Determinants of Red-light Camera Violation Behavior: Evidence from Chicago, Illinois

Red Light Camera (RLC) enforcement is designed to increase road safety by reducing traffic violations and crashes at road intersections. To understand the effect of traffic features, intersection factors, and signal configuration on the frequency of RLC violations, this study uses regression models to analyze violations at 152 RLCs in the city of Chicago, Illinois over a 6-year period between 2010 and 2015. The main contribution of this study is introducing panel-data analysis to better understand RLC violation behavior over time using two types of correlations in the panels (i.e. serial and spatial) that were tested to be significant in the RLC violations data. Results showed that among the factors that have a positive effect (increase) on the frequency of RLC violations are traffic volume, number of lanes, and speed limit of the approaching traffic (in direction of movement), in addition to signal cycle and an all-red phase duration of 2 seconds compared to 1. On the other hand, among the factors that have a negative effect (decrease) on the frequency of RLC violations are left-turn bays and right-on-red prohibition, in addition to a yellow-phase duration of 4 seconds compared to 3. Results also show a monthly trend in the frequency of violations where frequency is highest in Summer and lowest in Winter, and an annual learning curve where violations decrease continuously from 2010 to 2015. This paper helps decision makers and researchers in understanding the effect of different elements on violation behavior in the presence of red-light cameras.

Language

  • English

Media Info

  • Media Type: Digital/other
  • Features: Figures; Maps; References; Tables;
  • Pagination: 16p
  • Monograph Title: TRB 96th Annual Meeting Compendium of Papers

Subject/Index Terms

Filing Info

  • Accession Number: 01628222
  • Record Type: Publication
  • Report/Paper Numbers: 17-06817
  • Files: TRIS, TRB, ATRI
  • Created Date: Mar 7 2017 10:25AM