For every 100mcd increase in the reverse number of the edge solid line of road hot-melt paint, the traffic accident rate decreases by 8.6%

For every 100mcd increase in the reflectance brightness coefficient of the white edge solid line of traffic markings, the traffic safety accident rate decreases by 8.6%. For every 100mcd increase in the reflectance brightness coefficient of the white dashed line, the nighttime collision accidents and bicycle nighttime collision accidents decrease by 23.7%.

Research on Reflective Performance and Safety of Marking Lines
An Investigation of Longitudinal Pavement 
Research on the Reflectivity and Safety of Longitudinal Road Surface Markings
、
Introduction

This study aims to determine whether there is a correlation between the reflectance brightness coefficient of road markings and safety. Previous research on this topic has provided mixed and sometimes even abnormal results. This report includes a summary of previous work and the latest research report attempting to link the reflectance brightness coefficient of road markings with safety.

Several attempts have been made to evaluate the safety benefits of road marking retroreflection. A major challenge is that the reflectivity level of road markings will fluctuate over time. The attempt to model the degradation curve of the reflectance brightness coefficient of road markings has not been widely successful (1,2). Although the reflectance brightness coefficient of road markings has some predictability (AADT (Average Daily Traffic Volume) is widely considered an important predictor variable), it may undergo unpredictable substantial changes with changes in rainfall frequency and intensity (clean markings), product quality, and even road conditions. Therefore, it is difficult to know the exact time and location of the road markings’ level of reflection at each collision. Although collision data is available, researchers have to make assumptions about the level of reflectance brightness for their analysis. Some researchers model retroreflection using measurement data from various sources, while others make assumptions about retroreflection without measurement.

In 2006, researchers in New Zealand studied the safety impacts of brighter pavement markings and concluded that there was not a conclusive improvement in safety (3). This study took advantage of a policy change in New Zealand in 1997 that required a minimum maintained retroreflectivity level of 70 mcd/m2/lx. Using a before–after approach, the authors compared crash rates before the change in policy. They assumed that markings were brighter during the after period. It should also be pointed out that, in New Zealand, all state roadways are delineated as a function of traffic volume. As volumes increase, they progressively apply the following treatments: delineators, centerlines, edge lines, and then RRPMs. Therefore, roadways withcenterlines had delineators too. Previous research in the United States has shown that supplemental delineation treatments, such as delineators or RRPMs, overpower the potential effect of pavement markings (4).

The results of an NCHRP study were published in 2006 with the following conclusions: “. . . the difference in safety between new markings and old markings during non-daylight conditions on non-intersection locations is approximately zero” (5). While the study incorporated large amounts of crash data and utilized the latest statistical techniques, there were significant limitations. For instance, the research only included crashes from California and modeledretroreflectivity (no measurements were made). While the study included efforts to overcome thepossible limitations in modeling retroreflectivity, these efforts presuppose that markings in California reach a value where there is an adverse impact on safety. The pavement marking maintenance policy of California is such that higher-volume highways are restriped up to three times a year with paint, or every two years with thermoplastic markings. As a result, there is only the occasional roadway with retroreflectivity levels below100 mcd/m2/lx.

Overlooking the concerns regarding the modeled retroreflectivity levels, the researchers also binned the retroreflectivity levels. The binning thresholds were derived linearly, which by itself is a limitation since the performance of retroreflectivity has been repeatedly shown to be best modeled logarithmically rather than linearly (6,7). In addition, the lowest bins for the edge lines included retroreflectivity levels from 21 to 183 mcd/m2/lx, thus including both inadequate levels and near-desired levels in the same bin (according to a synthesis of perception studies reported elsewhere (8)). Eight additional bins included retroreflectivity levels up to 413 mcd/m2/lx. Therefore, all binning used in the analyses included levels deemed to be acceptable or at least above previously recommended minimum retroreflectivity levels. These concerns limit acceptability of the quoted concluding remarks shown above.

In 2007, researchers reported results from an effort to develop a statistical association between measured pavement marking retroreflectivity and traffic crash frequency (9). For this research, data from North Carolina were used. The results suggest that increased levels of the average pavement marking retroreflectivity on multi-lane highways may be associated with lower expected target crash frequencies; however, the association was small in magnitude and not statistically significant. On two-lane highways, the association between pavement marking retroreflectivity and crash frequency was larger in magnitude and marginally significant. While this study used measured retroreflectivity levels (recorded once per year), it should be noted that all the retroreflectivity data were well above what might be considered minimum levels, and even near what might be considered desired levels (all data were above 100 mcd/m2/lx with an overall average of 240 mcd/m2/lx).

In 2008, a similar effort was reported that included 3 years of measured retroreflectivity (measured once per period) in Iowa (10). These data were analyzed along with crash records from the same year. The distributions and models of the entire database, and a subset including only two-lane highways, did not show that pavement marking retroreflectivity correlated to crash probability. When truncating the data to only records with retroreflectivity values less than 200 mcd/m2/lx, a statistically significant relationship was determined. However, the correlation was small. 

The four studies summarized here present the latest information regarding the relationship between pavement marking retroreflectivity and safety. Two of the studies conclude that there is no relationship, but both studies appear to have significant limitations. The remaining two studies point to some possible relationships with statistical significance but the findings are small and not consistent.

The objective of this research was to evaluate relationships between crashes and longitudinal pavement marking retroreflectivity. The retroreflectivity data consist of the measurements of pavement markings representing white edge lines (WEdge), white lane lines (WLane), yellow edge lines (YEdge), and yellow center lines (YCntr). The retroreflectivity data are from Michigan DOT road segments from 2002 to 2008. The research team combined the geometric and crash data from Michigan rural two-lane roadways and freeways (obtained during a previous project (11)) with the retroreflectivity data. Only nighttime crashes that occurred at nonintersection and noninterchange segments during the nonwinter months (between April and October) were considered (wet crashes were also excluded). The following specific types of crashes were initially identified as target crashes for this study: nighttime, single vehicle nighttime, fatal plus injury nighttime, and single vehicle nighttime fatal plus injury.

DATABASE PREPARATION

The data used in this research were compiled from the tables with many different formats and contents. Major source tables consist of retro data tables, crash report tables, roadway segment tables and other supporting tables collected from 2002 through 2008. Since the source tables were originally created with different purposes, there is no direct way to connect the retro values with crash records by road segments by time period. Hence, it required significant database development efforts to produce the final crash-retroreflectivity and retroreflectivity-crash tables prior to analysis as described in the sections below.

Retroreflectivity Data Table

The initial retroreflectivity table includes 24,862 retroreflectivity values from 3,553 sites for seven years (2002 – 2008) for four major line types (WEdge, WLane, YCntr, and YEdge). Michigan DOT restripes about 85 percent of their system with paint each year. They commission retroreflectivity measurements on about 15 percent of their system each year. The retroreflectivity measurements have been made with mobile technologies that produce data every 0.1 mile interval. Each 0.1 mile interval contains roughly 50 readings. 

As shown in Figure 1, most of the retroreflectivity values were recorded in the late summer after Michigan DOT completed their annual striping program. During the spring period about 6 percent of the retroreflectivity values were collected in April and May in the given data set.

An initial review of retroreflectivity values by line type shown in Figure 2 indicates that the yellow markings are mostly between 150 and 250 mcd/m2/lx. In contrast, most of the white markings have measurements between 250 and 350 mcd/m2/lx. The average retroreflectivityvalue of YCntr is 177.1 mcd/m2/lx and YEdge for 197.6 mcd/m2/lx. WEdge has the highest average value of 310 mcd/m2/lx followed by WLane with 297.1 mcd/m2/lx. Table 1 shows the actual numbers of Figure 2.

对下图2所示线型的逆反射亮度系数的初步审查表明，黄色标记大多在150和250 mcd/m2/lx之间。相比之下，大多数白色标记的测量值在250到350 mcd/m2/lx之间。YCntr的平均逆反射值为177.1 mcd/m2/lx，YEdge为197.6 mcd/m2/lx。WEdge的平均值最高，为310 mcd/m2/lx，其次是WLane，为297.1 mcd/m2/lx。

Crash Data Table

The crash data table contains detailed information about accidents such as crash id, crash location, severity, accident type, weather, light condition, traffic control present, and road condition. For the accuracy and convenience of the database management they are coded as predefined parameter values as shown in Table 2. Since not all the variables are necessary for this research, the research team went through the filtering and cleaning process before building actual crash record databases. The crash records were filtered to exclude the ones with the following conditions:

 winter crashes: January, February, March, November, and December

 intersection crashes

 interchange crashes

 wet, ice/snow, debris crashes

 daytime crashes.

Actual location of a crash consists of primary milepost and PR (physical reference) number based on the Michigan Geographic Framework. However, this alone is not enough information to merge databases so the beginning milepost and end milepost values of the PR number were added to make connection to retroreflectivity data table.

Development of Databases

Because of the inherent limitation of the retroreflectivity data such that the measurements were available only at certain locations and times, the research team put significant effort into preparation of the database that can be used in the statistical analysis. After an initial review of the available data on retroreflectivity and crashes, there seemed to be two possible ways for constructing a database that can be used to analyze the crash-retroreflectivity relationships based on the Michigan data: 

The inherent limitation of the current retroreflectivity data such that the measurements are available only at certain locations and times hinder establishing the relationship between crashes and retroreflectivity without extensive imputation of the original retroreflectivity data. Regularly scheduled measurements (e.g., each month) of retroreflectivity of pavement markings at road segments that can be easily connected to the crash database as well as maintaining the crash-retroreflectivity database will greatly aid the evaluation of relationships between crash and longitudinal pavement marking retroreflectivity.

Our company is a professional manufacturer of road hot-melt coatings and road glass beads. If you are interested, please feel free to contact me via email at any time export@toproadtraffic.com