Evaluation of a brake assistance system (BAS) using an injury severity prediction model for pedestrians

Through the years, traffic engineers and researchers have developed a variety of countermeasures to enhance pedestrian safety. Pedestrian-vehicle collisions are regarded as the most serious type of accident since they incur high fatality rates. A fundamental concept in developing effective countermeasures is to analyze pedestrian-vehicle collisions scientifically, which can identify the causes of accidents and accident severity. The objective of this study was to investigate the pedestrian safety benefit of the brake assistance system (BAS) and a functional requirement associated with BAS, namely the time needed to safely detect a pedestrian ahead. An injury severity prediction model for pedestrians was developed to systematically evaluate the BAS in this study. Ordered multinomial logistic regression analysis was used to establish a statistical model capable of predicting pedestrian injury severity. In addition to vehicle characteristics, collision speed and pedestrian characteristics were used as independent predictor variables. The outcomes of this study would be useful in directing the development of safety policies and technologies associated with pedestrian safety.