TECHBRIEF Safety Evaluation of 

Wet-Reflective Pavement

Markings

FHWA Publication No.: FHWA-HRT-15-083

FHWA Contact: Roya Amjadi, HRDS-20, (202) 493-3383, 

roya.amjadi@fhwa.dot.gov

This document is a technical summary of the Federal 

Highway Administration report, Safety Evaluation of 

Wet-Reflective Pavement Markings (FHWA-HRT-15-065).

Objective

The Federal Highway Administration (FHWA) organized 

38 States for the FHWA Evaluation of Low-Cost Safety 

Improvements Pooled Fund Study as part of its strategic 

highway safety plan support effort. The purpose of the 

study is to evaluate the safety effectiveness of several 

low-cost safety improvement strategies through scientifically rigorous crash-based studies. 

One of the strategies selected for evaluation for this study 

was the application of wet-reflective pavement markings. 

This strategy involves upgrading existing markings from 

standard marking materials to wet-reflective markings, 

which may be applied as a paint, tape, or thermoplastic 

material. These markings are designed to provide an 

improved level of retroreflectivity during wet road surface 

conditions. 

Introduction

This research examined the safety impacts of wet-reflective 

markings in Minnesota, North Carolina, and Wisconsin. 

In Minnesota, data were provided where the markings 

were applied on two-lane roadways and freeways on the 

center line, edge line, or lane lines. In North Carolina, 

the markings were applied on the edge line and/or lane 

lines on freeways. In Wisconsin, the markings have been 

Research, Development, and 

Technology

Turner-Fairbank Highway 

Research Center

6300 Georgetown Pike

McLean, VA 22101-2296

www.fhwa.dot.gov/research
2

applied for the lane lines on freeways and 

multilane divided roadways.

A literature review found that although there 

was some cross-sectional research relating 

retroreflectivity levels to crashes, there 

has been no published research evaluating 

the effect on crashes after applying wetreflective markings. 

Methodology

The objective of this study was to estimate 

the safety effectiveness of this strategy 

as measured by crash frequency. Crashes 

occurring at or related to an intersection 

and snow/slush/ice- and animal-related 

crashes were not included. 

Target crash types considered included the 

following: 

• Total crashes (all types and severities 

combined).

• Injury crashes (K (fatal), A (incapacitating), B (non-incapacitating), and C 

(possible) injuries on KABCO scale).

• Run-off-road crashes (all severities 

combined).

• Sideswipe-same-direction crashes (all 

severities combined).

• Wet-weather crashes (all types and 

severities combined).

• Nighttime crashes (all types and 

severities combined).

• Nighttime wet-weather crashes (all 

types and severities combined).

The effects for dry-road crashes, which were 

not specifically evaluated as a target crash 

type, were inferred from the effects for total 

and wet-road crashes.

A further objective was to conduct a 

disaggregate analysis to investigate 

whether the safety effects vary by factors 

such as the level of traffic volume, the 

frequency of crashes before treatment, 

roadway type, posted speed limit, lane 

width, and shoulder width.

The evaluation of overall effectiveness 

included the consideration of the installation costs and crash savings in terms of 

the benefit/cost (B/C) ratio. 

The empirical Bayes (EB) methodology for 

observational before-after studies was used 

for the evaluation.(1) 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, safety performance functions 

(SPFs) are applied. SPFs are equations used 

to estimate the expected crash frequency of 

a site based on characteristics that influence 

crashes (e.g., traffic volumes). The use of 

SPFs in the EB methodology addresses the 

following:

• It overcomes the difficulties of using 

crash rates in normalizing for volume 

differences between the before and 

after periods.

• It accounts for time trends.

• It reduces the level of uncertainty in the 

estimates of safety effect.

• It properly accounts for differences in 

crash experience and reporting practice 

in amalgamating data and results from 

diverse jurisdictions.
3

The methodology also provides a 

foundation for developing guidelines for 

estimating the likely safety consequences 

of a contemplated strategy.

The SPFs used in the EB methodology 

were estimated 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, an overdispersion 

parameter, which is used in the EB 

calculations, was estimated iteratively 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 

explanation of the methodology, including 

a description of how the estimate of safety 

effects for target crashes was calculated.

Results

Based on the data for all three States 

combined, results are presented in two 

parts. The first part contains aggregate 

results, and the second part discusses a 

disaggregate analysis that attempted to 

discern factors that may be most favorable 

to the installation of wet-reflective pavement markings.

Aggregate Analysis

Estimates are provided in table 1 through 

table 3 for expected crashes in the after 

period without treatment, the observed 

crashes in the after period, and the estimated crash modification factor (CMF) and 

its standard error for all crash types considered. The percent change in crashes is 

100(1 − Estimate of the CMF); thus, a CMF of 

0.80 with a standard error of 0.025 indicates 

a 20-percent reduction in crashes with a 

standard error of 2.5 percent.

Sideswipe-opposite-direction crashes were 

not analyzed because of very low numbers. 

The effects for dry-road crashes, which were 

not specifically evaluated as a target crash 

type, were inferred from the effects for total 

and wet-road crashes and are also shown in 

these tables for information purposes. 

The aggregate results for freeways for all 

three States combined, which are shown in 

table 1, indicate reductions for total, injury, 

run-off-road, wet-road, nighttime, and 

nighttime wet-road, but only the injury and 

wet-road effects are statistically significant at 

the 95-percent confidence level. The results 

for sideswipe-same-direction and dry-road 

crashes show negligible and statistically 

insignificant increases in these crash types.

The results for Minnesota two-lane roads 

in table 2 indicate reductions for total, wetroad, dry-road, nighttime, and nighttime wetroad crashes, none of which are statistically 

significant at the 95-percent confidence 

level. The results for wet-road crashes, 

however, are statistically significant at the 

90-percent confidence level. Sideswipe-samedirection, run-off-road, and injury crashes 

experienced statistically insignificant 

increases. For the results in table 2, the total 

number of crashes are low, so lack of statistical significance in the analysis results is 

not unexpected. The indications of reductions 

in wet, nighttime, and nighttime wet-road 

crashes do still support the hypothesis 

that wet-reflective markings reduce these 

types of crashes. The results for Wisconsin 
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Total Injury Run-OffRoad

SideswipeSameDirection

WetRoadDryRoad Nighttime Nighttime

Wet-Road

EB estimate 

of crashes 

expected 

in the after 

period 

without 

strategy

4,111.97 1,219.76 466.37 618.28 887.49 3,224.48 1,103.63 248.69

Count of 

crashes 

observed 

in the after 

period

4,019 1,075 450 625 765 3,254 1,067 244

Estimate 

of CMF 0.977 0.881 0.964 1.010 0.861 1.009 0.966 0.979

Standard 

error of 

estimate of 

CMF

0.020 0.033 0.054 0.054 0.040 0.024 0.038 0.080

Table 1. Results for combined State freeways.

Bold = Results that are statistically significant at the 95-percent confidence level.

Total Injury Run-OffRoad

SideswipeSameDirection

WetRoadDryRoad Nighttime Nighttime

Wet-Road

EB estimate 

of crashes 

expected 

in the after 

period 

without 

strategy

186.26 84.43 79.19 10.61 24.76 161.50 52.04 8.48

Count of 

crashes 

observed 

in the after 

period

176 89 81 14 17 159 51 7

Estimate 

of CMF 0.944 1.053 1.022 1.310 0.685 0.984 0.979 0.823

Standard 

error of 

estimate of 

CMF

0.075 0.116 0.118 0.365 0.169 0.083 0.141 0.313

Table 2. Results for Minnesota two-lane roads.
5

multilane roads in table 3 indicate reductions for total, injury, run-off-road, wet-road, 

dry-road, and nighttime crashes that are 

all statistically significant at the 95-percent 

confidence level. Sideswipe-same-direction 

results indicate a statistically insignificant 

decrease, and nighttime wet-road results 

indicate a negligible and statistically 

insignificant increase in crashes.

Disaggregate Analysis

An attempt was made to further analyze 

the combined freeway dataset for wetroad crashes to identify site characteristics 

under which the safety benefits are greater. 

Only wet-road crashes were considered 

because they are the principal target crash 

type and the only one with a consistent 

and statistically significant effect across all 

three States individually. Only freeways 

were considered because the datasets for 

multilane and two-way roadways had too 

few crashes for such an analysis. 

A number of variables were investigated, 

including surface width, shoulder width, 

area type (urban versus rural), number of 

lanes, presence of shoulder rumble strips, 

average annual daily traffic, and expected 

wet-road crash frequency per mile prior to 

treatment.

No differences or clear trends were seen for 

any of these variables and the estimated 

CMFs. Therefore, for this dataset, the 

expected effect of this strategy on wetroad crashes on freeways is the same, 

regardless of differences in these aspects of 

the roadway environment. 

Total Injury Run-OffRoad

SideswipeSameDirection

WetRoadDryRoad Nighttime Nighttime

Wet-Road

EB estimate 

of crashes 

expected 

in the after 

period 

without 

strategy

556.77 256.08 110.93 93.17 92.62 465.15 133.13 16.71

Count of 

crashes 

observed 

in the after 

period

460 153 60 88 70 390 93 17

Estimate 

of CMF 0.825 0.595 0.538 0.941 0.751 0.838 0.696 1.001

Standard 

error of 

estimate of 

CMF

0.051 0.059 0.078 0.115 0.108 0.058 0.082 0.270

Table 3. Results for Wisconsin multilane roads.

Bold = Results that are statistically significant at the 95-percent confidence level.
6

Economic Analysis

An economic analysis was conducted to 

determine the estimated B/C ratio for this 

strategy for multilane roads and freeways. 

(For two-lane roads, an economic analysis 

could not be performed because the crash 

reductions were too small and statistically 

insignificant.) The statistically significant 

reduction in total crashes for Wisconsin 

was used as the benefit in the analysis 

of multilane roads. For freeways, the 

statistically significant reduction in targeted 

wet-road crashes for the three States 

combined was used as the benefit. 

On the cost side, for the installations on 

multilane roads in Wisconsin, the analysis 

conservatively assumed, in the absence 

of details of each installation, that the 

grooved contrast 4-inch tape, costing 

$9,200 per mi for a single-lane line treatment, was used for all installations. In total, 

259.76 lane mi were installed at an estimated cost of $2,389,792. For freeways, 

the same per-mile treatment cost was 

assumed for Wisconsin. For the North 

Carolina installations, the North Carolina 

Department of Transportation (NCDOT) 

indicated that the polyurea treatment 

costing $1.10 per linear ft was 

applied. For Minnesota, the analysis 

conservatively assumed that the 

ground in markings cost $17,000 per mi. 

With these assumptions, the total estimated 

cost for freeway installations in the three 

States was $6,765,373. 

The analysis assumed the useful service 

life for safety benefits was 2 years. This 

conclusion is based on information from the 

Minnesota Department of Transportation, 

which found that the retroreflectivity lasted 

2 years under wet conditions and 4 years 

under dry conditions. Service lives reported 

by NCDOT and the Wisconsin Department 

of Transportation indicated longer periods, 

so a 2-year life was assumed as the 

conservative option.

Based on information from the Office of 

Management and Budget Circular A-4, a 

real discount rate of 7 percent was used to 

calculate the annual cost of the treatment 

based on the 2-year service life.(2) With this 

information, the installation costs convert 

to annual costs of $3,741,928 for freeways 

in the three States and $1,321,794 for 

multilane roads in Wisconsin.

For the benefit calculations, the most recent 

FHWA mean comprehensive crash costs 

disaggregated by crash severity, location 

type, and speed limit were used as a base to 

derive comprehensive 2014 unit crash costs 

of $147,181 for freeways and $139,316 for 

multilane roads.(3)

The crash reduction was calculated by 

subtracting the actual crashes in the after 

period from the expected crashes in the 

after period had the treatment not been 

implemented. The number of crashes 

saved per year was 36.87 wet-road crashes 

for freeways and 51.59 total crashes for 

multilane roads, which was obtained by 

dividing the crash reductions (122.49 and 

96.77) by the average number of after period 

years per site (3.32 and 1.88). 

The annual benefits (i.e., crash savings) 

of $5,426,563 and $7,187,312 for freeways 

and multilane roads, respectively, are the 

product of the crash reductions per year 

(36.87 and 51.59) and the aggregate costs 

of a crash, all severities combined ($147,181 
7

and $139,316). The B/C ratio is calculated as 

the ratio of the annual benefit to the annual 

cost. The B/C ratios are estimated to be 

1.45 for freeways and 5.44 for multilane 

roads. The U.S. Department of Transportation (USDOT) recommends that 

a sensitivity analysis be conducted by 

assuming values of a statistical life 0.57 

and 1.41 times the recommended 2014 

value.(4) These factors can be applied directly 

to the estimated B/C ratios to get a range 

of 0.83 to 2.04 for freeways and 3.10 to 

7.67 for multilane roads. These results, 

which are summarized in table 4, suggest 

that the treatment, even with conservative 

assumptions on cost, service life, and 

the value of a statistical life, can be cost 

effective, especially for multilane roads. 

Summary and Conclusions

The objective of this study was to undertake a rigorous before-after evaluation 

of the safety effectiveness of wet-reflective pavement markings as measured by 

crash frequency. The study used data from 

three States, Minnesota, North Carolina, 

and Wisconsin, to examine the effects for 

specific crash types, including total, injury, 

run-off-road, sideswipe-same-direction, 

wet-road, dry-road, nighttime, and nighttime 

wet-road crashes. Table 5 shows the various 

crash types for which a statistically significant CMF (at the 95-percent confidence 

level) could be estimated. Crashes occurring 

at or related to an intersection and snow/

slush/ice- and animal-related crashes were 

not included and should not be included for 

applying the recommended CMFs. 

B/C ratios estimated with conservative 

cost and service life assumptions are 1.45 

for freeways and 5.44 for multilane roads. 

With the USDOT-recommended sensitivity 

analysis, these values could range from 

0.83 to 2.04 for freeways and 3.10 to 7.67 

for multilane roads. These results suggest 

that the treatment—even with conservative 

assumptions on cost, service life, and 

the value of a statistical life—can be cost 

effective, especially for multilane roads. 

With additional data, future research may 

provide statistically significant results 

for those crash types for which a CMF 

could not be recommended as well as 

more informative analyses to develop 

disaggregate CMFs. 

B/C Ratio

Point Estimate Lower Bound Upper Bound

 Freeways 1.45 0.83 2.04

Multilane Roads 5.44 3.1 7.67

Table 4. Economic analysis results.

Total Injury Run-OffRoad Wet-Road Nighttime

 Freeways 0.881

(0.033)

0.861

(0.040)

Multilane Roads 0.825

(0.051)

0.595

(0.059)

0.538

(0.078)

0.751

(0.108)

0.696

(0.082)

Table 5. Recommended CMFs and standard errors.

Blank cell = No CMF is recommended.
8

DECEMBER 2015 FHWA-HRT-15-083

HRDS-20/12-15(200)E

Researchers—Craig Lyon, Dr. Bhagwant Persaud, and Kimberly Eccles.

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—Wet-reflective, pavement markings, low-cost, safety improvements, safety evaluations, 

empirical Bayes.

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 highquality information to serve the Government, industry, and public in a manner that promotes public 

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References 

1. Hauer, E. Observational Before-After 

Studies in Road Safety—Estimating the 

Effect of Highway and Traffic Engineering Measures on Road Safety. Elsevier 

Science, Incorporated, 1997.

2. Office of Management and Budget. 

Circular A-4. September 17, 2003. 

Available at: https://www.whitehouse.

gov/omb/circulars_a004_a-4/.

3. Zaloshnja, E., Miller, T., Council, F., and 

Persaud, B. “Crash Costs in the United 

States by Crash Geometry,” Accident 

Analysis and Prevention 38(4), 2006, 

pp. 644–651.

4. U.S. Department of Transportation. 

Guidance on Treatment of the Value 

of a Statistical Life (VSL) in U.S. 

Department of Transportation 

Analyses—2014 Adjustment. Memo, 

June 13, 2014. Accessed November 

12, 2014. Available at: http://www.

dot.gov/sites/dot.gov/files/docs/VSL_

Guidance_2014.pdf.