Driving Behavior at Intersections Equipped with Red Light Cameras – A Monte Carlo Simulation Based on Driving Simulator Data

Joris, Cornu; Kris, Brijs; Stijn, Daniels; Tom, Brijs; Elke, Hermans; Geert, Wets · 2021 · Crossref

DOI: 10.54941/ahfe100683

archive: archived pipeline: cataloged verified

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Summary

This study investigates the impact of red light cameras (RLCs) on driver behavior and rear-end collision risk at urban intersections. While RLCs are widely used to reduce red light running, previous research indicates they often cause a significant increase in rear-end collisions due to sudden braking maneuvers. The authors aimed to evaluate driving and looking behaviors under three conditions: no RLC (control), RLC present, and RLC with an upstream warning sign (RLCWS). The study specifically sought to determine if warning signs could mitigate the increased collision risk associated with RLC installation. The research utilized a medium-fidelity driving simulator to replicate a real-world urban intersection in Belgium. Sixty-three participants drove through the intersection under the three experimental conditions. The scenario was designed to place drivers in the "dilemma zone," where the traffic light turned yellow when participants were 2.5 seconds from the stop line. Eye-tracking technology recorded visual attention, while driving parameters such as speed and deceleration were logged. To estimate collision risk, the authors employed a Monte Carlo Simulation with 100,000 iterations per condition. This simulation combined simulator data (speed, deceleration) with real-world field observations of distance headways between leading and following vehicles. The results demonstrated that the presence of an RLC significantly altered driver behavior. In the control condition, only 11% of participants stopped for the yellow light, compared to 13% with an RLC and 30% with an RLCWS. Consequently, the relative risk of rear-end collisions increased from 1.97% in the control condition to 12.65% with an RLC. However, the addition of an upstream warning sign reduced this risk to 7.89%. Deceleration rates were highest in the RLC condition (-4.28 m/s²), indicating harsher braking, whereas the RLCWS condition resulted in lower speeds at yellow onset and more moderate deceleration (-3.45 m/s²). Eye-tracking data revealed that drivers who stopped were more likely to fixate on the RLC and warning signs than those who proceeded through the intersection. The study concludes that while RLCs effectively reduce red light running, they substantially increase the risk of rear-end collisions. However, installing warning signs upstream of the camera mitigates this risk by encouraging earlier, smoother braking. The authors recommend that road administrations carefully consider the installation of RLCs and, when necessary, pair them with warning signs to minimize safety trade-offs. These findings support the broader literature suggesting that countermeasures like warning signs can reduce the unfavorable effects of enforcement cameras without diminishing their deterrent impact on red light violations.

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Summary generated by qwen3.6-27b-prismaquant on 2026-06-09; verification: verified.

Topics

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• automated enforcement cameras
• roadway lighting effects

Information type

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• Empirical Findings: crash risk outcomes, behavioral performance data
• Methodological Resource: tool software