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.     

Integrated model of simulated occupant injury risk and real medical costs

Introduction

The purpose of this study was to develop an integrated methodology that links occupant injury risk functions, estimated in the laboratory, with real world medical treatment costs by using the abbreviated injury score (AIS). Using our model, the expected medical treatment costs for crash injuries to various body regions and of different severities can be investigated.

Methods

First, the simulation results are compared with NHTSA crash data. We used a modified kinematics simulation model that incorporates an F = E^b function as a supplement to the previous Steffan's model to obtain a more accurate acceleration history a(t). Second, head injury criteria HIC₃₆ can be calculated from a(t), and we use the injury probability P as a function of HIC_36, as proposed by Kuppa, to obtain the injury risk function for various AIS values. Third, medical treatment cost models for various AIS values can be calculated by using a regression cost model with real world data. Finally, the injury risk function and medical treatment cost models are linked through AIS values. We establish an integrated methodology and predict medical costs and car safety data using real world police reports, medical treatment costs, and laboratory simulation results.

Results

Using head injuries in frontal crashes as an example, we focus on simulation parameters for different vehicle models, with and without airbags. We specifically examine impact closing speed, Delta-V, and impact directions.

Conclusion

Simulation results can be used to supplement insufficient real crash data, in particular ΔV, and injury risk results from police crash reports.

Impact on industry

The proposed integrated methodology may provide the vehicle industry with a new safety assessment method. Real crash data coupling provides consumers with more realistic and applicable information.     

Effect of vehicle and crash factors on older occupants

PROBLEM: The expected substantial increase in people aged 65 or older is important for those concerned about transportation injuries. However, much of the previous research concentrates on older drivers and overlooks the fact that vehicle and crash factors may provide significant explanations of older occupant injury rates. METHOD: Differences across age groups are explored using two nationwide travel surveys, crash involvement, fatalities, and injuries from crash databases and an ordered probit model of injury severity. RESULTS AND DISCUSSION: Two noticeable differences that help explain injury risk are that older people are more likely to travel in passenger cars than younger people who frequently use light trucks, and that seriously injured older occupants are more likely to be involved in side-impact crashes than their younger counterparts. IMPACT: Increased attention to vehicle engagement in side-impact crashes and to vehicle technologies that can help drivers avoid side collisions would be particularly helpful for older occupants.     

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.     

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.     

Assessment of Bilateral Thoracic Loading on the Near-Side Occupant Due to Occupant-to-Occupant Interaction in Vehicle Crash Tests

Objective: This study aims, by means of the WorldSID 50th percentile male, to evaluate thoracic loading and injury risk to the near-side occupant due to occupant-to-occupant interaction in combination with loading from an intruding structure.

Method: Nine vehicle crash tests were performed with a 50th percentile WorldSID male dummy in the near-side (adjacent to the intruding structure) seat and a THOR or ES2 dummy in the far-side (opposite the intruding structure) seat. The near-side seated WorldSID was equipped with 6 + 6 IR-Traccs (LH and RH) in the thorax/abdomen enabling measurement of bilateral deflection. To differentiate deflection caused by the intrusion, and the deflection caused by the neighboring occupant, time history curves were analyzed. The crash tests were performed with different modern vehicles, equipped with thorax side airbags and inflatable curtains, ranging from a compact car to a large sedan, and in different loading conditions such as car-to-car, barrier, and pole tests. Lateral delta V based on vehicle tunnel acceleration and maximum residual intrusion at occupant position were used as a measurement of crash severity to compare injury measurements.

Result: In the 9 vehicle crash tests, thoracic loading, induced by the intruding structure as well as from the far-side occupant, varied due to the size and structural performance of the car as well as the severity of the crash. Peak deflection on the thoracic outboard side occurred during the first 50 ms of the event. Between 70 to 150 ms loading induced by the neighboring occupant occurred and resulted in an inboard-side peak deflection and viscous criterion. In the tests where the target vehicle lateral delta V was below 30 km/h and intrusion less than 200 mm, deflections were low on both the outboard (20–40 mm) and inboard side (10–15 mm). At higher crash severities, delta V 35 km/h and above as well as intrusions larger than 350 mm, the inboard deflections (caused by interaction to the far-side occupant) were of the same magnitude or even higher (30–70 mm) than the outboard deflections (30–50 mm).

Conclusion: A WorldSID 50th percentile male equipped with bilateral IR-Traccs can detect loading to the thorax from a neighboring occupant making injury risk assessment feasible for this type of loading. At crash severities resulting in a delta V above 35 km/h and intrusions larger than 350 mm, both the inboard deflection and VC resulted in high risks of Abbreviated Injury Scale (AIS) 3+ injury, especially for a senior occupant.     

Sensitivity of Head and Cervical Spine Injury Measures to Impact Factors Relevant to Rollover Crashes

Objective: Serious head and cervical spine injuries have been shown to occur mostly independent of one another in pure rollover crashes. In an attempt to define a dynamic rollover crash test protocol that can replicate serious injuries to the head and cervical spine, it is important to understand the conditions that are likely to produce serious injuries to these 2 body regions. The objective of this research is to analyze the effect that impact factors relevant to a rollover crash have on the injury metrics of the head and cervical spine, with a specific interest in the differentiation between independent injuries and those that are predicted to occur concomitantly.

Methods: A series of head impacts was simulated using a detailed finite element model of the human body, the Total HUman Model for Safety (THUMS), in which the impactor velocity, displacement, and direction were varied. The performance of the model was assessed against available experimental tests performed under comparable conditions. Indirect, kinematic-based, and direct, tissue-level, injury metrics were used to assess the likelihood of serious injuries to the head and cervical spine.

Results: The performance of the THUMS head and spine in reconstructed experimental impacts compared well to reported values. All impact factors were significantly associated with injury measures for both the head and cervical spine. Increases in impact velocity and displacement resulted in increases in nearly all injury measures, whereas impactor orientation had opposite effects on brain and cervical spine injury metrics. The greatest cervical spine injury measures were recorded in an impact with a 15° anterior orientation. The greatest brain injury measures occurred when the impactor was at its maximum (45°) angle.

Conclusions: The overall kinetic and kinematic response of the THUMS head and cervical spine in reconstructed experiment conditions compare well with reported values, although the occurrence of fractures was overpredicted. The trends in predicted head and cervical spine injury measures were analyzed for 90 simulated impact conditions. Impactor orientation was the only factor that could potentially explain the isolated nature of serious head and spine injuries under rollover crash conditions. The opposing trends of injury measures for the brain and cervical spine indicate that it is unlikely to reproduce the injuries simultaneously in a dynamic rollover test.     

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.     

Reliability of police-reported information for determining crash and injury severity

Posted speed limit and police-reported injury codes are commonly used by researchers to approximate vehicle impact and occupant injury severity. In-depth crash investigations, however, produce more precise measures of crash and injury severity: change in velocity (delta-V) for crash severity and Abbreviated Injury Scale (AIS) scores for injury severity. A comparison of data from police crash reports with that gathered by National Automotive Sampling System (NASS) investigators highlighted the inadequacy of speed limit and police injury codes as proxies for delta-V and AIS injury severity. In general, delta-V increased with speed limit and higher values of AIS were associated with higher police-coded injury severity, but there were a number of anomalies. In particular, 49% of the drivers coded by police as having incapacitating injuries actually had sustained no more than minor injuries. This overstatement of injury severity was less frequent among male (44%) and elderly (37%) drivers than among female (53%) and nonelderly (50%) drivers. Also, 79% of the investigated vehicles that crashed on roads posted at 60 mph (96 km/h) or higher experienced a delta-V less than 25 mph (40 km/h). Safety studies depending on data from only police reports to establish injury or crash severity therefore could produce erroneous results.     

Effect of automated versus manual emergency braking on rear seat adult and pediatric occupant precrash motion

Abstract

Objective: Emergency braking can potentially generate precrash occupant motion that may influence the effectiveness of restraints in the subsequent crash, particularly for rear-seated occupants who may be less aware of the impending crash. With the advent of automated emergency braking (AEB), the mechanism by which braking is achieved is changing, potentially altering precrash occupant motion. Further, due to anatomical and biomechanical differences across ages, kinematic differences between AEB and manual emergency braking (MEB) may vary between child and adult occupants. Therefore, the objective of this study was to quantify differences in rear-seated adult and pediatric kinematics and muscle activity during AEB and MEB scenarios.

Methods: Vehicle maneuvers were performed in a recent model year sedan traveling at 50?km/h. MEB (acceleration ～1?g) was achieved by the driver pressing the brake pedal with maximum effort. AEB (acceleration ～0.8?g) was triggered by the vehicle system. Inertial and Global Positioning System data were collected. Seventeen male participants aged 10–33 were restrained in the rear right passenger seat and experienced each maneuver twice. The subjects’ kinematics were recorded with an 8-camera 3D motion capture system. Electromyography (EMG) recorded muscle activity. Head and trunk displacements, raw and normalized by seated height, and peak head and trunk velocity were compared across age and between maneuvers. Mean EMG was calculated to interpret kinematic findings.

Results: Head and trunk displacement and peak velocity were greater in MEB than in AEB in both raw and normalized data (P?≤?.01). No effect of age was observed (P?≥?.21). Peak head and trunk velocities were greater in repetition 1 than in repetition 2 (P?≤?.006) in MEB but not in AEB. Sternocleidomastoid (SCM) mean EMG was greater in MEB compared to AEB, and muscle activity increased in repetition 2 in MEB.

Conclusions: Across all ages, head and trunk excursions were greater in MEB than AEB, despite increased muscle activity in MEB. This observation may suggest an ineffective attempt to brace the head or a startle reflex. The increased excursion in MEB compared to AEB may be attributed to differences in the acceleration pulses between the 2 scenarios. These results suggest that AEB systems can use specific deceleration profiles that have potential to reduce occupant motion across diverse age groups compared to sudden maximum emergency braking applied manually.     

Seatbelt non-use and car crash injury: an interview study

OBJECTIVES: To examine the relationship between seatbelt non-use at the time of a crash, habitual non-use of seatbelts, and car crash injury; and to calculate the population attributable risk for car crash injury due to seatbelt non-use. METHODS: A population-based case control, interview study in Auckland, New Zealand, with 571 injured or killed drivers as cases and 588 population-based controls randomly selected from the driving population. RESULTS: Unbelted drivers had 10 times the risk of involvement in an injury crash compared to belted drivers after adjustment for multiple confounders. Habitual non-users were likely to be unbelted when involved in a crash. The population attributable risk for seatbelt non-use was 13%. CONCLUSIONS: Non-use of seatbelts is very strongly associated with increased injury crash involvement. Even where seatbelt use rates are higher than 90%, there remains a small group of habitual non-users who are at high risk; these drivers may benefit from targeted interventions.     

Modeling crash severity by considering risk indicators of driver and roadway: A Bayesian network approach

Introduction: Traffic crashes could result in severe outcomes such as injuries and deaths. Thus, understanding factors associated with crash severity is of practical importance. Few studies have deeply examined how prior violation and crash experience of drivers and roadways are associated with crash severity. Method: In this study, a set of risk indicators of road users and roadways were developed based on their prior violation and crash records (e.g., cumulative crash frequency of a roadway), in order to reflect certain aspect or degree of their driving risk. To explore the impacts of those indicators on crash severity and complex interactions among all contributing factors, a Bayesian network approach was developed, based on citywide crash data collected in Kunshan, China from 2016 to 2018. A variable selection procedure based on Information Value (IV) was developed to identify significant variables, and the Bayesian network was employed to explicitly explore statistical associations between crash severity and significant variables. Results: In terms of balanced accuracy and AUCs, the proposed approach performed reasonably well. Bayesian modeling results indicated that the prior crash/violation experiences of road users and roadways were very important risk indicators. For example, migrant workers tend to have high injury risk due to their dangerous violation behaviors, such as retrograding, red-light running, and right-of-way violation. Furthermore, results showed that certain variable combinations had enhanced impacts on severity outcome than single variables. For example, when a migrant worker and a non-motorized vehicle are involved in a crash happening on a local road with high cumulative violation frequency in the previous year, the probability for drivers suffering serious injury or fatality is much higher than that caused by any single factor. Practical applications: The proposed methodology and modeling results provide insights for developing effective countermeasures to reduce crash severity and improve traffic system safety performance.     

Case study: 128 injured in rollover coach crashes in Sweden—Injury outcome,mechanisms and possible effects of seat belts

The risk for injuries in rollover coach crashes are dependent on whether the occupants are belted or not. However, the influence of the different belt systems for reducing injuries has remained unclear. Since many injuries sustained are caused by impacts with the interior, passenger interactions or ejection through a window, the advantages by proper seat belt systems are evident. In this study, representing the most common serious crash scenario for serious injury, 128 injured in rollover cases were analysed with regard to the injury outcome, mechanisms and the possible injury reduction for occupants when using a safety belt. Furthermore, the different belt systems were compared to explain their contribution to increased safety. Based on medical reports and questioning of the passengers, the injuries sustained are recorded according to the AIS classification. The next step was the identification of the injury mechanisms, using the passenger statements as well as results from numerical occupant simulations. It is important to mention that this study was purely focused on detection of the injury mechanism to avoid the reported injuries. The possibility of additional injuries due to the wearing of a belt were not taken into account. However, the analysis of the 128 injured showed a considerable increase in safety for belted occupants through limiting interior contacts, minimising passenger interaction and reducing the possibility of ejection.     

A multinomial logit model of motorcycle crash severity at Australian intersections

Introduction: Motorcyclists are exposed to more fatalities and severe injuries per mile of travel as compared to other vehicle drivers. Moreover, crashes that take place at intersections are more likely to result in serious or fatal injuries as compared to those that occur at non-intersections. Therefore, the purpose of this study is to evaluate the contributing factors to motorcycle crash severity at intersections. Method: A data set of 7,714 motorcycle crashes at intersections in the State of Victoria, Australia was analyzed over the period of 2006–2018. The multinomial logit model was used for evaluating the motorcycle crashes. The severity of motorcycle crashes was divided into three categories: minor injury, serious injury and fatal injury. The risk factors consisted of four major categories: motorcyclist characteristics, environmental characteristics, intersection characteristics and crash characteristics. Results: The results of the model demonstrated that certain factors increased the probability of fatal injuries. These factors were: motorcyclists aged over 59 years, weekend crashes, midnight/early morning crashes, morning rush hours crashes, multiple vehicles involved in the crash, t-intersections, crashes in towns, crashes in rural areas, stop or give-way intersections, roundabouts, and uncontrolled intersections. By contrast, factors such as female motorcyclists, snowy or stormy or foggy weather, rainy weather, evening rush hours crashes, and unpaved roads reduced the probability of fatal injuries. Practical Applications: The results from our study demonstrated that certain treatment measures for t-intersections may reduce the probability of fatal injuries. An effective way for improving the safety of stop or give-way intersections and uncontrolled intersections could be to convert them to all-way stop controls. Further, it is recommended to educate the older riders that with ageing, there are physiological changes that occur within the body which can increase both crash likelihood and injury severity.     

Weather impacts on single-vehicle truck crash injury severity

IntroductionThe focus of this paper is on illustrating the feasibility of aggregating data from disparate sources to investigate the relationship between single-vehicle truck crash injury severity and detailed weather conditions. Specifically, this paper presents: (a) a methodology that combines detailed 15-min weather station data with crash and roadway data, and (b) an empirical investigation of the effects of weather on crash-related injury severities of single-vehicle truck crashes.MethodRandom parameters ordinal and multinomial regression models were used to investigate crash injury severity under different weather conditions, taking into account the individual unobserved heterogeneity. The adopted methodology allowed consideration of environmental, roadway, and climate-related variables in single-vehicle truck crash injury severity.Results and conclusionsResults showed that wind speed, rain, humidity, and air temperature were linked with single-vehicle truck crash injury severity. Greater recorded wind speed added to the severity of injuries in single-vehicle truck crashes in general. Rain and warmer air temperatures were linked to more severe crash injuries in single-vehicle truck crashes while higher levels of humidity were linked to less severe injuries. Random parameters ordered logit and multinomial logit, respectively, revealed some individual heterogeneity in the data and showed that integrating comprehensive weather data with crash data provided useful insights into factors associated with single-vehicle truck crash injury severity.Practical applicationsThe research provided a practical method that combined comprehensive 15-min weather station data with crash and roadway data, thereby providing useful insights into crash injury severity of single-vehicle trucks. Those insights are useful for future truck driver educational programs and for truck safety in different weather conditions.     

A study on chest injury mechanism and the effectiveness of a headform impact test for pedestrian chest protection from vehicle collisions

This study was aimed at investigating the injury mechanism of pedestrian chests in collisions with passenger vehicles of various frontal shapes and examining the influence of the local structural stiffness on the chest injury risk by using the headform impact test at the chest contact area of the vehicle. Three simulations of vehicle to pedestrian collisions were conducted using three validated pedestrian finite element (FE) models of three pedestrian heights of 177 (AM50th), 165 and 150 cm and three FE vehicles models representing a one-box vehicle, a minicar and a medium car. The validity of the vehicle models was evaluated by comparing the headform acceleration against the measured responses from headform impact tests. The chest impact kinematics and the injury mechanisms were analyzed in terms of the distribution of the von Mises stress of the ribcage and in terms of the chest deflections. The chest contact locations on the front panel and the bonnet top were identified in connection to the causation of rib fractures. The risk of rib fractures was predicted by using the von Mises stress distribution. The headform impact tests were carried out at the chest contact area on the front panel and bonnet to examine the safety performance with respect to pedestrian chest protection. In simulations of the one-box vehicle to pedestrian collisions, the chest was struck directly by the frontal structure at a high velocity and deformed substantially, since a shear force was generated by the stiff windshield frame. The acceleration of the headform was related to the rib deflections. The injury threshold of the ribcage deflection (42 mm) corresponded to the headform average acceleration of 68 G. In the minicar collision, the chest was struck with the bonnet top and cowl area at a low velocity, and the deformation was small due to the distributed contact force between the chest and the bonnet top. Besides, the ribcage deformation was too small for bridging a relation between the headform accelerations and rib deflections. In the medium car collision, the deformation mode of the chest was similar to that in the minicar collision. The chest collided with the bonnet top at a low velocity and deformed uniformly. The deflection of the ribs had an observable correlation with the headform accelerations measured in the headform impact tests. The frontal shape of a vehicle has a large influence on a pedestrian’s chest loadings, and the chest deformation depends on the size of the pedestrian and the stiffness of the vehicle. The one-box passenger vehicle causes a high chest injury risk. The headform impactor test can be utilized for the evaluation of the local stiffness of a vehicle’s frontal structure. The reduction of the headform acceleration is an effective measure for pedestrian chest protection for specific shapes of vehicles by efficacy in modifying the local structural stiffness.     

A study of pedestrian and bicyclist exposure to head injury in passenger car collisions based on accident data and simulations

The objective was to assess head injury risks and kinematics of adult pedestrians and bicyclists in primary impact to the passenger cars and secondary impact to the ground using real world accident data and computer reconstructions of the accidents. For this purpose, a subsample of 402 pedestrians and 940 bicyclists from the GIDAS database, Germany, was used for the statistical analysis, from which 22 pedestrian and 18 bicyclist accidents were further selected for reconstruction. PC-Crash was used to calculate impact conditions, such as vehicle impact velocity, vehicle kinematic sequence, and thrown distance. These conditions were employed to identify the initial conditions in reconstruction in MADYMO program. A comparable analysis was conducted based on the results from accident analysis and computer reconstructions for the impact configurations and the resulting injury patterns of pedestrians and bicyclists in view of head injury risks. Differences in HIC, head-relative impact velocity, linear acceleration, maximum angular velocity and acceleration, contact force, thrown distance, Wrap Around Distance (WAD), and head contact time were evaluated. Injury risk curves were generated by using a logistic regression model for vehicle impact velocity. The results indicate that bicyclists suffered less severe injuries compared with severity of pedestrian injuries. In the selected samples, the AIS 2+ and AIS 3+ head injury risks for pedestrians are 50% probability at impact speed of 38.87 km/h and 54.39 km/h respectively, while for bicyclists at 53.66 km/h and 58.89 km/h respectively. The findings of high injury risks suggested that in the area with high frequency car-pedestrian accidents, the vehicle speed limit should be 40 km/h, while in the area with high frequency car-cyclist accidents the vehicle speed limit should be 50 km/h.