Safety Evaluation of Red-Light Indicator Lights (RLILs) At Intersections

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FOREWORD

The research documented in this report was conducted as part of the Federal Highway Administration’s (FHWA) Evaluation of Low-Cost Safety Improvements Pooled Fund Study (ELCSI-PFS). FHWA established this PFS in 2005 to conduct research on the effectiveness of the safety improvements identified by the National Cooperative Highway Research Program Report 500 guides as part of the implementation of the American Association of State Highway and Transportation Officials Strategic Highway Safety Plan. The ELCSI-PFS studies provide a crash modification factor and benefit–cost (B/C) economic analysis for each of the targeted safety strategies identified as priorities by the pooled fund member States.

This study evaluated red-light indicator lights (RLILs). RLILs are auxiliary lights mounted on signal heads, mast arms, or poles that were connected to a traffic-control signal. This strategy is to reduce the frequency of crashes resulting from drivers disobeying traffic signals by providing a safer means for police to enforce the red interval. The RLIL activates at the onset of the red phase and allows an enforcement officer to observe red-light running from downstream of the intersection. Results indicate statistically significant crash reductions for most crash types (i.e., total crashes, fatal and injury crashes, right-angle, and left-turn). The B/C ratio estimated with conservative cost and service life assumptions indicates this strategy was highly beneficial for four-legged signalized intersections. This report will benefit traffic engineers, enforcement personnel, and safety planners by providing insight for greater intersection safety.

Monique R. Evans
Director, Office of Safety
Research and Development

Technical Report Documentation Page

SI* (Modern Metric) Conversion Factors

TABLE OF CONTENTS

Executive Summary

Chapter 1. Introduction

• Background on Strategy
• Background on Study
• Literature Review

Chapter 2. Objective

Chapter 3. Study Design

• Sample Size Estimation Overview

Chapter 4. Methodology

Chapter 5. Data Collection

• Installation Data
• Reference Sites
• Roadway Data
• Crash Data
• Traffic Data
• Treatment Cost Data
• Data Characteristics and Summary

Chapter 6. Development of SPFs

• SPFs for Spillover and Migration Effects
• SPFs for Combined Reference Data

Chapter 7. Before–After Evaluation Results

• Aggregate Analysis
• Disaggregate Analysis

Chapter 8. Economic Analysis

Chapter 9. Summary and Conclusions

Appendix. Additional Installation Details

Acknowledgments

References

LIST OF FIGURES

• Figure 1. Photo. RLIL on signal head.
• Figure 2. Equation. Estimated change in safety.
• Figure 3. Equation. EB estimated of expected crashes.
• Figure 4. Equation. EB weight.
• Figure 5. Equation. Index of effectiveness.
• Figure 6. Equation. Standard deviation of index of effectiveness.
• Figure 7. Equation. SPF for spillover and migration.
• Figure 8. Graph. Yearly multiplier by year for reference groups.
• Figure 9. Equation. SPF for EB analysis.
• Figure 10. Graph. Crash totals by year before treatment.
• Figure 11. Diagram. Assembly sheet for confirmation light with globe.

LIST OF TABLES

• Table 1. Before-period crash rate assumptions for signalized intersections in Florida.
• Table 2. Minimum required before-period intersection-years for treated intersections at the 95‑percent confidence level.
• Table 3. Minimum required before-period intersection-years for treated intersections at the 90‑percent confidence level.
• Table 4. Sample analysis for crash effects.
• Table 5. Definitions of crash types.
• Table 6. Before and after data summary for treatment and reference sites.
• Table 7. Parameter estimates for the reference group SPF for total crashes.
• Table 8. Observed and predicted crashes for reference groups.
• Table 9. SPF results with indicator variable for potential spillover/migration sites.
• Table 10. SPF estimates for nearby treatment effect for group 2.
• Table 11. Parameter estimates and SEs for Florida signalized intersection SPF for total crashes.
• Table 12. SPF-generated yearly multipliers.
• Table 13. Aggregate results.
• Table 14. Results disaggregated by treatment duration and district.
• Table 15. Results disaggregated by indicator type and area type.
• Table 16. Results disaggregated by entering volume and proportion entering on minor road approaches.
• Table 17. Crash costs and distributions by crash type and severity.
• Table 18. Results of Florida

LIST OF ABBREVIATIONS

Executive Summary

The Federal Highway Administration (FHWA) established the Development of Crash Modification Factors (DCMF) program in 2012 to address highway safety research needs for evaluating new and innovative safety strategies (improvements) by developing reliable quantitative estimates of their effectiveness in reducing crashes. The ultimate goal of the DCMF program is to save lives by identifying new safety strategies that effectively reduce crashes and promote those strategies for nationwide implementation by providing measures of their safety effectiveness and benefit–cost (B/C) ratios through research. State transportation departments and other transportation agencies need to have objective measures for safety effectiveness and B/C ratios before investing in broad applications of new strategies for safety improvements. Forty State transportation departments provide technical feedback on safety improvements to the DCMF program and implement new safety improvements to facilitate evaluations. These States are members of the Evaluation of Low-Cost Safety Improvements Pooled Fund Study (ELCSI-PFS), which functions under the DCMF program.

This study investigated the safety effectiveness of red-light indicator lights (RLILs). RLILs are auxiliary lights mounted on signal heads, mast arms, or poles that are directly connected to a traffic-control signal. The RLIL activates at the onset of the red phase and allows an enforcement officer to observe red-light running from downstream of the intersection. This strategy is intended to reduce the frequency of crashes resulting from drivers disobeying traffic signals by providing a safer and more efficient means for police to enforce the red interval. Moreover, for the strategy to be effective, agencies should educate drivers of their existence and intent. Few studies have explored the safety effectiveness of RLILs; in particular, no studies have shown the crash-based safety effectiveness for four-legged intersections.

The research team obtained geometric, traffic, and crash data at treated four-legged rural and urban intersections in Florida. To account for potential selection bias and regression-to-the-mean (RTM), the research team conducted an empirical Bayes (EB) before–after analysis using reference groups of untreated four-legged signalized intersections with characteristics similar to those of the treated sites. The analysis also controlled for changes in traffic volumes over time and time trends in crash counts unrelated to the treatment.

The results indicate reductions for all crash types analyzed except rear-end crashes. Reductions were statistically significant at the 95-percent confidence level for all crash types. The crash type with the smallest crash modification factor (CMF)—which translated to the greatest reduction—was left-turn crashes with a CMF of 0.60. For all crash types combined, the research team estimated a CMF of 0.94. The CMFs for disobeyed signal, fatal and injury, right-angle, and nighttime crashes were 0.71, 0.86, 0.91, and 0.89, respectively. The research team estimated an insignificant CMF of 1.016 for rear-end crashes.

A disaggregate analysis sought to identify those conditions under which the treatment was most effective. Because total, fatal and injury, right-angle, and disobeyed signal crashes were the focus of this treatment, these crash types were the focus of the disaggregate analysis. The disaggregate analysis showed that CMFs decreased over the first few years of treatment, indicating that they were more effective in reducing crashes as drivers became accustomed to them. The smallest CMFs (i.e., the greatest reductions) found were for the only district with agencies that noted increased enforcement and public awareness campaigns. The research team found no significant difference in effects between white incandescent and blue light-emitting diode (LED) indicators.

For total, fatal and injury, and right-angle crashes, RLILs appeared to be more effective in rural areas and at intersections with lower total entering volume and a lower proportion of entering traffic from the minor road. The data indicated that the opposite was true for disobeyed signal crashes; the research team found RLILs were more effective in urban areas and at intersections with higher total entering volume and a higher proportion of entering traffic from the minor road. Owing to correlations among these factors, the disaggregate effects should not be combined for quantitative analysis; however, the indications can be considered when prioritizing intersections for treatment.

The B/C ratio estimated with conservative cost and service life assumptions and considering the benefits for total crashes was 92:1 for all signalized intersections. With the recommended U.S. Department of Transportation (USDOT) sensitivity analysis, this value could range from 53:1 to 130:1. These results suggest that the strategy—even with conservative assumptions on cost, service life, and the value of a statistical life—can be highly cost effective.

In addition to the crash-related benefits, RLILs can improve the efficiency and safety of red-light running enforcement efforts. While this study did not evaluate the efficiency and safety impacts with respect to enforcement, it is important to note that RLILs do allow police to observe violators from a downstream position, eliminating the need for a second observer (upstream) and the need to pursue a violator through the intersection during the red interval.