Empirical bayes approach for estimating urban deer-vehicle crashes using police and maintenance records

Konstantina Gkritza, Reginald R. Souleyrette, Michael J. Baird, Brent J. Danielson

Research output: Contribution to journalArticlepeer-review

10 Scopus citations


Deer-vehicle crashes are a growing problem in Iowa where deer-vehicle crashes represent 13% of all crashes reported. In 2009, these crashes resulted in nine fatalities and 451 injuries in the state. Deer-vehicle crashes are a problem even in urban areas of Iowa. It is known that deer-vehicle crashes are typically underreported. To address this underreporting, deer carcass salvage reports may be used to augment deer-vehicle crash reports. The objective of this paper is to exploit two sources of deer-vehicle crash data using a statistically reliable assessment methodology, empirical Bayes, to assess the potential for safety improvement of 150 urban highway sections in Iowa. Reconciliation of records to reduce double counting is discussed and a negative binomial regression model of deer-vehicle crash frequency as a function of roadway and environmental factors is estimated. The 25 most promising segments for deer-vehicle crash countermeasures are identified, mostly located on high-speed roadways, roadway segments with gravel right shoulders, and segments adjacent to grasslands. The methodology facilitates the identification of locations for countermeasure implementation as well as monitoring deer-vehicle crash trends.

Original languageEnglish
Article number04013002
JournalJournal of Transportation Engineering
Issue number2
StatePublished - 2014


  • Deer carcass data
  • Deer-vehicle crashes
  • Empirical bayes
  • Ranking
  • Urban areas

ASJC Scopus subject areas

  • Civil and Structural Engineering
  • Transportation


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