Evaluation and Comparison of Roadside Crash Injury Metrics (2023)

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147 10 Correlate MASH Intrusion Criteria with Real-World Injury Introduction The purpose of this study was to evaluate MASH guidelines on acceptable intrusion limits based on real-world crash experience. The analysis had three primary components: 1. Analysis of occupant compartment intrusion magnitude and occupant injury 2. Evaluation of current MASH occupant compartment intrusion limits 3. Estimation of real-world frequency of vehicle damage patterns For convenience, the current MASH occupant compartment deformation limits are summarized in Table 10-1. Table 10-1. Summary of MASH occupant compartment deformation limits (AASHTO 2016). Vehicle Component or Area Deformation Limit / Criteria Windshield ≤ 3 inches and no tear of plastic liner Roof ≤ 4 inches A and B pillars ≤ 5 inches of resultant deformation (≤ 3 inches laterally). No complete severing of support member. Wheel/foot well and toe pan ≤ 9 inches Front side door area (above seat) Side front panel (forward of A pillar) ≤ 12 inches Front side door area (below seat) Floor pan and transmission tunnel areas Window No shattering of side window resulting from direct contact with a structural member of the test article, except for tall, continuous barrier elements. For laminated side windows, windshield guidelines apply. Much of this chapter is provided in Gabauer, D.J. and Juengprasertsak, S., “Examination of Current MASH Occupant Compartment Intrusion Limits using Real-World Crash Data,” Transportation Research Record: Journal of the Transportation Research Board, Vol. 2676, Issue 6, pp. 413-423, which is listed as the second cited work at the end of this document. Text and figures are reproduced largely verbatim and are © 2022, SAGE Publishing. Methods In general, this study used real-world in-depth crash data, which contain detailed vehicle deformation measurements and occupant injury data, to investigate the relationship between occupant compartment intrusion and resulting occupant injury. The available data included both tabulated numeric values, such as documented occupant compartment intrusion magnitudes and occupant injury severity levels, as well as the available scene and vehicle damage photographs. The specific methods used for each component of the analysis are described in the sections below. 10.2.1 Analysis of Occupant Compartment Intrusion Magnitude and Occupant Injury The purpose of this portion of the study is to update the Eigen and Glassbrenner (2003) study using the most recent years of NASS/CDS data available. Cases were selected from NASS/CDS using the following criteria:

148 1. Case years 2000 through 2015, inclusive. 2. Vehicle strikes another vehicle or a fixed object or some combination of vehicles and/or fixed objects. 3. No vehicle rollover present. 4. The vehicle has either a full or partial inspection with “relevant intrusion” present, as defined by Eigen and Glassbrenner (2003), such as non-zero intrusion in one or more of the following vehicle areas: a. Toe pan, b. Floor pan, and/or c. Forward of the A-pillar. 5. The “relevant intrusion” is adjacent to the included occupant (e.g., a vehicle with “relevant intrusion” on the right front passenger side of the vehicle, but only a driver present would not be included in the analysis). 6. Driver and right front passengers who are 13 years of age or older and not ejected from the vehicle. 7. Known occupant injury information present with at least one injury linked to one of the relevant intrusions. The most recent 16 years of NASS/CDS were used to provide a larger sample size than used in the Eigen and Glassbrenner (2003) study, yet with minimal overlap with the Eigen and Glassbrenner data (i.e., a single year overlap only). For each included vehicle, the object struck was classified as either a vehicle or a non-vehicle. The non-vehicle category includes all types of fixed objects, roadside hardware, trees, poles, etc., as well as non-fixed objects. For vehicles striking multiple objects, the object strike associated with the largest change in vehicle velocity was used to classify the strike as vehicle or non-vehicle. All vehicles with any rollover present in the event sequence were excluded, as MASH occupant risk procedures are predicated on passenger vehicles remaining upright. Ejected occupants were excluded, as the intent is to discern how occupant compartment intrusions relate to occupant injury. NASS/CDS captures intrusion information for up to 10 intrusions for each vehicle. For each intrusion, the intrusion location is captured relative to the immediately adjacent occupant (e.g., driver, right front passenger) as well as the intruding vehicle component (e.g., steering wheel, door, roof). To be included in this portion of the analysis, a vehicle had to have measured intrusion in at least one of the areas listed above but could have measured intrusion in other vehicle areas. The magnitude of the intrusion is categorized into ranges by the NASS/CDS investigator as summarized in Table 10-2. Only intrusions with measured magnitudes were included in this study (CDS codes 1 thru 6). For vehicle-occupant combinations with more than one relevant intrusion, the largest relevant intrusion was retained.

149 Table 10-2. Summary of NASS/CDS intrusion magnitude. CDS Code Intrusion Magnitude Range [cm] Intrusion Magnitude Range [inches] 1 3-7 1.2 – 2.8 2 8-14 3.1 – 5.5 3 15-29 5.9 – 11.4 4 30-45 11.8 – 17.7 5 46-60 18.1 – 23.6 6 61 or more 24 or more 7 Catastrophic Catastrophic 8 Multiple/Other severe intrusions Multiple/Other severe intrusions U Unknown Unknown Occupant injury was measured via the AIS (AAAM 2008). The 1998 AIS was used to determine injury severity to allow comparison of these results with the previous study. For each NASS/CDS occupant, an AIS score is assigned to each specific injury. For each recorded injury, NASS/CDS contains information linking the injury, if applicable, to an associated intrusion. Injured occupants were only included if one or more injuries could be linked to a relevant intrusion. If an occupant had more than one injury linked to a relevant intrusion, the highest AIS value was retained. Non- injured occupants adjacent to relevant intrusions were also included in the available dataset (i.e., MAIS score of 0). Contingency table analysis and chi-square tests were used to test for significance between various occupant compartment intrusion levels (in the relevant areas) and resulting occupant injury. For the purposes of the analysis, the highest AIS injury score linked to a relevant intrusion was compared to the largest nearside relevant intrusion value. Similar to the Eigen and Glassbrenner (2003) study, this was done for any nearside relevant intrusion as well as toe-pan only intrusion. Injury levels were categorized using differing threshold values: AIS 1+, AIS 2+, and AIS 3+. For the AIS 1+ category, only occupants sustaining an AIS 1 or higher injury would be considered injured. Similarly, for AIS 2+, injured occupants would need to have sustained an AIS 2 or higher injury. Occupant compartment intrusion levels were classified according to the levels shown in Table 10-2. Results were tabulated for the statistically significant comparisons where significance is considered when the chi-square test p-value was less than 0.05. The chi- square tests were performed using the SURVEYFREQ procedure in SAS that appropriately accounts for the complex sampling design of NASS/CDS. 10.2.2 Evaluation of Current MASH Occupant Compartment Intrusion Limits The overall approach of this portion of the analysis is to classify real-world crashes using the MASH occupant compartment intrusion criteria, as either above or below the associated intrusion value, and then examine corresponding maximum occupant injury. Case selection for this analysis was similar to the update to the Eigen and Glassbrenner (2003) study. Cases were selected from NASS/CDS using the following criteria: 1. Case years 2000 through 2015, inclusive. 2. Vehicle strikes another vehicle or a fixed object or some combination of vehicles and/or fixed objects. 3. No vehicle rollover present.

150 4. The vehicle has either a full or partial inspection with or without intrusion present. Any intrusion present must be “nearside” (i.e., adjacent to the occupant). 5. Driver and right front passengers who are 13 years of age or older and not ejected from the vehicle. 6. Known occupant injury information present. Current MASH intrusion limits are specified for nine different locations on a vehicle, as summarized in Table 10-1. Based on the available NASS/CDS occupant intrusion locations and intrusion magnitude ranges, intrusion is classified as above or below current MASH intrusion thresholds based on seven vehicle regions: (1) windshield, (2) roof, (3) A/B pillar, (4) toe pan, (5) door, (6) side front panel, and (7) floor pan. Since the NASS/CDS intrusion magnitude is a range and not an exact value, the CDS intrusion levels corresponding could not always be precisely categorized as above or below a particular MASH intrusion threshold. For the purposes of this study, Table 10-3 shows how the CDS intrusion levels mapped to the MASH intrusion thresholds in each vehicle region. Table 10-3. Mapping of MASH occupant compartment deformation areas to NASS/CDS intruding component. MASH Vehicle Component or Area MASH Deformation Limit / Criteria NASS/CDS Intruding Component(s) [code] CDS Intrusion Code(s) Exceeding MASH Threshold Windshield ≤ 3 inches and no tear of plastic liner Windshield [15] 2,3,4,5,6 Roof ≤ 4 inches Roof/convert top [13] Roof side rail [14] 2,3,4,5,6 A and B pillars ≤ 5 inches of resultant deformation (≤ 3 inches laterally). No complete severing of support member. A-pillar [6] B-pillar [7] 3,4,5,6 Wheel/foot well and toe pan ≤ 9 inches Toe pan [5] 4,5,6 Front side door area (above seat) Door panel [11] Door FUQ [35] Door RUQ [37] Door UND [41] Side front panel (forward of A pillar) ≤ 12 inches Side panel [10/12] 4,5,6 Front side door area (below seat) Door FLQ [36] Door RLQ [38] Floor pan and transmission tunnel areas Floor pan [18] An example of an “exact” match between MASH and CDS would be the windshield area, where CDS code 1 contains intrusions less than 3 inches and CDS codes 2-6 contain intrusions greater than 3 inches. An example of an “approximate” match would be the 9-inch threshold for the toe pan area since 9 inches is within the CDS code 3 range (5.9 to 11.4 inches). Since most of the CDS code 3 range is below the 9-inch MASH threshold, only CDS codes of 4 or higher were considered to exceed the MASH intrusion threshold for that vehicle region. Note that MASH does specify

151 different limits for the door above and below the seat. The MASH door intrusion areas, however, were combined for this study for two reasons: (1) only a portion of the available NASS/CDS data (2008 and later) differentiate the quadrant of the door that has the intrusion and (2) the impreciseness of the CDS intrusion ranges to differentiate between 9 and 12 inches of intrusion. Two different measures were used to indicate whether a particular occupant in a vehicle had intrusion above the MASH threshold: 1. A single “overall” binary variable indicating one or more areas are in excess of the corresponding MASH threshold. 2. Vehicle region-specific binary indicators (seven total) that indicate whether the corresponding MASH intrusion threshold was exceeded. The purpose of the first measure is to determine if the MASH intrusion criteria as a whole serve as a predictor of occupant injury. The second set of measures is to determine if intrusions in certain vehicle areas are stronger predictors of injury than intrusions in other areas. Occupant injury is measured via the AIS (AAAM 2008) using the 1998 AIS. The MAIS score recorded for each occupant is used to gauge overall injury severity. For this portion of the study, there was no stipulation that injuries were linked to an associated intrusion. Non-injured occupants were also included in the available dataset (MAIS score of 0). Occupants with an unknown injury severity were excluded unless their treatment status was for that of a fatal injury. These occupants were included in the injured category, regardless of MAIS level. A binary logistic regression model was developed to predict serious injury based on the MASH intrusion limit indicator while accounting for other potentially confounding factors. As MASH does not provide a specific definition of “serious” injury relative to an AIS score, several MAIS cutoff values were used: MAIS1+F, MAIS2+F, and MAIS3+F. Confounding factors considered included occupant age (13 ≤ age < 65 years or age ≥ 65), sex (male or female), belt status (belted or unbelted), BMI (obese or not obese), and vehicle type (PC or LTV). These confounding factor definitions are consistent with those defined in the development of the frontal, oblique, and side impact injury risk curves in earlier chapters. Odds ratios were used to compare occupant injury risk based on whether or not intrusion in excess of one or more MASH limits was present as well as quantify the effects of the possible confounding factors. A similar procedure was used to develop a binary logistic regression model using all seven MASH intrusion level indicator variables, in excess of MASH threshold or not, as predictors. All binary logistic regression models were fit using the SURVEYLOGISTIC procedure in SAS that appropriately accounts for the complex sampling design of NASS/CDS. 10.2.3 Estimation of Real-World Frequency of Vehicle Damage Patterns Full-scale crash testing with roadside safety hardware has identified several vehicle damage patterns. These include (but are not limited to) the following: 1. Glued seam separation for unibody type passenger vehicles that creates an opening into the occupant compartment. 2. A-pillar/B-pillar and door damage as a result of a cable barrier impact. NASS/CDS contains detailed vehicle damage photographs for case vehicles that have been fully or partially inspected. These photos were used in conjunction with the available intrusion data to

152 determine which crashes have any of these damage modes present. Cases were selected from NASS/CDS using the following criteria: 1. Case years 2000 through 2015, inclusive. 2. Single vehicle crashes where the vehicle strikes a roadside hardware device. Multiple event crashes are permissible only if the vehicle strikes the same type of roadside hardware. 3. No vehicle rollover present. 4. The vehicle has either a full or partial inspection with intrusion present. As we are primarily interested in damage that occurs as a result of impacts with roadside safety hardware devices, the cases were limited to impacts with roadside hardware. Single-vehicle, single-event crashes are ideal, as any damage can be attributed to the impact with the roadside hardware device. Based on an initial review of single-vehicle multiple-event cases, however, we found that NASS/CDS investigators often code impacts with longitudinal barriers as two impacts (e.g., vehicle front impacts the barrier followed by the vehicle side impacting the barrier). Given this, we expanded the available cases to single-vehicle multiple-event crashes as long as the object struck code is the same. For the purposes of this study, the following were considered roadside hardware devices (with associated NASS/CDS object struck codes):  Guardrail (46, 48, 56)  Guardrail end terminal (49)  Concrete barrier (56)  Cable barrier (47)  Breakaway pole (45)  Impact attenuator (55) Vehicles that rolled were excluded as it is not possible to reliably discern vehicle damage resulting from the impact with the roadside hardware from damage resulting from the rollover. Cases were limited to those with any documented intrusion, as these cases are the most likely to have more extensive vehicle damage. The scene and vehicle photographs for each selected case were manually reviewed by the research team for the presence of damage modes. Cases with damage modes of interest were identified, and the available NASS/CDS weights were used to estimate the proportion of crashes where each damage mode is present. This process was repeated for crashes with each different type of roadside hardware device struck. Available Cases 10.3.1 Analysis of Occupant Compartment Intrusion Magnitude and Occupant Injury Table 10-4 summarizes the available front-row nearside occupants with relevant intrusion present and at least one injury linked to a relevant intrusion. Note that the weighted values are shown with the associated unweighted values in parentheses immediately below. There were 2,202 unweighted suitable occupants who represent more than 400,000 crash-exposed occupants.

153 Table 10-4. Summary of weighted (unweighted) front row nearside occupants by maximum relevant intrusion level and object struck for available NASS/CDS cases (2000 – 2015, inclusive). Object Contacted Maximum Relevant Intrusion Magnitude Total 3-7 cm 8-14 cm 15-29 cm 30-45 cm 46-60 cm 61 or more cm Vehicle 116,256 (339) 80,237 (396) 48,059 (403) 18,732 (198) 3,105 (61) 1,198 (26) 267,587 (1,423) Non-Vehicle 46,353 (103) 46,216 (198) 31,324 (217) 31,278 (166) 3,358 (61) 1,162 (34) 159,689 (779) Total 162,609 (442) 126,452 (594) 79,382 (620) 50,010 (364) 6,642 (122) 2,360 (60) 427,276 (2,202) 10.3.2 Evaluation of Current MASH Occupant Compartment Intrusion Limits Table 10-5 summarizes the characteristics of the available front-row occupants for inclusion in the MASH intrusion limit binary logistic regression models. Both the unweighted and weighted values are shown as well as the corresponding percentages. There were more than 56,000 unweighted occupants available representing more than 26 million crash-exposed front-row occupants. 10.3.3 Estimation of Real-World Frequency of Vehicle Damage Patterns Table 10-6 summarizes the single vehicle NASS/CDS cases involving roadside safety hardware. Note that the NASS/CDS object struck codes have changed over the years so some categories, such as cable barrier, are only available for a portion of the NASS/CDS years investigated.

154 Table 10-5. Summary characteristics of weighted and unweighted occupants for inclusion in the MASH intrusion evaluation dataset (NASS/CDS 2000-2015 inclusive). Unweighted Weighted Number of Occupants % Number of Occupants % All Vehicles All Vehicles 56,088 100% 26,220,282 100% Injury MAIS 0, 1 43,597 78% 24,493,606 93% MAIS2+F 12,491 22% 1,726,676 7% Gender Male 29,001 52% 13,493,630 51% Female 27,087 48% 12,726,652 49% Belt Use Belted 44,157 79% 21,940,709 84% Unbelted 11,931 21% 4,279,573 16% Age Group < 65 50,067 89% 23,672,972 90% ≥ 65 6,021 11% 2,547,309 10% BMI Obese (BMI >= 30) 12293 22% 5,207,368 20% Not obese (BMI < 30) 43795 78% 23,672,972 80% Vehicle Type Passenger Car 37465 67% 17,889,937 68% Light Truck or Van 18623 33% 8,330,344 32% Exceed MASH Intrusion Limit(s)? No 52294 93% 25,750,396 98% Yes (one or more areas) 3794 7% 469,886 2% Table 10-6. Summary of unweighted (weighted) NASS/CDS single vehicle roadside hardware impacts by object struck. Device Type Total Raw Single-Vehicle (single and multi-event) Crashes [weighted] Cases with Vehicle Inspection [weighted] Cases with Documented Intrusion [weighted] Cable Barrier + 35 [34,920] 30 [32,529] 1 [634] Guardrail Face* 238 [167,030] 171 [117,466] 13 [3,919] Guardrail End Terminal* 48 [25,663] 35 [15,441] 4 [389] Impact Attenuator 72 [40,472] 43 [25,233] 8 [1,858] Breakaway Pole 140 [54,420] 93 [39,176] 44 [14,013] Other Traffic Barrier** 516 [355,010] 408 [299,953] 81 [24,241] +Cable barrier a separate category from year 2008 onward *Guardrail face and end terminals separate categories from year 2010 onward **All metal barriers (w-beam, cable, box beam) included in this category from 2000 thru 2007 Analysis Results 10.4.1 Analysis of Occupant Compartment Intrusion Magnitude and Occupant Injury Table 10-7 summarizes the chi-square test results comparing relevant intrusion level to nearside occupant linked injury level using the available 1,423 occupants exposed to a vehicle impact and 779 occupants exposed to a non-vehicle impact. The results are separated by object struck (vehicle or non-vehicle) as well as intrusion type (any “relevant” intrusion as previously defined, or toe-

155 pan intrusion only). As there are five different intrusion levels and three different injury severity levels, there are 15 possible combinations. Table 10-7. Summary of statistically significant chi-square test results comparing maximum relevant intrusion level to nearside occupant maximum linked injury level. Contact with another vehicle and toe pan, floor pan, and/or forward of A-pillar intrusion present Contact with another vehicle and toe pan intrusion present Contact with non-vehicle and toe pan, floor pan, and/or forward of A-pillar intrusion present Contact with non- vehicle and toe pan intrusion present Intrusion Injury p Intrusion Injury p Intrusion Injury p Intrusion Injury p ≥ 8 cm AIS ≥ 1 <0.001 ≥ 8 cm AIS ≥ 1 <0.001 ≥ 8 cm AIS ≥ 1 <0.001 ≥ 8 cm AIS ≥ 1 <0.001 ≥ 8 cm AIS ≥ 2 <0.001 ≥ 8 cm AIS ≥ 2 <0.001 ≥ 8 cm AIS ≥ 2 <0.001 ≥ 8 cm AIS ≥ 2 <0.001 ≥ 8 cm AIS ≥ 3 <0.001 ≥ 8 cm AIS ≥ 3 <0.001 ≥ 8 cm AIS ≥ 3 <0.001 ≥ 8 cm AIS ≥ 3 <0.001 ≥ 15 cm AIS ≥ 1 <0.001 ≥ 15 cm AIS ≥ 1 <0.001 ≥ 15 cm AIS ≥ 2 <0.001 ≥ 15 cm AIS ≥ 3 0.0014 ≥ 15 cm AIS ≥ 2 <0.001 ≥ 15 cm AIS ≥ 2 <0.001 ≥ 15 cm AIS ≥ 3 0.0003 ≥ 46 cm AIS ≥ 1 <0.001 ≥ 30 cm AIS ≥ 1 0.0454 ≥ 15 cm AIS ≥ 3 <0.001 ≥ 30 cm AIS ≥ 2 <0.001 ≥ 46 cm AIS ≥ 2 0.0018 ≥ 30 cm AIS ≥ 2 0.0047 ≥ 30 cm AIS ≥ 1 0.0409 ≥ 46 cm AIS ≥ 1 <0.001 ≥ 46 cm AIS ≥ 3 0.0003 ≥ 46 cm AIS ≥ 2 <0.001 ≥ 30 cm AIS ≥ 2 0.0057 ≥ 46 cm AIS ≥ 2 0.0010 ≥ 61 cm AIS ≥ 1 <0.001 ≥ 46 cm AIS ≥ 3 0.0079 ≥ 30 cm AIS ≥ 3 0.0026 ≥ 46 cm AIS ≥ 3 0.0008 ≥ 61 cm AIS ≥ 2 0.0008 ≥ 61 cm AIS ≥ 2 0.0065 ≥ 46 cm AIS ≥ 2 <0.001 ≥ 61 cm AIS ≥ 1 <0.001 ≥ 46 cm AIS ≥ 3 <0.001 ≥ 61 cm AIS ≥ 2 0.0002 ≥ 61 cm AIS ≥ 2 0.0034 10.4.2 Evaluation of Current MASH Occupant Compartment Intrusion Limits The initial binary logistic regression models were developed using the “overall” binary MASH intrusion variable (indicating whether intrusion in excess of one or more MASH thresholds was present for the nearside occupant). These models also included seat belt use, sex, age, BMI, and vehicle type as covariates. Table 10-8 through Table 10-10 show the regression coefficients for each of the injury risk models. A p-value < 0.05 was considered significant and is denoted by ** in the parameter tables. A negative coefficient indicates that, with all other predictors held constant, the baseline condition (listed in the model tables) reduces the injury risk. A positive coefficient indicates that, with all other predictors held constant, the non-baseline condition reduces the injury risk. For example, age (≥ 65) always has a positive coefficient because older occupants are more likely to suffer an injury.

156 Table 10-8. Parameters for the binary logistic regression model used to predict occupant MAIS1+F injuries using overall MASH intrusion. ** indicates statistical significance (p-value < 0.05). Predictor Variable Parameter Coefficient p-Value --- β0, Intercept 1.353 < 0.001** Exceed One or More MASH Intrusion Limit(s) β1, Exceed MASH 1.136 < 0.001** Belt Use β2, Belted -0.355 < 0.001** Gender β3, Male -0.312 < 0.001** Age β4, Age ≥ 65 0.043 0.319 BMI β5, BMI ≥ 30 kg/m2 0.253 < 0.001** Vehicle Type β6, Passenger Car 0.072 0.034** Table 10-9. Parameters for the binary logistic regression model used to predict occupant MAIS2+F injuries using overall MASH intrusion. ** indicates statistical significance (p-value < 0.05). Predictor Variable Parameter Coefficient p-Value --- β0, Intercept -0.774 < 0.001** Exceed One or More MASH Intrusion Limit(s) β1, Exceed MASH 1.407 < 0.001** Belt Use β2, Belted -0.536 < 0.001** Gender β3, Male -0.194 < 0.001** Age β4, Age ≥ 65 0.299 < 0.001** BMI β5, BMI ≥ 30 kg/m2 0.187 0.005** Vehicle Type β6, Passenger Car -0.001 0.813 Table 10-10. Parameters for the binary logistic regression model used to predict occupant MAIS3+F injuries using overall MASH intrusion. ** indicates statistical significance (p-value < 0.05). Predictor Variable Parameter Coefficient p-Value --- β0, Intercept -1.612 < 0.001** Exceed One or More MASH Intrusion Limit(s) β1, Exceed MASH 1.664 < 0.001** Belt Use β2, Belted -0.766 < 0.001** Gender β3, Male -0.027 0.506 Age β4, Age ≥ 65 0.553 < 0.001** BMI β5, BMI ≥ 30 kg/m2 0.136 0.009** Vehicle Type β6, Passenger Car 0.001 0.976 Table 10-11 summarizes the odds ratio results for all three models. Odds ratios larger than 1 indicate a larger risk of occupant injury for the listed “value” condition compared to the “comparison group.” Likewise, odds ratios less than 1 indicate a reduced risk of occupant injury. Note that the statistically significant predictors will have 95% confidence bounds that exclude 1.0.

157 Table 10-11. Summary of odds ratio results for the MAIS1+F, MAIS2+F, and MAIS3+F injury models. Model Predictor Variable Value Comparison Group Odds Ratio 95% CI MAIS1+F Exceed 1+ MASH Limit Yes No Intrusion > MASH Limits 9.69 5.6 – 16.8 Belt Use Belted Unbelted 0.49 0.41 – 0.59 Gender Male Female 0.54 0.46 – 0.62 Age ≥ 65 years < 65 years 1.09 0.92 – 1.29 BMI ≥ 30 kg/m2 < 30 kg/m2 1.66 1.32 – 2.09 Vehicle Type Passenger Car LTV 1.15 1.01 – 1.32 MAIS2+F Exceed 1+ MASH Limit Yes No Intrusion > MASH Limits 16.68 12.2 – 22.8 Belt Use Belted Unbelted 0.34 0.27 – 0.44 Gender Male Female 0.68 0.58 – 0.79 Age ≥ 65 years < 65 years 1.82 1.40 – 2.37 BMI ≥ 30 kg/m2 < 30 kg/m2 1.45 1.12 – 1.88 Vehicle Type Passenger Car LTV 0.98 0.85 – 1.13 MAIS3+F Exceed 1+ MASH Limit Yes No Intrusion > MASH Limits 27.9 20.6 – 37.7 Belt Use Belted Unbelted 0.22 0.18 – 0.26 Gender Male Female 0.95 0.81 – 1.11 Age ≥ 65 years < 65 years 3.02 2.34 – 3.90 BMI ≥ 30 kg/m2 < 30 kg/m2 1.31 1.07 – 1.61 Vehicle Type Passenger Car LTV 1.00 0.83 – 1.22 Similar model results were obtained using the vehicle region-specific intrusion indicators (model parameter values not shown). Table 10-12 summarizes the odds ratio results for exceeding the MASH intrusion limits in each specific vehicle region based on the three injury level threshold models. In each case, the odds ratio compares the odds of occupant injury if the MASH intrusion limit is exceeded compared to the odds of injury if the MASH intrusion limit is not exceeded. These can be interpreted as similar to the odds ratios shown in Table 10-11 where values larger than 1.0 indicate an increased risk of injury.

158 Table 10-12. Abbreviated summary of odds ratio results for the MAIS1+F, MAIS2+F, and MAIS3+F injury models with area specific intrusion variables. Model Predictor Variable Value Comparison Group Odds Ratio 95% CI MAIS1+F Exceed Windshield Limit Yes No 6.23 3.25 - 12.0 Exceed Roof Limit Yes No 6.52 3.13 – 13.6 Exceed A/B Pillar Limit Yes No 6.60 3.90 – 11.2 Exceed Toe Pan Limit Yes No 74.4 19.6 – 282 Exceed Side Door Limit Yes No 0.98 0.20 – 4.82 Exceed Side Panel Limit Yes No 17.7 2.52 – 124.8 Exceed Floor Pan Limit Yes No 9.94 2.42 – 40.8 MAIS2+F Exceed Windshield Limit Yes No 6.31 3.84 – 10.4 Exceed Roof Limit Yes No 3.52 2.23 – 5.55 Exceed A/B Pillar Limit Yes No 6.10 4.46 – 8.34 Exceed Toe Pan Limit Yes No 61.9 22.8 – 168 Exceed Side Door Limit Yes No 3.80 1.95 – 7.40 Exceed Side Panel Limit Yes No 20.1 2.03 – 200 Exceed Floor Pan Limit Yes No 5.40 1.91 – 15.1 MAIS3+F Exceed Windshield Limit Yes No 7.99 4.38 – 14.6 Exceed Roof Limit Yes No 3.64 2.24 – 5.90 Exceed A/B Pillar Limit Yes No 8.86 6.46 – 12.2 Exceed Toe Pan Limit Yes No 22.7 10.0 – 51.2 Exceed Side Door Limit Yes No 4.36 2.26 – 8.41 Exceed Side Panel Limit Yes No 1.87 0.53 – 6.56 Exceed Floor Pan Limit Yes No 5.07 2.43 – 10.6 10.4.3 Estimation of Real-World Frequency of Vehicle Damage Patterns Table 10-13 summarizes the rate of intrusion observed for the available impacts with various roadside safety hardware devices. Table 10-13. Summary of intrusion rates for roadside safety hardware devices. Device Type Total Cases [weighted] Percent of Cases with Any Intrusion Present [weighted %] Cable Barrier 30 [32,539] 3.3 [1.9] Guardrail Face 171 [117,466] 7.6 [3.3] All Guardrail 579 [417,419] 16.2 [6.7] Guardrail Terminal 35 [15,441] 11.4 [2.5] Breakaway Pole 93 [39,176] 47.3 [35.8] Impact Attenuator 43 [25,233] 18.6 [7.4] The research team conducted a manual review of the roadside safety hardware impacts with documented intrusion. Given the relatively small number of cable barrier cases, the research team has manually reviewed all of the available cable barrier cases where a vehicle inspection was performed. Based on this review, there were nine vehicles with evidence of cable contact with the vehicle A-pillar (49.1% of cases based on the weighted values). In the vast majority of cases, however, the damage to the A-pillar as a result of the presumed cable contact was relatively minor with no cases where the contact resulted in severing of the A-pillar.

159 Based on the review of the available roadside hardware impacts, there was no evidence of separation of glued seams in unibody type vehicles that has been observed in some full-scale MASH tests. Of the investigated devices, the breakaway pole had the largest proportion of crashes with observed intrusion present (44 of the 93 cases available). Intrusion in the roof and windshield areas was prevalent in these cases. Of the seven total documented windshield intrusions, six were greater than the current MASH limit. For the 15 documented roof intrusions, 13 of 15 were greater than the MASH limit. Discussion 10.5.1 Analysis of Occupant Compartment Intrusion Magnitude and Occupant Injury Similar to the previous Eigen and Glassbrenner (2003) study, the chi-square test results suggest a strong link between intrusion and linked occupant injury level. For the four investigated categories (any relevant intrusion with vehicle contact, toe pan intrusion with vehicle contact, any relevant intrusion with non-vehicle contact, and toe pan intrusion with non-vehicle contact), the majority of the intrusion and injury level combinations were found to be statistically significant. Many of the non-significant intrusion and injury level combinations appear to be primarily a result of a small number of occupants present in one or more of the four contingency table cells. 10.5.2 Evaluation of Current MASH Occupant Compartment Intrusion Limits Eigen and Glassbrenner (2003) selected the “relevant” intrusion areas to focus on the occupant compartment intrusions common in vehicle-to-barrier impacts as, at the time of the Eigen and Glassbrenner study, there were no vehicle region-specific intrusion limits. The intent of this portion of the present study was to provide information relative to the currently used MASH occupant compartment intrusion thresholds. Similar to Eigen and Glassbrenner, the crashes were not limited to roadside hardware or fixed object crashes as the intrusion-to-injury link should be relevant regardless of object struck. Based on the model results using the overall MASH intrusion indicator variable, the MASH intrusion limits are found to be strong predictors of occupant injury at the MAIS1+, MAIS2+, and MAIS3+ levels. The odds of occupant injury were found to range between 10 and 30 times higher for nearside occupants where one or more of the MASH intrusion thresholds were exceeded compared to nearside occupants where none of the MASH intrusion thresholds were exceeded. In each model, this variable had the largest magnitude coefficient compared to the other included predictors, suggesting it has the largest effect on occupant injury risk. With respect to the confounding factors, older, obese, and unbelted occupants were found to have a statistically significant increased risk of injury, regardless of injury level threshold. In general, males were found to be less likely to be injured, but this was only statistically significant at the MAIS1+ and MAIS2+ levels. For the MAIS1+ level, passenger car occupants had a statistically significant increase in injury risk, but vehicle type was not a statistically significant effect for the higher injury threshold models. The models developed using the individual vehicle region intrusion indicators suggest similar results with regard to the specific MASH intrusion limits. With the exception of the side door limit

160 at the MAIS1+ level (which was not statistically significant), all the odds ratios exceeded 1.0 and were statistically significant, suggesting an increased occupant injury risk if the corresponding threshold is exceeded. Based on the odds ratio values and associated lower 95% confidence bounds, exceeding the MASH toe pan intrusion limit appears to have the largest influence on occupant injury risk. At the lower injury levels (MAIS1+ and MAIS2+), exceeding the MASH side panel intrusion limit appears to have a large influence on injury risk, but this effect was not found to be statistically significant at the MAIS3+ level. Also, the lower 95% confidence bound of the side panel indicator was roughly the same as many of the other vehicle region indicators; this coupled with the large range on the confidence bounds suggests more cases with side panel intrusion are needed to better understand this relationship. The odds ratio estimates also suggest that the windshield, A/B pillar, and floor pan areas are influential to injury risk prediction and that the side door area intrusion becomes more influential as the injury threshold level is increased. 10.5.3 Estimation of Real-World Frequency of Vehicle Damage Patterns The vehicle occupant compartment intrusion rates for various roadside safety hardware devices are varied, with the lowest rates present for cable barriers, guardrails (including terminals), and impact attenuators. Generally, these devices result in vehicle occupant compartment intrusion in less than 10% of single vehicle impacts. Impacts with breakaway poles were found to have the highest proportion of vehicle occupant compartment intrusion at approximately one third of cases based on the available weighted data. For a large portion of these impacts, damage to the roof and windshield present was in excess of the current MASH threshold values. Based on a manual review of the cable barrier cases available, cable contact with the vehicle A-pillar appears to be a common occurrence in tow-away level crashes with cable barriers, but there were no instances of severing of the A-pillar. Based on a review of all available roadside hardware impacts, there was no evidence of glued seam separation for unibody type vehicles. Conclusions The analysis of available real-world crashes to correlate vehicle occupant compartment intrusion to occupant injury resulted in the following conclusions: • MASH intrusion limits are found to be strong predictors of occupant injury at the MAIS1+, MAIS2+, and MAIS3+ levels. The odds of occupant injury were found to range between 10 and 30 times higher for nearside occupants where one or more of the MASH intrusion thresholds were exceeded compared to nearside occupants where none of the MASH intrusion thresholds were exceeded. In each model, this variable had the largest magnitude coefficient compared to the other included predictors, suggesting it has the largest effect on occupant injury risk. • With respect to the confounding factors, older, obese, and unbelted occupants were found to have a statistically significant increased risk of injury, regardless of injury level threshold. In general, males were found to be less likely to be injured, but this was only statistically significant at the MAIS1+ and MAIS2+ levels. For the MAIS1+ level, passenger car occupants had a statistically significant increase in injury risk, but vehicle type was not a statistically significant effect for the higher injury threshold models.

161 • The models developed using the individual vehicle region intrusion indicators suggest similar results with regard to the specific MASH intrusion limits. With the exception of the side door limit at the MAIS1+ level (which was not statistically significant), all the odds ratios exceeded 1.0 and were statistically significant, suggesting an increased occupant injury risk if the corresponding threshold is exceeded. • Based on the odds ratio values and associated lower 95% confidence bounds, exceeding the MASH toe pan intrusion limit appears to have the largest influence on occupant injury risk. At the lower injury levels (MAIS1+ and MAIS2+), exceeding the MASH side panel intrusion limit appears to have a large influence on injury risk, but this effect was not found to be statistically significant at the MAIS3+ level. Also, the lower 95% confidence bound of the side panel indicator was roughly the same as many of the other vehicle region indicators; this coupled with the large range on the confidence bounds suggests more cases with side panel intrusion are needed to better understand this relationship. The odds ratio estimates also suggest that the windshield, A/B pillar, and floor pan areas are influential to injury risk prediction and that the side door area intrusion becomes more influential as the injury threshold level is increased. • With the exception of breakaway poles, vehicle occupant compartment intrusion for single vehicle real-world impacts with roadside hardware devices was estimated to occur in less than 10% of crashes. • A manual review of vehicles damaged in single vehicle real-world impacts with cable barriers suggest that cables interact with the vehicle A-pillar in approximately half of the crashes but that the interaction generally results in minor damage and no severing of the A- pillar. No evidence of glued seam separation of unibody type vehicles was observed.