Evaluation of Law Enforcement Presence on Changing Drivers’ Behaviors – Red Light Running International Traffic Records Forum July 2003

Funding & Participants Funding – Joint Transportation Research Program Purdue University Co-PIs - Andrzej Tarko – Civil Engineering, Purdue University - Robert Zahnke – Center for the Advancement of Transportation Safety (CATS), Purdue University - Maria Drake - Clifford Stover - Jose Thomaz - John Ragan - Carolyn Bridge

Project Objectives Assessment of presence/seriousness of RLR Effectiveness of a media campaign Development of enforcement model

Approaches Civil Engineering  Random Telephone Survey  Longitudinal Survey of Single intersection  24/7 video monitoring CATS  Literature Review  Cross-Section Observational monitoring  Crash/citation data  Media/law enforcement

Center for the Advancement of Transportation Safety (CATS) Selection of intersections Observational survey protocols Survey schedules Results Media/enforcement efforts Crash/citation correlation Conclusions Recommendations for the future

Selection of Intersections Compiling the inventory  Categorizing sites into “buckets”  Criteria/attributes Speed limit Traffic volume Roadway configuration & intersection design Number of lanes Turn lanes

Observational Survey Protocols Data captured  Date/observation time  5-minute pre/post count (traffic volume)  Direction of vehicle  Vehicle type  Gender/race/approximate age

Observation Form

Observational Survey Schedules All days of the week Daylight hours  Early morning rush hour  Mid Morning  Lunch  Mid Afternoon  Evening Rush  Evening

Number of RLRs by Type of Vehicle Maneuver

Number of RLR Violations by Traffic Volume

Number of RLRs per 45-Minute Observation Period by Observation Starting Time

Number of RLRs by Driver Gender and Age Group Driver Gender YoungAverageOlder Female45.2%33.2%31.5% Male54.8%66.8%68.5%

Number of RLRs by Driver Race RaceCountsPercent Caucasian % Other474.9% African American313.2% Unknown212.2% Data Not Collected202.1% Total %

Collapsing the Data Vehicle TypeCountsPercent Passenger Cars % Pickup Trucks % Mini or Large Vans % Sport Utility Vehicles % Motorcycles90.9% Other Vehicle Types434.5% Total %

Vehicle Maneuver by Vehicle Type Vehicle Type Vehicle Maneuver LeftRightStraight Passenger Cars34.7%11.3%54.0% Pickup Trucks33.1%16.1%50.8% Mini & Large Vans37.1%12.9%50.0% Others25.0%15.9%59.1% Sport Utility Vehicles 29.2%16.7%54.2% Total for All Vehicles 33.4%13.2%53.4%

Distribution of Intersection Crashes by Time of Day in Lafayette and West Lafayette,

Distribution of RLR Crashes by Time of Day in Lafayette & West Lafayette,

Distribution of RLR

Signalized Intersection Crashes in Lafayette and West Lafayette in 1999

Distribution of Intersection Crashes by Day of Week in Lafayette and West Lafayette,

Percentage of Signalized Intersection Crashes Due to RLR in Lafayette and West Lafayette in 1999

RLR Observations

Results – 3 rd Round Targeted Highest Rates of Incidence – Location and Time of 2 Sites  Intersection of a state highway and US highway  5-point intersection  Lunch time

Media/Enforcement efforts Media  Print – local newspaper  Television/radio Enforcement  Saturation patrols  Parked vehicles

Media/Enforcement Results Media – 3 types  By itself had no effect on reducing RLR Enforcement  Only when visibly present

Overall Conclusions RLR occurs during all hours, on all days of week, and on all types of roads Range: 4 – 18 violations per hour Peaked Lunch time Occurrences increased as work week progressed No common, typical violator or scenario— varied vehicle, driver, or intersection types More likely to encounter RLR at higher traffic density intersections

Other Observations Over 50% of RLR violators observed were proceeding straight through intersection when red light was run Ratio of passenger car violators and pickup truck violators paralleled Indiana vehicle registrations (no over-representation noted) Young Male to Young Female ratio 1:1 Average Male to Average Female ratio 2:1 Older Male to Older Female ratio 2:1 Race of violators matched IN Census Bureau counts (no over-representation noted)

Other Observations Signage had an immediate impact on reducing RLR at video-monitored intersection

For further information Bob Zahnke  Purdue University    CATS web site – JTRP link 