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Publication Number: FHWA-HRT-11-039
Date: April 2011
Evaluation of Pedestrian and Bicycle Engineering Countermeasures: Rectangular Rapid-Flashing Beacons, HAWKs, Sharrows, Crosswalk Markings, and the Development of an Evaluation Methods Report
CHAPTER 6. CROSSWALK MARKING FIELD VISIBILITY STUDY
This chapter summarizes the FHWA report, Crosswalk Marking Field Visibility Study, FHWA-HRT-10-068.(26)
The objective of this study was to investigate the relative daytime and nighttime visibility of three crosswalk marking patterns: transverse lines, continental markings, and bar pair markings.
Crosswalk markings provide guidance for pedestrians crossing roadways by defining and delineating paths on approaches. These markings are used in conjunction with signs and other measures to alert road users of a designated pedestrian crossing point. Part 3 of the 2009 MUTCD contains basic information about crosswalk markings.(2) Because some States adopt their own supplement or manual on traffic control devices and some develop policies and practices for subjects not discussed in MUTCD, differences in markings can occur among States, cities, and other jurisdictions.
While greater emphasis has recently been placed on researching pedestrian treatments, there is insufficient research to determine the relative visibility and driver behavior effects of the many different styles and patterns of crosswalk markings being used in the United States and abroad. Previous research studies focused on whether the presence of the markings (rather than a specific pattern) was effective.(27–29) The lack of information of the relative visibility of different marking patterns has inhibited the development of a consensus on whether more uniformity is needed in the form of tighter MUTCD standards or more comprehensive guidance on crosswalk markings.
Participants drove an instrumented vehicle on a route through the Texas A&M University campus in College Station, TX. The route provided an open road environment for the drivers that included portions in a typical college setting (e.g., sidewalks, buildings, basketball arena, etc.) and roads through the agricultural area of the campus (e.g., roadways that are more rural). Roadway lighting was present at all crosswalk locations. The study vehicle was equipped with instrumentation that allowed the researchers to measure and record various driving performance data. However, the vehicle operated and drove like a normal vehicle. The study was conducted during the day and at night.
The 78 participants were nearly evenly divided by gender and age (younger than 55 years old and 55 years old or older). Existing markings (six intersection and two midblock locations) and new markings installed for this study (nine midblock locations) were tested. Figure 13 shows an example of bar pairs installed for this study, figure 14 shows an example of continental markings, and figure 15 shows an example of transverse markings.
Figure 13. Photo. Example of bar pair markings.
Figure 14. Photo. Example of continental markings.
Figure 15. Photo. Example of transverse markings.
Once each participant was comfortable in the instrumented vehicle and had driven to a parking lot near the start of the route, he or she was reminded to indicate when one of the following items was seen: crosswalk markings, two-way left-turn arrows, or speed limit signs. The arrows and signs were included to ensure that the driver utilized a normal eye glance pattern and was not exclusively searching for crosswalks. As soon as the driver said "crosswalk," the rear seat experimenter pressed the appropriate button to place a mark in the computer file to indicate detection. Detection distances were adjusted by an experimenter response-time factor determined through pretesting. For the nine crosswalks installed for this study, the adjustments to the participant's detection distance ranged between 3 and 13 percent.
After completing the initial route, each participant was given additional instructions and asked to drive the same route again to rate each crosswalk marking on how easy it was to see using a scale of A (excellent, very easy to see) to F (completely unacceptable, it would have missed if not looking for it).
The prime objective of this study was to determine the detection distance of a crosswalk and to identify the variables that affect this distance. The differences in detection distances were evaluated with consideration of variables grouped into the following classes:
Initially, the statistical model contained all main effects and possible two-way interactions (termed the extended model). Not all variables could be included in the extended model due to exact linear dependency issues for some of the factors (i.e., a linear combination of one or more factors' values can exactly duplicate another factor's values). Next, several models with a subset of variables in the extended model were explored to determine the best model for identifying the variables that influence detection distance (termed the reduced model). Interactions were dropped from the reduced models when the p-value was less than 0.05 (i.e., not statistically significant).
The evaluations were conducted separately for the study sites (where new markings were installed at midblock locations) and the existing sites (where markings were already present at an intersection or were already present midblock and had pedestrian warning signs). The preliminary evaluations clearly showed a difference in detection distance for day and night. Because the nighttime condition had the additional variable retroreflectivity to consider and some of the variables were believed to have different effects during the night (i.e., marking type, vehicle type, and driver eye height), separate analyses were performed for daytime and nighttime conditions. In all combinations, daytime detection distances were longer than nighttime detection distances.
For the study sites, the marking type (bar pair, continental, or transverse) was statistically significant. The detection distances for bar pairs and continental markings were statistically similar, and they were both statistically different from and longer than the detection distance to the transverse markings both during the day and at night (see figure 16).
Figure 16. Graph. Least square mean detection distance by marking type and light level for study sites.
The presence of traffic had an impact on detection distance at the study sites, which limited the ability to see the markings farther upstream in most cases, as expected (see figure 17). The impact of traffic on the transverse markings was minimal, as the detection distances to these markings were already relatively small compared to the detection distances for bar pairs or continental markings.
Figure 17. Graph. Least square mean daytime adjusted detection distance by marking type and traffic presence at study sites.
Overall, shorter detection distances were associated with higher operating speeds; however, in most cases, the detection distances were only slightly shorter. The characteristics of the streets also influenced the detection of the crosswalk markings. An unexpected result was that the street group with a posted speed limit of 45 mi/h had longer nighttime adjusted detection distances than the 30 mi/h roadway sections. This finding was opposite the finding for daytime conditions. Daytime adjusted detection distances were slightly shorter for higher speeds.
Age (younger versus older) was only a significant factor during the day for the existing sites. However, the size of this difference was small and was not considered to be meaningful by the research team. Variables that included gender, driver eye height, and vehicle type as part of an interaction term were found to be statistically significant, but closer examination found them to not be of practical significance.
For the existing sites, marking type had a significant effect on detection distance. Figure 18 illustrates the least square mean daytime adjusted detection distance by marking type and location. There were no existing sites with bar pair markings. As a result, only continental and transverse markings were compared. During the day, the detection distances to the continental and transverse markings at intersections were not significantly different. The detection distance to midblock continental was statistically different (longer) from the detection distance to midblock transverse markings.
Figure 18. Graph. Least square mean daytime adjusted detection distance by marking type and location at existing sites.
During nighttime conditions at existing sites, variables, in addition to marking type, had an effect on detection distances, including location (midblock or intersection) and driver speed. Driver speed had mixed effects on detection distance depending on location (intersection or midblock) and light level (day or night). For intersections, an increase in driver speed was associated with longer detection distances for both the daytime and nighttime conditions. All of the intersections included in this project were either stop-controlled or signal-controlled. Several drivers appeared to be more focused on the stopping maneuver than the detection task and would not call out the recognition of a crosswalk until close to the stop bar.
For midblock (uncontrolled) approaches, findings were dependent on light level. Nighttime detection distance at midblock crosswalks was similar to those at intersections—longer detection distances were associated with higher speeds. For daytime, the opposite occurred—higher driver speeds were associated with shorter detection distances at the midblock crosswalks. While higher driver speeds were associated with shorter detection distances, the differences were small and were not considered to be of practical significance.
The subjective ratings of visibility using the letter-grade system (A, B, C, D, and F) were compared for all the groups/variables identified in the preceding analysis. The ratings for continental and bar pairs were consistent over various comparison groups, with better ratings for bar pairs and continental markings than for transverse markings. Figure 19 shows the overall rating received by each marking type for study sites.
Figure 19. Graph. Rating by marking type for study sites.
The conclusions from this study were as follows:
Based on the findings from this research, it is recommended that consideration be given to revising the 2009 MUTCD as follows:
Topics: research, safety
Keywords: research, safety, Pedestrian treatments, Bicycle treatments, HAWK, Rectangular rapid-flashing beacon, Sharrow, Crosswalk markings, Evaluation methods
TRT Terms: research, Safety and security, Safety, Transportation safety