Smart Red Clearance Extensions to Reduce Red-Light Running Crashes

Hurwitz, David; Abadi, Masoud Ghodrat; McCrea, Sarah; Quayle, Shaun; Marnell, Patrick · 2016 · ROSA P / Oregon. Dept. of Transportation

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Summary

This study addresses the safety hazard of red-light running (RLR) at signalized intersections, which contributes to significant fatalities and injuries in Oregon and the United States. The research evaluates the accuracy, efficiency, and operational impact of Red Clearance Extension (RLE) systems, a countermeasure that extends the all-red interval when an RLR vehicle is detected, allowing it to clear the conflict zone safely. The project specifically compares three detection strategies to determine the most effective method for triggering these extensions without significantly increasing intersection delay. The methodology combined field data collection with hardware-in-the-loop (HIL) simulation. Researchers conducted a field study at five high-RLR intersections in Oregon, transcribing 149 hours of video data to analyze driver behavior during yellow and red intervals. This data, along with signal timings and geometric information, was used to calibrate a VISSIM simulation model of one intersection. The HIL simulation tested three RLE alternatives: downstream detection and two smart upstream speed-conditional detection setups located at 215 feet and 475 feet from the stop line. Novel R code was developed to process simulation outputs into time-space diagrams for detailed analysis of detection accuracy and efficiency. The results indicated that while downstream detection triggered the highest rate of RLE events, it was less effective at ensuring safety for vehicles receiving the extension. In contrast, the smart upstream speed-conditional detection alternatives consistently provided a greater degree of safety for vehicles that received an RLE. Crucially, these upstream systems achieved this safety improvement without causing a significant increase in intersection delay. The study demonstrated that the logic for these systems can be implemented using the Econolite 2070 controller and NWS Voyage™ software. The significance of this research lies in providing evidence-based guidance for implementing RLE systems to mitigate RLR crashes. The findings suggest that smart upstream detection is superior to downstream detection for balancing safety and operational efficiency. The study concludes that these systems are viable for field implementation, offering a practical engineering countermeasure for jurisdictions seeking to reduce RLR-related injuries and fatalities. The work supports the adoption of adaptive signal control technologies that respond dynamically to vehicle trajectories rather than relying solely on fixed timing or enforcement measures.

Key finding

Smart upstream speed-conditional detection alternatives at 215 feet and 475 feet consistently provided a greater degree of safety for vehicles that received a red clearance extension while causing no significant increase to intersection delay.

Methodology

mixed_methods

Sample size: 149

Provenance

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Summary generated by qwen3.6-27b-prismaquant on 2026-06-10; verification: verified.

Topics

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• automated enforcement cameras
• roadway lighting effects

Information type

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• Empirical Findings: crash risk outcomes