U.S. Department of Transportation
Federal Highway Administration
1200 New Jersey Avenue, SE
Washington, DC 20590
SRS and CLRS on rural, two-lane highways are proven safety countermeasures. National Cooperative Highway Research Program (NCHRP) Report 641: Guidance for the Design and Application of Shoulder and Centerline Rumble Strips documented significant crash reductions for SRS and CLRS on rural, two-lane highways. SRS were found to provide a 36-percent reduction in ROR fatal and injury crashes while CLRS were found to provide a 44-percent reduction in head-on fatal and injury crashes.(7) However, researchers have found that rumble strips are not equally effective for all roadway geometries and traffic volumes. Additionally, rumble strips can be used to target drowsy or distracted driving, while other roadway treatments do not fulfill this need. Rumble strips are most effective and should be considered in corridors with the greatest need. This section provides an overview of methodologies for selecting sites for installation, identifying rumble strip effectiveness, and conducting B/C analysis for treatments.
Roadway departure crashes, which include ROR crashes and head-on crashes, are typically a systemic problem, meaning that they account for a high number of crashes, but their density is often low. High crash locations often prove to be difficult to identify, although more success can be found in identifying high crash corridors. As noted in the Low Cost Treatments for Horizontal Curve Safety 2016 the most effective safety improvement processes include both a systemic component and site analysis, or in this case, corridor analysis component.(8) Additionally, agencies utilize an additional systematic component for installing rumble strips based on agency-level policy.
Systemic and corridor analyses are most commonly used to identify corridors for retrofit installations. Retrofit installations are projects in which the objective is to install rumble strips where they did not previously exist. Systematic analyses are most commonly used for installing rumble strips on new, reconstructed, or resurfaced roadways (i.e., rumble strips are applied on corridors while on-site performing other activities). Each of these approaches is defined below and explained in further detail in terms of rumble strip safety.
Using the systemic safety approach, agencies implement rumble strips on corridors based on risk features that are correlated with higher severity focus crash types (e.g., K and A severities on the KABCO scale). In this approach, corridor crash history is not considered for identifying rumble strip treatment locations. Rather, crash data analyses are used to identify risk factors associated with fatal and severe injury ROR crashes, fatal and severe injury head-on crashes, or other focus crashes outcomes. Severe crash types are typically addressed using a systemic approach since they are often less concentrated than total crashes, but tend to be over-represented at locations with more risk factors. Risk factors for severe ROR crashes often include characteristics such as lane width, shoulder width, and traffic volume, among others. Analyses are conducted across all corridors within a facility type (e.g., rural, two-lane highways) to identify factors that contribute to increased risk of focus crash outcomes. Risk factors may be combined in a weighted manner to identify specific corridors for treatment.
For example, analysis of all rural, two-lane highway corridors within a jurisdiction may identify risk factors for fatal and severe ROR crashes as being annual average daily traffic (AADT) greater than 400 and less than 2,000, lane width less than 12 feet, shoulder width less than 4 feet, curve density greater than 2 curves per mile, and roadside hazard rating greater than 3. The jurisdiction may prioritize corridors with all of these risk factors for rumble strip installation or may develop weights for each risk factor and prioritize segments with the highest combined ranking of risk factors within a given budget.
Agencies have traditionally used crash frequency (e.g., locations with a high number of crashes or higher than expected number of crashes) to justify additional corridors for installing rumble strips on an as-needed basis. This approach may also be referred to as a case-by-case approach because installation must be considered for each corridor based on multiple factors, and the decision to install or not is made independently in each instance based on these factors. Agencies often consider the crash rate in relation to the statewide average to determine if a corridor should be examined further for rumble strip installation. Most often, they base installation recommendations on three to five years of historical crash data.
The Highway Safety Manual (HSM) defines the crash rate as "the number of crashes that occur at a given site during a certain time period in relation to a particular measure of exposure." (9) Commonly this is computed as the average crash frequency, or crashes per year, divided by the average traffic volume (expressed as AADT) for the same time period. At this point, the crash rate for a corridor is compared to the average crash rate for all corridors within the specific facility type (e.g., rural, two-lane highways). Typically, the corridors with the highest crash rates or crash rates that are above average are selected for treatment. This methodology is simple to employ; however, it suffers from the following limitations:
SPFs provide the predicted number of crashes for corridors based on data from corridors with similar characteristics, and is a function of the AADT and corridor length. SPFs account for the non-linear relationship between traffic volume and crash frequency, as well as potential differences in characteristics for short versus long corridors. As noted in the HSM, the SPF prediction can be utilized for several methods for identifying high crash corridors that are more statistically valid than the crash rate method.(9) The following performance measures utilize SPFs:
The Excess Predicted Average Crash Frequency using SPFs is the easiest to compute, as this performance measure simply compares the difference between the SPF predicted average crash frequency and the observed average crash frequency. However, this performance measure cannot account for RTM bias. The Excess Expected Average Crash Frequency with EB Adjustment performance measure goes one step further, to calculate the expected average crash frequency. The expected average crash frequency is a weighted average of the observed average crash frequency and predicted average crash frequency from the SPF. The expected average crash frequency accounts for RTM bias. The expected average crash frequency is compared to the predicted average crash frequency and the difference is the excess expected average crash frequency. If this value is greater than zero, then a site experiences more crashes than is expected and may be a better candidate for an improvement. See Chapter 4 of the HSM for more details on performance measures and their strengths and limitations.
While the systemic approach to safety focuses on identifying locations for rumble strip installation based on risk, the systematic approach to safety focuses on installing rumble strips system-wide, often while completing other construction activities, with exceptions to installation that are based on policy. Most agencies have policies outlining criteria for systematic rumble strip installation. Criteria for installation are based on special considerations, including accommodating bicycles, minimizing noise disturbance, and avoiding potential pavement quality issues. For CLRS, the systematic approach is typically based on pavement condition, posted speed limit, and lane or pavement width. For SRS, the systematic approach is typically based on pavement condition, posted speed limit, shoulder width, and presence of curb or guardrail. Posted speed limit is often used as a surrogate measure for built-up environment.
Rumble strip safety effectiveness is established through the development and use of crash modification factors (CMFs). A CMF is an index of the expected change in safety performance following a change in traffic operations or installation of a countermeasure. The percent change in crashes is calculated as 100*(1-CMF); thus, a CMF of 0.70 with a standard deviation of 0.12 indicates a 30 percent reduction in crashes with a standard deviation of 12 percent.
Users may apply the CMF directly to the expected number of crashes without treatment to estimate the number of crashes with treatment, or to estimate the change in crashes. Alternatively, the upper limit of the confidence interval provides a conservative estimate of the expected change in crashes. The upper 95-percent confidence limit of the CMF is determined by multiplying the standard deviation by 1.96 and adding this to the CMF. [Note this is approximated by CMF+2×standard error.] In this example, the analyst can use 0.70 or a conservative value of 0.94. Users may choose to use the upper limit if the CMF is of lower quality (explained in further detail in the next section) or if it is unlikely that the specified reduction can be achieved.
The CMF Clearinghouse and the HSM Part D contain CMFs for center line and shoulder rumble strips and their combination. Part D of the HSM contains CMFs that passed a screening process or met expert panel approval for adequate reliability and stability. The CMF Clearinghouse is a living website that contains all CMFs for treatments, including those in the HSM Part D. The CMFs in the Clearinghouse range from high quality to low quality. The Clearinghouse is updated quarterly and contains the most up-to-date CMFs related to rumble strips on all facility types. Further information about CMFs in the Clearinghouse is presented in the next section.
There are more than 500 research-based CMFs relevant to rumble strips located in the CMF Clearinghouse. This section provides a brief overview of identifying the most appropriate CMFs and searching for CMFs in the CMF Clearinghouse. More details on using the CMF Clearinghouse are located at www.cmfclearinghouse.org; select the "About the CMF Clearinghouse" tab.
Having identified the countermeasure of interest, the user navigates a list of CMFs to identify which CMF best approximates the reduction that can be expected for proposed installation or policy. CMFs can be generally applicable (e.g., all rural, two-lane highways), or may be specific to a unique set of factors (e.g., rural, two-lane highway horizontal curves with a shoulder width less than or equal to five feet). The applicable factors may be found in the countermeasure name or they may be buried in the CMF details. The CMF details are discussed in more detail in the "Searching for CMFs" in the CMF Clearinghouse section.
Major factors in identifying the most relevant CMF include the following:
Additional factors may be used to help narrow the list of applicable CMFs for rumble strips. The following list includes additional minor factors used to help identify the most applicable CMF.
CMFs are often developed for a specific value of minor characteristics or the researchers will provide the values of minor characteristics for which the CMFs were developed. However, some minor factors, such as speed limit, are often unreported. The reported minor factors for the CMFs can be used to identify which is closest to the applicable scenario if multiple CMFs remain after screening based on the major factors. Traffic volumes and jurisdictions (most often States) are reported for many CMFs. Geometric characteristics may be more difficult to determine–see the "Searching for CMFs" in the CMF Clearinghouse section for more details–however, geometric characteristics, such as applicability for horizontal curves or for certain shoulder widths are available for several CMFs.
In addition to relevance, CMFs are characterized based on quality. The quality is provided as a star rating. The CMF may be rated from 0 to 5 stars, with higher quality CMFs having a higher star rating. Higher quality CMFs control for potential biases, have larger sample sizes, and are more generalizable (i.e., are developed from more diverse geography). Sample 5-star and 4-star CMFs from the CMF Clearinghouse are provided in Appendix A for CLRS, SRS, and their combination. These CMFs represent the highest quality currently available in the CMF Clearinghouse and provide an example of the breadth in applicability for CMFs in the Clearinghouse. See Appendix A for further details and descriptions of information available for the sample CMFs.
This section discusses searching the CMF Clearinghouse for the most appropriate CMF based on the factors covered in the Identifying the Most Appropriate CMF(s) section. This discussion is focused on using the website to identify CMFs specifically for rumble strips. For further information, visit the CMF Clearinghouse website.
The CMF Clearinghouse homepage allows users to search for CMFs based on the countermeasure name, research study information, and CMF ID. The countermeasure name will be the most useful for most practitioners, and specificity in search terms is important. For example, if searching "rumble strip," the search will return (at the time of this publication) more than 500 CMFs. If looking for CMFs related to CLRS, entering "center line rumble strips" returns more than 100 CMFs. Leaving the search terms blank will return all CMFs in the clearinghouse.
Having conducted a search, users can browse the returned CMFs by category (e.g., roadway) and subcategory (e.g., roadway rumble strips). Additionally, users can filter the search to include only CMFs of a certain star rating or other major factors. Using the filtered list, users can explore the remaining countermeasures for applicable CMFs. Countermeasure names may vary in terms of specificity, and it is possible more than one countermeasure name will apply to a search. At this point, the CMF, quality, crash type, crash severity, and area type are presented; users can choose to select one CMF for further details, or can select a check box to compare multiple CMFs.
When selecting one CMF for further evaluation, the CMF/crash reduction factor (CRF) details page will appear. This contains information on the following relevant CMF characteristics:
The applicability section defines several important major and minor factors for which the CMF is appropriate. The section provides details on the applicable crash type, crash severity, roadway types, number of lanes, road division type, speed limit, area type, traffic volume, and time of day for the CMF. The development details section provides further useful information for selecting an appropriate CMF, including the municipality(ies), State(s), or country(ies) from which the CMF was developed. If multiple CMFs are relevant, the selection may be made on the State or municipality that is more similar to the user’s State or municipality. Finally, the other details section includes comments related to the CMF. The comments box is used to provide further information on other details of the CMF that do not fit into the other categories. For example, there may be comments on whether the CMF applies only to horizontal curves or tangents among other potential geometric characteristics.
Alternatively, multiple CMFs may be applicable, and users can select up to six for comparison. The comparison function provides side-by-side details of the major and minor factors and highlights any differences with a light blue bar. The light blue bars can be used to look for differences, and the countermeasure name and the comments section can be reviewed for any further details that will help to identify the most appropriate CMF.
Figure 4 provides an example comparison for CLRS. Consider a scenario where a user is interested in determining the CMF for CLRS for all fatal and injury crashes on rural, two-lane highways with curves. CMF ID 3387 is not applicable because the crash type and severity do not match the desired scenario. CMF IDs 3350 and 3383 apply to the same crash type and severities (and are identical for all other factors not shown here). However, from the countermeasure name, CMF ID 3350 applies to general roadway corridors while CMF ID 3383 applies only to tangent sections (i.e., non-curve locations). In this case, the user would select the first CMF of 0.91 for further evaluation because the desired scenario includes both tangents and curves.
Figure 4. Screen capture. CMF Clearinghouse comparison for CLRS.
A B/C analysis is an important tool for determining if the proposed treatment is worthwhile. The B/C analysis compares the present value of annual benefits divided by the present value of total costs. Total costs include installation costs and annual operating or maintenance costs. A ratio greater than 1.0 indicates the benefits are greater than costs and a ratio less than 1.0 indicates the benefits are less than costs.
The safety benefits for rumble strips are measured by the change in crash costs, which is computed by multiplying the change in crashes per year by the average cost of a crash. It is important to note the average crash cost should match the crash type used in the analysis. For example, if the CMF is for fatal and injury crashes, then the average crash cost should reflect the cost for fatal and injury crashes, not all crashes. The FHWA report Crash Cost Estimates by Maximum Police-Reported Injury Severity within Selected Crash Geometries provides crash costs by severity level, crash geometry, and speed limit, based on 2001 dollars.(10) The HSM also provides crash costs by severity level, which are based on the FHWA report. The 2001 values can be updated using the ratio of most recent United States Department of Transportation value of a statistical life and the 2001 value of 3.8 million dollars. Using the 2015 value (9.4 million dollars), the unit cost multiplier is approximately 2.47 as shown in Figure 5.
Figure 5. Equation. Conversion from 2001 dollars to 2015 dollars.
From the FHWA report, the 2001 average cost for a property damage only crash is 7,428 dollars and the average cost for a fatal or injury crash is 158,177 dollars. If a corridor targeted for SRS has a 2001 weighted (by severity) crash cost of 82,803 dollars, then the updated average crash cost would be 204,523 dollars (82,803 × 2.47). The annual benefit is computed by multiplying the average crash cost by the estimated change in crashes per year.
The present value is computed by multiplying the annual benefit or cost by the Capital Recovery Factor, as shown in Figure 6.
Figure 6. Equation. Present value of uniform annual benefit or cost.
A = annual benefit or cost.
i = inflation rate.
n = service life.
The present value equation applies only to annual costs and is not applied to the installation cost. The service life for rumble strips is often assumed to be the time until the next pavement overlay, unless the rumble strip is deemed to still be effective after a thin overlay or chip seal. Most commonly, the service life is reported to be 7 to 10 years, but has been reported to be as high as 15 to 20 years. The Office of Management and Budget Circular A-4 suggests a conservative real discount rate of 7 percent for .(11)
Rumble strip installation costs vary widely among and within States. Unit prices for rumble strips range between 500 dollars and 6,000 dollars per mile. There are many factors that can influence the cost, and they are provided in detail on the FHWA Rumble Strips and Rumble Stripes website.(12) For economic analysis, agencies can use historical data for installations to determine an average installation unit price. Typically, the unit price for SRS is for one side of the road, and would be multiplied by two for installation on both shoulders for two-lane roadways, or on the inside and outside shoulder for a directional analysis of multilane roadways.
An agency has identified 7,500 miles of rural, two-lane highways for retrofit installation of ELRS. Before recommending installation, a B/C ratio was calculated. The necessary assumptions for analysis are provided below as well as the results of the study. See Appendix B for details on calculating the results shown. The analysis focuses on fatal and injury ROR crashes.
The results indicate that while the targeted facilities experience an average 0.017 fatal and injury ROR crashes per mile, the installation is economically justified. The analysis indicates that approximately 41 fatal and injury ROR crashes would be reduced per year.
For a 2.5-mile section of rural, two-lane highway, an analyst identified the following information from a roadway inventory, crash database, and safety performance function:
Given information for CLRS and SRS include the following:
The upper 95-percentile estimate of the CMF is 0.79, resulting in a reduction of 0.49 ROR crashes per mile per year. The annualized benefit is calculated to be 101,018 dollars per mile. The resulting B/C ratio is 121.0, indicating that even a conservative estimate of the reduction results in a highly cost-effective solution.
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