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Jonathan M. Hankey

Researcher at Virginia Tech

Publications -  78
Citations -  2828

Jonathan M. Hankey is an academic researcher from Virginia Tech. The author has contributed to research in topics: Poison control & Night vision. The author has an hindex of 22, co-authored 77 publications receiving 2360 citations. Previous affiliations of Jonathan M. Hankey include University of Iowa.

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Driver crash risk factors and prevalence evaluation using naturalistic driving data.

TL;DR: The results show that crash causation has shifted dramatically in recent years, with driver-related factors present in almost 90% of crashes, and definitively show that distraction is detrimental to driver safety, with handheld electronic devices having high use rates and risk.
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Near Crashes as Crash Surrogate for Naturalistic Driving Studies

TL;DR: In this article, the authors evaluated the use of near crashes as a surrogate measure for assessment of the safety impact of driver behaviors and other risk factors, and concluded that using near crash as a crash surrogate provides definite benefit when naturalistic studies are not large enough to generate sufficient numbers of crashes for statistical analysis.
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Human Factors Field Evaluation of Automotive Headway Maintenance/Collision Warning Devices

TL;DR: Results indicate that when drivers are provided with salient visual information regarding safe headways, they utilize the information and increase their headway when appropriate, and a study to investigate the long term effects of such displays on behavior is strongly recommended prior to mass marketing of headway maintenance/collision warning devices.

The Impact of Hand-Held and Hands-Free Cell Phone Use on Driving Performance and Safety-Critical Event Risk

TL;DR: This study investigated the effects of distraction from the use of three types of cell phones: (1) hand-held (HH), (2) portable handsfree (PHF), and (3) integrated hands-free (IHF), making this the first NDS to date to combine call and text records with continuous naturalistic driving data.
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The effects of age on crash risk associated with driver distraction.

TL;DR: Teenaged, young adult drivers and senior drivers are more adversely impacted by secondary-task engagement than middle-aged drivers, whereas cognitive distraction may have a larger impact on young drivers.