Objective
The development of adaptive safety systems addressing vehicle occupant protection requires the use of in depth knowledge of various occupant features, specifically those related to the risk of injury. All occupants in passenger vehicles are at risk of sustaining whiplash injuries in a low severity crash. Whiplash associated disorders (WAD), so called whiplash injuries, resulting from car crashes, are a serious traffic safety issue, resulting in over 4 billion € costs to European society. Yearly more than 300 000 European citizens suffer neck problems from these injuries and 15 000 result in long terms consequences. In the population, the females are at higher risk of these injuries than the males. The difference in risk between the robust, male, population and the vulnerable, female, part of the population is between 40-100%. This has been reported from epidemiological studies from all over the world since the end of the 1960s until today. Yet still, when assessing the vehicle safety the only available occupant model for these impact scenarios is an average male. Adaptive anti-whiplash systems need to be evaluated for their benefits both for males and females. If there are no improved protective systems, further rising costs for the European Society can be expected.
This project aims at establishing the properties for a model of an average female and to implement those in a computational model in order to provide an improved tool for the development and evaluation of adaptive systems with special focus on protection against whiplash injuries.
The project will result in a computational model of a female, in addition to the male model that already exists, for low severity testing. In addition, the computational models will be used in the design and evaluation of adaptive seat systems in order to provide enhanced neck injury protection from the seat.
Keywords
Call for proposal
FP7-SST-2008-RTD-1
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Funding Scheme
CP-FP - Small or medium-scale focused research projectCoordinator
58195 Linkoeping
Sweden
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Participants (12)
412 96 Goteborg
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80539 Muenchen
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10660 Stockholm
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8010 Graz
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67081 Strasbourg
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8006 Zuerich
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LE11 3TU Loughborough
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Participation ended
2600JA Delft
47151 Valladolid
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405 31 Goteborg
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92000 Nanterre
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69126 Heidelberg
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