U.S. Department of Commerce

Economics and Statistics Administration

U.S. CENSUS BUREAU

census.gov

Modes Less Traveled—Bicycling and Walking to 

Work in the United States: 2008–2012

American Community Survey Reports

By Brian McKenzie

Issued May 2014

ACS-25

Bicycling and walking make up a relatively small portion of commuting activity in the United States, but 

these nonmotorized travel modes play important roles 

within many of the nation’s local transportation systems. Infrastructure that supports bicycling and walking 

expands transportation options and may complement 

other forms of transportation by supplementing segments of trips. Several state and local agencies have 

taken steps to promote pedestrian and bicycle travel. 

Strategies to accommodate nonmotorized travel vary 

across communities, but may include sidewalk modifications, pedestrian-oriented commercial centers, or 

bicycle lanes to name a few. In recent years, the number 

of cities with bicycle sharing programs has increased 

considerably.1 These efforts reflect ongoing changes 

in infrastructure and travel options across the nation’s 

dynamic transportation systems. Such changes influence decisions people make about their trip to work. 

The American Community Survey (ACS) is an important 

tool for tracking how the nation’s travel patterns change 

across time and places.

Among other questions on work-related travel, the ACS 

asks respondents how they get to work. Respondents 

may choose from among several transportation modes, 

including bicycle or walked (Figure 1). The ACS commuting questions have served as the basis for several 

U.S. Census Bureau reports, but this is the first report 

to focus on bicycling or walking.2 This report provides 

a national overview of commuting by bicycle and 

1 Bicycle sharing programs include networks of bicycles available 

for short-term public use with designated pick-up and drop-off bicycle 

locations. 2 For more Census Bureau reports on specific commuting modes, 

see <www.census.gov/hhes/commuting/data/commuting.html>.

walking in the United States. It highlights differences 

in rates of nonmotorized travel for selected social and 

economic population characteristics and across geographic areas.3 The report uses the 5-year 2008–2012 

ACS data to take advantage of its large sample size 

relative to the 1-year data, thus reducing margins of 

error of estimates for small subpopulations.4

3 All comparisons presented in this report have taken sampling 

error into account and are significant at the 90 percent confidence level 

unless otherwise noted. 4 The analysis is limited to workers 16 years and over who worked 

during the ACS reference week, the calendar week preceding the date 

respondents completed their questionnaire, and who did not work at 

home.

Figure 1. 

2012 American Community Survey 

Questionnaire

Source: U.S. Census Bureau, 2012 American Community Survey

Questionnaire.

31 How did this person usually get to work LAST 

WEEK? If this person usually used more than one 

method of transportation during the trip, mark (X) 

the box of the one used for most of the distance. 

Car, truck, or van 

Bus or trolley bus 

Streetcar or trolley car 

Subway or elevated 

Railroad 

Ferryboat 

Taxicab 

Motorcycle 

Bicycle 

Walked 

Worked at 

home ➔ SKIP 

to question 39a 

Other method 
2 U.S. Census Bureau

HIGHLIGHTS

• The number of U.S. workers

who traveled to work by bicycle

increased from about 488,000

in 2000 to about 786,000 in

2008–2012, a larger percentage

increase than that of any other

commuting mode.

• The combined rate of bicycle

commuting for the 50 largest

U.S. cities increased from 0.6

percent in 2000 to 1.0 percent

in 2008–2012.

• The Northeast showed the highest rate of walking to work at

4.7 percent of workers, while

the West had the highest rate of

biking to work at 1.1 percent.

The South had the lowest rate of

biking and walking to work.

• Among large cities, Portland,

OR, has the highest bicycle commuting rate at 6.1 percent.

• Workers	living	in	principal	cities

walked to work at a rate of 4.3

percent, compared with 2.4

percent for workers in suburbs.

• Several “college towns”

showed high rates of walking

to work, including Ithaca, NY,

and Athens, OH, where about

42.0 percent and 37.0 percent

of workers walked to work,

respectively.

• Younger workers,those aged 16

to 24, had the highest rate of

walking to work at 6.8 percent.

• At 0.8 percent, the rate of

bicycle commuting for men

was more than double that of

women at 0.3 percent.

• At 0.9 percent, the most educated workers, those with a

graduate or professional degree,

had the highest rate of bicycle

commuting, followed by the

least educated workers, those

who did not graduate from high

school at 0.7 percent.

• Workers who walked to work

had an average commute time

of 11.5 minutes, considerably

shorter than that of bicycle commuters at 19.3 minutes, and all

other workers who did not work

at home at about 25.9 minutes.

The ACS is a survey conducted 

annually by the Census Bureau to 

gather information about changes 

in the socioeconomic, housing, 

and demographic characteristics 

of communities across the United 

States and Puerto Rico.5 It provides 

one of the most robust sources 

of information on commuting by 

bicycle and walking. ACS questions 

related to travel focus solely on 

commuting and do not ask about 

leisure travel or other nonwork 

trips. Commutes may involve 

multiple transportation modes, but 

ACS respondents are restricted to 

indicating the single mode used for 

the longest distance. 

5 Estimates for Puerto Rico are not

included in this report. 

Information on nonmotorized travel 

is limited relative to that of travel 

by automobile or transit. This presents challenges for transportation 

planners and researchers interested 

in gaining a better understanding 

of bicycle and pedestrian travel 

behavior and demand.6 Analysis 

of trends in commuting by bicycle 

and walking is complicated by the 

relatively low prevalence of these 

modes, creating issues related 

to small sample size. Because 

bicycling and walking often serve 

as secondary travel modes that 

supplement modes such as transit 

or driving, some commutes that 

involve bicycling and walking are 

not reflected as such in the ACS 

because another mode is used for a 

longer distance. 

6 Greg Griffin, Krista Nordback, Thomas 

Götschi, Elizabeth Stolz, and Sirisha Kothuri, 

“Monitoring Bicyclist and Pedestrian Travel

and Behavior, Current Research and Practice,”

Transportation Research Board, Washington, 

DC, 2014. Please see <http://onlinepubs.trb

.org/onlinepubs/circulars/ec183.pdf>.

DEFINITIONS

Nonmotorized travel refers to travel by bicycle and walking. 

Workers are civilians and members of the Armed Forces, 16 years 

and older, who were at work the previous week. Persons on vacation

or not at work the prior week are not included.

Means of transportation to work refers to the principal mode of 

travel that the worker usually used to get from home to work during 

the reference week. People who used different means of transportation on different days of the week were asked to specify the one they 

used most often. People who used more than one means of transportation to get to work each day were asked to report the one used for 

the longest distance during the work trip. Workers who worked at 

home are not included in information presented in this report unless 

otherwise stated. 

The largest city in each metropolitan or micropolitan statistical area 

is designated a principal city. Additional cities qualify if specific 

requirements are met concerning population size and employment. 

For more detailed definitions of these terms and other ACS terms, 

see the ACS subject definitions list at <www.census.gov/acs/www

/data_documentation/documentation_main/>.
U.S. Census Bureau 3

As bicycling and walking become 

integral to the national conversation about transportation, demand 

for data related to nonmotorized 

travel will increase. Initiatives to 

integrate bicycle and pedestrianoriented infrastructure into local 

transportation systems are far from 

uniform across cities and regions. 

Rates of bicycling and walking to 

work also vary considerably across 

geographies. Though not without 

limitations, the size and geographic 

reach of the ACS make it a valuable 

source of information on nonmotorized travel.

NATIONAL TRENDS 

IN NONMOTORIZED 

COMMUTING

Much of the developed landscape 

in the United States was designed 

to accommodate automobile travel, 

complicating travel by walking 

or bicycling in many areas. The 

2008–2012 5-year ACS data show 

that, among the approximately 140 

million workers in the United States 

during that period, 2.8 percent 

walked to work and 0.6 percent 

commuted by bicycle, compared 

with 86.2 percent of workers who 

drove alone or carpooled to work 

(Figure 2). Between 2000 and 

2008–2012, the number of workers who traveled to work by bicycle 

increased by 60.8 percent, from 

about 488,000 in 2000 to about 

786,000.7 This increase in the number of bicycle commuters exceeded 

the percentage increase of all other 

travel modes during that period 

(not shown), but the overall share 

of workers who commute by bicycle 

remains low. In 1980, 0.5 percent 

of workers commuted by bicycle. 

This rate dropped to 0.4 percent in 

1990, where it remained in 2000.8

7 Source: U.S. Census Bureau, American

Community Survey, 2008–2012, Table B08006. 8 Rates of bicycle commuting for 1980, 

1990, and 2000, are not statistically different 

from one another.

By 2008–2012, the share of bicycle 

commuters reached 0.6 percent.

Between 1980 and 1990, the rate 

of walking to work declined from 

5.6 percent to 3.9 percent, and 

continued to decline over the 

1990s, reaching 2.9 percent in 

2000 (Figure 3). The rate of decline 

slowed during the 2000s, reaching 2.8 percent by 2008–2012.9

Although the share of workers 

who walked to work declined 

slightly over the 2000s, the number of walkers increased from 

9 Rates of walking to work for 2000 and 

2008–2012 are not statistically different from 

one another.

Figure 2. 

How People Commute to Work: 2008–2012

(In percent. Data based on sample. For information on confidentiality 

protection, sampling error, nonsampling error, and definitions, see 

www.census.gov/acs/www/)

Source: U.S. Census Bureau, American Community Survey, 2008–2012.

86.2

5.0

4.3

0.6

2.8

Other means 1.2

Walk

Bicycle

Work at home

Public transportation

Car, truck, or van

Figure 3. 

Walking and Bicycling to Work: 1980 to 2008–2012

(Data based on sample. For information on confidentiality protection, 

sampling error, nonsampling error, and definitions, see 

www.census.gov/acs/www/)

Sources: U.S. Census Bureau, Decennial Census, 1980, 1990, 2000; American 

Community Survey, 2008–2012.

Percent

2.8 2.9

3.9

5.6

0.5 0.4 0.4 0.6

Bicycle

Walk

0

1

2

3

4

5

6

2008–2012

ACS

2000 

Census

1990 

Census

1980 

Census
4 U.S. Census Bureau

about 3,759,000 in 2000 to about 

3,938,000 in 2008–2012. When 

comparing decennial Census estimates with those from the 

ACS, it is important to note that 

decennial Census data were collected primarily during a single 

month, April, while ACS data are 

collected continuously throughout 

the year. The timing of data collection might influence many workers’ 

likelihood of walking or riding a 

bicycle to work, especially in more 

severe climates. 

WALKING AND BICYCLE 

COMMUTING ACROSS REGIONS 

AND TYPES OF COMMUNITIES

Rates of walking and bicycle commuting vary considerably across 

communities and regions. Local 

factors such as community size, 

design, infrastructure, and climate 

influence the availability, attractiveness, and affordability of each 

transportation mode. For example, 

in smaller cities, a greater percentage of the area’s potential destinations are likely to be within biking 

or walking distance and automobile 

traffic might be relatively light, 

increasing the attractiveness of 

nonmotorized travel.10 Cities with 

large, dense populations are more 

likely to offer public transportation, 

making bicycling and walking more 

attractive as travel modes that 

supplement transit. 

Figures 4 and 511 show rates of 

nonmotorized commuting by 

region and population of workers’ place of residence.12 For 

Figures 4 and 5, small cities are 

defined as those with populations between 20,000 and 99,999, 

10 Susan Handy, Eva Heinen, and Kevin J.

Krizek, “Cycling in Small Cities,” in City 

Cycling, edited by John Pucher and Ralph

Buehler, 2012; 257–286. 11 For estimates and margins of error associated with Figures 4 and 5, see Appendix 

Table A-1. 12 For more information on regions, 

see <www.census.gov/popest/about/geo

/terms.html>.

Figure 4. 

Walking to Work by Region and City Size: 

2008–2012

(Data based on sample. For information on confidentiality protection, 

sampling error, nonsampling error, and definitions, see 

www.census.gov/acs/www/)

Source: U.S. Census Bureau, American Community Survey, 2008–2012.

Total

Small cities

Medium cities

Large cities

Percent

0

2

4

6

8

10

12

Northeast South Midwest West

Figure 5. 

Bicycling to Work by Region and City Size: 

2008–2012

(Data based on sample. For information on confidentiality protection, 

sampling error, nonsampling error, and definitions, see 

www.census.gov/acs/www/)

Source: U.S. Census Bureau, American Community Survey, 2008–2012.

Total

Small cities

Medium cities

Large cities

Percent

0

1

2

3

4

Northeast South Midwest West
U.S. Census Bureau 5

medium-sized cities as those with 

populations between 100,000 and 

199,999, and larger cities as those 

of 200,000 people or greater.13

Although ACS data are collected 

continuously throughout the year, 

data for specific segments of the 

year are not differentiated due to 

data weighting concerns. If this 

were possible, regional variation 

in rates of nonmotorized travel 

might be evident across seasons. 

The Northeast showed the highest rates of walking to work at 

4.7 percent, while the West had 

the highest rate of biking to work 

at 1.1 percent, about four times 

higher than that of the South. In 

large Northeastern cities, about 1 

in 10 workers walked. The South 

had the lowest rates of walking to 

work for all place size categories. 

Bicycle commuting was highest 

in large Western cities, where 1.4 

percent of workers biked to work. 

Within each region, walking was 

more prevalent in large cities than 

small or medium-sized cities. 

Within regions and metropolitan 

areas, the likelihood of walking 

or bicycling to work varies across 

community types such as cities or 

“suburbs.”14 Downtown areas within 

cities accommodate high population 

and worker densities, particularly 

during typical business hours. Cities 

respond to the challenge of accommodating a large number of people 

traveling to, from, and within their 

boundaries with varied strategies, 

but walkability is a common concern. Figure 6 shows that rates of 

walking to work are highest for 

workers living in a principal city 

within a metropolitan area at 4.3 

percent, compared with 2.4 percent 

for workers in suburbs (those living 

in a metropolitan area, but outside 

13 Population thresholds based on 2012

ACS population estimates. 14 For this report, the term “city” refers to

a principal city within a metropolitan area and 

“suburb” refers to areas within a metropolitan

area but outside of a central city. 

of a principal city), and 1.9 percent 

outside of metropolitan areas. 

Workers in principal cities also had 

a high rate of bicycle commuting at 

1.0 percent, compared to 0.4 percent for suburban workers or those 

who lived outside of a metropolitan area. In recent years, several 

large cities such as New York and 

Washington, DC, have invested 

in programs and infrastructure 

to support bicycle usage. To the 

extent that principal cities tend to 

be large compared with others in 

the same metropolitan area, the 

high rate of nonmotorized travel in 

principal cities is consistent with 

that observed for large places. 

RATES OF WALKING AND 

BICYCLE COMMUTING ACROSS 

PLACES

Population and infrastructure

characteristics that foster high 

rates of nonmotorized travel tend 

to be spatially concentrated, often 

contributing to considerable differences in travel patterns across 

cities and neighborhoods within 

the same metropolitan area. For 

example, 4.1 percent of workers 

in the city of Minneapolis commuted by bicycle, compared with 

only 0.9 percent for workers in the 

Minneapolis-St. Paul-Bloomington,

MN-WI, metropolitan area. Similarly, 

12.1 percent of District of Columbia 

workers walked to work, compared with only 3.2 percent of the 

Washington-Arlington-Alexandria, 

DC-VA-MD-WV, metro area.15 For 

several regions, comparatively low 

rates of nonmotorized travel within 

surrounding suburbs contribute to 

lower overall nonmotorized commuting rates for the metropolitan 

area than for the central city. Still, 

numerous smaller places have 

higher rates of walking or bicycling 

15 For more information on commuting by 

bicycle and walking in metropolitan areas, see 

American Community Survey Table S0801, 

2008–2012 ACS on American Factfinder at 

<www.Factfinder2.census.gov>.

Figure 6. 

Walking and Bicycling to Work by Residence 

Community Type: 2008–2012

(Data based on sample. For information on confidentiality protection, 

sampling error, nonsampling error, and definitions, see 

www.census.gov/acs/www/)

Source: U.S. Census Bureau, American Community Survey, 2008–2012.

Walk

Bicycle

City

Percent

Suburb Outside metro area

0

1

2

3

4

5
6 U.S. Census Bureau

than their larger principal city counterpart within the same metropolitan area. For example, Davis, CA, 

has a bicycle commuting rate of 

18.6 percent, but Sacramento, the 

largest city within the same metropolitan area, has a bicycle commuting rate of 2.5 percent. 

Across the nation’s largest cities, 

growth in commuting by bicycle 

outpaced that of walking during 

the 2000s. Table 1 lists biking and 

walking commuting rates for the 

50 largest U.S. cities, sorted by 

population size. The combined rate 

of bicycle commuting for the 50 

cities increased from 0.6 percent in 

2000 to 1.0 percent in 2008–2012. 

The combined rate of walking did 

not change significantly, which is 

notable given that the national rate 

of walking to work declined slightly 

over the 2000s. Twenty-four cities 

on the list experienced a significant 

change in the rate of walking to 

work between 2000 and 2008–

2012 (Table 1), 15 of which 

showed a decline in walking to 

work. Boston had the highest rate 

of walking to work in 2008–2012 at 

15.1 percent, up from 13.0 percent 

in 2000. Washington, DC, follows 

Boston at 12.1 percent. Among 

cities that experienced a significant change, more cities declined 

in their rate of walking to work 

than increased across the 2000s, 

while changes in bicycle commuting rates showed almost universal 

increases. Among the 29 cities that 

experienced a significant change, 

only two—Phoenix, AZ, and Mesa,

AZ—declined in their rate of bicycle

commuting. 

Some of the nation’s largest cities, such as Chicago, IL, more 

than doubled their rate of bicycle 

commuting between 2000 and 

2008–2012, although bicycle commuting rates remain low relative 

to other travel modes. Among 

large cities, Portland, OR, stands

out for its relatively high bicycle 

commuting rate of 6.1 percent in 

2008–2012, but also for its notable 

increase in bicycle commuting 

since 2000, when it was at 1.8 

percent. Minneapolis is also notable 

in this respect, increasing from 1.9 

percent in 2000 to 4.1 percent in 

2008–2012. Five cities on the list 

had bicycle commuting rates of at 

least 3.0 percent in 2008–2012,16

while no city reached 3.0 percent 

in 2000. Although several cities 

showed increases in their rates 

of bicycle commuting over the 

decade, in 2008–2012, the rate of 

walking exceeded that of bicycle 

commuting in every city except 

Portland, OR.17

WALKING AND BICYCLE 

COMMUTING RATE 

COMPARISON BY CITY SIZE

Table 2 lists 15 places among 

those with the highest walking and 

bicycle commuting rates for each 

of three population size categories 

presented previously. Due to small 

sample sizes of nonmotorized 

travel and large margins of error 

associated with them, the lowest 

population category is restricted to 

places with populations of at least 

20,000.18 Margins of error for some 

areas are still relatively high and 

readers should consider this when 

making comparisons.19

Davis, CA, and Key West, FL, 

stand out as having high bicycle 

16 The bicycle commuting rate for 

Washington, DC, was not significantly 

different than 3.0 percent. 17 For Portland, OR, the rates of walking

and bicycle commuting in 2008–2012 were 

not statistically different from one another. 18 For a complete list of rates of 

commuting by bicycle and walking for places 

within the population thresholds specified in 

Table 2, see Supplemental Tables 1 through 6 

at <www.census.gov/hhes/commuting/data

/commuting.html> or visit ACS Table S0801 

on American Factfinder, which includes 

estimates for all places, including those of 

fewer than 20,000 people. 19 Estimates from the 5-year ACS 

sample might differ from those of the 

most recent 2012 single-year ACS data 

available on American FactFinder at 

<www.Factfinder2.census.gov>.

commuting rates among places 

with populations of 20,000 or 

larger at 18.6 percent and 17.4 

percent of workers, respectively. 

Most of the top biking cities listed 

are in the Pacific or Mountain

divisions. Many of them are also 

“college towns,” or home to at least

one large college or university. 

Portland, OR, has the highest rate

of bicycle commuting among large 

places at 6.1 percent. Portland is

among cities such as Washington, 

DC, Minneapolis, MN, Denver, CO, 

and Madison, WI, that have made 

infrastructure investments aimed 

at achieving more bicycle-friendly 

landscapes. 

Ithaca, NY, had the highest rate of 

walking at 42.4 percent of workers, although its rate was not 

statistically different from that 

of Athens, OH. Ithaca is among 

several places with a significant 

university or college presence. 

This is particularly relevant to the 

small and medium-sized cities 

listed such as Athens, OH, State 

College, PA, Boulder, CO, and

Cambridge, MA, where students 

and others associated with educational institutions make up a large 

percentage of the total population. 

Across all place size categories, 

relatively few places in the South 

are listed among those with high 

rates of walking. Among larger 

places, Boston had the highest rate 

of walking to work at 15.1 percent, 

followed by Washington, DC,

and Pittsburgh, PA at 12.1 and

11.3 percent, respectively. Among 

large cities with high walking 

rates, several also have high rates 

of transit commuting (not shown). 

This reflects the complimentary 

relationship between transit and 

walkable neighborhoods.20

20 Jeff Speck, “Walkable Cities: How

Downtown Can Save America, One Step at a 

Time,” North Point Press, New York, 2013.
U.S. Census Bureau 7

WALKING AND BICYCLE 

COMMUTING ACROSS STATES

Mapping state-level rates of commuting by bicycle and walking 

illuminates broad regional patterns 

that might go undetected from 

city-level data (Figure 7 and Figure 

8). States with relatively high rates 

of bicycle commuting are largely 

concentrated in the West, with 

exceptions such as the District of 

Columbia. Oregon, for example, 

has a bicycle commuting rate of 

2.3 percent, and the District of 

Columbia has a rate of 3.1 percent, 

higher than any state.21 The five 

states with bicycle commuting 

rates lower than 0.2 percent are 

in the South, including Arkansas, 

Alabama, Mississippi, Tennessee, 

and West Virginia. Geographic patterns are also apparent across rates 

of walking to work. States with the 

lowest rates of walking to work 

make up a distinct cluster spanning much of the South. Alabama 

has the lowest rate of walking to 

work at 1.2 percent, followed by 

Tennessee at 1.3 percent. In two 

states, Alaska and New York, at 

least 6.0 percent of workers walked 

to work. The District of Columbia 

also fell into this category, with 

a walking rate of 12.1 percent of 

workers, higher than any state. 

WALKING AND BICYCLE 

COMMUTING RATES ACROSS 

SOCIAL AND ECONOMIC 

CHARACTERISTICS

Just as nonmotorized rates of 

commuting vary across places 

and regions, they also vary across 

population characteristics such as 

age, sex, race, and income. The 

rate of nonmotorized commuting 

by a particular population group 

21 For rates of commuting by bicycle 

and walking for states, see American 

Community Survey Table S0801, 

2008–2012 ACS on American Factfinder at 

<www.Factfinder2.census.gov>.

to some extent may reflect travel 

preferences, but it is also influenced by group differences in factors such as financial constraints, 

region of residence, household 

location within a city, physical 

ability, or the presence of children 

within a household. Disentangling 

the independent effects of each 

population characteristic on travel 

mode choice is beyond the scope 

of this report. For all workers, Table 

3 compares rates of commuting 

by bicycle, walking, and all other 

modes of travel combined for 

several population characteristics. 

Although biking and walking rates 

vary by social and economic characteristics, rates of nonmotorized 

travel are uniformly low, relative to 

other forms of commuting. 

Age, Sex, Race, and Ethnicity

Younger workers had relatively 

high rates of nonmotorized commuting compared with their older 

counterparts (Figure 9). The highest 

rate of bicycle commuting occurred 

for workers between 16 and 24 

years of age at 1.0 percent. As each 

subsequent category increased 

in age range, the rate of bicycle 

commuting declined. Workers ages 

55 years and older showed the 

lowest rate of bicycle commuting 

at 0.3 percent. The decline in the 

prevalence of bicycle commuting 

with increased age may be linked 

to factors such as workers’ physical 

abilities, residential location, and 

income. At 6.8 percent, workers in 

the youngest age category—aged 

16 to 24—had the highest rate of 

walking to work. This rate sharply 

declined to 3.1 percent for workers 

in the next oldest age category and 

remained lower than 3.0 percent 

for all subsequent categories.

In the United States, men walked to 

work at a rate of 2.9 percent, compared to 2.8 percent for women. 

Differences in bicycle commuting 

rates between men and women 

were sharper than walking rates. 

At 0.8 percent, the rate of bicycle 

commuting for men was more than 

double that of women at 0.3 percent. Such stark differences in the 

rates of bicycle commuting between 

men and women are also found in 

other countries with relatively low 

overall rates of bicycle usage, such 

as Canada and Australia.22

Black workers had the lowest rate

of bicycle commuting at 0.3 percent, and those who identified as 

Some other race or Two or more 

races and Hispanic workers had 

the highest rates of bicycle commuting at 0.8 percent and 0.7 

percent, respectively (Figure 10).23

Workers who identified as Some 

other race or Two or more races 

had the highest rates of walking 

at 4.2 percent, while those who 

identified as White had the lowest 

walking rate at 2.6 percent.

HOUSEHOLD INCOME 

Rates of nonmotorized travel 

generally declined as household 

income increased, with some 

exceptions (Figure 11). Workers 

living in households making less 

than $10,000 biked to work at a 

22 John Pucher and Ralph Buehler,

“International Overview: Cycling Trends in

Western Europe, North America, and 

Australia,” in City Cycling, edited by John 

Pucher and Ralph Buehler, 2012; 9–30. 23 Federal surveys now give respondents 

the option of reporting more than one race. 

Therefore, two basic ways of defining a race 

group are possible. A group such as Asian 

may be defined as those who reported Asian 

and no other race (the race-alone or singlerace concept) or as those who reported Asian 

regardless of whether they also reported 

another race (the race-alone or in-combination 

concept). This report shows data using the 

first approach (race alone). Use of the singlerace population does not imply that it is the 

preferred method of presenting or analyzing 

data. The Census Bureau uses a variety of 

approaches. For further information, see 

the Census 2000 Brief Overview of Race and 

Hispanic Origin: 2000 (C2KBR/01-1) at 

<www.census.gov/population/www/cen2000

/briefs.html>.
8 U.S. Census Bureau

Table 1.

Rates of Walking and Bicycling to Work for the Nation’s 50 Largest Cities:

Census 2000 and American Community Survey 2008–2012

(For information on confidentiality protection, sampling error, and definitions, see www.census.gov/acs/www/Downloads 

/data_documentation/ Accuracy/ACS_Accuracy_of_Data_2012.pdf)

Rank

City

Total workers 

(all modes) Percent walked Percent bicycled 

Census 

2000

ACS 

2008–2012

Census 

2000

ACS 

2008–2012

Direction 

of change

Census 

2000

ACS 

2008–2012

Direction 

of change

1

2

3

4

5

6

7

8

9

10

11

12

13

14

15

16

17

18

19

20

21

22

23

24

25

26

27

28

29

30

31

32

33

34

35

36

37

38

39

40

41

42

43

44

45

46

47

48

49

50

 Total for 50 largest cities . . .

New York, NY . . . . . . . . . . . . . . . . .

Los Angeles, CA . . . . . . . . . . . . . .

Chicago, IL . . . . . . . . . . . . . . . . . .

Houston, TX . . . . . . . . . . . . . . . . . .

Philadelphia, PA . . . . . . . . . . . . . . .

Phoenix, AZ . . . . . . . . . . . . . . . . . .

San Antonio, TX . . . . . . . . . . . . . . .

San Diego, CA . . . . . . . . . . . . . . . .

Dallas, TX . . . . . . . . . . . . . . . . . . .

San Jose , CA . . . . . . . . . . . . . . . .

Austin, TX . . . . . . . . . . . . . . . . . . .

Jacksonville, FL . . . . . . . . . . . . . . .

Indianapolis, IN . . . . . . . . . . . . . . .

San Francisco, CA . . . . . . . . . . . . .

Columbus, OH . . . . . . . . . . . . . . . .

Fort Worth, TX . . . . . . . . . . . . . . . .

Charlotte, NC . . . . . . . . . . . . . . . . .

Detroit, MI . . . . . . . . . . . . . . . . . . .

El Paso, TX . . . . . . . . . . . . . . . . . .

Memphis, TN . . . . . . . . . . . . . . . . .

Boston, MA . . . . . . . . . . . . . . . . . .

Seattle, WA . . . . . . . . . . . . . . . . . .

Denver, CO . . . . . . . . . . . . . . . . . .

Washington, DC . . . . . . . . . . . . . . .

Nashville, TN . . . . . . . . . . . . . . . . .

Baltimore, MD . . . . . . . . . . . . . . . .

Louisville, KY . . . . . . . . . . . . . . . . .

Portland, OR . . . . . . . . . . . . . . . . .

Oklahoma City, OK . . . . . . . . . . . .

Milwaukee, WI . . . . . . . . . . . . . . . .

Las Vegas, NV . . . . . . . . . . . . . . . .

Albuquerque, NM . . . . . . . . . . . . . .

Tucson, AZ . . . . . . . . . . . . . . . . . . .

Fresno, CA . . . . . . . . . . . . . . . . . . .

Sacramento, CA . . . . . . . . . . . . . .

Long Beach, CA . . . . . . . . . . . . . .

Kansas City, MO . . . . . . . . . . . . . .

Mesa, AZ . . . . . . . . . . . . . . . . . . . .

Virginia Beach, VA . . . . . . . . . . . . .

Atlanta, GA . . . . . . . . . . . . . . . . . .

Colorado Springs, CO . . . . . . . . . .

Raleigh, NC . . . . . . . . . . . . . . . . . .

Omaha, NE . . . . . . . . . . . . . . . . . .

Miami, FL . . . . . . . . . . . . . . . . . . . .

Oakland, CA . . . . . . . . . . . . . . . . .

Tulsa, OK . . . . . . . . . . . . . . . . . . . .

Minneapolis, MN . . . . . . . . . . . . . .

Cleveland, OH . . . . . . . . . . . . . . . .

Wichita, KS . . . . . . . . . . . . . . . . . .

Arlington, TX . . . . . . . . . . . . . . . . .

19,320,642

3,192,070

1,494,895

1,192,139

841,686

569,761

599,592

491,435

580,318

537,006

427,984

353,109

350,458

385,208

418,553

367,387

235,799

280,528

319,449

208,101

274,934

278,463

316,493

278,715

260,884

274,028

249,373

110,930

270,996

234,222

249,889

210,806

215,222

216,314

156,569

166,419

184,479

208,554

182,582

222,648

178,970

183,806

151,655

196,801

126,539

170,503

187,612

203,951

175,727

164,725

172,355

21,563,097

3,685,786

1,745,818

1,213,901

988,261

601,331

648,328

598,236

635,805

557,672

442,728

428,445

382,986

378,820

439,726

388,186

332,892

364,855

209,600

267,531

272,054

317,930

350,673

311,360

306,336

299,021

265,053

270,657

298,389

277,957

253,783

257,665

257,389

225,987

183,813

197,486

207,072

219,966

193,281

230,566

198,677

199,043

204,399

206,463

175,513

178,694

183,576

204,885

146,263

179,294

178,945

4 .9

10 .4

3 .6

5 .7

2 .3

9 .1

2 .2

2 .2

3 .6

1 .9

1 .4

2 .5

1 .8

2 .0

9 .4

3 .2

1 .7

1 .5

2 .8

2 .0

1 .9

13 .0

7 .4

4 .3

11 .8

2 .4

7 .1

4 .1

5 .2

1 .6

4 .7

2 .2

2 .7

3 .4

2 .1

2 .8

2 .5

2 .3

2 .1

2 .0

3 .5

2 .5

2 .9

2 .4

3 .7

3 .7

2 .2

6 .6

4 .0

1 .4

1 .6

5 .0

10 .3

3 .7

*6 .4

*2 .1

*8 .6

*1 .8

*2 .0

*2 .9

*1 .8

*1 .8

2 .5

*1 .4

2 .0

9 .9

*2 .8

*1 .2

2 .1

3 .1

1 .9

1 .9

*15 .1

*9 .1

4 .4

12 .1

*1 .9

6 .5

*2 .2

5 .7

1 .6

5 .0

1 .9

*2 .0

3 .6

1 .9

*3 .2

2 .8

2 .1

*1 .6

2 .2

*4 .7

2 .6

*2 .1

*2 .8

3 .9

4 .2

2 .0

6 .4

*4 .8

1 .3

1 .8















































0 .6

0 .5

0 .6

0 .5

0 .5

0 .9

0 .9

0 .2

0 .7

0 .1

0 .6

0 .9

0 .4

0 .2

2 .0

0 .3

0 .1

0 .1

0 .2

0 .1

0 .1

1 .0

1 .9

1 .0

1 .2

0 .1

0 .3

0 .4

1 .8

0 .1

0 .3

0 .4

1 .1

2 .2

0 .8

1 .4

0 .7

0 .1

1 .2

0 .3

0 .3

0 .5

0 .3

0 .1

0 .6

1 .2

0 .2

1 .9

0 .2

0 .2

0 .2

*1 .0

*0 .8

*1 .0

*1 .3

0 .4

*2 .0

*0 .7

0 .2

*0 .9

0 .1

*0 .9

*1 .5

0 .4

*0 .4

*3 .4

*0 .7

0 .1

0 .2

0 .3

0 .2

0 .2

*1 .7

*3 .4

*2 .3

*3 .1

*0 .3

*0 .8

0 .4

*6 .1

0 .2

*0 .8

0 .4

1 .3

2 .4

0 .8

*2 .5

*1 .1

*0 .3

*0 .9

*0 .7

*0 .8

0 .5

0 .6

0 .2

0 .7

*2 .4

*0 .4

*4 .1

*0 .6

0 .3

0 .2





























































* Denotes a statistically significant change since 2000 .

Denotes a statistically significant increase between estimates .

Denotes a statistically significant decrease between estimates .

Notes: “Largest” refers to the size of the population . Population thresholds are based on 2012 Population Estimates . Margins of error for American Community 

Survey estimates in this table are available at <www .Factfinder2 .census .gov> .

Sources: U .S . Census Bureau, American Community Survey 2008–2012, Tables S0801 and B08006, available on American Factfinder at 

<www .Factfinder2 .census .gov> .
U.S. Census Bureau 9

Table 2.

Rates of Walking and Bicycling to Work by City Size: 2008–2012

(For information on confidentiality protection, sampling error, and definitions, see www.census.gov/acs/www/Downloads 

/data_documentation/ Accuracy/ACS_Accuracy_of_Data_2012.pdf)

Small Cities (Population of 20,000–99,999)

Walk Bicycle

Rank City Percent	

Margin of 

error (±)

1 City Percent	

Margin of 

error (±)

1

1

2

3

4

5

6

7

8

9

10

11

12

13

14

15

Ithaca, NY . . . . . . . . . . . . . . . . . . .

Athens, OH . . . . . . . . . . . . . . . . . .

State College, PA . . . . . . . . . . . . . .

North Chicago, IL . . . . . . . . . . . . . .

Kiryas Joel, NY . . . . . . . . . . . . . . .

Oxford, OH . . . . . . . . . . . . . . . . . .

Pullman, WA . . . . . . . . . . . . . . . . .

East Lansing, MI . . . . . . . . . . . . . .

College Park, MD . . . . . . . . . . . . .

Burlington, VT . . . . . . . . . . . . . . . .

Moscow, ID . . . . . . . . . . . . . . . . . .

Morgantown, WV . . . . . . . . . . . . . .

Rexburg, ID . . . . . . . . . . . . . . . . . .

Atlantic City, NJ . . . . . . . . . . . . . . .

Urbana, IL . . . . . . . . . . . . . . . . . . .

42 .4

36 .8

36 .2

32 .2

31 .6

29 .7

23 .5

23 .3

21 .5

20 .3

20 .2

18 .2

18 .0

17 .8

16 .6

3 .8

5 .4

3 .2

4 .2

4 .2

3 .8

3 .2

2 .2

3 .2

1 .9

3 .6

2 .9

3 .7

2 .7

2 .3

Davis, CA . . . . . . . . . . . . . . . . . . . .

Key West, FL . . . . . . . . . . . . . . . . .

Corvallis, OR . . . . . . . . . . . . . . . . .

Santa Cruz, CA . . . . . . . . . . . . . . .

Palo Alto, CA . . . . . . . . . . . . . . . . .

Menlo Park, CA . . . . . . . . . . . . . . .

East Lansing, MI . . . . . . . . . . . . . .

Laramie, WY . . . . . . . . . . . . . . . . .

San Luis Obispo, CA . . . . . . . . . . .

Ashland, OR . . . . . . . . . . . . . . . . .

Missoula, MT . . . . . . . . . . . . . . . . .

Chico, CA . . . . . . . . . . . . . . . . . . .

Santa Barbara, CA . . . . . . . . . . . .

Bozeman, MT . . . . . . . . . . . . . . . .

Urbana, IL . . . . . . . . . . . . . . . . . . .

18 .6

17 .4

11 .2

9 .2

8 .5

7 .6

6 .8

6 .8

6 .6

6 .2

6 .2

5 .8

5 .8

5 .8

5 .8

1 .8

2 .9

1 .5

1 .7

1 .1

1 .6

1 .2

1 .8

1 .3

1 .9

0 .9

1 .0

1 .1

1 .2

1 .2

Medium-Sized Cities (Population of 100,000–199,999)

Walk Bicycle

Rank City Percent 

Margin of 

 error (±)

1 City Percent 

Margin of 

error (±)

1

1

2

3

4

5

6

7

8

9

10

11

12

13

14

15

Cambridge, MA .

Berkeley, CA . . .

Ann Arbor, MI . . . 

Provo, UT . . . . . .

New Haven, CT .

Columbia, SC . .

Providence, RI . .

Syracuse, NY . . .

Boulder, CO . . . .

Hartford, CT . . . .

Dayton, OH . . . .

Eugene, OR . . . .

Elizabeth, NJ . . .

Columbia, MO . .

Wichita Falls, TX

 .

 .

 . 

 .

 .

 .

 .

 .

 .

 .

 .

 .

 .

 .

 .

 .

 .

 . 

 .

 .

 .

 .

 .

 .

 .

 .

 .

 .

 .

 .

 .

 .

 . 

 .

 .

 .

 .

 .

 .

 .

 .

 .

 .

 .

 .

 .

 .

 . 

 .

 .

 .

 .

 .

 .

 .

 .

 .

 .

 .

 .

 .

 .

 . 

 .

 .

 .

 .

 .

 .

 .

 .

 .

 .

 .

 .

 .

 .

 . 

 .

 .

 .

 .

 .

 .

 .

 .

 .

 .

 .

 .

 .

 .

 . 

 .

 .

 .

 .

 .

 .

 .

 .

 .

 .

 .

 .

 .

 .

 . 

 .

 .

 .

 .

 .

 .

 .

 .

 .

 .

 .

 .

 .

 .

 . 

 .

 .

 .

 .

 .

 .

 .

 .

 .

 .

 .

 .

 .

 .

 . 

 .

 .

 .

 .

 .

 .

 .

 .

 .

 .

 .

 .

 .

 .

 . 

 .

 .

 .

 .

 .

 .

 .

 .

 .

 .

 .

 .

 .

 .

 . 

 .

 .

 .

 .

 .

 .

 .

 .

 .

 .

 .

 .

 .

 .

 . 

 .

 .

 .

 .

 .

 .

 .

 .

 .

 .

 .

 .

 .

 .

 .

 .

 .

 .

 .

 .

 .

 .

 .

 .

 .

 .

 .

24 .0

17 .0

15 .6

14 .5

12 .4

11 .3

10 .6

10 .4

9 .2

8 .2

7 .9

6 .8

6 .8

6 .7

6 .3

1 .2

1 .1

1 .3

1 .2

1 .0

1 .3

0 .8

0 .9

0 .8

0 .8

0 .8

0 .8

1 .0

0 .8

1 .3

Boulder, CO . . . . . . . . . . . .

Eugene, OR . . . . . . . . . . . .

Berkeley, CA . . . . . . . . . . .

Cambridge, MA . . . . . . . . .

Fort Collins, CO . . . . . . . . .

Gainesville, FL . . . . . . . . . .

Tempe, AZ . . . . . . . . . . . . .

Ann Arbor, MI . . . . . . . . . . . 

Provo, UT . . . . . . . . . . . . . .

New Haven, CT . . . . . . . . .

Salt Lake City, UT . . . . . . .

Charleston, SC . . . . . . . . .

Costa Mesa, CA . . . . . . . .

Pasadena, CA . . . . . . . . . .

Athens-Clarke County, GA . 

 .

 .

 .

 .

 .

 .

 .

 . 

 .

 .

 .

 .

 .

 .

 . 

 .

 .

 .

 .

 .

 .

 .

 . 

 .

 .

 .

 .

 .

 .

 . 

 .

 .

 .

 .

 .

 .

 .

 . 

 .

 .

 .

 .

 .

 .

 . 

 .

 .

 .

 .

 .

 .

 .

 . 

 .

 .

 .

 .

 .

 .

 . 

 .

 .

 .

 .

 .

 .

 .

 . 

 .

 .

 .

 .

 .

 .

 . 

 .

 .

 .

 .

 .

 .

 .

 .

 .

 .

 .

 .

 .

 .

 .

10 .5

8 .7

8 .1

7 .2

6 .8

6 .5

4 .2

3 .7

3 .1

2 .7

2 .5

2 .2

2 .2

2 .1

1 .7

1 .0

0 .9

1 .0

0 .8

0 .6

1 .0

0 .6

0 .5

0 .5

0 .5

0 .3

0 .4

0 .6

0 .6

0 .5

Larger Cities (Population of 200,000 or Greater)

Walk Bicycle

Rank City Percent 

Margin of 

error (±)

1 City Percent 

Margin of 

error (±)

1

1

2

3

4

5

6

7

8

9

10

11

12

13

14

15

Boston, MA . . . . . . . . . .

Washington, DC . . . . . . . 

Pittsburgh, PA . . . . . . . .

New York, NY . . . . . . . . .

San Francisco, CA . . . . .

Madison, WI . . . . . . . . . .

Seattle, WA . . . . . . . . . .

Urban Honolulu CDP, HI

Philadelphia, PA . . . . . . .

Jersey City, NJ . . . . . . . .

Newark, NJ . . . . . . . . . .

Baltimore, MD . . . . . . . .

Minneapolis, MN . . . . . .

Chicago, IL . . . . . . . . . .

Rochester, NY . . . . . . . .

 . . . . . . . .

 . . . . . . . .

 . . . . . . . .

 . . . . . . . .

 . . . . . . . .

 . . . . . . . .

 . . . . . . . .

 . . . . . . . .

 . . . . . . . .

 . . . . . . . .

 . . . . . . . .

 . . . . . . . .

 . . . . . . . .

 . . . . . . . .

 . . . . . . . .

15 .1

12 .1

11 .3

10 .3

9 .9

9 .1

9 .1

9 .0

8 .6

8 .5

8 .0

6 .5

6 .4

6 .4

6 .2

0 .5

0 .5

0 .6

0 .1

0 .4

0 .7

0 .3

0 .6

0 .3

0 .6

0 .8

0 .4

0 .3

0 .2

0 .7

Portland, OR . . . . . . . . .

Madison, WI . . . . . . . . . .

Minneapolis, MN . . . . . .

Boise, ID . . . . . . . . . . . .

Seattle, WA . . . . . . . . . .

San Francisco, CA . . . . .

Washington, DC . . . . . . . 

Sacramento, CA . . . . . .

Tucson, AZ . . . . . . . . . . .

Oakland, CA . . . . . . . . .

Denver, CO . . . . . . . . . .

New Orleans, LA . . . . . .

Richmond, VA . . . . . . . .

Philadelphia, PA . . . . . . .

Urban Honolulu CDP, HI

 . . . . . . . .

 . . . . . . . .

 . . . . . . . .

 . . . . . . . .

 . . . . . . . .

 . . . . . . . .

 . . . . . . . .

 . . . . . . . .

 . . . . . . . .

 . . . . . . . .

 . . . . . . . .

 . . . . . . . .

 . . . . . . . .

 . . . . . . . .

 . . . . . . . .

6 .1

5 .1

4 .1

3 .7

3 .4

3 .4

3 .1

2 .5

2 .4

2 .4

2 .3

2 .1

2 .1

2 .0

1 .8

0 .3

0 .5

0 .3

0 .4

0 .2

0 .2

0 .2

0 .3

0 .2

0 .3

0 .2

0 .2

0 .3

0 .2

0 .2

1

 Data are based on a sample and are subject to sampling variability . A margin of error is a measure of an estimate’s variability . The larger the margin of error 

in relation to the size of the estimates, the less reliable the estimate . When added to and subtracted from the estimate, the margin of error forms the 90 percent 

confidence interval .

Notes: For total number of workers who commute by bicycle or walk for these places and others, see American Community Survey (ACS) 2008–2012, Table 

B08006 . Population thresholds are based on 3-year 2010–2012 ACS population estimates .

Sources: U .S . Census Bureau, American Community Survey 2008–2012, Tables S0801 and B08006, available on American Factfinder at 

<www .Factfinder2 .census .gov> .
10 U.S. Census Bureau

MT

AK

NM

OR MN

KS

SD

ND

MO

WA

FL

IL IN

WI NY

PA

MI

OH

IA

ME

MA

CT 

AZ

HI

NV

TX

CA CO

WY

UT

ID

NE

OK

GA

AR

AL

NC

MS

LA

TN

KY VA

SC

WV

RI 

DE 

MD 

DC 

NJ 

VT NH

Figure 7.

Bicycling to Work by State: 2008–2012

(Data based on sample. For information on confidentiality protection, sampling error, 

nonsampling error, and definitions, see www.census.gov/acs/www/)

United States: 0.6 percent

Percentage of workers

0 to .19

.20 to .39

.40 to .59

.60 to .79

.80 to .99

1.0 to 1.99

2.0 or greater

Source: U.S. Census Bureau, American Community Survey, 2008–2012.

MT

AK

NM

OR MN

KS

SD

ND

MO

WA

FL

IL IN

WI NY

PA

MI

OH

IA

ME

MA

CT 

AZ

HI

NV

TX

CA CO

WY

UT

ID

NE

OK

GA

AR

AL

NC

MS

LA

TN

KY VA

SC

WV

RI 

DE 

MD 

DC 

NJ 

VT NH

Figure 8.

Walking to Work by State: 2008–2012

(Data based on sample. For information on confidentiality protection, sampling error, 

nonsampling error, and definitions, see www.census.gov/acs/www/)

United States: 2.8 percent

Percentage of workers

0 to 1.9

2.0 to 2.9

3.0 to 3.9

4.0 to 4.9

5.0 to 5.9

6.0 or greater

Source: U.S. Census Bureau, American Community Survey, 2008–2012.
U.S. Census Bureau 11

rate of 1.5 percent. The rate for 

subsequent categories declined or 

held steady as household income 

increased with the exception of 

the two highest income categories. 

Households with income between 

$150,000 and $199,000 had a 

slightly higher bicycle commuting rate than the previous income 

category, as did the highest income 

category of $200,000 or more. 

Households in the lowest income 

category of less than $10,000 per 

year showed the highest walking rate at 8.2 percent. Rates 

of walking showed patterns of 

decline similar to biking as income 

increased, but this pattern reversed 

slightly for the two highest income 

categories. Workers with incomes 

of $200,000 or more walked to 

work at a higher rate than those 

in the three lower income categories below it. The relatively high 

rates of biking and walking among 

lower-income workers may reflect 

financial necessity and lower rates 

of automobile ownership. The 

slight increase in biking and walking for high-income households 

may reflect their prevalence in 

large pedestrian-friendly cities such 

as New York, San Francisco, and 

Washington, DC, where average 

incomes are relatively high. 

EDUCATIONAL 

ATTAINMENT AND 

PRESENCE OF CHILDREN

Workers in households without 

their own children are more likely 

to walk and ride a bicycle to work 

than those in households with children. Workers in households without children biked to work at a rate 

of 0.7 percent, followed by those 

in households with children under 

6 years old at 0.5 percent. The rate 

of walking to work was highest 

for workers in households with no 

children at 2.8 percent, about a 

percentage point higher than each 

category of workers in households 

with children.24

Rates of nonmotorized commuting by educational attainment are 

presented for workers aged 25 

and older. The two groups with the 

highest rates of commuting by biking and walking were the most educated and least educated workers. 

At 0.9 percent, the most educated 

workers, those with a graduate 

or professional degree, had the 

highest rate of bicycle commuting, followed by the least educated 

workers, those who did not graduate from high school at 0.7 percent. 

The least educated workers had the 

highest rate of walking to work at 

3.7 percent, followed by the most 

educated workers at 2.7 percent. 

24 Analysis is limited to workers in 

households.

WALKING AND BICYCLE 

COMMUTING RATES 

ACROSS COMMUTING 

CHARACTERISTICS

Travel mode choices influence other 

aspects of travel, such as how 

long it takes to get to work and 

what time to leave home in order 

to arrive on time. The availability 

of vehicles and the relationship 

between the home and workplace 

location also influence the likelihood of traveling by a particular 

mode. For selected worker and 

household characteristics, Table 4 

shows rates of commuting for bicycle, walking, and other modes.25

25 Appendix Table A-2 shows the 

distribution of several commuting 

characteristics by travel mode, an alternative 

way of showing the relationship between 

these characteristics and workers who bicycle 

or walk to work. 

Figure 9. 

Walking and Bicycling to Work by Age: 2008–2012

(Data based on sample. For information on confidentiality protection, 

sampling error, nonsampling error, and definitions, see 

www.census.gov/acs/www/)

Source: U.S. Census Bureau, American Community Survey, 2008–2012.

Walk 2.3 2.4

1.9 1.9

3.1

Age

1.0

6.8

0.8 0.7 0.5 0.4 0.3 Bicycle

0

1

2

3

4

5

6

7

8

16 to 24 25 to 29 30 to 34 35 to 44 45 to 54 55 and over

Percent
12 U.S. Census Bureau

Table 3.

Travel Mode by Selected Social and Economic Characteristics: 2008–2012

(For information on confidentiality protection, sampling error, and definitions, see www.census.gov/acs/www/Downloads 

/data_documentation/ Accuracy/ACS_Accuracy_of_Data_2012.pdf)

Selected characteristics for 

workers 16 years and over Total 

workers

Bicycle Walk All other modes

Percent 

Margin of 

error (±)1 Percent 

Margin of 

error (±)1 Percent 

Margin of 

error (±)1

 Nation

Age

16 to 24 years . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18,419,637 1 .0 Z 6 .8 0 .1 92 .2 0 .1

25 to 29 years . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15,301,696 0 .8 Z 3 .1 Z 96 .1 Z

30 to 34 years . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14,824,955 0 .7 Z 2 .4 Z 96 .9 Z

35 to 44 years . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31,043,598 0 .5 Z 1 .9 Z 97 .6 Z

45 to 54 years . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32,874,031 0 .4 Z 1 .9 Z 97 .7 Z

55 years and over . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Sex

27,429,722 0 .3 Z 2 .3 Z 97 .4 Z

 Male . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 73,887,429 0 .8 Z 2 .9 Z 96 .4 Z

 Female . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Race and Hispanic origin

66,006,210 0 .3 Z 2 .8 Z 96 .9 Z

Hispanic or Latino (any race) . . . . . . . . . . . . . . . . . . . . 20,803,714 0 .7 Z 3 .3 Z 96 .0 Z

Not Hispanic or Latino . . . . . . . . . . . . . . . . . . . . . . . . . 119,089,925 0 .5 Z 2 .7 Z 96 .7 Z

White alone . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 94,084,919 0 .6 Z 2 .6 Z 96 .8 Z

Black or African American alone . . . . . . . . . . . . . . . . . 14,762,128 0 .3 Z 2 .8 Z 97 .0 Z

Asian alone . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7,132,081 0 .5 Z 4 .0 0 .1 95 .4 0 .1

Some other race or Two or more races . . . . . . . . . . . .

Presence of children in household

3,110,797 0 .8 Z 4 .2 0 .1 95 .1 0 .1

Under 6 years and 6 to 17 years . . . . . . . . . . . . . . . . . 9,768,648 0 .4 Z 1 .8 Z 97 .8 Z

Under 6 years only . . . . . . . . . . . . . . . . . . . . . . . . . . 11,102,415 0 .5 Z 1 .9 Z 97 .7 Z

 6 to 17 years . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32,128,022 0 .4 Z 1 .9 Z 97 .8 Z

No own children present . . . . . . . . . . . . . . . . . . . . . . .

Household income in the past 12 months 

85,494,497 0 .7 Z 2 .8 Z 96 .5 Z

Less than $10,000 . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2,270,324 1 .5 0 .1 8 .2 0 .2 90 .3 0 .2

$10,000 to $14,999 . . . . . . . . . . . . . . . . . . . . . . . . . . . 2,559,351 1 .1 0 .1 6 .6 0 .1 92 .2 0 .1

$15,000 to $24,999 . . . . . . . . . . . . . . . . . . . . . . . . . . . 7,567,161 1 .0 Z 5 .0 0 .1 94 .0 0 .1

$25,000 to $34,999 . . . . . . . . . . . . . . . . . . . . . . . . . . . 10,193,150 0 .7 Z 3 .8 0 .1 95 .5 0 .1

$35,000 to $49,999 . . . . . . . . . . . . . . . . . . . . . . . . . . . 17,007,317 0 .6 Z 2 .9 Z 96 .5 Z

$50,000 to $74,999 . . . . . . . . . . . . . . . . . . . . . . . . . . . 28,486,645 0 .5 Z 2 .2 Z 97 .3 Z

$75,000 to $99,999 . . . . . . . . . . . . . . . . . . . . . . . . . . . 23,042,419 0 .4 Z 1 .7 Z 97 .8 Z

$100,000 to $149,999 . . . . . . . . . . . . . . . . . . . . . . . . . 26,991,873 0 .4 Z 1 .5 Z 98 .1 Z

$150,000 to $199,999 . . . . . . . . . . . . . . . . . . . . . . . . . 10,723,452 0 .5 Z 1 .6 Z 98 .0 Z

$200,000 or more . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Educational attainment for workers aged 25 and 

 older

9,651,890 0 .5 Z 2 .1 Z 97 .4 Z

Less than high school graduate . . . . . . . . . . . . . . . . . . 10,232,045 0 .7 Z 3 .7 0 .1 95 .6 0 .1

High school graduate . . . . . . . . . . . . . . . . . . . . . . . . . . 30,427,068 0 .3 Z 2 .2 Z 97 .4 Z

Some college or associates degree . . . . . . . . . . . . . . . 37,966,296 0 .3 Z 1 .7 Z 97 .9 Z

Bachelors degree . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26,164,533 0 .6 Z 2 .0 Z 97 .5 Z

Graduate or professional degree . . . . . . . . . . . . . . . . . 15,841,086 0 .9 Z 2 .7 Z 96 .5 Z

Z Rounds to zero .

1

 This number, when added to or subtracted from the estimate, represents the 90 percent confidence interval around the estimate . 

Sources: U .S . Census Bureau, American Community Survey 2008–2012, Tables S0801 and B08006, available on American Factfinder at 

<www .Factfinder2 .census .gov> .
13 U.S. Census Bureau

TRAVEL TIME AND TIME OF 

DEPARTURE FROM HOME 

Nonmotorized travel is often 

suited for relatively short trips or 

as supplements to other travel 

modes such as transit. This is 

reflected in the low average travel 

time and high percentage of relatively short commutes for workers 

using nonmotorized travel modes. 

Workers who walked to work had 

an average commute time of 11.5 

minutes, considerably shorter than 

that of bicycle commuters at 19.3 

minutes, and all other workers 

who did not work at home at about 

25.9 minutes (Figure 12). About 1 

out of 10 workers with a commute 

of less than 10 minutes walked to 

work. As the length of the work trip 

increased, the percentage of workers who walked to work declined or 

held steady, reaching 0.5 percent 

for trips of 35 to 44 minutes and 

longer. Bicycle commuting was most 

prevalent for commutes between 

10 and 14 minutes in length, with 

longer trips showing a relatively low 

percentage of bicycle commutes. 

Compared with other workers, 

those who commuted by walking 

or bicycle generally departed for 

work later in the day. The highest 

rate of bicycle commuting occurred 

between 9:00 a.m. to 11:59 a.m. at

1.1 percent. Earlier departure time 

periods, particularly those before 

8:00 a.m., had the lowest rates

of bicycle commuting. Similarly, 

the highest rate of walking to 

work occurred between 9:00 a.m.

and 11:59 a.m. at 5.7 percent.

Industries or occupations that 

require later arrival or allow more 

scheduling flexibility may disproportionately employ workers who 

walk or bicycle to work. 

VEHICLE AVAILABILITY

Vehicle availability influences the 

likelihood of traveling by bicycle 

or walking. Workers with no 

available vehicles biked to work 

at a rate of 2.8 percent, compared 

with 0.8 percent for workers with 

one available vehicle, 0.4 percent 

for workers with two available 

vehicles, and 0.3 percent for workers with three or more available 

vehicles (Figure 13). Similarly, 14.8 

Figure 10. 

Walking and Bicycling to Work by Race and Ethnicity:

2008–2012

(Data based on sample. For information on confidentiality protection, 

sampling error, nonsampling error, and definitions, see 

www.census.gov/acs/www/)

Source: U.S. Census Bureau, American Community Survey, 2008–2012.

Walk

Bicycle

Percent

0 246 8 10

 Some other race or

 Two or more races

White Alone

 Black or African

 American alone

 Asian alone

Not Hispanic

 or Latino

Hispanic or Latino

 (any race)

Figure 11. 

Walking and Bicycling to Work by Household Income:

2008–2012 

(Data based on sample. For information on confidentiality protection, 

sampling error, nonsampling error, and definitions, see 

www.census.gov/acs/www/)

Source: U.S. Census Bureau, American Community Survey, 2008–2012.

Walk

Bicycle

Percent

0246 8 10

$200,000 or more

$150,000 to $199,999

$100,000 to $149,999

$75,000 to $99,999

$50,000 to $74,999

$35,000 to $49,999

$25,000 to $34,999

$15,000 to $24,999

$10,000 to $14,999

Less than $10,000
14 U.S. Census Bureau

percent of workers with no available vehicle walked to work, compared with 3.7 percent for workers 

with one available vehicle. At 1.5 

percent and 1.3 percent, respectively, workers with two available 

vehicles and three or more available vehicles walked to work at 

rates below the national average of 

2.8 percent. 

RELATIONSHIP BETWEEN 

HOME AND WORKPLACE

For any given commute, the utility 

of different travel modes is influenced by distance traveled. The 

ACS does not ask respondents 

about distance traveled to work, 

but the relationship between the 

place of residence and the workplace location may serve as a 

rough proxy for distance. Workers 

who live and work in the same 

place (meaning the same censusdefined city, not those who work 

at home) have notably higher rates 

of walking and bicycling to work 

than workers who travel outside 

of their city of residence for work. 

Workers who live and work in the 

same place commute by bicycle at 

a rate of 1.2 percent, about four 

times higher than those who live 

and work in different places at 0.3 

percent. Similarly, people who live 

and work in the same place walk 

at a rate of 6.6 percent, compared 

with 0.9 percent for other workers. 

These patterns are consistent with 

the relatively short travel times 

observed for nonmotorized commuting modes. 

CONCLUSION

This report highlights the geographic, social, and economic 

dimensions that shape work-related 

travel by bicycle and walking. It 

unpacks the local variation overlooked in national snapshots of 

nonmotorized commuting rates 

and it reinforces that local factors 

play an important role in shaping 

travel behavior. A regional comparison shows that bicycle commuting is highest in the West, where 

a handful of cities, particularly 

college towns, consistently show 

notably high rates of bicycle commuting. The Northeast stands out 

as having high rates of walking 

to work, which is driven by large, 

densely populated cities. Among 

the nation’s largest cities that 

experienced a significant change 

in the rate of bicycle commuting during the 2000s, almost all 

experienced an increase. Across 

large cities, changes in walking 

were more mixed over the decade. 

Where workers live also matters, 

as workers who live in cities had a 

higher rate of walking and bicycle 

commuting than those in suburbs 

or outside of a metropolitan area. 

ACS data, with its geographic 

reach and mix of social, economic, 

and housing information, provide 

an important tool for addressing 

unique transportation challenges 

across communities and the diverse 

set of transportation needs across 

local populations. Men were more 

than twice as likely to bicycle to 

work as women were. Younger 

workers and those with low household incomes were more likely to 

walk and bicycle to work than their 

older counterparts and workers 

with higher household incomes. 

Workers reporting Hispanic or Some 

other race or Two or more races 

had relatively high rates of bicycle 

commuting. The presence of children in the household is associated 

with relatively low rates of nonmotorized travel. 

The rapid increase in the number of bicycle sharing programs 

and the implementation of other 

bicycle-related facilities, along with 

the proliferation of local events 

such as “bike to work day,” reflect

local-level interest in incorporating 

bicycle travel into the overall transportation mix across communities. 

In 2013, New York City became 

one of several large U.S. cities to 

have implemented a bicycle sharing 

Figure 12. 

Average Travel Time for Bicycling, Walking, and Other 

Modes: 2008–2012

(In minutes. Data based on sample. For information on confidentiality 

protection, sampling error, nonsampling error, and definitions, 

see www.census.gov/acs/www/)

Source: U.S. Census Bureau, American Community Survey, 2008–2012.

Walk Bicycle All other modes

Minutes

0

5

10

15

20

25

30
15 U.S. Census Bureau

program and several more cities have plans for bicycle sharing 

programs of some sort. Several 

communities have also demonstrated public and private interest in promoting more walkable 

built environments. In some large 

cities, indicators of neighborhood 

walkability have become a selling 

point in real estate advertising, and 

several communities have invested 

in pedestrian-oriented commercial 

spaces for economic development 

purposes.26 The U.S. Department of 

Transportation has also expressed 

its support for the development of 

integrated transportation systems 

that include bicycle and pedestrian 

infrastructure.27

26 Christopher B. Leinberger and Mariela 

Alfonzo,	“Walk	This	Way:	The	Economic	

Promise	of	Walkable	Places	in	Metropolitan	

Washington,	D.C.,”	Metropolitan	Policy	

Program	at	Brookings,	Washington,	DC,	2012. 27 For more information, see 

<www.fhwa.dot.gov/environment/bicycle 

_pedestrian/overview/policy_accom.cfm>.

As cities invest in walkability and 

bicycle-friendly programs and 

infrastructure, the demand for and 

relevance of bicycle and pedestrian 

data will increase. Local governments and planning agencies are 

interested in not only understanding changes in the rates of nonmotorized forms of travel, but also 

how these rates relate to transportation safety and performance 

standards, environmental protection, economic development, and 

Table 4.

Travel Mode to Work by Selected Commuting Characteristics: 2008–2012

(For information on confidentiality protection, sampling error, and definitions, see www.census.gov/acs/www/Downloads 

/data_documentation/ Accuracy/ACS_Accuracy_of_Data_2012.pdf)

Selected characteristics for 

workers 16 years and over Total 

workers

Bicycle Walk All other modes

Percent 

Margin of 

error (±)1 Percent 

Margin of 

error (±)1 Percent 

Margin of 

error (±)1

Nation

Average travel time to work2 . . . . . . . . . . . . .

Travel time to work

133,916,010 19 .3 0 .1 11 .5 0 .1 25 .9 Z

Less than 10 minutes . . . . . . . . . . . . . . . . . 18,281,648 0 .8 Z 10 .5 0 .1 88 .7 0 .1

10 to 14 minutes . . . . . . . . . . . . . . . . . . . . 19,304,483 0 .9 Z 4 .0 Z 95 .1 Z

15 to 19 minutes . . . . . . . . . . . . . . . . . . . . 20,787,002 0 .7 Z 2 .5 Z 96 .8 Z

20 to 24 minutes . . . . . . . . . . . . . . . . . . . . 19,785,976 0 .6 Z 1 .5 Z 97 .9 Z

25 to 29 minutes . . . . . . . . . . . . . . . . . . . . 8,144,297 0 .4 Z 1 .0 Z 98 .6 Z

30 to 34 minutes . . . . . . . . . . . . . . . . . . . . 18,189,632 0 .5 Z 1 .0 Z 98 .5 Z

35 to 44 minutes . . . . . . . . . . . . . . . . . . . . 8,537,406 0 .4 Z 0 .5 Z 99 .1 Z

45 to 59 minutes . . . . . . . . . . . . . . . . . . . . 10,073,930 0 .3 Z 0 .5 Z 99 .2 Z

60 or more minutes . . . . . . . . . . . . . . . . . .

Time of departure

10,811,636 0 .3 Z 0 .5 Z 99 .2 Z

12:00 a .m . to 4:59 a .m . . . . . . . . . . . . . . . . 5,607,965 0 .5 Z 2 .0 Z 97 .5 0 .1

5:00 a .m . to 5:59 a .m . . . . . . . . . . . . . . . . . 11,326,773 0 .4 Z 1 .5 Z 98 .1 Z

6:00 a .m . to 6:59 a .m . . . . . . . . . . . . . . . . . 25,223,444 0 .4 Z 1 .5 Z 98 .1 Z

7:00 a .m . to 7:59 a .m . . . . . . . . . . . . . . . . . 37,337,021 0 .4 Z 2 .0 Z 97 .6 Z

8:00 a .m . to 8:59 a .m . . . . . . . . . . . . . . . . . 22,153,870 0 .7 Z 3 .8 Z 95 .5 Z

9:00 a .m . to 11:59 a .m . . . . . . . . . . . . . . . . 13,860,156 1 .1 Z 5 .7 0 .1 93 .2 0 .1

12:00 p .m . to 3:59 p .m . . . . . . . . . . . . . . . . 9,391,080 0 .8 Z 5 .1 0 .1 94 .0 0 .1

4:00 p .m . to 11:59 p .m . . . . . . . . . . . . . . . .

Vehicles available for workers in 

 household

9,015,701 0 .7 Z 4 .6 0 .1 94 .7 0 .1

No vehicle available . . . . . . . . . . . . . . . . . . 6,134,666 2 .8 0 .1 14 .8 0 .1 82 .4 0 .1

1 vehicle available . . . . . . . . . . . . . . . . . . . 29,608,754 0 .8 Z 3 .7 Z 95 .5 Z

2 vehicles available . . . . . . . . . . . . . . . . . . 58,600,079 0 .4 Z 1 .5 Z 98 .2 Z

3 or more vehicles available . . . . . . . . . . . .

Workplace location for workers who 

 lived in a place

Workplace and residence are within the 

44,150,083 0 .3 Z 1 .3 Z 98 .5 Z

 same place . . . . . . . . . . . . . . . . . . . . . . . .

Workplace is located outside place of 

44,092,758 1 .2 Z 6 .6 Z 92 .2 Z

 residence . . . . . . . . . . . . . . . . . . . . . . . . . 59,927,706 0 .3 Z 0 .9 Z 98 .8 Z

Z Rounds to zero .

1

 This number, when added to or subtracted from the estimate, represents the 90 percent confidence interval around the estimate . 

2

 Travel time estimates do not include workers who worked at home .

Sources: U .S . Census Bureau, American Community Survey 2008–2012, Tables S0801 and B08006, available on American Factfinder at 

<www .Factfinder2 .census .gov> .
16 U.S. Census Bureau

mobility options. The ACS provides 

one of the nation’s most robust 

sources of data on bicycling and 

walking to work. It provides a valuable resource for planners, policy 

makers, and the general population 

to assess changes in these travel 

modes across communities.28

SOURCE OF THE ESTIMATES

The American Community Survey 

(ACS) is a nationwide survey 

designed to provide communities 

with reliable and timely demographic, social, economic, and 

housing data for congressional 

districts, counties, places, and 

other localities every year. It has 

an annual sample size of about 3.5 

million addresses across the United 

States and Puerto Rico and includes

both housing units and group quarters (e.g., nursing homes and prisons). The ACS is conducted in every 

county throughout the nation, and 

every municipio in Puerto Rico,

where it is called the Puerto Rico

Community Survey. Beginning in 

2006, ACS data for 2005 were 

released for geographic areas with 

populations of 65,000 and greater. 

For information on the ACS sample 

design and other topics, visit 

<www.census.gov/acs/www>.

ACCURACY OF 

THE ESTIMATES

The data presented in this report 

are based on the ACS sample interviewed between 2008 and 2012. 

The estimates based on this sample 

approximate the actual values and 

represent the entire U.S. resident 

household and group quarters 

population. Sampling error is the 

28 For information on bicycle and 

pedestrian travel as a share of overall travel, 

see the National Household Travel Survey at 

<www.nhts.ornl.gov>.

difference between an estimate 

based on a sample and the corresponding value that would be 

obtained if the estimate were based 

on the entire population (as from a 

census). Measures of the sampling 

error are provided in the form of 

margins of error for all estimates 

included in this report. All comparative statements in this report 

have undergone statistical testing, 

and comparisons are significant at 

the 90 percent level unless otherwise noted. In addition to sampling 

error, nonsampling error may be 

introduced during any of the operations used to collect and process 

survey data such as editing, reviewing, or keying data from questionnaires. For more information on 

sampling and estimation methods, 

confidentiality protection, and 

sampling and nonsampling errors, 

please see the 2012 ACS Accuracy 

of the Data document located at 

<www.census.gov/acs/www

/Downloads/data_documentation

/Accuracy/ACS_Accuracy_of

_Data_2012.pdf>.

For more information about the 

commuting patterns of U.S. workers, go to the U.S. Census Bureau’s 

Journey to Work and Migration 

Statistics Branch Web site at 

<www.census.gov/hhes

/commuting/>, or contact the 

Journey to Work and Migration 

Statistics Branch at 301-763-2454.

SUGGESTED CITATION

McKenzie, Brian, “Modes Less

Traveled: Commuting by Bicycle

and Walking in the United States,”

2008–2012, American Community 

Survey Reports, ACS-26, U.S. Census 

Bureau, Washington, DC, 2014.

Figure 13. 

Vehicles Available by Bicycling and Walking to Work:

2008–2012

(Data based on sample. For information on confidentiality protection, 

sampling error, nonsampling error, and definitions, see 

www.census.gov/acs/www/)

Source: U.S. Census Bureau, American Community Survey, 2008–2012.

Walk

Bicycle

No vehicle 

available

1 vehicle 

available

2 vehicles 

available

3 or more

vehicles available

Percent

0

2

4

6

8

10

12

14

16
U.S. Census Bureau 17

Appendix Table A-1.

Rates of Walking and Bicycling to Work by Region and City Size: 2008–2012

(For information on confidentiality protection, sampling error, and definitions, see www.census.gov/acs/www/Downloads 

/data_documentation/ Accuracy/ACS_Accuracy_of_Data_2012.pdf)

Region and city size

Walk Bicycle

Percent Margin of error (±)1 Percent Margin of error (±)1

West

 Total . . . . . . . . . . . . . . . . 3.0 Z 1 .1 Z

Small cities . . . . . . . . . . . 2 .8 Z 0 .8 Z

Medium cities . . . . . . . . . 2 .7 0 .1 1 .3 Z

Large cities . . . . . . . . . . . 3 .4 Z 1 .4 Z

Midwest

 Total . . . . . . . . . . . . . . . . 2 .7 Z 0 .5 Z

Small cities . . . . . . . . . . . 2 .4 Z 0 .4 Z

Medium cities . . . . . . . . . 2 .9 0 .1 0 .6 Z

Large cities . . . . . . . . . . . 4 .4 0 .1 1 .1 Z

Northeast

 Total . . . . . . . . . . . . . . . . 4 .7 Z 0 .5 Z

Small cities . . . . . . . . . . . 3 .1 Z 0 .3 Z

Medium cities . . . . . . . . . 7 .2 0 .2 1.0 0 .1

Large cities . . . . . . . . . . . 10 .2 0 .1 1.0 Z

South

 Total . . . . . . . . . . . . . . . . 1 .8 Z 0 .3 Z

Small cities . . . . . . . . . . . 1 .6 Z 0 .2 Z

Medium cities . . . . . . . . . 2 .3 0 .1 0 .6 Z

Large cities . . . . . . . . . . . 2 .7 Z 0 .6 Z

Z Rounds to zero .

1

 Data are based on a sample and are subject to sampling variability . A margin of error is a measure of an estimate’s variability . The larger the margin of error 

in relation to the size of the estimates, the less reliable the estimate . When added to and subtracted from the estimate, the margin of error forms the 90 percent 

confidence interval .

Sources: U .S . Census Bureau, American Community Survey 2008–2012, Tables S0801 and B08006, available on American Factfinder at 

<www .Factfinder2 .census .gov> .
U.S. Census Bureau 18

Appendix Table A-2.

Commuting Characteristics for Workers Who Walked or Bicycled to Work: 2008–2012

(For information on confidentiality protection, sampling error, and definitions, see www.census.gov/acs/www/Downloads 

/data_documentation/ Accuracy/ACS_Accuracy_of_Data_2012.pdf)

Travel Time to Work by Travel Mode

Workers who Minutes

Travel mode did not work Less 60 or 

at home than 10 10 to 14 15 to 19 20 to 24 25 to 29 30 to 34 35 to 44 45 to 59 more

Bicycle . . . . . . . . . . . . . . . 785,665 18 .7 21 .0 19 .2 14 .6 4 .6 10 .5 3 .9 3 .8 3 .7

 Margin of error (±)1 . . . . 0 .3 0 .3 0 .4 0 .3 0 .2 0 .3 0 .2 0 .2 0 .2

Walked . . . . . . . . . . . . . . . 3,938,418 48 .7 19 .8 13 .1 7 .7 2 .0 4 .8 1 .2 1 .2 1 .4

 Margin of error (±)1 . . . . 0 .2 0 .1 0 .1 0 .1 0 .1 0 .1 Z Z Z

All other modes . . . . . . . . 129,191,927 12 .6 14 .2 15 .6 15 .0 6 .2 13 .9 6 .5 7 .7 8 .3

Margin of error (±)1 . . . . Z Z Z Z Z Z Z Z Z

Time of Departure to Work by Travel Mode

Workers who 12:00 a .m . 5:00 a .m . 6:00 a .m . 7:00 a .m . 8:00 a .m . 9:00 a .m . 12:00 p .m . 4:00 p .m . 

Travel mode did not work to to to to to to to to 

at home 4:59 a .m . 5:59 a .m . 6:59 a .m . 7:59 a .m . 8:59 a .m . 11:59 a .m . 3:59 p .m . 11:59 p .m .

Bicycle . . . . . . . . . . . . . . . 785,665 3 .3 5 .5 12 .3 20 .9 20 .3 19 .4 9 .8 8 .6

 Margin of error (±)1

 . . . . 0 .2 0 .2 0 .3 0 .4 0 .4 0 .4 0 .3 0 .3

Walked . . . . . . . . . . . . . . . 3,938,418 2 .8 4 .3 9 .7 19 .0 21 .3 20 .2 12 .3 10 .4

 Margin of error (±)1 . . . . 0 .1 0 .1 0 .1 0 .2 0 .1 0 .2 0 .1 0 .1

All other modes . . . . . . . . 129,191,927 4 .2 8 .6 19 .2 28 .2 16 .4 10 .0 6 .8 6 .6

Margin of error (±)1 . . . . Z Z Z Z Z Z Z Z

Workplace Location by Travel Mode

Work- Workplace and place is 

residence located Travel mode Workers who within outside 

did not work the same place of 

at home place residence

Bicycle . . . . . . . . . . . . . . . 785,665 73 .5 26 .5

 Margin of error (±)1

 . . . . 0 .4 0 .4

Walked . . . . . . . . . . . . . . . 3,938,418 84 .7 15 .3

 Margin of error (±)1 . . . . 0 .2 0 .2

All other modes . . . . . . . . 129,191,927 40 .7 59 .3

Margin of error (±)1 . . . . Z Z

Vehicles Available by Travel Mode

3 or more 

Workers in No vehicle 1 vehicle 2 vehicles vehicles 

Travel mode households available available available available

Bicycle . . . . . . . . . . . . . . . 766,475 22 .6 31 .9 28 .9 16 .6

 Margin of error (±)1

 . . . . 0 .5 0 .4 0 .5 0 .4

Walked . . . . . . . . . . . . . . . 3,408,036 26 .6 32 25 .2 16 .2

 Margin of error (±)1

 . . . . 0 .2 0 .2 0 .2 0 .2

All other modes . . . . . . . . 134,319,071 3 .8 21 .1 42 .8 32 .4

Margin of error (±)1 . . . . Z 0 .1 0 .1 Z

Z Represents or rounds to zero .

1

 This number, when added to or subracted from the estimate, represents the 90 percent confidence interval around the estimate . 

Sources: U .S . Census Bureau, American Community Survey 2008–2012, Tables S0801 and B08006, available on American Factfinder at 

<www .Factfinder2 .census .gov> .