Characteristics of Anti-Whiplash Seat Designs with Good Rear-Life
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CHARACTERISTICS OF ANTI-WHIPLASH SEAT DESIGNS WITH GOOD REAL-LIFE PERFORMANCE Ola Bostrom*, Anders Kullgren** *Autoliv Research, Sweden **Folksam and Karolinska Institutet, Sweden ABSTRACT In the last 10 years car seats have been specifically designed to mitigate short and long-term neck injuries caused by rear end impacts. During this period of time, anti-whiplash seat ratings also have been introduced. Recent research have shown rating methods to correlate to real-life performance. The objective of this study was to describe possible characteristics of real-life good performing anti- whiplash seat designs. To meet the objective, first a real-life data analysis was performed. In total 1111 Folksam and 2630 police reported injuries between 1998 and 2006 were included. As a result, the redesign of the Saab, Volvo and Toyota seats in the late 90s showed a 50-70% reduction in risk of whiplash symptoms for more than 1 month. Secondly, a rating test series with Saab, Volvo and Toyota seats before and after the anti-whiplash redesign were performed. Also, published rating performances of seats with these designs were analyzed. As a conclusion, possible characteristics of good performing seats were good performance in dynamic rating tests, especially for the low and medium severity pulses, through designs aimed at reducing head-to-head restraint distance and yielding/energy absorption of the seat. Keywords: Disabled, Neck, Rear impacts, Seats, Whiplash Long-term neck injuries caused by rear-end impacts have been an issue since the first car seat was designed. According to Krafft (1998) the risk of injury was doubled in car models from 90s compared to 80s. In the late 90s, the first rear-end impact crash test dummy was launched as a result of a Swedish research program. A few years later, the first public dynamic ratings of anti-whiplash seat designs were introduced by IIHS, Folksam/SRA, Thatcham and ADAC. In these rating tests, both seat evaluations as well as injury parameters were used. In a study by Kullgren et al (2003) of numerical reconstructions of real-life crashes, the predictability of the dummy evaluation parameters NIC and Nkm were shown to be applicable in seat evaluation. Moreover, for these parameters risk curves for more than one month of symptom duration were established. Real-life rear-end impact performance of various cars have been published (IIHS; Folksam) and recent research by Kullgren et al (2007) has shown that public ratings of seats do correlate with real-life performance. Although it is known that overall rating performance does reflect overall real-life performance, the characteristics of good seat designs are less known. Studies have indicated that headrest geometry, including head-to-headrest backset, reduces risk of injury (Jakobsson, 2004; Nygren, 1985). In a study where 8500 cars with poor headrest geometry were redesigned with yielding seat attachment brackets (YSAB), the yielding function (the only design change) was shown to considerably reduce the risk of whiplash injury leading to long-term consequences (Krafft et al, 2004). Also, the car manufacturers Saab and Volvo have shown their SAHR (Saab Active Head Restraint) (Wiklund and Larsson, 1997) and Whips (Whiplash Protection System) (Lundell et al, 1998) systems to be effective in real life rear- end impacts (Viano and Olsén, 2001; Jakobsson, 2004). Adding the Toyota WIL (Whiplash Injury Lessening) system (Sekizuka 1998), these three systems were claimed by each car manufacturer to be designed to reduce head-to-headrest distance and/or yield/absorb energy in a force controlled manner. The objective of this study was to describe possible characteristics of real-life good performing anti-whiplash seat designs. Therefore, a real-life as well as dynamic rating analysis was performed of Saab, Volvo and Toyota car models just before and after the SAHR/Whips/WIL redesign. In addition, published rating of seats with these designs was included in the analysis. IRCOBI Conference - Maastricht (The Netherlands) - September 2 007 219 METHOD The method and result sections are divided into two sub-sections, a real-life performance and a dynamic rating performance section. REAL LIFE PERFORMANCE - The real-life evaluation was based on two different data sources. To calculate the proportion of injuries leading to long-term symptoms (defined below) all whiplash injuries in rear-end crashes reported to the insurance company Folksam between 1998 and 2006 were used. In total 1111 reported whiplash injuries were included. To calculate relative risk of an injury in rear-end crashes all two-car crashes reported by the police between 1998 and 2006 were used, in total 2630 crashes. Injury classification - Claims reports including possible medical journals for all crashes with injured occupants between 1998 and 2006 were examined. Whiplash injuries reported in rear-end crashes within a range between +/-30 degrees from straight rear-end were noted. Insurance claims were used to verify if the reported whiplash injuries led to long-term symptoms. Occupants with long-term symptoms were defined as those where a medical doctor examined the occupant and the occupant claimed injury symptoms for more than 1 month, which corresponds to a payment of at least 2000 SEK (about 300 US$) in the claims handling process used by Folksam. Out of the 1111 persons reporting a whiplash injury, 130 (12%) led to long-term symptoms according to that definition. Calculation of relative injury risk - According to Evans (1986), when two cars collide with each other, the injury risk for Car 1 in relation to Car 2 can be expressed as the number of injured occupants in Car 1 in relation to the number in Car 2. This is equal to the risk of injury in Car 1 in relation to the risk of injury in Car 2, which can be denoted as p1/p2. Assuming that the probabilities p1 and p2 are independent, and that the injury risk in Car 2 can be expressed as the injury risk in Car 1 multiplied by a constant, four cases can be summed: x1, x2, x3 and x4. The relative injury risk in the whole range of impact severity is equal to equation (1). In this study the relative injury risk for the sum of all cars in each group studied was calculated. In a similar way the relative risk of injury in rear-end crashes can be calculated with the same technique, where the number of crashes with injured drivers in the struck car in rear-end crashes in relation to the number of crashes with injured drivers in the striking car are summed, see Table 1. The method used in this study to calculate relative injury risk has been further described by Hägg et al. (1992) and Hägg et al (1999). The initially presented method is relevant for cars of similar mass. If Car 1 and Car 2 have unequal mass, the exposure to impact severity will be unequal as well. While crashworthiness rating based on real-life experience should preferably show the benefit or dis-benefit of mass, the current method would give too much attention to mass, as it would also include the benefit or dis-benefit for the colliding partner. When calculating the injury risk for car models relative to the average car, it is important that the relative injury risk for all car models can be compared with the identical average car. This is not the case if the influence of mass differences on the exposure for the collision partner is not compensated. The initial estimate, equation (1), must therefore be modified to take mass relations into account. The factor m was calculated for the car models in each group under study, and thus used to compensate the relative injury risk for the models in each group, see equation (2). 220 IRCOBI Conference - Maastricht (The Netherlands) - September 2 007 Table 1. Classification of combinations of injured drivers in the struck and striking car in rear- end crashes. Drivers in the striking car Total Driver not driver injured injured driver Drivers X x x+ x injured 1 2 1 2 in the driver struck not X x car 3 4 injured Total x1+ x3 x1 = number of crashes with injured drivers in both cars x2 = number of crashes with injured drivers in struck car and not in the striking car x3= number of crashes with injured drivers in striking car and not in struck car x4= number of crashes without injured drivers in both cars R = (x1 + x2) / (x1 + x3) (1). ((M-Maverage)/100) Rmodified = R*m = ((M-Maverage)/100) = (x1 + x2) / (x1 + x3) *m (2). M is the mass of the studied vehicle and Maverage is the average mass of all vehicles. In these calculations the factor m was set as 1.035, see Hägg et al. (1992), which mean that the mass effect used to control for the exposure on impact severity was 3.5% per 100 kg. The relative risk of sustaining an injury with long-term symptom was calculated as the product of the relative injury risk and the proportion of occupants with long-term symptoms in relation to the number of reported whiplash injuries (no symptom length constraint). Categories of cars studied - The reported whiplash injury (no symptom length limit) and long-term injury (1 months as defined above) risks were calculated for some different categories with and without whiplash protection system as described in Table 2. Note that in the Volvo S70/V70 model WHIPS was introduced in May 1999. Because it was not possible to identify whether these cars in real-life crashes were fitted with WHIPS or not, this model year was excluded in the analysis. Table 2. Car models included in the defined groups.