Developing Crash 

Modification Factors for 

Separated Bicycle Lanes

FHWA Publication No.: FHWA-HRT-23-025

FHWA Contact: Ann Do, HRSO-30, ORCID: 0000-0001-9932-7422, 

(202) 493-3319, ann.do@dot.gov

This document is a technical summary of the Federal Highway 

Administration report Developing Crash Modification Factors (CMFs) 

for Separated Bicycle Lanes (forthcoming).

TECHBRIEF

Research, Development, 

and Technology

Turner-Fairbank Highway 

Research Center

6300 Georgetown Pike

McLean, VA 22101-2296

https://highways.dot.gov/research

INTRODUCTION

In 2020, the United States had 938 bicycle fatalities due to roadway-related 

crashes.(1)

 As bicycle use increases, transportation agencies are tasked with 

determining the optimal location and configuration for constructing on-road 

bicycle facilities. Several bicycle lane configurations are available, including 

the traditional bicycle lane, a buffered bicycle lane, and a separated bicycle 

lane (SBL). Recently, many U.S. transportation agencies have started 

implementing SBLs—also known as protected bicycle lanes—as a safety 

enhancement. Figure 1 provides an example of an installation. SBLs provide 

a bicycle lane that is separated from the adjacent motor vehicle lanes by 

including both a buffer and a vertical element between the motor vehicle 

lanes and the bicycle lane. 

Figure 1. Photo. Example of an SBL on a two-way street.

Source: FHWA. 
2

STUDY OBJECTIVE

The large number of bicycle-involved collisions 

demonstrates the need to prioritize analyzing and 

enhancing the safety of bicyclists. In recent years, 

transportation agencies have constructed a variety 

of bicycle lane configurations, including SBLs, yet 

the associated influence that an SBL may have on 

reducing crashes has yet to be determined. This Federal 

Highway Administration (FHWA) project evaluated 

the safety effect for various on-street bicycle facilities. 

The research focused on the feasibility of developing a 

crash modification factor (CMF) for the placement of 

SBLs at roadway segment locations.

SITE IDENTIFICATION 

The criteria established for a site to be included in this 

FHWA study are as follows:

• The study region, at a minimum, must include 

traditional bicycle lanes and SBLs.

• Data that can be used to estimate bicycle exposure 

must be available.

• Reported crash data are available for all 

bicycle-involved crashes, and the data must be 

multiyear data prior to 2020. 

• The SBL configuration should be consistent 

throughout the study region.

• Site features, such as roadway cross-sectional 

characteristics and direction of travel, can be 

acquired from an online source.

First, the research team identified several candidate 

locations based on published literature and a bicycle 

database known as the Green Lane Project.(2)

 For that 

project, bicyclists were encouraged to document any 

locations they encountered with SBLs. Even though 

a database primarily developed by volunteers can 

be error-prone, this resource provided information 

about locations that were equipped with some sort 

of bicycle facility.

Based on the location information included in the 

Green Lanes database and other published literature, 

the research team was then able to identify several 

potential locations to study. Following additional 

site screening via aerial photographs and jurisdiction 

databases, the research team identified the following 

promising study locations:

• Cambridge, MA.

• San Francisco, CA.

• Seattle, WA. 

In addition to these three cities, the team identified 

two locations with smaller sample sizes that could be 

used for CMF validation. These locations included 

the following:

• Austin, TX.

• Denver, CO. 

DATA COLLECTION 

The team compiled a list of data-related issues to 

consider when assessing the safety of an SBL facility. 

Table 1 identifies and defines these data requirements. 

To develop a CMF, there must be a base condition 

(e.g., no bicycle lane or traditional bicycle lane) and a 

target CMF (e.g., buffered bicycle lanes, SBLs). For 

this reason, site selection included all bicycle facilities 

within the study region. The research team populated the 

data needed for each study site segment, as summarized 

in table 1.

Table 1. Site information in database.

DATA NEED TYPE OF DATA COLLECTED SITE 

DATA ELEMENTS

Location description Location Street name, city, and State (including 

beginning and ending cross streets).

Starting latitude/longitude Location Measured to extended curb 

if at intersection.
3

Table 1. Site information in database. (Continued)

DATA NEED TYPE OF DATA COLLECTED SITE 

DATA ELEMENTS

Ending latitude/longitude Location Measured to extended 

curb if at intersection.

Length Location Distance in miles.

Cross streets Location Between beginning

 and ending points.

Number of motor 

vehicle lanes Site characteristics Total for both directions of travel.

Roadway facility type Site characteristics

Urban arterial (two-way and one-way).

Urban collector (two-way and one-way).

Urban local street (two-way and one-way).

Intersection channelization 

and traffic control Site characteristics

Islands (traditional, bend-in, 

bend-out, turn lanes, etc.).

Motor vehicle and bicycle signalization.

Signage and pavement markings.

Lighting Site characteristics Street light presence, 

placement, and type.

Corridor information Site characteristics

Speed limit; driveway density; number, 

type, and width of lanes; number 

and type of intersections; street 

network configuration; vehicle 

parking restriction hours; presence 

and location of sidewalks.

Direction of bicycle 

traffic flow Site characteristics Approaching or departing field of view.

Traffic operations for 

motor vehicle lanes Site characteristics One-way or two-way.

Median Site characteristics Physical separation of opposing 

motor vehicle maneuvers.
4

Table 1. Site information in database. (Continued)

DATA NEED TYPE OF DATA COLLECTED SITE 

DATA ELEMENTS

Parking lane location Site characteristics

Presence and location of 

parking lane; located left and/or 

right side of road if applicable.

Type of bicycle facility Bicycle facility 

characteristics

No dedicated lane, traditional 

bicycle lane, buffered bicycle 

lane, or SBL.

Year of construction Bicycle facility 

characteristics

SBLs constructed earlier than 2010 

may not be suitable if exposure 

information and crash data 

are not available. 

Width of buffer Bicycle facility 

characteristics

Locations with on-street parking 

should be further assessed to determine 

actual and effective buffer widths.

Vertical element Bicycle facility 

characteristics

Flexible posts, bollards, or light poles; 

curb or raised median; landscaping 

and planters; concrete (zebra/armadillo) 

bumps, buttons, and parking stops; 

parked cars; grade; concrete 

barrier, guardrail, or fence.

SBL facility configuration Bicycle facility 

characteristics

Right side one-way, or two-way.

Left side one-way, or two-way.

Middle two-way.

Unique SBL features Bicycle facility 

characteristics

Truck aprons, mixing zones, 

or elevated SBLs at 

driveways/crossings; green 

markings; bicycle facility continuity 

and operational consistency.

Crash data Supplemental data from agency 

where sites are located

Total number of crashes 

and number of fatal and injury 

crashes (specific consideration 

to who is injured: motor vehicle 

drivers or passengers, 

bicyclists, and pedestrians).
5

The project team included variables that potentially 

could influence the safety performance of SBL facilities 

and the bicycle exposure estimate. This supplemental 

information provided valuable insights into the 

operational characteristics of the facilities. 

ANALYSIS APPROACHES

The research team used the initial site characteristic 

information to develop exposure models for each site. 

Because the available count data ranged from long-term 

hourly to short-term daily, the exposure model was 

unique to each jurisdiction. The team also acquired 

crash data for all of the study site locations and merged 

them into a data file that ultimately included estimated 

bicycle counts, site data information, and crash history. 

The regression analysis focused on bicycle-involved 

crashes. Note that data for 2020 and 2021 were excluded 

from the CMF development efforts because those data 

were atypical. The team could not locate a dataset 

that included the date of implementation for each site, 

so they elected to use a cross-sectional analysis with 

propensity score weights.

The team developed regression equations to create 

CMFs for the following combinations:

• SBLs versus traditional bicycle lanes.

• SBLs versus buffered bicycle lanes.

• SBLs versus either traditional bicycle lanes 

or buffered bicycle lanes.

Ultimately, this combination of CMFs will enable a user 

to assess the benefits of deploying an SBL when the base 

condition is either a traditional bicycle lane or a buffered 

bicycle lane. This CMF development activity focused on 

Cambridge, San Francisco, and Seattle. Following CMF 

development, the team then assessed if the CMFs 

could be applied to Austin and Denver.

FINDINGS

The research team developed several regression 

models for Cambridge, San Francisco, and Seattle 

(both independently and with a merged dataset). 

Following that effort, the team used the data from 

Austin and Denver to validate the models. The Austin 

model performed quite well, but the Denver model 

appeared to underpredict bicycle crashes. The research 

team conducted an equivalency test and could not rule 

out that the CMFs for the different jurisdictions were 

not equivalent, so the models passed the validation 

test; however, the CMF for Denver conditions should 

be applied cautiously. The team was not completely 

sure about why these data differed, but Colorado has 

different weather patterns (particularly in the winter) 

and has a greater elevation than the other study 

sites. Table 2 summarizes the research finding.

The CMFs for SBLs show a clear trend that, with 

their implementation, a transportation agency can 

expect to see a reduction in bicycle crashes. The 

individual city models suffer from smaller sample 

sizes; however, they continue to result in estimated 

crash reductions consistent with those of larger sample 

sizes. The combination of data from different cities 

also results in similar trends and, for the most part, 

greater statistical significance. For baseline conditions, 

the use of traditional bicycle lanes, bicycle lanes with 

buffers but no vertical elements, or bicycle lanes with 

a combination of traditional and buffers resulted in 

generally similar trends. The SBL treatments that were 

the most effective included flexible delineator post 

treatments and treatments that were blended (most often 

flexible delineator posts and other vertical elements).

Table 1. Site information in database. (Continued)

DATA NEED TYPE OF DATA COLLECTED SITE 

DATA ELEMENTS

Exposure Supplemental data from agency 

where sites are located

Average daily traffic or peak-hour 

volumes for motor vehicles 

(passenger cars and trucks), 

bicycles, and pedestrians; land 

use and driveway types (as potential 

volume surrogates). The increase 

in bicyclists due to the placement 

of SBL facilities is also an important 

exposure consideration.
6

Table 2. CMFs for Bicycle Crashes (San Francisco, Seattle, and Cambridge).

CONDITION CMF ESTIMATE STANDARD 

ERROR ESTIMATE PROBABILITY VALUE SIGNIFICANCE

Flush buffera 1.128 0.121 0.173 0.484 —

Flexible 

delineator postsa 0.498 -0.698 0.264 0.008 **

Flexible 

delineator postsb 0.441 -0.819 0.297 0.006 **

Flexible 

delineator postsc 0.468 -0.758 0.267 0.005 **

Blendeda 0.822 -0.196 0.252 0.437 —

Blendedb 0.729 -0.316 0.300 0.292 —

Blendedc 0.774 -0.256 0.263 0.331 —

Flexible 

delineator postsd 0.605 -0.502 0.318 0.114 —

Flexible delineator 

posts or blendeda 0.640 -0.447 0.203 0.028 *

Flexible 

delineator posts 

or blendedb

0.567 -0.568 0.253 0.025 *

Flexible 

delineator posts 

or blendedc

0.602 -0.507 0.212 0.017 *

a

Base condition: Traditional bicycle lane.

b

Base condition: Flush buffered bicycle lane.

c

Base condition: Traditional or flush buffered bicycle lane.

d

Base condition: Blended vertical element.

*Statistically significant at the 0.05 level.

**Statistically significant at the 0.01 level.

***Statistically significant at the 0.001 level.

—Not statistically significant.
7

CONCLUSIONS

In addition to developing an SBL CMF for bicycle-involved 

crashes, this research identified multiple statistically 

significant factors that could influence bicycle operations 

and safety. In general, the analysis indicates the following:

• Bicycle crashes are more likely to occur at locations 

with mixed land use and less likely to occur at 

locations with industrial or public land use.

• Bicycle crashes occur less frequently at locations with 

more motor vehicle lanes. This observation could be 

an indicator of route choice by the bicyclist.

• Bicycle crashes occur less frequently at locations 

where parking is not permitted in at least one direction 

compared to locations without parking restrictions.

Table 3. Overview of significant variables in models.

SIGNIFICANCE LEVEL BEFORE CONDITION AFTER CONDITION CMF STANDARD 

ERROR ESTIMATE

0.01 Traditional 

bicycle lane.

SBL with flexible 

delineator posts. 0.498 0.173

0.01 Flush buffered 

bicycle lane.

SBL with flexible 

delineator posts. 0.441 0.297

0.01 Traditional or flush 

buffered bicycle lane.

SBL with flexible 

delineator posts. 0.468 0.267

0.05 Traditional 

bicycle lane.

SBL with blend of flexible 

delineator posts and 

other vertical elements.

0.640 0.203

0.05 Flush buffered 

bicycle lane.

SBL with blend of flexible 

delineator posts and 

other vertical elements.

0.567 0.253

0.05 Traditional or flush 

buffered bicycle lane.

SBL with blend of flexible 

delineator posts and 

other vertical elements.

0.602 0.212

The report documents exposure models and 

region-specific regression estimates. Collectively, 

the research yielded the summary of CMFs, 

based on a combined model, as shown in table 3. 

The use of flexible delineator posts consistently 

resulted in a decrease in total crashes. When 

flexible delineator posts are blended with another 

treatment, the crash reduction remains significant.
8

Researchers—This study was conducted by Principal Investigator Karen Dixon (ORCID: 0000-0002-8431-9304), 

Raul Avelar-Moran (ORCID: 0000-0002-3962-1758), and Maryam Mousavi Seyedeh (ORCID: 0000-0001-8188-

4466), of Texas A&M Transportation Institute under Contract No. HRDS30180007PRPR-DTFH6116D00039.

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 at https://highways.dot.gov/research.

Key Words—Separated bicycle lane, protected bicycle lane, crash modification factor

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 TechBrief 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.

Recommended citation: Federal Highway Administration, 

Developing Crash Modification Factors for Separated 

Bicycle Lanes (Washington, DC: 2023) 

FEBRUARY 2023 https://doi.org/10.21949/1521970

FHWA-HRT-23-025

HRSO-30/02-23(WEB)E

REFERENCES

1. National Highway Safety Administration. n.d. 

“Bicycle Safety” (webpage). https://www.nhtsa.

gov/road-safety/bicycle-safety, last accessed 

October 18, 2022.

2. Monsere, C., J. Dill, N. McNeil, K. Clifton, N. Foster, 

T. Goddard, M. Berkow, J. Gilpin, K. Voros, D. van 

Hengel, and J. Parks. 2014. Lessons from the Green 

Lanes: Evaluating Protected Bike Lanes in the U.S.

Report No. NITC-RR-583. Portland, OR: National 

Institute for Transportation and Communities. 

https://ppms.trec.pdx.edu/media/project_files/NITCRR-583_Executive_SummaryProtectedLanes.pdf, last 

accessed October 18, 2022.