Validation of Vehicle-Based Injury Severity Prediction Using Crash Telemetry Data

Subaru has developed vehicle-based Injury Severity Predictions (ISP) models using data from the National Automotive Sampling System Crashworthiness Data System (NASS-CDS) covering calendar years 1999–2015, for integration into Advanced Automatic Collision Notification (AACN) systems. This study evaluates the accuracy of these ISP models by comparing predictions derived from Subaru vehicle telemetry with actual Injury Severity Scores (ISS) of transported occupants. Two crash databases were utilized: Subaru Telematics Assisted Accident Research (STAAR) data for calendar years 2021–2024, which includes Automatic Collision Notification (ACN) data, police reports, emergency medical services (EMS), and medical records from the medical centers across Michigan; and the Fatality Analysis Reporting System (FARS) data for calendar years 2021–2023, matched with ACN data to supplement serious injury cases. ISS values were obtained from medical records in STAAR, while fatal cases in FARS were assigned as fatal injury. Four ISP models were evaluated, grouped into two main approaches: (1) models using categorical impact directions (Front, Right, Rear, Left), (2) models applying functional data analysis with cyclic spline modeling of Principal Direction of Force (PDOF). The presence of a right-front passenger was also considered as an interaction factor. Among 56 STAAR cases, only one involved serious injury (ISS ≥ 15), limiting sensitivity analysis. All models demonstrated specificity above 90%. In 102 FARS cases, 44 were fatal, yielding sensitivity between 52% and 57%. Models using PDOF splines performed similarly to directional models. When multiple impacts were excluded, sensitivity improved to 63%–74%, suggesting that in such crashes, PDOF may not be clearly identifiable from vehicle telemetry data. Although functional data analysis was expected to enhance sensitivity, this improvement was not confirmed. Additional data collection is needed to improve ISP accuracy. Vehicle telemetry remains a rapid and cost-effective method for acquiring crash data to advance vehicle safety.