Pedestrian injury risk functions based on contour lines of equal injury severity using real world pedestrian/passenger-car accident data.

Injury risk assessment plays a pivotal role in the assessment of the effectiveness of Advanced Driver Assistance Systems (ADAS) as they specify the injury reduction potential of the system. The usual way to describe injury risks is by use of injury risk functions, i.e. specifying the probability of an injury of a given severity occurring at a specific technical accident severity (collision speed). A method for the generation of a family of risk functions for different levels of injury severity is developed. The injury severity levels are determined by use of a rescaled version of the Injury Severity Score (ISS) namely the ISSx. The injury risk curves for each collision speed is then obtained by fixing the boundary conditions and use of a case-by-case validated GIDAS subset of pedestrian-car accidents (N=852). The resultant functions are of exponential form as opposed to the frequently used logistic regression form. The exponential approach in combination with the critical speed value creates a new injury risk pattern better fitting for high speed/high energy crashes. Presented is a family of pedestrian injury risk functions for an arbitrary injury severity. Thus, the effectiveness of an ADAS can be assessed for mitigation of different injury severities using the same injury risk function and relying on the internal soundness of the risk function with regard to different injury severity levels. For the assessment of emergency braking ADAS, a Zone of Effective Endangerment Increase (ZEEI), the speed interval in which a one percent speed increase results at least in a one percent of injury risk increase, is defined. The methodology presented is kept in such general terms that a direct adaption to other accident configurations is easily done.