RED LIGHT RUNNING PREDICTION AND ANALYSIS

Transportation professionals and engineers have identified red light running as a major traffic safety hazard. However, there are currently only limited tools available to assist transportation professionals in selecting intersections for remediation or law enforcement based upon red light running violation risk. The goal of this research was to develop statistical models to predict red light running violation frequency (violations/hour) based upon traffic operational and intersection geometric characteristics for four-approach intersections. Red light running violation data over the time period of 2-8 PM was gathered from 19 intersection approaches in four states (Alabama, Texas, Iowa, and California) and was compiled and analyzed. A total of 1,775 violations were observed over 554 hours (for an observed rate of 3.2 violations/hour). Additionally, fourteen geometric and traffic operational characteristics were recorded for each intersection. The results of this research present several regression equations (linear, curvilinear, and multiple linear) which can be used to predict the red light running frequency that can be expected at an intersection approach based upon several geometric and traffic operational characteristics. Variables showing predictive power included average daily traffic (ADT), number of approach lanes, speed limit, number of lanes crossed by the approach, and distance to preceding and following intersections.

• Record URL:
  http://utca.eng.ua.edu/research/projects/?id=02112
• 
• Corporate Authors:

  University Transportation Center for Alabama

  University of Alabama
  Tuscaloosa, AL  United States  35487
• Authors:
  • Hill, S E
  • Lindly, J K
• Publication Date: 2003-7-7

Language

• English

Media Info

• Features: Figures; References; Tables;
• Pagination: 37 p.

Subject/Index Terms

• TRT Terms: Approach lanes; Average daily traffic; Distance; Forecasting; Geometric segments; Highway safety; Intersections; Red light running; Speed limits; Statistical analysis; Traffic characteristics; Traffic safety; Traffic violators
• Geographic Terms: Alabama; California; Iowa; Texas
• Subject Areas: Data and Information Technology; Highways; Operations and Traffic Management; Safety and Human Factors; Security and Emergencies; I82: Accidents and Transport Infrastructure; I83: Accidents and the Human Factor;

Filing Info

• Accession Number: 00965930
• Record Type: Publication
• Report/Paper Numbers: UTCA Report Number 02112, Final Report
• Contract Numbers: HPP-1602(524)
• Files: UTC, TRIS
• Created Date: Nov 21 2003 12:00AM