TECHBRIEF Safety Evaluation of 

Profiled Thermoplastic 

Pavement Markings 

FHWA Publication No.: FHWA-HRT-17-076

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 Profiled Thermoplastic Pavement Markings

(FHWA-HRT-17-076). 

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 

promote those strategies for nationwide implementation 

by providing measures of their safety effectiveness 

and benefit-to-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 the application of profiled thermoplastic 

pavement markings. This strategy involves upgrading 

existing markings from flat-line thermoplastic or other 

standard markings to the profiled product. These markings 

are designed to provide an improved level of vision to 

drivers, particularly during wet-road surface conditions. 

The profiled nature also provides a rumble effect for 

Research, Development, and 

Technology

Turner-Fairbank Highway 

Research Center

6300 Georgetown Pike

McLean, VA 22101-2296

www.fhwa.dot.gov/research
2

errant vehicles. There are two types of 

profiled markings—raised and inverted 

profile patterns—as shown in figure 1 and 

figure 2.

Introduction

This research examined the safety impacts 

of profiled thermoplastic pavement 

markings in Florida and South Carolina. 

The States applied the markings only on 

edge lines and mostly on rural, two-lane 

undivided roads, with some use on rural, 

multilane divided roadways. 

A literature review found no published 

research evaluating the effect of profiled 

thermoplastic pavement markings on 

crashes after the application. According 

to FHWA, several agencies have used the 

treatment with good results, but none 

have conducted a safety effectiveness 

evaluation.(1)

Methodology

The objective of this study was to estimate 

the safety effectiveness of this strategy as 

measured by crash frequency. This study 

excluded intersection-related, snow/

slush/ice, and animal crashes. The study 

considered the following target crash types: 

• Total crashes (all types and severities 

combined).

• Fatal and injury crashes (K, A, B, and C 

injuries on the KABCO scale) (K is fatal 

injury, A is incapacitating injury, B is 

non-incapacitating injury, C is possible 

injury, and O is property damage only).

• Run-off-road crashes (all severities 

combined).

• Head-on crashes (all severities 

combined).

• Sideswipe-opposite-direction crashes 

(all severities combined).

• Sideswipe-same-direction crashes (all 

severities combined).

• Wet-road crashes (all types and 

severities combined).

• Nighttime crashes (all types and 

severities combined).

• Nighttime wet-road crashes (all types 

and severities combined).

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.

Figure 1. Photo. Raised profiled thermoplastic marking.(1)

Figure 2. Photo. Inverted profiled thermoplastic marking.(1)
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The evaluation of overall effectiveness 

included the consideration of the 

installation costs and crash savings in 

terms of the B/C ratio. 

The project team used the empirical 

Bayesian (EB) methodology for 

observational before–after studies for 

this evaluation.(2) 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 project team 

applied safety performance functions 

(SPFs). SPFs are equations that serve 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 

was found to have the following 

advantages:

• Overcomes the difficulties of using

crash rates in normalizing for volume 

differences between the before and 

after periods.

• Accounts for time trends.

• Reduces the level of uncertainty in the 

estimates of safety effect.

• Properly accounts for differences in 

crash experience and reporting practice 

in amalgamating data and results from 

diverse jurisdictions.

The methodology also provides a 

foundation for developing guidelines for 

estimating the likely safety consequences 

of a contemplated strategy.

The project team 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 

project team iteratively estimated an 

overdispersion parameter, which is used 

in the EB calculations, from the model and 

the data. For a given dataset, smaller values 

of this parameter indicate relatively better 

models. 

The full report contains a detailed 

explanation of the methodology, including 

a description of how the project team 

calculated the estimate of safety effects for 

target crashes.

Results

The 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 profiled thermoplastic 

pavement markings.

Aggregate Analysis

Table 1 and table 2 detail the results for 

each State. This includes the estimates 

of predicted 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 results were consistent between the 

two States in that no CMF results were 

statistically significantly different from 1.0. 

Results for both States also indicated a 

modest reduction in total crashes and a 

reduction in nighttime wet-road crashes of 

approximately 10 percent, although these 

were not statistically significant at the 

95-percent confidence level. 

Table 3 provides the results for the 

combined South Carolina and Florida 

data for the crash types analyzed in both 

States. Even with the combined data, none 

of the estimated CMFs were statistically 

significant at the 95-percent confidence 

level.
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Crash 

Type

EB Estimate of Crashes 

Predicted in After Period 

Without Strategy

Count of 

Crashes 

Observed in 

After Period

Estimate 

of CMF

Standard 

Error of 

Estimate of 

CMF

Total 789.81 779 0.986 0.041

Fatal and injury 312.59 281 0.898 0.060

Run-off-road 254.45 292 1.146 0.078

Head-on and 

sideswipe-oppositedirection49.09 44 0.894 0.143

Sideswipe-samedirection 35.57 36 1.009 0.177

Wet-road 152.73 157 1.027 0.089

Nighttime 281.57 261 0.926 0.064

Nighttime wet-road 60.76 55 0.903 0.131

Table 1. Results for South Carolina.

Crash 

Type

EB Estimate of Crashes 

Predicted in After Period 

Without Strategy

Count of 

Crashes 

Observed in 

After Period

Estimate 

of CMF

Standard 

Error of 

Estimate of 

CMF

Total 1,136.28 1,085 0.954 0.035

Fatal and injury 582.48 590 1.012 0.049

Run-off-road 182.59 172 0.941 0.080

Head-on 19.47 24 1.229 0.259

Wet-road 204.13 201 0.983 0.078

Nighttime 348.31 352 1.010 0.062

Nighttime wet-road 63.52 58 0.910 0.129

Table 2. Results for Florida.
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Crash 

Type

EB Estimate of Crashes 

Predicted in After Period 

Without Strategy

Count of 

Crashes 

Observed in 

After Period

Estimate 

of CMF

Standard 

Error of 

Estimate of 

CMF

Total 1,926.09 1,864 0.968 0.027

Fatal and injury 895.07 871 0.973 0.038

Run-off-road 437.04 464 1.061 0.056

Wet-road 356.86 358 1.003 0.059

Nighttime 629.87 613 0.973 0.045

Nighttime wet-road 124.28 113 0.908 0.092

Table 3. Combined results for South Carolina and Florida.

Disaggregate Analysis

The project team attempted to further analyze the combined dataset for nighttime 

wet-road crashes to identify site characteristics under which the safety benefits may 

be greatest. The project team considered 

only nighttime wet-road crashes because 

this is a key target crash type and the only 

one that showed some consistency and 

sizable effect for both States; however, the 

CMF estimates were still not statistically significant at the 95-percent confidence level.

The project team investigated the following 

variables: number of lanes, surface width, 

average shoulder width, median width, 

annual average daily traffic, and expected 

nighttime wet-road crash frequency per 

mile prior to treatment. The project team 

saw no differences or clear trends in the 

estimated CMF for any of these variables. 

Therefore, for this dataset, the expected 

effect of this strategy on nighttime wetroad crashes was the same, regardless of 

differences in these aspects of the roadway 

environment.

There are some indications that the CMF 

for nighttime wet-road crashes might be 

smaller (the benefit larger) for sites with 

higher expected nighttime wet-road crash 

frequency per mile prior to treatment. 

However, the sample was too small for a 

robust conclusion in this regard.

Economic Analysis

The project team conducted an economic 

analysis to determine the estimated B/C 

ratio for this strategy. They considered 

nighttime wet-road crashes, which 

experienced a reduction, for this analysis. 

The observed benefit—a CMF of 0.908—

was not unexpected, because this was the 

principal target crash type. Although the 

team based the estimated CMF on a small 

sample of crashes and it was not statistically 

significant at the 95-percent confidence 

level, it was consistent between the two 

States, which suggests that its use is 

justified for this purpose.

For cost, the project team used specific 

costs and information provided by the 
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South Carolina Department of Transportation 

(DOT), which were reasonably consistent 

with the range of costs provided by the 

Florida DOT for various contracts. The project team conservatively assumed the base 

condition that characterized the reference 

group of untreated sites consisted of flatline thermoplastic pavement markings with 

an average cost of $0.40 per linear foot. The 

cost provided for profiled thermoplastic 

pavement markings was $0.50 per linear 

foot, so the project team used the relative 

cost of $0.10 per linear foot as the unit 

treatment cost for the analysis. With these 

assumptions, the estimated treatment cost 

for the two States combined was $524,691.

Although the two DOTs provided service 

lives of between 3 and 5 years, the analysis 

assumed, conservatively, a useful service 

life for safety benefits of 2.5 years, which 

corresponds to the average after-period 

length at the treatment sites. 

Based on information from the Office of 

Management and Budget Circular A-4, the 

project team used a real discount rate of 

7 percent to calculate the annual cost of 

the treatment based on the 2.5-year service 

life.(3) With this information, the installation 

costs convert to annual costs of $125,926. 

For the benefit calculations, the project 

team used the most recent FHWA mean 

comprehensive crash costs as a base.(4) 

They based these costs on 2001 data 

and indicated that the unit costs (in 2001 

dollars) for property-damage-only (PDO) 

and fatal and injury crashes for all speed 

limits combined were $7,428 and $158,177, 

respectively.(4) The project team updated 

these to 2015 dollars by applying the ratio 

of the U.S. Department of Transportation 

(USDOT) 2015 value of a statistical life of 

$9.4 million to the 2001 value of $3.8 million.(5)

By applying this factor of 2.47 to the unit 

costs for PDO and fatal and injury crashes 

and then weighting by the frequencies of 

these two crash types in the after period, 

the project team obtained the aggregate 

2015 unit cost for total crashes as $192,337. 

The analysis did not consider fatal crashes 

alone because of the very low numbers of 

such crashes in the data, which would have 

skewed the results. 

The project team calculated the crash 

reduction by subtracting the actual crashes 

in the after period from the expected 

crashes in the after period had the 

treatment not been implemented (based 

on table 3). The number of nighttime wetroad crashes saved per year was 4.48, 

which was obtained by dividing the crash 

reduction of 11.28 by the average number 

of after-period years per site (2.52). 

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

of $862,033 is the product of the crash 

reduction per year (4.48) and the 

aggregate costs of a crash, with all 

severities combined ($192,337). The B/C 

ratio of 3.65:1 is calculated as the ratio 

of the annual benefit to the annual cost. 

The USDOT recommends that sensitivity 

analysis be conducted by assuming values 

of a statistical life 0.55 and 1.38 times the 

recommended 2015 value.(5) These factors 

can be applied directly to the estimated B/C 

ratio to get a range of 2.01:1 to 5.04:1. These 

results suggest that the treatment, even 

with conservative assumptions on cost, 

service life, and the value of a statistical 

life, can be applied cost effectively despite 

the relatively low crash effects.

Summary and Conclusions

The objective of this study was to undertake 

a rigorous before–after evaluation of the 

safety effectiveness of profiled thermoplastic pavement markings applied to edge 
7

lines as measured by crash frequency. 

The study used data from two-lane and 

multilane roads in two States—Florida and 

South Carolina—to examine the effects 

for specific crash types, including total, 

fatal and injury, run-off-road, head-on, 

sideswipe-opposite-direction, sideswipesame-direction, wet-road, nighttime, 

and nighttime wet-road crashes. Only 

nighttime wet-road crashes, the principal 

target crash type, experienced a material 

change in yielding a CMF of 0.908, which 

was not unexpected, because this was the 

primary target crash type. Although the 

project team based the estimated CMF on 

a small sample of crashes and it was not 

statistically significant at the 95-percent 

confidence level, it was consistent between 

the two States, which suggests its use may 

be justifiable.

Based on the consistent reduction in 

nighttime wet-road crashes, and estimated 

with conservative cost and service life 

assumptions, the B/C ratio relative to 

flat-line thermoplastic markings was 

3.65:1. Applying the sensitivity analysis 

recommended by the USDOT, this value 

could range from 2.01:1 to 5.04:1. These 

results suggest that the treatment—even 

with conservative assumptions on cost, 

service life, and the value of a statistical 

life—can be applied cost effectively despite 

the relatively low crash effects.

With additional data, future research may 

provide statistically significant results for 

those crash types for which a CMF could 

not be recommended or was statistically 

insignificant and provide more informative 

analyses to develop disaggregate CMFs that 

reflect different application circumstances. 

References

1. U.S. Department of Transportation 

Federal Highway Administration. (2006). 

Low-Cost Treatments for Horizontal 

Curve Safety, FHWA Report No. 

FHWA-SA-07-002, Federal Highway 

Administration, Washington, DC.

2. 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.

3. Office of Management and Budget.

(2003). Circular A-4: Regulatory Analysis. 

USDOT, Washington, DC. Available 

online: https://www.whitehouse.gov/

omb/circulars_a004_a-4/, last accessed 

December 15, 2015.

4. Council, F., Zaloshnja, E., Miller, 

T., and Persaud, B. (2005). Crash 

Cost Estimates by Maximum PoliceReported Injury Severity Within 

Selected Crash Geometries, FHWA 

Report No. FHWA-HRT-05-051, Federal 

Highway Administration, Washington, 

DC.

5. 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 Secretary of 

Transportation, Washington, DC. 

Available online: https://cms.dot.gov/

sites/dot.gov/files/docs/VSL2015_0.pdf, 

last accessed December 15, 2015.
8

DECEMBER 2017 FHWA-HRT-17-076

HRDS-20/12-17(200)E

Researchers—Craig Lyon, 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—Profiled thermoplastic pavement markings, 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 

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Trademarks or manufacturers’ names appear in this report only because they are 

considered essential to the objective of the document.

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