A Bayesian Approach to Model Criticism in Pedestrian Accident Reconstruction

• Activity Number: 375
• Type: Contributed
• Date/Time: Tuesday, August 6, 2013 : 10:30 AM to 12:20 PM
• Sponsor: Section on Physical and Engineering Sciences
• Author(s): Gary Davis*+
• Companies: Univ of Minnesota
• Keywords: model criticism ; accident reconstruction ; Markov Chain Monte Carlo

Abstract

In accident reconstruction, model criticism is possible when two different measurements can be used to estimate the same accident feature, such as when measured skidmark length and pedestrian throw distance each provide an estimate of impact speed. In this case a Bayesian criticism can be carried out by (1) using one measurement and Bayes theorem to compute a posterior distribution for the impact speed, (2) using this posterior distribution to compute a predictive distribution for the second measurement, and then (3) comparing the actual second measurement to this predictive distribution. This presentation describes an implementation of these ideas using WinBUGS, illustrated using 15 staged collisions between vehicles and pedestrian dummies. In 13 of the 15 cases the skidding and throw models yielded consistent results, while in two cases the resulting impact speed estimates were substantially different. In both of the discrepant cases it was possible to identify the sources of the discrepancies, and produce consistency once these were accounted for.