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Coordinating, Developing, and Delivering Highway Transportation Innovations

 
REPORT
This report is an archived publication and may contain dated technical, contact, and link information
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Publication Number:  FHWA-HRT-15-065    Date:  September 2015
Publication Number: FHWA-HRT-15-065
Date: September 2015

 

Safety Evaluation of Wet-Reflective Pavement Markings

 

Chapter 6. Before–After Evaluation Results

Aggregate Analysis

Table 9 through table 14 provide the estimates of expected crashes in the after period without treatment, the observed crashes in the after period, and the estimated CMF and its standard error for all crash types considered. Sideswipe-opposite-direction crashes were not analyzed because of the very low number of crashes. 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; they are shown in these tables for information purposes. Results are provided separately for each State as well as all States combined. All results obtained are reported in this section. Recommended CMFs are presented in chapter 8.

The results for North Carolina freeways in table 9 indicate reductions for injury, wet-road, and nighttime wet-road crashes although only the reductions for injury and wet-road crashes were statistically significant at the 95-percent confidence level. All other crash types indicate a slight increase in crashes, but only the increase for dry-road was statistically significant.

Table 9. Results for North Carolina freeways.

Metric Total Injury Run-Off-Road Sideswipe-Same-Direction Wet-Road Dry-Road Nighttime Nighttime Wet-Road
EB estimate of crashes expected in after period without strategy 2,502.24 727.42 124.21 388.47 615.70 1,886.53 637.75 183.27
Number of crashes observed in after period 2,583 634 135 392 532 2,051 664 167
Estimate of CMF 1.032 0.871 1.081 1.006 0.863 1.087 1.040 0.907
Standard error of estimate of CMF 0.028 0.044 0.122 0.073 0.051 0.034 0.055 0.093
Note: CMF estimates that are statistically significant at the 95-percent confidence level are shown in boldface.

The results for Wisconsin freeways in table 10 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 and nighttime wet-road crashes had non-statistically significant increases.

Table 10. Results for Wisconsin freeways.

Metric Total Injury Run-Off-Road Sideswipe-Same-Direction Wet-Road Dry-Road Nighttime Nighttime Wet-Road
EB estimate of crashes expected in after period without strategy 1,497.71 444.37 283.82 217.45 255.89 1241.82 426.64 60.53
Number of crashes observed in after period 1,329 397 247 221 223 1106 373 71
Estimate of CMF 0.887 0.893 0.870 1.015 0.870 0.890 0.874 1.170
Standard error of estimate of CMF 0.030 0.051 0.061 0.075 0.065 0.033 0.052 0.149
Note: CMF estimates that are statistically significant at the 95-percent confidence level are indicated in boldface.

The results for Wisconsin multilane roads in table 11 indicate reductions for total, injury, run-off-road, wet-road, dry-road, and nighttime crashes that were all statistically significant at the 95‑percent confidence level. Sideswipe-same-direction and nighttime wet-road crashes had non-statistically significant increases crashes had non-statistically significant decreases, while nighttime wet-road crashes had negligible and non-statistically significant increases.*

Table 11. Results for Wisconsin multilane roads.

Metric Total Injury Run-Off-Road Sideswipe-Same-Direction Wet-Road Dry-
Road
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
Note: CMF estimates that are statistically significant at the 95 percent confidence level are indicated in boldface.

The results for Minnesota two-lane roads in table 12 indicate reductions for total, wet-road, dry-road*, nighttime, and nighttime wet-road crashes, none of which were statistically significant at the 95‑percent confidence level. However, the results for wet-road crashes were statistically significant at the 90-percent confidence level. SInjury, run-off-road, and sideswipe-same-direction crashes* and nighttime wet-road crashes had non-statistically significant increases. For Minnesota two-lane roads, the total numbers of crashes were low, so lack of statistical significance in the analysis results was 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.

* Revised 3/12/2019

Table 12. Results for Minnesota two-lane roads.

Metric Total Injury Run-Off-Road Sideswipe-Same-Direction Wet-Road Dry-
Road
Nighttime Nighttime Wet-Road
EB estimate of crashes expected in 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 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

The results for Minnesota freeways in table 13 indicate reductions for total, injury, sideswipe-same-direction, wet-road, and nighttime crashes but none were statistically significant at the 95‑percent confidence level. The results for wet-road crashes were statistically significant at the 90‑percent confidence level. Run-off-road and nighttime wet-road crashes had non-statistically significant increases. For Minnesota freeways, as with the Minnesota two-lane roads, the total numbers of crashes were low, so the statistical insignificance was not unexpected. However, the indications of reductions in wet and nighttime crashes do still support the hypothesis that wet-reflective markings reduce these types of crashes.

Table 13. Results for Minnesota freeways.

Metric Total Injury Run-Off-Road Sideswipe-Same-Direction Wet-Road Dry-
Road
Nighttime Nighttime Wet-Road
EB estimate of crashes expected in after period without strategy 112.02 47.98 58.34 12.33 15.90 96.12 39.24 4.89
Number of crashes observed in after period 107 44 68 12 10 97 30 6
Estimate of CMF 0.949 0.907 1.153 0.949 0.614 1.002 0.756 1.181
Standard error of estimate of CMF 0.117 0.165 0.182 0.305 0.211 0.133 0.159 0.515

The combined results for all freeway sites (North Carolina, Wisconsin, and Minnesota) in table 14 indicate reductions for total, injury, run-off-road, wet-road, nighttime, and wet-road nighttime crashes, but only those for injury and wet-road crashes were statistically significant at the 95-percent confidence level. The results for sideswipe-same-direction and dry-road crashes showed negligible and non-statistically significant increases for these crash types.

Table 14. Results for combined States freeways.

Metric Total Injury Run-Off-Road Sideswipe-Same-Direction Wet-Road Dry-
Road
Nighttime Nighttime Wet-Road
EB estimate of crashes expected in after period without strategy 4,111.97 1,219.76 466.37 618.28 887.49 3224.48 1,103.63 248.69
Count of crashes observed in after period 4,019 1,075 450 625 765 3254 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
Note: CMF estimates that are statistically significant at the 95 percent confidence level are indicated in boldface.

 

Disaggregate Analysis

An attempt was made to further analyze the combined freeway dataset for wet-road crashes to identify site characteristics for which the safety benefits were greater. Only wet-road crashes were considered because this was the principal target crash and the only one with a consistent and statistically significant effect in each of the three States. 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 the following:

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 wet-road crashes on freeways was the same regardless of differences in these aspects of the roadway environment.

 

 

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