<div class="section abstract"><div class="htmlview paragraph">Road accidents are a major concern worldwide and vulnerable road users make up more than half of the victims of road accident deaths. In order to combat this issue, several countries worldwide have mandated pedestrian safety test regulations viz., AIS100 & UN-R127. One of the requirements of the regulations is when Flexible Pedestrian Legform Impactor (Flex-PLI) is impacted onto the frontal structure of the vehicle at a speed of 40kmph, the Bending moment (BM) of tibia bone of Flex-PLI shall not exceed the regulatory limit of 340Nm. In this paper, we have built a statistical model for predicting the BM of tibia in Flex-PLI using regression analysis. 13 vehicles have been selected from all applicable vehicle categories viz., Sedan, hatchback, Coupe & SUV/MUV for this undertaking. An exhaustive analysis of the vehicle frontal structures and Flex-PLI test videos have been done to identify & measure the design parameters to be used as predictor variables. The vehicles have then been physically impacted with the Flex-PLI and the recorded tibia BMs have been used as the response variables. A regression model has been prepared using the predictor and response variables and an empirical equation has been established. The regression model has been validated by separating the available data into training and test data. Among the 312 evaluated data points across the 13 vehicles, 79.8% of the data points have Full-scale (FS) error less than 10% and 93.6% of the data points have FS error less than 15%. This model can be deployed in the design stage of the vehicle development process to identify concerns in the vehicle design. This enables a quantitative approach to designing vehicles while ensuring regulatory compliance. Also, its time-efficient operation will have a positive impact in reducing the vehicle development timeline.</div></div>
