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Of the injuries sustained by belted rear occupants in a frontal collision event in Japan, the neck and the head are the regions of the body most likely to be injured, while children and female occupants are accounting for the highest rate of injuries. For the purpose of reducing rear seat occupant injuries, the occurrence mechanism of neck and head injuries is clarified by sled tests with the current rear seat belt system. When a high load is applied to the occupant via the seat belt, the occupant experiences sudden deceleration of the chest, resulting in a great relative velocity difference between the head and the chest. This causes injury to the occupant's neck and head. To reduce occupant injuries, therefore, it is important to minimize the relative velocity difference by control of belt load.

With an aim to improve compatibility performance, vehicle-to-vehicle frontal impact simulations have been conducted between large car and small car. Focusing on sub-frame structure that disperses applied force with multiple load paths, a large saloon car with sub-frame was selected and three different front structures were studied: original, forward-extended sub-frame, and original with 25%-stiffness reduced structures. The types of collision contained four different crash modes in a combination of lateral overlap rate difference and side member height difference. As a result, it was found that the front structure with forward-extended sub-frame improved aggressivity by preventing override effect through structural interaction enhancement. Height of Force (HOF) was also improved.

Driver fatality rate of a passenger vehicle is considerably high when struck on the side by an LTV (light truck and van). Aggressivity of LTVs, particularly in side crashes, needs to be reduced to improve this incompatible situation. Crash energy absorption share of a passenger car struck on the side by an LTV was measured through component tests. As a result, B-pillar of the struck passenger car was found to receive most of the crash energy intensively. This intensive energy triggered large B-pillar deformation. Computer simulation proved that B-pillar deformation was closely related to occupant injury. The key to mitigate the injury of side-struck car occupant, therefore, is to disperse crash energy to other structural parts than B-pillar. Front-end structures of LTVs that realize crash energy dispersion were designed and examined. The structures include (a) optimization of the vehicle height, and (b) adoption of a forward-extended sub-frame.

This paper clarifies aggressivity reduction approach for MPV, Multi-Purpose Vehicles, derived from large passenger vehicles toward small passenger vehicles. The effects of aggressivity-reducing approach were measured through full-frontal rigid barrier crash simulations with TRL aluminum honeycomb by Finite Element Method. The front-end structures of large vehicles studied in this paper based on this aggressivity reduction approach show good front-end homogeneity and low average height of force. The structures were also found to effectively reduce aggressivity toward small vehicles by car-to-car simulation. However, there are some cases where the effect was influenced by overlap ratios. From this result, overlap ratio is considered to be one of the important factors to improve compatibility performance.

To reduce real world fatal/serious/minor injuries, factors causing such injuries should be investigated in depth from wider perspectives. The aim of this paper is to clarify the factors based on Japanese accident database compiled by ITARDA (Institute for Traffic Accident Research and Data Analysis). ITARDA database has data for injury rates, seatbelt use rate of driver and age of driver involved in crashes, etc. by vehicle model. As a result of an elaborate statistical analysis, the most influential and essential factors on all injuries including fatality were quantitatively found to be seatbelt use rate and vehicle weight. The increase by 1% in seatbelt use rate makes injury rate decrease by 7%. The influence of vehicle weight is 1.7 times higher than seatbelt use rate. Multiple regression analysis on these two parameters was also conducted. The present analysis successfully predicted all injury rates by model per 10,000 units.