Validation of a Smartphone Telematics Algorithm For Classifying Driver Trips.

Details

• Alternative Title:
  Transportation Research Interdisciplinary Perspectives, 2024, v. 25: Validation of a Smartphone Telematics Algorithm For Classifying Driver Trips.
• Journal Article:
  Transportation Research Interdisciplinary Perspectives
• Personal Author:
  Ebert, Jeffrey P. ; Xiong, Ruiying A. ; Patel, Arjun ; Abdel-Rahman, Dina ; McDonald, Catherine C. ; Delgado, M. Kit
• Description:
  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
  
  , 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.
• Content Notes:
  Author manuscript
• Subjects:
  • Automobiles
  • Mobile Applications
  • Smartphone
  • Algorithms
  • Insurance
  • Habits
• Keywords:
  • Driver classification algorithm
  • mobile telematics application
  • driver risk score
  • naturalistic study
  • accuracy
  • usage-based insurance
• Source:
  Transportation Research Interdisciplinary Perspectives, 2024, v. 25
• DOI:
  https://doi.org/10.1016/j.trip.2024.101109
• ISSN:
  2590-1982
• Pubmed ID:
  40927251
• Pubmed Central ID:
  PMC12416331
• Document Type:
  Text
• Funding:
  R49 CE003083/CE/NCIPC CDC HHSUnited States/
• Genre:
  Journal Article
• Pages in Document:
  101109(10 pdf pages)
• Volume:
  25
• Download URL:
  https://stacks.cdc.gov/view/cdc/262116/cdc_262116_DS1.pdf
• File Type:
  [PDF - 569.69 KB]
• Collection(s):
  CDC Public Access
• Main Document Checksum:
  urn:sha-512:6066395ce701e9ee03e602668ede6e264c55af3f64a0bf629ed2c434ef147b3586206e7d7abdb2b0dab4dd84381778b27c25dc3982670f15c8e1306647f4633d