Harmonizing Insurance Crash Data with the IGLAD Common Data Scheme: Reconstruction and Digitization: A Weighted Compatibility Rating System for Assessing Crash Data

Abstract

Road traffic accidents involving vulnerable road users (VRUs) remain a significant global safety concern, and the in-depth accident database Initiative for the Global Harmonization of Accident Data (IGLAD) plays an important role in advancing safety research. Insurance companies hold large volumes of crash data that could potentially enrich such databases, and effective methods for evaluating their harmo nization readiness are of practical value. Utilizing the People Around the Vehicle (PAV) crash database from If P&C Insurance as an example, this project investi gates the feasibility of harmonizing car-to-VRU-oriented insurance crash data with the IGLAD common data scheme. Variable-level mapping and structural harmo nization strategies are explored, and the Weighted Compatibility Rating System (WCRS) is proposed to quantitatively evaluate reconstruction relevant variables at both the dataset and individual case level. Applied to PAV and existing IGLAD member datasets, the results reveal gaps in multiple variable aspects. Case-level assessments further show that reconstruction feasibility of the given case samples is constrained by the absence of measured scene geometry, objective velocity ref erences, and VRU anthropometric data. Accordingly, targeted recommendations for data collection practice are proposed. The tools developed are designed for broader applicability and are expected to support the evaluation of future datasets contributing to IGLAD.