Procesos Logísticos Internos

Table 5.1 Summary table for the risk curves developed in Figure 5.3 c–f). Impact severity measured in terms of ∆v_lat, where all values are specified in km h⁻¹.

%^ile Tho.MAIS3+ 95%CI tSAB No tSAB

deployed deployed Non-Senior

Age:45

10^th 22.1 20.7–23.6 21.4 22.3

25^th 32.1 30.4–33.8 32.7 31.8

50^th 44.4 41.6–47.5 47.4 43.2

75^th 57.5 52.7–62.6 63.6 55.1

Senior Age:67

10^th 17.6 14.3–21.6 18.7 17.3

25^th 26.2 21.8–31.4 27.3 25.8

50^th 37.1 30.2–45.5 37.9 36.8

75^th 48.8 38.2–62.3 49.1 48.5

5.3 Module Discussion

Age cohort Curves

Consumer testing of lateral impacts generally occurs with a ∆v_lat of 20− 35kmh⁻¹ for barrier impacts [Sunnevang et al. (2010)]. When considering the predicted curve as a point estimate, within the bounds of consumer testing a predicted 40% risk of Tho.MAIS3+ for the senior population and a predicted risk approaching 30% for the non-senior population are achieved. The distribution of thoracic injuries in the non-senior populations appears to exhibit a non-skewed, symmetrical distribution where the greatest number of injuries occurs at the upper bounds of the consumer test. Inversely, the impact severity that corresponds to the largest number of non-injured occupants was at severities below consumer test limits.

This would provide reason to increase the (lateral) test speed in an effort to reduce the prevalence of real-world non-senior occupant injuries⁷⁸. On the other hand, the distribution of injured senior occupants appears more shallow with no noticeable peak in injuries at any given collision severity interval. The relative percentages of occupants incurring injury were greater in the senior population (21% senior and 10% non-senior). Whilst the elderly are more susceptible to injury, the frequency of injury was not as apparent as the non-senior population. This emphasizes the trade-off problem faced by vehicle engineers. Should they account for the more susceptible injured population or the population with greater frequency?

The senior population will account for the largest increase in driving population in the not so distant future as the baby boomers age [Yoganandan et al. (2005)]. Parallel to the increasing

78An initiative that will be phased into new Euro NCAP testing protocols by 2020 with an increased impact speed [van Ratingen (2017)]

numbers of the senior population, is their willingness to drive. This was shown in a review of the American driving market which indicated that approximately 19 million senior⁷⁹ licensed drivers existed in 2000, an increase of 36% from the previous decade - with similar projections expected for the forthcoming decades [NCSA (2001)].

The general curves for the senior and non-senior population present different results to those reported in a similar study [Sunnevang et al. (2010)]. This was most likely attributable to a different methodology and the non-use of the collision weighting factors. The Sunnevang et al. (2010) study used logistic regression, which was less favoured by McMurry and Poplin⁸⁰ (2015). Additionally, when using survival analysis a level of complexity arises in calculating confidence intervals as mentioned in the Section 5.2.3. If one were to account for the larger proportion of lower severity collisions, it would be expected that the curves parametrise in a manner where they remain flatter over an extended ∆v_latrange. The slope would exhibit a steep increase at a given ∆v_lat value. Nonetheless, the 50^th%^ilefor both the senior and non-senior populations only differed by a few km h⁻¹, with greater tolerances (higher 50^th%^ilecollision severities) associated with the results in the presented study. The most likely cause of the slight differences was that Sunnevang et al., included vehicles with design years prior to 1998. As our study excluded vehicles with design years prior to 1999, the increase in ∆v_lattolerances was likely attributable to improved self-protection associated with the introduction of US–NCAP. Therefore, a supplementary analysis was conducted in which vehicles were separated by vehicle year, ignoring any influence of the tSAB.

New Tho.MAIS3+ injury risk curves were developed for 1999-2004 and 2005-2015 model year vehicles⁸¹ and appear in Figure Appendix C.2 . The curves indicated that the predicted risk of injury at the 10^th%^ile was statistically significant at the 5% level.

Additionally, an observable lateral shift in risk curves was seen for the newer vehicles -the affect we expected to see for -the tSAB vehicles. Such results infer that -the level of protection provided by a late-model post-US NCAP vehicle exceeds that from an early-model post-US NCAP vehicle. This finding complements Figure 3.1, that vehicle crashworthiness standards have been continually improved and greatest protection is afforded to the latest model vehicles.

In keeping with the ISO document, risk curves were developed for an occupant aged between 45 and 67 years. Secondary curves were developed for age offsets, to highlight the linear effect of age within the two groups. The curves described in Figure 5.3a-b) and Table 5.1, indicated that statistically significant results were not obtained due to the overlapping of the confidence intervals. This was solely attributable to the ages selected - as an occupant

79In this study, the senior population were those aged 70 and older

80Discussed in Section 3.4

81According to the VIN

5.3 Module Discussion

aged 67 encapsulates the lower age limit for the senior population. The linear effect of age shows the magnitude of model shift for an occupant aged 82. The amount of shift between the solid and dashed lines would be mirrored in the confidence intervals. Thus, for ages greater than 67 years, it would become apparent that the senior population exhibit greater susceptibility to injury for a given crash severity than an occupant aged 45. This remains a limitation of the ISO document which outlined the definition of 67 years. Reasoning for selecting the age was due to its association as the median PMHS age used for the development of World SID injury risk curves. In defining such an age, it may not encapsulate the greater susceptibility to injury that is associated with the senior population.

Airbag deployment

The analysis considers the risk curves based on the raw events which are recorded in NASS-CDS and does not account for the associated weighting factors for the previously mentioned reasons.

The primary purpose of this study was to investigate the efficacy of the deploying thoracic side airbag (tSAB) in preventing serious thoracic injury. It would be expected a visible shift to the right⁸² for the airbag curves relative to the vehicles without this technology. Such a result would indicate that occupants have greater tolerance to crash load with the presence of a deployed tSAB. Yet it is well established, this passive safety technology increases the energy that must be dissipated during a collision.

When considering the non-senior population, the curves did not differ until a severity of ∆v_lat > 30km h⁻¹ was attained. One must acknowledge that collisions at this severity seldomly occur, as indicated by the histogram in Figure 5.3a). Above this severity a slight positive effect in the injury risk became apparent for the occupants exposed to the deployed tSAB. Yet the results were not conclusive as confidence intervals were overlapping. The parametrisation of the curves suggested a protective-trend may be apparent, however the overlapping confidence intervals only allowed for interpretation of a possible trend. For severities exceeding ∆v_lat> 60km h⁻¹, curves trended towards similarity once again, where it was expected that injury, at the MAIS3+ level, was inevitable at such high collision severities.

The acutely similar curves predicted for lower severity collisions (∆v_lat< 30km h⁻¹), indicated that occupants were at equal risk of injury. Reasoning that the curves did not differ may be attributable to the greater presence of pioneering tSABs first available in the vehicle fleet. Of which, the geometry, pressurisation and other characteristics have since been continuously improved and designs optimised. A study compared the breakout times of different geometric side airbags and indicated that those enclosed within a casing appeared

82Similar to that seen in Figure C.2 when vehicle were separated on vehicle year

more quickly than those which deployed through the seat seam [Balavich et al. (2011)].

These designs are now less favoured than those which deploy through the seat upholstery.

Aside from a manufacturing cost perspective, the units enclosed within a casing, may have additionally been phased out of production. Furthermore, as the casing itself opens during deployment, it has the possibility as being attributable to an association of injury.

Retrospective analysis, despite accounting for only post-US NCAP vehicles, consisted of vehicles that were designed almost two decades ago. The results nonetheless, did not indicate additional thoracic injury mitigation ability associated with the deployed tSAB.

This does raise some initial concern, as the vehicles with the deployed tSAB are generally newer vehicles, which are assumingly stiffer [Lee et al. (2014)], thus one would expect a noticeable shift in risk of injury favouring the exposed occupants. However, this was not evident suggesting that despite the stiffness increases, energy mitigation associated with airbag deployment is not being sufficiently executed.

When considering the senior population, the curve suggests the tSAB showed no ability to prevent serious thoracic injury. Given the rate of change for the predicted injury risk curves over ∆v_lat= 20− 45kmh⁻¹, the results infer that risk of injury was primarily dependent on

∆v_lat. Griffin et al. (2012) suggested that the seniors may be more susceptible to injury when the airbag deploys, however, was not evident from the curves. The reason may be that the authors also used collisions from a secondary database (CIREN database) which is biased towards severely injured occupants or the use of raw events. Yet, if one were able to truly account for the stiffness changes associated with the fleet, one may expect such a trend to be evident.