SRA-E Lisbon 2017

An extensive number of research studies have attempted to capture the factors that influence the severity of vehicle impacts. The high number of risks facing all traffic participants, inclusive of pedestrians, motorised and non-motorised transport, has led to a gradual increase in sophisticated data collection schemes linking crash characteristics to subsequent severity measures. This study combines the National Highway Traffic Safety Administration’s (NHTSA) Crash Injury Research (CIREN) database for the years 2005–2014 with the Book of Quantum, an Irish governmental document that offers guidelines on the appropriate compensation to be awarded for injuries sustained in accidents. An Ordinary Least Squares (OLS) Linear Regression is carried out to identify the crash factors that significantly influence expected compensation costs. The model offers encouraging results, attaining an adjusted R-squared fit of 20.7% when uninfluential factors are removed. It is found that relative speed at time of impact and vehicle age increase the expected costs, while incidents sustained both in the rain and while turning result in lower expected compensations, as do rear-end incidents. The scalar-outcome approach used in this research offers an alternative methodology to the discrete-outcome models that dominate traffic safety analyses by expanding on the flexibility afforded by random parameter and latent-class variable models. The results raise queries on the future development of claims reserving based on classic statistical models, as advanced driver assistant systems (ADASs) seek to eradicate the most frequent types of crash factors on which insurance mathematics base their assumptions.