Location

Manchester Village, Vermont

Date

29-6-2017

Session

Session 6 — Hybrid Presentations

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.

Rights

Copyright © 2017 the author(s)

DC Citation

Proceedings of the Ninth International Driving Symposium on Human Factors in Driver Assessment, Training and Vehicle Design, June 26-29, 2017, Manchester Village, Vermont. Iowa City, IA: Public Policy Center, University of Iowa, 2017: 403-409.

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Jun 29th, 12:00 AM

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

Manchester Village, Vermont

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.