field data. Then occupant kinematics data were extracted from a full-factorial sensitivity study that used MADYMO simulations to investigate how changes in anthropometry and seating position would affect occupant–roof impacts across all 13 cases. Finite element (FE) simulations of ATD and Global Human Body Models Consortium (GHBMC) human body model (HBM) roof impacts were performed to investigate the most severe cases from the MADYMO simulations to generate a distribution of head-to-roof impact energies.

Results: From the multiparameter design of experiment and experimental study, kinematics and energy output were extracted and analyzed. Based on dummy-to-roof impact force and dummy-to-roof impact velocity, the most severe rollover scenarios were identified. In the DRoTS experiments followed by the drop tests, the range of identified impact velocities was between 2 and 5.8 m/s. However, computational simulations of the rollover crashes showed higher impact velocities and similar effective masses. The largest dummy-to-roof impact velocity was 11 m/s.

Conclusions: This study combined computational and experimental analyses to determine a range of possible unbelted occupant-to-roof impact energies. These results can be used to determine design parameters for an impactor for the assessment of the risk of roof glazing ejection for unbelted occupants in rollover crashes.     

Evaluation of geometrically personalized THUMS pedestrian model response against sedan–pedestrian PMHS impact test data

Objective: Evaluating the biofidelity of pedestrian finite element models (PFEM) using postmortem human subjects (PMHS) is a challenge because differences in anthropometry between PMHS and PFEM could limit a model's capability to accurately capture cadaveric responses. Geometrical personalization via morphing can modify the PFEM geometry to match the specific PMHS anthropometry, which could alleviate this issue. In this study, the Total Human Model for Safety (THUMS) PFEM (Ver 4.01) was compared to the cadaveric response in vehicle–pedestrian impacts using geometrically personalized models.

Methods: The AM50 THUMS PFEM was used as the baseline model, and 2 morphed PFEM were created to the anthropometric specifications of 2 obese PMHS used in a previous pedestrian impact study with a mid-size sedan. The same measurements as those obtained during the PMHS tests were calculated from the simulations (kinematics, accelerations, strains), and biofidelity metrics based on signals correlation (correlation and analysis, CORA) were established to compare the response of the models to the experiments. Injury outcomes were predicted deterministically (through strain-based threshold) and probabilistically (with injury risk functions) and compared with the injuries reported in the necropsy.

Results: The baseline model could not accurately capture all aspects of the PMHS kinematics, strain, and injury risks, whereas the morphed models reproduced biofidelic response in terms of trajectory (CORA score = 0.927 ± 0.092), velocities (0.975 ± 0.027), accelerations (0.862 ± 0.072), and strains (0.707 ± 0.143). The personalized THUMS models also generally predicted injuries consistent with those identified during posttest autopsy.

Conclusions: The study highlights the need to control for pedestrian anthropometry when validating pedestrian human body models against PMHS data. The information provided in the current study could be useful for improving model biofidelity for vehicle–pedestrian impact scenarios.     

The Contribution of Pre-impact Posture on Restrained Occupant Finite Element Model Response in Frontal Impact

Objective: The objective of this study was to discuss the influence of the pre-impact posture to the response of a finite element human body model (HBM) in frontal impacts.

Methods: This study uses previously published cadaveric tests (PMHS), which measured six realistic pre-impact postures. Seven postured models were created from the THUMS occupant model (v4.0): one matching the standard UMTRI driving posture as it was the target posture in the experiments, and six matching the measured pre-impact postures. The same measurements as those obtained during the cadaveric tests were calculated from the simulations, and biofidelity metrics based on signals correlation (CORA) were established to compare the response of the seven models to the experiments.

Results: The HBM responses showed good agreement with the PMHS responses for the reaction forces (CORA = 0.80 ± 0.05) and the kinematics of the lower part of the torso but only fair correlation was found with the head, the upper spine, rib strains (CORA= 0.50 ± 0.05) and chest deflections (CORA = 0.67 ± 0.08). All models sustained rib fractures, sternal fracture and clavicle fracture. The average number of rib fractures for all the models was 5.3 ± 1.0, lower than in the experiments (10.8 ± 9.0).

Variation in pre-impact posture greatly altered the time histories of the reaction forces, deflections and the rib strains, mainly in terms of time delay, but no definite improvement in HBM response or injury prediction was observed. By modifying only the posture of the HBM, the variability in the impact response was found to be equivalent to that observed in the experiments. The postured HBM sustained from 4 to 8 rib fractures, confirming that the pre-impact posture influenced the injury outcome predicted by the simulation.

Conclusions: This study tries to answer an important question: what is the effect of occupant posture on kinematics and kinetics. Significant differences in kinematics observed between HBM and PMHS suggesting more coupling between the pelvis and the spine for the models which makes the model response very sensitive to any variation in the spine posture. Consequently, the findings observed for the HBM cannot be extended to PMHS. Besides, pre-impact posture should be carefully quantified during experiments and the evaluation of HBM should take into account the variation in the predicted impact response due to the variation in the model posture.     

Investigation of Motorcyclist Cervical Spine Trauma Using HUMOS Model

Objective: With 16 percent of the total road user fatalities, motorcyclists represent the second highest rate of road fatalities in France after car occupants. Regarding road accidents, a large proportion of trauma was on the lower cervical spine. According to different clinical studies, it is postulated that the cervical spine fragility areas are located on the upper and lower cervical spine. In motorcycle crashes, impact conditions occur on the head segment with various orientations and impact directions, leading to a combination of rotations and compression. Hence, motorcyclist vulnerability was investigated considering many impact conditions. Method: Using the human model for safety (HUMOS), a finite element model, this work aims to provide an evaluation of the cervical spine weaknesses based on an evaluation of injury mechanisms. This evaluation consisted of defining 2 injury risk factors (joint injury and bone fracture) using a design of experiment including various velocities, impact directions, and impact orientations. Results: The results confirmed previously reported clinical and epidemiological work on the fragility of the lower cervical spine and the upper cervical spine segments. Joint injuries appeared before bone fractures on both the upper and lower cervical spine. Bone fracture risk was greater on the lower cervical spine than on the upper cervical spine. The compression induced by a high impact angle was identified as an important injury severity factor. It significantly increased the injury incidence for both joint injuries and bone fractures. It also induced a shift in injury location from the lower to the upper cervical spine. The impact velocity exhibited a linear relationship with injury risks and severity. It also shifted the bone fracture risk from the lower to upper spinal segments.     

Older Adults at Increased Risk as Pedestrians in Victoria,Australia: An Examination of Crash Characteristics and Injury Outcomes

Objectives: Engaging in active transport modes (especially walking) is a healthy and environmentally friendly alternative to driving and may be particularly beneficial for older adults. However, older adults are a vulnerable group: they are at higher risk of injury compared with younger adults, mainly due to frailty and may be at increased risk of collision due to the effects of age on sensory, cognitive, and motor abilities. Moreover, our population is aging, and there is a trend for the current cohort of older adults to maintain mobility later in life compared with previous cohorts. Though these trends have serious implications for transport policy and safety, little is known about the contributing factors and injury outcomes of pedestrian collision. Further, previous research generally considers the older population as a homogeneous group and rarely considers the increased risks associated with continued ageing.

Method: Collision characteristics and injury outcomes for 2 subgroups of older pedestrians (65–74 years and 75+ years) were examined by extracting data from the state police–reported crash dataset and hospital admission/emergency department presentation data over the 10-year period between 2003 and 2012. Variables identified for analysis included pedestrian characteristics (age, gender, activity, etc.), crash location and type, injury characteristics and severity, and duration of hospital stay. A spatial analysis of crash locations was also undertaken to identify collision clusters and the contribution of environmental features on collision and injury risk.

Results: Adults over 65 years were involved in 21% of all pedestrian collisions. A high fatality rate was found among older adults, particularly for those aged 75 years and older: this group had 3.2 deaths per 100,000 population, compared to a rate of 1.3 for 65- to 74-year-olds and 0.7 for adults below 65 years of age. Older pedestrian injuries were most likely to occur while crossing the carriageway; they were also more likely to be injured in parking lots, at driveway intersections, and on sidewalks compared to younger cohorts. Spatial analyses revealed older pedestrian crash clusters on arterial roads in urban shopping precincts. Significantly higher rates of hospital admissions were found for pedestrians over the age of 75 years and for abdominal, head, and neck injuries; conversely, older adults were underrepresented in emergency department presentations (mainly lower and upper extremity injuries), suggesting an increased severity associated with older pedestrian injuries. Average length of hospital stay also increased with increasing age.

Conclusion: This analysis revealed age differences in collision risk and injury outcomes among older adults and that aggregate analysis of older pedestrians can distort the significance of risk factors associated with older pedestrian injuries. These findings have implications that extend to the development of engineering, behavioral, and enforcement countermeasures to address the problems faced by the oldest pedestrians and reduce collision risk and improve injury outcomes.