title: Safety effectiveness and crash cost benefit of red light cameras in Missouri.
abstract: Red light cameras (RLCs) have generated heated discussions over issues of safety effectiveness, revenue generation, and procedural due process. This study focuses on the safety evaluation of RLCs in Missouri, including the economic valuation of safety benefits. The publication of the national Highway Safety Manual (HSM; American Association of State Highway and Transportation Officials) in 2010 produced statistical safety models for intersections and spurred the calibration of these models to local conditions.
  
  
  
  This study adds to existing knowledge by applying the latest statistical methodology presented in the HSM and more current data. Driver behavior constantly changes due in part to driving conditions and the use of technology. The safety and economic benefit evaluation was performed using the empirical Bayes method, which accounts for regression to the mean bias. For the economic benefit evaluation, the KABCO crash severity scale and crash cost estimates were used. A total of 24 4-leg urban intersections were randomly selected from a master list of RLCs in Missouri from 2006 to 2011. Additionally, 35 comparable nontreated intersections were selected for the analysis.
  
  
  
  The implementation of RLCs reduced overall angle crashes by 11.6%, whereas rear-end crashes increased by 16.5%. The net economic crash cost benefit of the implementation of RLCs was $35,269 per site per year in 2001 dollars (approximately $47,000 in 2015 dollars). Thus, RLCs produced a sizable net positive safety benefit that is consistent with previous statistical studies.
authors.affiliation: a Department of Civil and Environmental Engineering , University of Missouri-Columbia , Columbia , Missouri.
authors.forename: Boris
authors.initials: B
authors.lastname: Claros
authors.affiliation: a Department of Civil and Environmental Engineering , University of Missouri-Columbia , Columbia , Missouri.
authors.forename: Carlos
authors.initials: C
authors.lastname: Sun
authors.affiliation: a Department of Civil and Environmental Engineering , University of Missouri-Columbia , Columbia , Missouri.
authors.forename: Praveen
authors.initials: P
authors.lastname: Edara
mesh_terms: D000063:Accidents, Traffic / Q000191:economics / Q000517:prevention & control* / Q000706:statistics & numerical data; D001334:Automobile Driving / Q000592:standards*; D001499:Bayes Theorem; D003362:Cost-Benefit Analysis; D004779:Environment Design; D006801:Humans; D035846:Law Enforcement / Q000379:methods*; D008923:Missouri; D008962:Models, Theoretical; D010781:Photography / Q000295:instrumentation*; D012449:Safety / Q000191:economics
keywords: Automated enforcement; crash frequency modeling; intersection safety; right angle crashes