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mHealth Smartphone Application to Measure Risky Driving Behavior and Predict Crashes

Thursday, September 14, 2017 — Poster Session III

12:00 p.m. – 1:30 p.m.
FAES Terrace


  • RZ Freidlin
  • AD Dave
  • BG Espey
  • ST Stanley
  • MA Garmendia
  • CA Roque
  • TJ Pohida
  • JP Ehsani
  • BG Simons-Morton


Teenage drivers, compared to other age groups, have the highest risk of fatal automobile crashes per driven mile. In 2015, there were 221,313 teenage drivers admitted to hospital emergency rooms that tragically resulted in 2,333 fatalities (CDC statistics, average of 6 per day). Elevated gravitational force event rates (kinematic risky driving or KRD), representing erratic and risky driving, are associated with crash risk among young drivers. Presently, KRD measurement is complicated and expensive. The principal objective of our work is to develop a simple, non-proprietary smartphone-based tool (i.e., custom application) to assess KRD and facilitate and advance driving research to potentially reduce teenage automobile accidents and fatalities. mHealth solutions and data-centralization methods could reduce cost and resolved challenges associated with collecting objective KRD data on large samples. Data could be collected from previously unmeasured populations (e.g., lower socio-economic strata, low-income countries) and over long periods, which could result in further insights about teenage risky driving and methods for assessing KRD using smartphone applications. In this work, we evaluate the feasibility of using smart phone devices and corresponding applications as research tools for naturalistic driving studies. We compared linear acceleration acquired with iPhone 6 and Android (Samsung Galaxy S5) devices to acceleration measurements obtained on a test track with an in-vehicle Nextgen Data Acquisition System (DAS) developed at the Virginia Tech Transportation Institute (VTTI).

Category: Biomedical Engineering and Biophysics