Considering the significant sensitivity of impact velocity to pedestrian casualty rate, it is important to accurately estimate the effect of autonomous emergency braking systems for pedestrians (AEBP) on the casualty rate to further reduce pedestrian victims. This study developed a methodology to estimate the reduction of pedestrian casualties resulting from AEBP activation by applying the exact logic of a particular AEBP system to Japanese accident statistics. Focus was given to the sensitivity of applying the exact logic of a particular AEBP system and the parameters considered in the fatality/serious injury rate prediction to the estimated effect of the AEBP system.
Due to the difference in accident parameters relevant to the function of the AEBP system and the impact configurations and outcomes, two sets of accident data, which include different accident parameters with some overlap, were used to estimate the distribution of impact speed and the reduction in the fatality/serious injury rates. One dataset was used to estimate the impact speed distribution by applying the exact logic of a particular AEBP system, and the other dataset was used to determine the fatality/serious injury rates. The reduction of the number of victims was estimated by lumping the estimated impact speed distribution and the estimated fatality/serious injury rates into the accident scenarios defined by the common parameters. The sensitivity to the reduction in the number of victims was investigated for the application of the exact logic, and the parameters considered in the estimation of the fatality/serious injury functions.
The estimated reduction in the number of victims was 20% for the AEBP system investigated in this study. Relative to the use of a simple logic of the system, the application of the exact logic of the system resulted in the difference in the estimated reduction of fatalities and serious injuries by 5% and 12%, respectively. The most severely injured body region, the pedestrian age, and the vehicle category are the most sensitive to the estimated effect among the accident parameters used in the dataset relevant to impact configurations and outcomes except for the vehicle travel speed.