Mirko Junge

Pedestrian injury risk and the effect of age

Older adults and pedestrians both represent especially vulnerable groups in traffic. In the literature, hazards are usually described by the corresponding injury risks of a collision. This paper investigates the MAIS3+F risk (the risk of sustaining at least one injury of AIS 3 severity or higher, or fatal injury) for pedestrians in full-frontal pedestrian-to-passenger car collisions. Using some assumptions, a model-based approach to injury risk, allowing for the specification of individual injury risk parameters for individuals, is presented. To balance model accuracy and sample size, the GIDAS (German In-depth Accident Study) data set is divided into three age groups; children (0-14); adults (15-60); and older adults (older than 60). For each group, individual risk curves are computed. Afterwards, the curves are re-aggregated to the overall risk function. The derived model addresses the influence of age on the outcome of pedestrian-to-car accidents. The results show that older people compared with younger people have a higher MAIS3+F injury risk at all collision speeds. The injury risk for children behaves surprisingly. Compared to other age groups, their MAIS3+F injury risk is lower at lower collision speeds, but substantially higher once a threshold has been exceeded. The resulting injury risk curve obtained by re-aggregation looks surprisingly similar to the frequently used logistic regression function computed for the overall injury risk. However, for homogenous subgroups - such as the three age groups - logistic regression describes the typical risk behavior less accurately than the introduced model-based approach. Since the effect of demographic change on traffic safety is greater nowadays, there is a need to incorporate age into established models. Thus far, this is one of the first studies incorporating traffic participant age to an explicit risk function. The presented approach can be especially useful for the modeling and prediction of risks, and for the evaluation of advanced driver assistance systems.

Cross-correlation between the controlled collision environment and real-world motor vehicle collisions: Evaluating the protection of the thoracic side airbag

ABSTRACT Objective: Thoracic side airbags (tSABs) were integrated into the vehicle fleet to attenuate and distribute forces on the occupants chest and abdomen, dissipate the impact energy, and move the occupant away from the intruding structure, all of which reduce the risk of injury. This research piece investigates and evaluates the safety performance of the airbag unit by cross-correlating data from a controlled collision environment with field data. Method: We focus exclusively on vehicle–vehicle lateral impacts from the NHTSAs Vehicle Crash Test Database and NASS-CDS database, which are replicated in the controlled environment by the (crabbed) barrier impact. Similar collisions with and without seat-embedded tSABs are matched to each other and the injury risks are compared. Results: Results indicated that dummy-based thoracic injury metrics were significantly lower with tSAB exposure (P <.001). Yet, when the controlled collision environment data were cross-correlated with NASS-CDS collisions, deployment of the tSAB indicated no association with thoracic injury (tho. MAIS 2+ unadjusted relative risk [RR] = 1.14; 90% confidence interval [CI], 0.80–1.62; tho. MAIS 3+ unadjusted RR = 1.12; 90% CI, 0.76–1.65). Conclusion: The data from the controlled collision environment indicated an unequivocal benefit provided by the thoracic side airbag for the crash dummy; however, the real-world collisions demonstrate that no benefit is provided to the occupant. This has resulted from a noncorrelation between the crash test/dummy-based design taking the abstracting process too far to represent the real-world collision scenario.

Injury risk functions for frontal oblique collisions

ABSTRACT Objective: The objective of this article was the construction of injury risk functions (IRFs) for front row occupants in oblique frontal crashes and a comparison to IRF of nonoblique frontal crashes from the same data set. Method: Crashes of modern vehicles from GIDAS (German In-Depth Accident Study) were used as the basis for the construction of a logistic injury risk model. Static deformation, measured via displaced voxels on the postcrash vehicles, was used to calculate the energy dissipated in the crash. This measure of accident severity was termed objective equivalent speed (oEES) because it does not depend on the accident reconstruction and thus eliminates reconstruction biases like impact direction and vehicle model year. Imputation from property damage cases was used to describe underrepresented low-severity crashes―a known shortcoming of GIDAS. Binary logistic regression was used to relate the stimuli (oEES) to the binary outcome variable (injured or not injured). Results: IRFs for the oblique frontal impact and nonoblique frontal impact were computed for the Maximum Abbreviated Injury Scale (MAIS) 2+ and 3+ levels for adults (18–64 years). For a given stimulus, the probability of injury for a belted driver was higher in oblique crashes than in nonoblique frontal crashes. For the 25% injury risk at MAIS 2+ level, the corresponding stimulus for oblique crashes was 40 km/h but it was 64 km/h for nonoblique frontal crashes. Conclusions: The risk of obtaining MAIS 2+ injuries is significantly higher in oblique crashes than in nonoblique crashes. In the real world, most MAIS 2+ injuries occur in an oEES range from 30 to 60 km/h.

Thoracic side airbags and structural performance in vehicle–vehicle lateral impacts

ABSTRACT Over the last few decadesthe longitudinal and lateral stiffness of the vehicle fleet has increased and a greater presence of passive safety measures have been integrated. The analysis reviews a series of real world vehicle-vehicle lateral collisions from NASS-CDS to identify any shifts in crashworthiness. The study attempts to isolate an effectiveness estimation for the deployed thoracic side airbag (tSAB) in preventing thoracic injury and secondly identify if newer struck vehicles are more resistant to intrusion than older vehicles. To assess the proposed hypotheses, similar severity collisions are paired to one another and traditional statistic tests can be applied. The results indicated that, the rate of rate of injury between the occupants in vehicles with the deployed tSAB did not differ to those unexposed to the tSAB. Results attaining to the second hypothesis demonstrated that newer vehicles are more resistant to lateral intrusion than older vehicles, mostly evident with an impact velocity of 40–60 km/h.

Detection of the toughest: Pedestrian injury risk as a smooth function of age

ABSTRACT Objective: Though it is common to refer to age-specific groups (e.g., children, adults, elderly), smooth trends conditional on age are mainly ignored in the literature. The present study examines the pedestrian injury risk in full-frontal pedestrian-to–passenger car accidents and incorporates age—in addition to collision speed and injury severity—as a plug-in parameter. Methods: Recent work introduced a model for pedestrian injury risk functions using explicit formulae with easily interpretable model parameters. This model is expanded by pedestrian age as another model parameter. Using the German In-Depth Accident Study (GIDAS) to obtain age-specific risk proportions, the model parameters are fitted to the raw data and then smoothed by broken-line regression. Results: The approach supplies explicit probabilities for pedestrian injury risk conditional on pedestrian age, collision speed, and injury severity under investigation. All results yield consistency to each other in the sense that risks for more severe injuries are less probable than those for less severe injuries. As a side product, the approach indicates specific ages at which the risk behavior fundamentally changes. These threshold values can be interpreted as the most robust ages for pedestrians. Conclusions: The obtained age-wise risk functions can be aggregated and adapted to any population. The presented approach is formulated in such general terms that in can be directly used for other data sets or additional parameters; for example, the pedestrians sex. Thus far, no other study using age as a plug-in parameter can be found.

Efficacy of seat-mounted thoracic side airbags in the German vehicle fleet

ABSTRACT Objective: Thoracic side airbags (tSABs) deploy within close proximity to the occupant. Their primary purpose is to provide a protective cushion between the occupant and the intruding door. To date, various field studies investigating their injury mitigation has been limited and contradicting. The research develops efficacy estimations associated for seat-mounted tSABs in their ability to mitigate injury risk from the German collision environment. Methods: A matched cohort study using German In-Depth Accident Study (GIDAS) data was implemented and aims to investigate the efficacy of seat-mounted tSAB units in preventing thoracic injury. Inclusion in the study required a nearside occupant involved in a lateral collision where the target vehicle exhibited a design year succeeding 1990. Collisions whereby a tSAB deployed were matched on a 1:n basis to collisions of similar severity where no airbag was available in the target vehicle. The outcome of interest was an incurred bodily or thoracic regional injury. Through conditional logistic regression, an estimated efficacy value for the deployed tSAB was determined. Results: A total of 255 collisions with the deployed tSAB matched with 414 collisions where no tSAB was present. For the given sample, results indicated that the deployed tSAB was not able to provide an unequivocal benefit to the occupant thoracic region, because individuals exposed to the deployed tSAB were at equal risk of injury (Thorax Maximum Abbreviated Injury Scale (Tho.MAIS)2+ odds ratio [OR] = 1.04, 95% confidence interval [CI], 0.41–2.62; Tho.MAIS3+ OR = 1.15, 95% CI, 0.41–3.18). When attempting to isolate an effect for skeletal injuries, a similar result was obtained. Yet, when the tSAB was coupled with a head curtain airbag, a protective effect became apparent, most noticeable for head/face/neck (HFN) injuries (OR = 0.59, 95% CI, 0.21–1.65). Conclusion: The reduction in occupant HFN injury risk associated with the coupled tSAB and curtain airbag may be attributable to its ability to provide coverage over previous mechanisms of injury. Yet, the sole presence of the tSAB showed no ability to provide additional benefit for the occupants thoracic region. Future work should identify mechanisms of injury in tSAB cases and attempt to quantify improvements in the vehicles ability to resist intrusion.

Expanding Pedestrian Injury Risk to the Body Region Level: How to Model Passive Safety Systems in Pedestrian Injury Risk Functions

Objective: Assessment of the effectiveness of advanced driver assistance systems (ADAS) plays a crucial role in accident research. A common way to evaluate the effectiveness of new systems is to determine the potentials for injury severity reduction. Because injury risk functions describe the probability of an injury of a given severity conditional on a technical accident severity (closing speed, delta V, barrier equivalent speed, etc.), they are predestined for such evaluations. Methods: Recent work has stated an approach on how to model the pedestrian injury risk in pedestrian-to–passenger car accidents as a family of functions. This approach gave explicit and easily interpretable formulae for the injury risk conditional on the closing speed of the car. These results are extended to injury risk functions for pedestrian body regions. Starting with a double-checked German In-depth Accident Study (GIDAS) pedestrian-to-car accident data set (N = 444) and a functional–anatomical definition of the body regions, investigations on the influence of specific body regions on the overall injury severity will be presented. As the measure of injury severity, the ISSx, a rescaled version of the well-known Injury Severity Score (ISS), was used. Though traditional ISS is computed by summation of the squares of the 3 most severe injured body regions, ISSx is computed by the summation of the exponentials of the Abbreviated Injury Scale (AIS) severities of the 3 most severely injured body regions. The exponentials used are scaled to fit the ISS range of values between 0 and 75. Results: Three body regions (head/face/neck, thorax, hip/legs) clearly dominated abdominal and upper extremity injuries; that is, the latter 2 body regions had no influence at all on the overall injury risk over the range of technical accident severities. Thus, the ISSx is well described by use of the injury codes from the same body regions for any pedestrian injury severity. As a mathematical consequence, the ISSx becomes explicitly decomposable into the 3 body regions and so are the risk functions as body region–specific risk functions. The risk functions for each body region are stated explicitly for different injury severity levels and compared to the real-world accident data. Conclusions: The body region–specific risk functions can then be used to model the effect of improved passive safety systems. These modified body region–specific injury risk functions are aggregated to a new pedestrian injury risk function. Passive safety systems can therefore be modeled in injury risk functions for the first time. A short example on how the results can be used for assessing the effectiveness of new driver assistance systems concludes the article.