U.S. Department of Transportation
Federal Highway Administration
1200 New Jersey Avenue, SE
Washington, DC 20590
202-366-4000


Skip to content
Facebook iconYouTube iconTwitter iconFlickr iconLinkedInInstagram

Federal Highway Administration Research and Technology
Coordinating, Developing, and Delivering Highway Transportation Innovations

 
TECHBRIEF
This techbrief is an archived publication and may contain dated technical, contact, and link information
Back to Publication List        
Publication Number:  FHWA-HRT-17-087    Date:  December 2017
Publication Number: FHWA-HRT-17-087
Date: December 2017

 

Safety Evaluation of Multiple Strategies at Stop-Controlled Intersections

PDF Version (474 KB)

PDF files can be viewed with the Acrobat® Reader®

 

FHWA Publication No.: FHWA-HRT-17-087
FHWA Contact: Roya Amjadi, HRDS-20, (202) 493-3383, roya.amjadi@dot.gov

This document is a technical summary of the Federal Highway Administration report Safety Evaluation of Multiple Strategies at Stop-Controlled Intersections (FHWA-HRT-17-086).

Objective

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 goal of the DCMF program is to save lives by identifying new safety strategies that effectively reduce crashes and to 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, which functions under the DCMF program.

This study evaluated a combined application of multiple low-cost treatments at stop-controlled intersections. Improvements included basic signing and pavement markings. The intent of this strategy is to reduce the frequency and severity of crashes at stop-controlled intersections by alerting drivers to the presence and type of approaching intersection.

Many studies have explored the safety effectiveness of basic signing or pavement marking improvements. However, no study has conducted a rigorous evaluation of the effectiveness of installing packages of these strategies in combination across many intersections. This study sought to fill this knowledge gap.

Introduction

In recent years, agencies have shown increased interest in the widespread installations of low-cost safety treatments throughout an entire jurisdiction.The South Carolina Department of Transportation (SCDOT) embraced this approach in its intersection safety improvement plan and identified a number of low-cost strategies for implementation at stop-controlled and signalized intersections statewide. Typical low-cost treatments at stop-controlled inter- sections in South Carolina included sign- ing and pavement marking improvements. Each intersection received all treatments appropriate for the site.

The following is an overview of the types of basic signing and pavement  mark- ing improvements. Each treatment was installed when appropriate. Each intersec- tion received a unique package of improve- ments suited for implementation at that site. The possible improvements included the following:

A literature search focused on the safety effects of the specific strategies at stop- controlled intersections. Very few studies investigated the effects of multiple strategies. An evaluation by the Institute of Transportation Engineers, which examined the safety effects of doubling up stop signs, found that these strategies yielded an 11-percent reduction in total crashes.(1) An FHWA study found that doubling up and oversizing stop signs resulted in a 48-percent reduction in total crashes; however, there were potential biases with study design, sample size, and selection bias.(2) Multiple studies confirm the conspicuity of fluorescent sign sheeting.(3,4) A Virginia Department of Transportation study used a video survey to link retroreflective sign posts with improved nighttime visibility in com- parison to signs without retroreflective material on the posts.(5) Several studies evaluated the installation of minor-road stop line pavement markings, resulting in a total crash reduction of 19 percent in two studies and a 47-percent reduction in right-angle crashes in one of the studies.(1,6) The combination of adding a center line, adding a stop line, and replacing a 24-inch stop sign with a 30-inch stop sign yielded a 67-percent reduction in right-angle crashes.(7) The combination of stop lines and short intervals of double yellow center lines through the intersection resulted in a 53-percent decrease in total crashes.(2)

Most of these studies employed study designs that lacked statistical rigor and frequently neglected to estimate standard errors for the crash reductions, which makes it difficult to put much credence in the results. Furthermore, none of the previous studies conducted a compre- hensive evaluation with regard to crash type and severity. The previous studies generally reported the effect on total crashes or angle crashes, and virtually none estimated the effect on injury crashes. Thus, there is a need for additional research of the stop- controlled strategies of interest that employs rigorous study designs and analyzes a full range of crash types and severities.

Methodology

This study examined the safety impacts of multiple low-cost signing and pavement marking treatments at stop-controlled inter- sections in South Carolina on total, fatal and injury, rear-end, right-angle, and nighttime crash frequency.

The data sample included 434 treatment sites and 568 reference sites of all intersec- tion types. The research team categorized intersections for evaluation using the fol- lowing configuration types:

The evaluation made use of the empirical Bayesian (EB) methodology for observational before–after studies.(8) This methodology is considered rigorous in that it accounts for regression to the mean using a reference group of similar, but untreated, sites.

In the process, the use of safety perfor- mance functions (SPFs) was found to have the following advantages:

The researchers estimated the SPFs used in the EB methodology through generalized linear modeling assuming a negative binomial error distribution, which is consistent with the state of research in developing these models. In specifying a  negative  binomial  error  structure, the researchers estimated a constant overdispersion parameter from the model and the data. For a given dataset, smaller values of this parameter indicate relatively better models.

The full report includes a detailed explana- tion of the methodology and the develop- ment of SPFs, including a description of how the estimate of safety effects for target crashes was calculated.

Results

This brief presents the research results in two parts. The first part contains aggregate results.The second part is based on a disag- gregate analysis that sought to identify the optimal conditions for installation of the treatment.

Aggregate Analysis

Table 1 shows the aggregate results. For all crash types, the table provides the estimates of expected crashes in the after period without treatment,  the  observed  crashes in the after period, the estimated crash modification factor (CMF), and the standard error of the CMF.

The reductions were statistically significant at the 95-percent  confidence level for all crash types. For all crash types combined, the CMFs were 0.917 for all severities and 0.899 for fatal and injury crashes. The crash type with the smallest CMF, which indicates the greatest crash reduction, was nighttime crashes with a CMF of 0.853. The CMFs for rear-end and right-angle crashes were 0.933 and 0.941, respectively.

Table 1. Aggregate results for EB before–after study.

Crash Type

After-Period  Crashes— Expected (Without Systemic Improvement)

After-Period  Crashes— Observed

Estimated CMF

Standard Error of Estimated CMF

Total

4,614

4,231

0.917*

0.017

Fatal and injury

1,434

1,290

0.899*

0.028

Rear-end

1,577

1,472

0.933*

0.030

Right-angle

1,955

1,840

0.941*

0.026

Nighttime

1,072

953

0.853*

0.031

*Indicates CMF estimates statistically significant at the 95-percent confidence level.

Disaggregate Analysis

The disaggregate analysis identified those conditions under which the multiple low- cost treatments are more effective. The research team identified several variables of interest, including area type, number of legs, lane configuration of the main line and cross street, traffic volumes, and expected crashes without treatment. All of these variables are likely correlated, and caution should be exercised in interpreting and applying the disaggregate analysis results.

The disaggregate analysis indicated larger crash reductions of all types for rural areas, four-legged intersections, and intersections with two-lane major roads. For total entering volume and expected crashes before treatment, the disaggregate analysis indicated the strategy is more effective on average for intersections with lower traffic volumes and fewer expected crashes per year. However, as noted above, this effect may be due to other correlated variables.

Economic Analysis

The research team conducted an economic analysis to estimate the B/C ratio for imple- menting various low-cost pavement mark- ing and signing improvements at stop- controlled intersections. The research team used the statistically significant aggregate reduction in total crashes to calculate the conservative value of benefits for an aver- age intersection.

Based on work order cost data for more than 800 unsignalized intersections pro- vided by SCDOT, the economic analysis assumed an average total construction cost of $5,900. Preliminary engineering, project management, and other general costs were not provided; however, analysts with this information can split these costs between all intersections. SCDOT used  contractors to select and construct treatments at each intersection, and State forces planned and managed the project. In addition, annual maintenance and operations costs were not available but were assumed to be zero (i.e., these costs will not be incurred within the service life).

The analysis assumed the useful  service life for safety benefits was approximately 7 years. Pavement markings were assumed to last roughly 7 years and signs roughly 10 years,  for  an  approximate  average  of 7 years for the overall project. A conserva- tive analysis using a service life of 3 years was also conducted.

Using comprehensive crash cost estimates for fatal, injury, and property-damage- only crashes and the severity distribution at treatment sites, the research team estimated the cost for an average crash at a stop-controlled intersection and updated this value to 2015 U.S. dollars  (USD)  at the time of analysis using the value of a statistical life provided in a 2015 USDOT memorandum. The team applied the ratio of the 2015 value of $9.4 million to the 2001 value of $3.8 million, yielding an average cost of $132,071 in 2015 USD.(9,10) The USDOT memo suggests that analysts should apply sensitivity analysis by estimating B/C ratios for 0.57 and 1.41 times the 2015 crash costs.(10)

The research team calculated total crash reduction by subtracting the actual crashes in the after period from the expected crashes in the after period had the intersection treat- ments not been implemented. The total crash reduction was then divided by the average number of after-period years per site to compute the total crashes saved per year. The treatments saved 119.7 crashes per year for the sample sites, or an average reduction of 0.3 crashes per site per year across  the  434  treatment  sites.  Similarly, the treatments reduced fatal and injury crashes by 45 crashes per year across the sample  sites,  or  an  average  reduction  of 0.1 fatal and injury crashes reduced per site per year.

To calculate the annual economic bene- fits, the research team multiplied the crash reduction per site per year by the cost of a crash. Table 2 presents the resulting B/C ratios with lower and upper bounds result- ing from the sensitivity analysis.

These results suggest that the unsignalized intersection treatments, even with con- servative assumptions of service life and the value of a statistical life, can be cost effective in reducing total crashes at stop- controlled intersections.

Table 2. B/C ratios.

Service Life

Lower Bound

Average B/C

Upper Bound

3 years

7.1

12.4

17.5

7 years

14.5

25.5

35.9

Summary and Conclusions

This study was a rigorous before–after evaluation of the safety effectiveness, as measured by crash frequency, of systemic low-cost improvements at stop-controlled intersections. The study used data from South Carolina to examine the effects for the specific crash types: total, fatal and injury, rear-end, right-angle, and nighttime crashes. Based on the aggregate results, table 3 presents the recommended CMFs for the various crash types.

Table 3. Recommended CMFs.

Variable

Total

Fatal and Injury

Rear-End

Right-Angle

Nighttime

CMF

0.917

0.899

0.933

0.941

0.853

Standard error

0.017

0.028

0.030

0.026

0.031

The disaggregate analysis sought to identify those conditions under which the multiple low-cost treatments are most effective. Variables of interest included area type, number of legs, lane configuration of the main line and the cross street, traffic volumes, and expected crashes without treatment. The disaggregate analysis indicated  larger  crash  reductions   of all types for rural areas, four-legged intersections, and intersections with two- lane major roads. For total entering volume and expected crashes before treatment, the disaggregate analysis indicated the strategy is more effective on average for intersections with lower traffic volumes and fewer expected crashes per year. However, it is important to be cautious in interpreting and applying these disaggregate analysis results, which are likely confounded by multiple correlative effects.

The B/C ratio, estimated with conservative cost and service life assumptions and considering the benefits for total crashes, is 12.4:1. With the USDOT recommended sensitivity analysis, these values could range from 7.1:1 up to 17.5:1. These results suggest  that  the  multiple  low- cost treatments, even with conservative assumptions on cost, service life, and the value of a statistical life, can be cost effective in reducing crashes at stop-controlled intersections.

References

  1. Institute of Transportation Engineers. (2004). Toolbox of Countermeasures and Their Potential Effectiveness to Make Intersections Safer, Briefing Sheet 8, ITE, FHWA, Washington, DC.

  2. Federal Highway Administration. (2009). Stop Sign-Controlled Intersections: Enhanced Signs and Markings, Report No. FHWA-SA-09-010, Federal Highway Administration, Washington, DC.

  3. Jenssen, G.D., Moen, J., Brekke, B., Augdal, A., and Sjohaug, K. (1996). Visual Performance of Fluorescent Retroreflective Traffic Control Devices, Part 1: Human Factors Visibility Study, Report No. STF22 A96606, Sintef Transport Engineering, Trondheim, Norway.

  4. Burns, D.M. and Johnson, N.L. (1997). The Correlation of Measured Spectral Radiance of Fluorescent and Non- fluorescent Materials to Perceived Conspicuity Under Natural Lighting, Die Farbe, 43, pp. 185–203.

  5. Virginia Department of Transportation. (2008). Evaluation of Retroreflective Material on Stop Sign Posts in Virginia, Virginia Department of Transportation, Richmond, VA. Available online: http://www.virginiadot.org/projects/resources/4_09_Retroreflective_Material_Final_Report.pdf, last accessed July 9, 2011.

  6. Golembiewski, G.A. and Chandler, B. (2008). Intersection Safety: A Manual for Local Rural Road Owners, Report No. FHWA-SA-11-08, Federal Highway Administration, Washington, DC.

  7. Polanis, S.F. (1999). “Low-Cost Safety Improvements,” The Traffic Safety Toolbox: A Primer on Traffic Safety, pp. 265–272, Institute of Transportation Engineers, Washington, DC.

  8. Hauer, E. (1997). Observational Before–After Studies in Road Safety— Estimating the Effect of Highway and Traffic Engineering Measures on Road Safety. Elsevier Science, Incorporated. Amsterdam, The   Netherlands.

  9. Council,   F.,   Zaloshnja,   E.,    Miller, T.,   and   Persaud,   B.   (2005).   Crash Cost Estimates by Maximum Police- Reported Injury Severity Within Selected Crash Geometries, Report No. FHWA-HRT05-051, Federal Highway Administration, McLean, VA.

  10. U.S. Department of Transportation. (2015). Guidance on Treatment of the Economic Value of a Statistical Life (VSL) in U.S. Department of Transportation Analyses—2015 Adjustment, Memorandum, U.S.  Department of Transportation, Office of the Sec- retary of Transportation,  Washington, DC. Available online: https://cms.dot.gov/sites/dot.gov/files/docs/VSL2015_0.pdf, last accessed March 29, 2016.

Researchers—Thanh Le, Frank Gross, Kimberly Eccles, Jonathan Soika, and Bhagwant Persaud.

Distribution—This TechBrief is being distributed according to a standard distribution. Direct distribution is being made to the Divisions and Resource Center.

Availability—This TechBrief may be obtained from the FHWA Product Distribution Center by e-mail to report.center@dot.gov, fax to (814) 239-2156, phone to (814) 239-1160, or online at http://www.fhwa.dot.gov/research.

Key Words—Stop-controlled intersection, signing, pavement marking, low-cost, safety improvements, safety evaluations, empirical Bayesian.

Notice—This document is disseminated under the sponsorship of the U.S. Department of Transportation in the interest of information exchange. The U.S. Government assumes no liability for the use of the information contained in this document. The U.S. Government does not endorse products or manufacturers. Trademarks or manufacturers’ names appear in this report only because they are considered essential to the objective of the document.

Quality Assurance Statement—The Federal Highway Administration (FHWA) provides high-quality information to serve the Government, industry, and public in a manner that promotes public understanding. Standards and policies are used to ensure and maximize the quality, objectivity, utility, and integrity of its information. FHWA periodically reviews quality issues and adjusts its programs and processes to ensure continuous quality improvement.

DECEMBER 2017

FHWA-HRT-17-087
HRDI-20/12-17(200)E

 

 

Federal Highway Administration | 1200 New Jersey Avenue, SE | Washington, DC 20590 | 202-366-4000
Turner-Fairbank Highway Research Center | 6300 Georgetown Pike | McLean, VA | 22101