Muscle Responses of Car Occupants Numerical Modeling and Volunteer Experiments under Pre-Crash Braking Conditions

Over 30 000 fatalities related to the road transport system are reported anually in Europe. Of these fatalities, the largest share is car occupants, even though significant improvements in vehicle safety have been achieved by the implementation of in-crash restraints and pre-crash driver support systems. Integration of pre-crash and in-crash safety systems has a potential to further reduce car occupant fatalities and to mitigate injuries. The aims of this thesis are to study the muscle responses of car occupants subjected to integrated safety interventions, and to model them in a numerical human model with active muscles. More specifically, pre-crash braking with standard and reversible pre-tensioned restraints is investigated. A method to model car occupant muscle responses in a finite element (FE) human body model (HBM) was developed, utilizing feedback control of Hill-type muscle elements. It was found that the car occupant response to autonomous braking can be modeled with feedback control, by which stabilizing muscle activations are generated in response to external perturbations. However, modeling driver initiated braking requires the inclusion of a hypothesized anticipatory feed-forward response. Volunteer tests to provide validation data for the HBM were conducted, analyzed, and utilized for model validation. It was found that, in some car occupants, seat belt pre-tension can cause a startle response in the form of a bilateral, simultaneous, short peak contraction of all upper body muscles. Car occupant muscle activation levels during normal driving and in braking events were also quantified in percent of maximum voluntary efforts. The HBM developed with active muscles was able to capture the kinematic response of the volunteers in these events, with muscle activation levels of magnitude similar to that of the volunteers. The method to model muscle responses with feedback control in an FE HBM has the potential to improve the model response in all pre-crash and in-crash scenarios in which muscle contraction can influence occupant kinematics, for instance multiple events and roll-over accidents. It provides a means for the virtual development of advanced integrated restraints that can lead to improved vehicle safety and a reduced number of fatalities and injuries in the road traffic environment.