Citation

Ebert JP, Xiong RA, Patel A, Abdel-Rahman D, McDonald CC, Kit Delgado M. Transp. Res. Interdiscip. Persp. 2024; 25: e101109.

Copyright

(Copyright © 2024, Elsevier Publishing)

DOI

10.1016/j.trip.2024.101109

PMID

unavailable

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.

Keywords

Accuracy; Driver classification algorithm; Driver risk score; Mobile telematics application; Naturalistic study; Usage-based insurance