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Federal Highway Administration Research and Technology
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|Publication Number: FHWA-HRT-14-004 Date: May/June 2014|
Publication Number: FHWA-HRT-14-004
Issue No: Vol. 77 No. 6
Date: May/June 2014
Yep, to get to the other side. But why at unmarked locations? A recent FHWA study examined that question with an eye on measures to increase safety.
|This pedestrian crossing is one of the locations in Washington, DC, where FHWA researchers collected data on midblock crossing behaviors.|
The ability to predict where pedestrians cross roadways has the potential to improve travel safety. That information can be used to better design roadways with pedestrians in mind and to inform the placement of crossing interventions.
Crashes involving pedestrians hit by vehicles are all too common and too often deadly. In 2012, pedestrian deaths represented 14.1 percent of all the fatalities that occurred in roadway crashes. Moreover, of the pedestrian fatalities that year, nearly three-quarters occurred away from intersections, somewhere at unmarked midblock locations.
Given the large proportion of pedestrian fatalities that take place away from intersections, investigating the causal factors of collisions at those unmarked locations is imperative. But in actuality, little research has been devoted to studying crossing behavior away from intersections.
The Federal Highway Administration (FHWA) is undertaking a number of projects investigating the performance of various solutions for improving safety at pedestrian crossings. Understanding the factors that influence pedestrians to cross at unmarked locations is a crucial step.
In 2012, FHWA conducted a study, which is described in the January 2014 report titled Human Factors Assessment of Pedestrian Roadway Crossing Behavior (FHWA-HRT-13-098). The overarching goal, as stated in the report, was to determine the environmental factors, such as roadway design, that “influence where pedestrians cross the roadway.”
The purpose of the study was to better understand environmental factors that influence both when and where pedestrians cross roadways. Some features appear to actually encourage people to cross in potentially risky ways. Such crossings can occur both in marked crosswalks (for example, during a DON’T WALK signal phase with traffic passing through a crosswalk) and outside marked crosswalks (for example, crossing midblock with flowing traffic). For a full definition of “risky” behavior, see the report.
The study team also researched influences that hinder risky crossings. For instance, a concrete lane divider or flower plantings along sidewalks definitely reduce the likelihood that pedestrians will attempt to cross a roadway at an inappropriate location.
To conduct the study, the FHWA researchers observed, coded, and analyzed the location, time, and other circumstances of more than 70,000 pedestrian crossings that took place at 20 locations in the metropolitan area of Washington, DC, with 3 of those in Virginia and 1 on the DC/Maryland border. During the study’s first phase, the observations occurred over a 2-week period in February 2012 (for temperatures, see the full report). The research team conducted two additional phases of data collection. Observations during the second and third phases took place over several days in March and December 2012. The team then created a mathematical model to predict crossing behaviors and thus forecast where collisions are likely to occur.
“These data have the potential to guide roadway design,” says FHWA Associate Administrator Michael Trentacoste, Office of Research, Development, and Technology. “Furthermore, this approach might aid in the selection and location of interventions, such as the installation of new pedestrian crossing treatments. Ultimately, the goal is to increase pedestrian safety in shared-use environments.”
The Research Parameters
The study omitted locations with driveways, exit ramps, rail grade crossings, rural environments, and freeways. These areas were omitted because they could result in circumstances that are distinctly different from those in traditional nonintersection crossings. With driveways and parking lots, for example, some vehicles might be moving in reverse and pedestrians might have no designated travel path. Instead, the study focused on urban areas with dense pedestrian populations where safety enhancements are most likely to be effective.
|Shown here is another pedestrian crossing where data were collected, located at the intersection of 3rd Street and H Street Northeast. A pedestrian is waiting on the far side of the intersection to cross.|
Some collisions result from pedestrians traveling along the roadway, either with or against traffic. The majority of pedestrian collisions, however, are likely to occur because of pedestrians crossing the roadway. Therefore, the study zeroed in on those crossings.
The FHWA researchers selected the Washington, DC, area for data collection because of the high volume of pedestrian traffic. Another deciding factor was the city’s proximity to the research team’s home base at FHWA’s Turner-Fairbank Highway Research Center (TFHRC) in McLean, VA.
Each of the 20 selected locations was one block in length, that is, a mean length of 375 feet (114 meters). In addition, the two intersections that flanked each location had marked crosswalks.
|This overhead photo shows the intersection of H Street and 3rd Street Northeast (highlighted by a solid red rectangle) and the intersection at 4th Street Northeast (highlighted by a dotted red rectangle). The DDOT camera was positioned facing east and captured pedestrians crossing north/south on H Street between 3rd and 4th Streets.|
The research team collected data in three phases. During the first 2-week phase, the team video-recorded pedestrian crossings at eight locations and later coded that data. Subsequently, during the second phase, the researchers captured video at the additional locations, and then during the third phase compared that data with in-person observations to ensure the accuracy of the video feed.
To qualify for the study, each location had to be captured on video by traffic management cameras owned by the District of Columbia Department of Transportation (DDOT). The cameras had to be able to record activity at both of the marked crosswalks (and the WALK/DON’T WALK phases of traffic signals) and the area between the intersections.
The team recorded all of the observed pedestrian crossings on the roadways between the two marked crossings at each location. They also recorded crossings within one of the two marked, signal-controlled crosswalks. The researchers did not record crossings at the other end of the block because they did not have appropriate vantage points at all of the locations.
“This study uses a methodology that provides a real-world look into the dynamics of pedestrian crossing behavior,” says George Branyan, coordinator of the pedestrian program at DDOT. “‘Why did the pedestrian cross the road’ is a question many transportation planners and engineers have asked. This study provides some surprising answers and the basis for choosing safety countermeasures that can save lives.”
For the most part, pedestrians tend to select the fastest and most direct routes. Their route planning, however, must take into account such factors as the features of the roadway, their own physical abilities, and their tolerance for risk.
The FHWA research team conducted an initial review of research related to pedestrian crossing behavior. The literature review suggested that several variables influence crossing behavior. First are differences in gender (males are more likely to attempt risky crossings). Second are age differences (older adults are less likely to attempt dangerous crossings; young children possibly make riskier crossing decisions).
Understanding the role of age differences in the rates of pedestrian injuries and fatalities might help direct educational efforts to encourage safe crossing behaviors. Similarly, age-related differences might help engineers target interventions to specific age groups. An example would be sidewalk markings in the vicinity of elementary schools to encourage children to cross streets at pedestrian-activated crosswalks rather than locations without marked crosswalks. Near retirement communities, longer protected crossings might be employed.
The team’s literature review also revealed three other factors that influence pedestrians’ decisions: alcohol use, self-identification as a safe person (pedestrians, for example, who see themselves as accepting only large gaps between vehicles as safe for crossing), and perceived control of the situation (being able to cross partway, for example, by taking refuge at medians).
Following the review of pedestrian factors, the team considered it reasonable to assume that environmental factors and educational interventions have the potential to lead to fewer crossings at unmarked locations. To take the environmental contingencies into account, the researchers coded daytime pedestrian crossings for factors that fell into the two categories. One included trip originators, such as homes, shopping malls, subway stations, and bus stops. Another category was trip destinations, like coffee shops and shopping centers, that later might become trip originators as well.
The team also recorded various stable environmental components at each location that might affect pedestrian travel patterns. These components include distance between the marked crosswalks at each end of a block; average annual daily traffic volume (AADT); street directionality (one- or two-way); physical barriers in or along the roadway that might prevent pedestrians from crossing easily; the presence and location of bus and transit stops; number of potential originators and destinations of pedestrian trips; and availability of street parking. Other components include presence of a center turn lane or a RIGHT TURN ONLY turning lane; length of WALK and DON’T WALK signal phases; width of the roadway; presence and type of median, such as raised concrete or painted asphalt; a T-intersection between the two marked crosswalks; a traffic signal, STOP sign, or no controls at the second crosswalk; and, finally, the pace at which pedestrians are required to travel to complete a crossing entirely during the WALK phase.
Crossing variables taken into account included location--that is, whether the crossing took place within the marked crosswalk. Another was traffic, which included crossings that did or did not conflict with traffic flow because the pedestrian-crossing signal was or was not activated as WALK or DON’T WALK.
Another crossing factor was the yielding behavior of both pedestrians and vehicles: pedestrians yielding to vehicles, and vice versa. A final crossing factor was evasive actions by vehicles or pedestrians to avoid conflict, such as pedestrians running to dodge vehicles or vehicles braking abruptly.
Analysis to Create The Model
To validate the video footage during the study’s first and second phases, the research team manually scored pedestrian crossing behavior at two of the locations. Agreement between the video and manual recordings was 98 percent. All data in phase three were collected by hand. As a result, that data could not be verified by video.
After data collection, the FHWA research team used the data to create a mathematical model to predict where pedestrians would be likely to cross a road, whether at marked intersection crosswalks or at nonintersections, based on the roadway environmental factors. Initially, the model included all of the environmental variables in the above list as possible predictors. The team members found, however, that not all variables were significantly related to crossing choices.
|These orange flags, although not examined as part of this study, are in a holder at an intersection in northwest Washington, DC. The flags can be taken by pedestrians and carried across the street as a way to increase their visibility, especially when used near a school. The flag holder is beneath a sign that instructs users to return the flags to the holder on the far side.|
The team omitted selected factors from the analysis and ultimately included in the model only the following environmental factors: travel pace and phasing (length of the WALK and DON’T WALK phases); traffic throughput (AADT volume, one- or two-way street, and street width); distance to safer locations (distance to the next marked crosswalk, presence and type of median, and presence of cross streets between marked crosswalks); external objects such as barriers and vehicles in the center of the road (including presence of a center turning lane); vehicles on the sides of the road (presence of parking, a RIGHT TURN ONLY lane); and whether the far marked crosswalk was signalized.
The Study’s Results
The probability of the model correctly predicting where pedestrians are likely to cross--whether at an intersection or at a nonintersection location--ranged from 80 percent at some locations to 95 percent for crossings at other locations. Overall, the model correctly predicted an average of 90 percent of crossings. The model was therefore successful in forecasting whether pedestrians would cross at marked crosswalks at intersections or outside of marked crossings.
Given the disproportionate percentage of fatalities that occur outside of intersection crosswalks, the low number of observations in the data of crossings outside the intersection crosswalks might be surprising. The percentage of nonintersection crossings ranged as low as 3 percent, up to 37 percent, suggesting that some locations are more prone to midblock crossings than others.
The outlier location--with 37 percent--is different from many of the other locations in two very specific ways that increase the attractiveness of nonintersection crossings. This location has a wide, grassy median that separates traffic directionality. This median enables pedestrians to cross one road segment, wait on the median for a gap in traffic, and complete the second portion of the crossing.
Beyond this, another difference is the juxtaposition of a Metro train station and bus stop and a surrounding neighborhood so that the most direct route in terms of absolute distance between the public transportation stops and the neighborhood involves crossing outside the marked intersection. Given that some pedestrians might perceive using the marked crosswalks as requiring them to go out of their way, many of them might increase their perceived control of the situation by using the median to cross midblock.
In examining the influence of environmental factors on crossing behaviors, the researchers found a significant relationship between the width of the crossing and the percentage of pedestrians who crossed entirely during the WALK signal phase at each location. In other words, the longer the distance that pedestrians were required to travel to cross the road, the more likely they were to cross entirely during the WALK phase of the traffic signal’s cycle.
In addition, the team found a significant relationship between crossing entirely during the DON’T WALK signal phase and traffic directionality: pedestrians were more likely to cross during the DON’T WALK phase on one-way streets than on two-way streets.
Not surprisingly, when physical barriers were present that might prevent pedestrians from easily walking from the sidewalk to the roadway, they were less likely to cross the roadway at unmarked locations. Thus, it appears that even small barriers such as benches and flower planters reduce perceived opportunities to cross midblock.
During the research study, the rates of drivers and pedestrians yielding to each other were very low.
The study’s report suggests various ways to modify environmental factors to influence pedestrian behavior, such as adding appropriate vegetation to separate the sidewalk and roadway and thereby help to dissuade pedestrians from crossing at inappropriate locations.
Other interventions can be used to alter pedestrians’ perceived control outside marked crossings. “However, it should be noted that these modifications can have unintended consequences in crossing behavior and should be evaluated carefully,” according to the report.
“By investigating the conditions that govern the behavior of pedestrians, FHWA was able to develop a model that has a surprisingly high predictive power,” says Director Monique Evans, FHWA Office of Safety Research and Development (R&D). “Used in conjunction with other FHWA safety tools, such as PEDSAFE, the model will help State and local departments of transportation select appropriate measures to improve those conditions. FHWA expects that a combined effort of pedestrian education and planning for shared road use will reduce pedestrian injuries and fatalities and ultimately increase roadway safety.”
Ann H. Do is a research highway engineer at FHWA’s TFHRC in McLean, VA, where she has managed the pedestrian and bicyclist safety research program since 2001. She joined FHWA in 1990 as a highway design engineer with the Eastern Federal Lands Highway Division. Do has a B.S. in civil engineering from Virginia Tech.
Stacy A. Balk, Ph.D., is a research psychologist with the Leidos human factors support team in FHWA’s Office of Safety R&D. She serves as a reviewer for various human factors and transportation journals and conferences. She received her B.S. from the University of Iowa and her M.S. and Ph.D. from Clemson University.
Jim W. Shurbutt, Ph.D., is a behavioral research psychologist with the Office of Safety R&D. He received his B.S. and M.S. degrees in psychology from Jacksonville State University and his Ph.D. in applied behavior analysis from Western Michigan University. Shurbutt’s areas of research include pedestrian and bicycle safety and access, rural roadways, complex interchanges, and traffic control devices.
For more information, contact Ann Do at 202–493–3319 or email@example.com for the full report, Human Factors Assessment of Pedestrian Roadway Crossing Behavior. For information on the broader context of pedestrian issues, see United States Department of Transportation Policy Statement on Bicycle and Pedestrian Accommodation Regulations and Recommendations at www.fhwa.dot.gov/environment/bicycle_pedestrian/overview/policy_accom.cfm.