TECHBRIEF

Research, Development, and 

Technology

Turner-Fairbank Highway 

Research Center

6300 Georgetown Pike

McLean, VA 22101-2296

www.fhwa.dot.gov/research

Where Pedestrians

Cross the Roadway 

FHWA Publication No. FHWA-HRT-13-099

FHWA Contact: Jim Shurbutt, HRDS-30, 202-493-3420, jim.

shurbutt@dot.gov; Ann Do, HRDS-30, 202-493-3319, ann.do@

dot.gov 

Objective

This TechBrief describes research on the environmental influences

on where and when pedestrians cross the roadway across 20

different sites. 

Introduction

Pedestrian-vehicle crashes are both common and deadly. 

In 2010, 13 percent of all crash fatalities were pedestrians.(1)

Of these, 68.1 percent occurred outside of intersections. 

As a result of the large proportion of pedestrian fatalities 

that occur at non-intersection locations, it is important to investigate the causal factors of these collisions. Despite the large 

proportion of crashes, there has been little research investigating 

why pedestrians cross roadways at unmarked locations.

The present study sought to better understand the environmental 

influences on both where and when pedestrians elect to cross 

the road. The study team observed, coded, and analyzed the 

circumstances surrounding when and where crashes took place 

at more than 70,000 crossings. The study team created a model 

to predict crossing behaviors. These data have the potential to 

guide roadway design. Furthermore, this approach may aid in 

the selection and location of pedestrian crossing interventions 

(e.g., new pedestrian activation crossing beacons), ultimately 

increasing pedestrian safety in shared use environments. 

Research

Researchers coded pedestrian roadway crossings at 20 different 

locations in the Washington, DC, metropolitan area. Each location 

was one block in length (M = 390 ft) and was flanked by two 

marked crosswalks at intersections. Crossings were recorded 

within one marked, signal-controlled crosswalk and the roadway in between it and the next marked crossing (but not within 

the far crossing). 
2

Daytime pedestrian crossings were coded for 

several different factors:

1. Location. Within the marked crosswalk 

or not.

2. Traffic status. Walk or don’t walk signal 

illuminated.

3. Yielding. Pedestrians yielding to vehicles 

or vehicles yielding to pedestrians in the 

roadway.

4. Evasive Actions. Any evasive movement 

made by a vehicle or pedestrian in order 

to avoid collision (e.g., running or abrupt 

braking).

Characteristics of each location were also recorded:

A. The distance between the marked cross

walks.

B. Average annual daily traffic volume 

(AADT).

C. Street directionality (one- or two-way).

D. Physical barriers in or along the roadway that

might prevent pedestrians from easily 

crossing between the roadway and sidewalk.

E. The presence and location of bus stops.

F. The number of potential pedestrian trip 

originators/destinations (e.g., shops).

G. The availability of street parking.

H. The presence of a center turn lane.

I. The presence of a “right turn only” lane.

J. The length of the walk signal phase.

K. The length of the don’t walk signal phase.

L. The width of the roadway/pedestrian

crossing.

M. The presence and type of median 

(e.g., raised concrete or painted asphalt).

N. The presence of a T-intersection between 

the two marked crosswalks.

O. The traffic control device of the second 

crosswalk (i.e., traffic signal, stop sign, or 

none).

P. The pace at which pedestrians are required 

to travel in order to complete a crossing 

entirely during the walk signal phase. 

Results and Conclusions 

Data were used to create a model to predict 

where pedestrians were likely to cross the 

road (marked-intersection crosswalk or nonintersection). All 16 environmental variables 

were included as possible predictors in the 

model. However, not all variables were significantly related to crossing location and, as 

a result, were not selected for the model. The 

environmental factors that were ultimately 

included in the model were A (the distance 

between marked crosswalks), B (AADT),

D (physical barriers that might prevent pedestrians from easily crossing the roadway), 

E (the presence and location of bus stops), F (the 

number of potential pedestrian trip originators 

and destinations), I (the presence of a “right 

turn only” lane), L (the width of the roadway/

pedestrian crossing), and N (the presence of 

a T-intersection between the two marked 

crossings).

The accuracy of the model ranged from 80.55 

to 95.22 percent based on location. The model 

Figure 1. Example of a crosswalk in Washington, DC.
3

correctly predicted a mean of 90 percent of 

crossings. Overall, the model was successful in 

predicting whether participants would cross at 

marked crosswalks at intersections or outside 

of a marked crossing. 

A mean of 13.89 percent of pedestrian crossings 

took place at unmarked non-intersection locations. Given the disproportionate percentage 

of fatalities that take place outside of marked 

intersections, this number may be a bit surprising. However, these data suggest that some 

locations are prone to having more unmarked 

non-intersection crossings than others. This was 

indeed the case here. Non-intersection crossings 

ranged from 3.02 to 36.55 percent. 

The location with 36.55 percent of the crossings 

taking place at a non-intersection was different 

from many of the other locations in very specific 

ways. The first is that there is a wide, grassy 

median that separates traffic directionality. 

This median allows 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, the juxtaposition of a 

Metro (subway) train station and a surrounding 

neighborhood is such that the most direct route 

(in terms of absolute distance) between the two 

areas involves crossing outside of the marked 

intersection. Given that some might consider 

traveling through the marked crosswalks to be 

out of the way, many people may increase their 

perceived control of the crossing by utilizing the 

median and cross midblock. 

Environmental factors were examined in terms 

of their influence on crossing behaviors. For 

example, a significant relationship between 

the width of the crossing and the percentage 

of pedestrians that crossed entirely during the 

walk signal phase at each location was found. 

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 light cycle. 

Interestingly, a significant relationship between 

crossing entirely during the don’t walk signal 

phase and traffic directionality was found, 

such that 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 that 

might prevent pedestrians from easily crossing 

between the roadway and sidewalk were present, pedestrians were less likely to cross the 

roadway at unmarked non-intersection areas. 

Thus, it appears that even small barriers such as 

flower planters reduce the perceived affordances 

to cross the roadway.

Overall, only 0.98 percent of crossings involved 

pedestrians yielding to vehicles. Not surprisingly, 

a significantly greater percentage of crossings in 

non-intersections involved pedestrian yielding 

than in marked crosswalks. 

Overall, 8.93 percent of crossings involved a 

vehicle yielding to a pedestrian. A significantly 

greater percentage of crossings in the marked 

intersection involved vehicle yielding than crossings in the unmarked non-intersection areas. 

This discrepancy is largely attributable to turning 

vehicles yielding to pedestrians crossing in the 

marked crossings during the walk phase. 

Within the marked intersections, a significantly 

greater percentage of crossings involved vehicle 

yielding than pedestrian yielding. However, outside of the marked pedestrian crossing, pedestrians and vehicles were equally likely to yield in 

order to avoid collision.

Recommendations 

When designing areas where there will be pedestrian traffic, an evaluation of the environmental 

features should be made in order to determine 

where pedestrian crossings are most likely. The 

developed model was successful in predicting 

almost 86 percent of the pedestrian crossings. 

Areas that have a high predicted likelihood of 

unmarked non-intersection crossings may be 

proactively targeted to modify the crossing 

affordances of the environment, presumably 

increasing the safety and meeting the needs of 

all road users. A combined effort of pedestrian 

education and shared road use planning is 

hoped to reduce pedestrian injuries and fatalities 

and ultimately increase roadway safety. 
4

Researchers—This study was performed by researchers at Turner-Fairbank Highway Research Center, 

Stacy Balk and Mary Anne Bertola of Leidos, and Jim Shurbutt of FHWA.

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—Pedestrian safety, midblock crossings, crosswalks, human factors evaluation.

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 document. The U.S. Government does not endorse 

products or manufacturers. Trademarks or manufacturers’ names appear in this report only because 

they are considered essential to the objective of the document.

Quality Assurance Statement—The Federal Highway Administration (FHWA) provides high-quality 

information to serve Government, industry, and the public in a manner that promotes public understanding. Standards and policies are used to ensure and maximize the quality, objectivity, utility, and 

integrity of its information. FHWA periodically reviews quality issues and adjusts its programs and 

processes to ensure continuous quality improvement.

DECEMBER 2013 FHWA-HRT-13-099

HRDS-30/12-13(WEB)

Reference

1. Fatality Reporting Analysis System (2011). 

http://www-fars.nhtsa.dot.gov/Main/index.

aspx. Accessed February 2013.