Validation of a smartphone telematics algorithm for classifying driver trips
Transportation Research Interdisciplinary Perspectives(2024)
Abstract
This study assessed the accuracy of a smartphone telematics algorithm that classifies car trips as driver or non-driver. Participants’ trips were measured for 4 weeks by Way to Drive, a research telematics application that uses the same data algorithms as leading auto-insurance companies. At the end of each week, participants completed a survey prompting them to review trips within the app and report time and nature of any misclassified trips. Overall accuracy of driver vs. non-driver classification was high (96.5 %, SD = 5.1 %). Sensitivity, the percentage of actual driver trips classified as such, was also high (97.5 %, SD = 4.6 %). Specificity, the percentage of non-driver trips classified as such, was slightly lower and more variable (91.2 %, SD = 14.8 %). The algorithm’s accuracy was generally robust to a variety of phone characteristics, vehicle features, and driving habits.
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Key words
Driver classification algorithm,Mobile telematics application,Driver risk score,Naturalistic study,Accuracy,Usage-based insurance
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