@article{ref1,
title="An investigation of the speeding-related crash designation through crash narrative reviews sampled via logistic regression",
journal="Accident analysis and prevention",
year="2016",
author="Fitzpatrick, Cole D. and Rakasi, Saritha and Knodler, Michael A.",
volume="98",
number="",
pages="57-63",
abstract="Speed is one of the most important factors in traffic safety as higher speeds are linked to increased crash risk and higher injury severities. Nearly a third of fatal crashes in the United States are designated as &quot;speeding-related&quot;, which is defined as either &quot;the driver behavior of exceeding the posted speed limit or driving too fast for conditions.&quot; While many studies have utilized the speeding-related designation in safety analyses, no studies have examined the underlying accuracy of this designation. Herein, we investigate the speeding-related crash designation through the development of a series of logistic regression models that were derived from the established speeding-related crash typologies and validated using a blind review, by multiple researchers, of 604 crash narratives. The developed logistic regression model accurately identified crashes which were not originally designated as speeding-related but had crash narratives that suggested speeding as a causative factor. Only 53.4% of crashes designated as speeding-related contained narratives which described speeding as a causative factor. Further investigation of these crashes revealed that the driver contributing code (DCC) of &quot;driving too fast for conditions&quot; was being used in three separate situations. Additionally, this DCC was also incorrectly used when &quot;exceeding the posted speed limit&quot; would likely have been a more appropriate designation. Finally, it was determined that the responding officer only utilized one DCC in 82% of crashes not designated as speeding-related but contained a narrative indicating speed as a contributing causal factor. The use of logistic regression models based upon speeding-related crash typologies offers a promising method by which all possible speeding-related crashes could be identified.<br><br>Published by Elsevier Ltd.<p /> <p>Language: en</p>",
language="en",
issn="0001-4575",
doi="10.1016/j.aap.2016.09.017",
url="http://dx.doi.org/10.1016/j.aap.2016.09.017"
}