Conference Proceeding

It’s All in the Timing: Using the Attend Algorithm to Assess Texting in the Nest Naturalistic Driving Database

Authors
  • Sean Seaman (Touchstone Evaluations, Inc.)
  • Joonbum Lee (MIT AgeLab and New England University Transportation Center)
  • Bobbie Seppelt (Touchstone Evaluations, Inc.)
  • Linda Angell (Touchstone Evaluations, Inc.)
  • Bruce Mehler (MIT AgeLab and New England University Transportation Center)
  • Bryan Reimer (MIT AgeLab and New England University Transportation Center)

Abstract

To better understand cellular phone texting behavior and its relationship to crashing, we combined the sample-level glance data of NEST with the AttenD buffer algorithm to visualize glancing during texting within naturalistic epochs ending in crashes or no crashes. We found that texting periods were quite similar across the two, both in duration, number of individual texting tasks, and overall shape of the AttenD buffer curve. However, we found that crash epoch texting tended to occur closer to the onset of a crash event, and that texting during crashing may be initiated when the AttenD buffer level is lower (indicating depleted situation awareness), possibly due to prior or ongoing operational or secondary activities. We also made similar comparisons for radio interaction tasks, and found substantial differences between radio crash and baseline interactions. We conclude that whether a texting period ends in a crash may be dependent upon more than the individual differences in length of texting or amount of glancing. One’s level of situation awareness at the start of the activity (indicating a potential lack of judgment in picking up the device), in combination with a cascading losses of situation awareness that arise from the temporal pattern of on-road and off-road glances upstream from a safety-critical event, may be key predictive factors.

How to Cite:

Seaman, S. & Lee, J. & Seppelt, B. & Angell, L. & Mehler, B. & Reimer, B., (2017) “It’s All in the Timing: Using the Attend Algorithm to Assess Texting in the Nest Naturalistic Driving Database”, Driving Assessment Conference 9(2017), 403-409. doi: https://doi.org/10.17077/drivingassessment.1665

Rights: Copyright © 2017 the author(s)

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Published on
29 Jun 2017
Peer Reviewed