U.S. Department of Commerce

Economics and Statistics Administration

U.S. CENSUS BUREAU

Commuting in the 

United States: 2009

American Community Survey Reports

By

Brian McKenzie

and

Melanie Rapino

ACS-15

Issued September 2011

Figure 1.

Reproduction of the Questions 

on Commuting From the 2009 

American Community Survey

Source: U.S. Census Bureau, 

2009 American Community Survey questionnaire.

This report describes patterns of commuting for the nation and metropolitan 

statistical areas (metro areas) based on 

the 2009 American Community Survey 

(ACS).1 In the United States, commutes 

make up less than 20 percent of all trips 

taken, but play a unique role within 

the mix of overall trips by determining 

peak travel demand across transportation systems.2 Federal, state, and local 

policymakers use the ACS to guide 

decisions about how to allocate limited 

public resources devoted to transportation. Planners use ACS commuting data 

to guide transportation improvement 

strategies, predict future travel demand, 

and gauge the amount of pressure placed 

on transportation infrastructure. 

The ACS is an ongoing survey conducted 

annually by the U.S. Census Bureau that 

captures changes in the socioeconomic, 

housing, and demographic characteristics 

of communities across the United States 

and Puerto Rico.3 The ACS questions 

1 This report discusses data for the United States, 

including the 50 states and the District of Columbia, 

but not the Commonwealth of Puerto Rico. For more 

information on metropolitan statistical areas, please 

see <www.whitehouse.gov/omb/assets/omb

/bulletins/fy2009/09-01.pdf>. 2 Summary of Travel Trends: 2009 National 

Household Travel Survey. 2011. Technical Report 

No. FHWA-PL-11-022. <http://nhts.ornl.gov

/publications.shtml>. 3 The ACS uses a series of monthly samples to 

produce annual estimates. Detailed questions that 

previously appeared on the decennial census long 

form are now included in the ACS, and the decennial 

census now simply produces a count of the nation’s 

population and a snapshot of its most basic demographic characteristics. The annual sampling rate for 

the ACS is about 2.5 percent of all housing units and 

includes residents living in group quarters. Five years 

of ACS data collection are necessary to achieve a 

cumulative sample large enough to ensure respondent confidentiality for smaller communities and for 

small geographies such as census tracts or block 

groups. For larger geographies, specifically those 

with populations of 65,000 or greater, estimates are 

available annually. For selected geographies with 

populations of 20,000 or greater, combined 3-year 

estimates are available. For the smallest geographic 

areas, the Census Bureau released 5-year estimates 

for the first time in December 2010. These estimates 

are based on data collected between 2005 and 2009. 

Workers are civilians and members of the Armed 

Forces, 16 years and over, who were at work the 

previous week. Persons on vacation or not at work 

the prior week are not included.
2 U.S. Census Bureau

related to travel focus solely on 

commuting and do not ask about 

leisure travel or other nonwork 

trips. This report discusses commuting characteristics for workers 16 years and over who were 

employed during the week prior to 

the ACS reference week and did not 

work at home. 

Respondents answer questions 

about where they work, what time 

they leave home for work, the 

means of transportation used to 

get there, the number of workers 

riding in a car, truck, or van, and 

how long it takes to travel to work. 

A reproduction of these questions 

can be found in Figure 1. The central topics of each section of this 

report are based on these commuting questions. 

For each commuting attribute, findings are presented at the national 

and metro area levels for a variety of population characteristics 

such as sex, race, ethnicity, and 

workplace location.4 A set of more 

detailed tables associated with 

each commuting attribute is available for download through links 

provided throughout the report. 

Commuting highlights from the 

2009 ACS are:

• Over three-quarters of the 

nation’s workers drove alone to 

work.

• Workers took an average of 

25.1 minutes to get to work.

4 The estimates in this report (which 

may be shown in text, figures, and tables) 

are based on responses from a sample of 

the population and may differ from actual 

values because of sampling variability or 

other factors. As a result, apparent differences between the estimates for two or more 

groups may not be statistically significant. 

All comparative statements have undergone 

statistical testing and are significant at the 

90 percent confidence level unless otherwise 

noted.

Table 1.

Means of Transportation, Time Leaving Home, and Travel 

Time to Work: 2009

(Numbers in thousands. For information on confidentiality protection, sampling 

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

Characteristic Total 

workers Percent distribution Margin of error1 (±)

Means of Transportation to Work2

Car, truck, or van . . . . . . . . . . . . . . . . . 119,393 86.1 0.1

Drove alone . . . . . . . . . . . . . . . . . . . 105,476 76.1 0.1

Carpooled . . . . . . . . . . . . . . . . . . . . 13,917 10.0 0.1

Public transportation . . . . . . . . . . . . . . 6,922 5.0 –

Bus or trolley bus . . . . . . . . . . . . . . . 3,673 2.7 –

Streetcar or trolley car . . . . . . . . . . . 89 0.1 –

Subway or elevated . . . . . . . . . . . . . 2,372 1.7 –

Railroad . . . . . . . . . . . . . . . . . . . . . . 750 0.5 –

Ferryboat . . . . . . . . . . . . . . . . . . . . . 37 0.0 –

Taxicab . . . . . . . . . . . . . . . . . . . . . . . . 157 0.1 –

Motorcycle . . . . . . . . . . . . . . . . . . . . . . 294 0.2 –

Bicycle . . . . . . . . . . . . . . . . . . . . . . . . . 766 0.6 –

Walked . . . . . . . . . . . . . . . . . . . . . . . . . 3,966 2.9 –

Other means . . . . . . . . . . . . . . . . . . . . 1,176 0.8 –

Worked at home . . . . . . . . . . . . . . . . . 5,918 4.3 –

Time Leaving Home to Go to Work3

12:00 a.m. to 4:59 a.m. . . . . . . . . . . . . 5,209 3.8 –

5:00 a.m. to 5:29 a.m. . . . . . . . . . . . . . 4,647 3.4 –

5:30 a.m. to 5:59 a.m. . . . . . . . . . . . . . 6,420 4.6 –

6:00 a.m. to 6:29 a.m. . . . . . . . . . . . . . 11,408 8.2 –

6:30 a.m. to 6:59 a.m. . . . . . . . . . . . . . 13,620 9.8 –

7:00 a.m. to 7:29 a.m. . . . . . . . . . . . . . 19,536 14.1 –

7:30 a.m. to 7:59 a.m. . . . . . . . . . . . . . 17,686 12.8 0.1

8:00 a.m. to 8:29 a.m. . . . . . . . . . . . . . 14,565 10.5 0.1

8:30 a.m. to 8:59 a.m. . . . . . . . . . . . . . 7,425 5.4 –

9:00 a.m. to 9:59 a.m . . . . . . . . . . . . . . 8,287 6.0 –

10:00 a.m. to 10:59 a.m . . . . . . . . . . . . 3,705 2.7 –

11:00 a.m. to 11:59 a.m . . . . . . . . . . . . 1,747 1.3 –

12:00 p.m. to 3:59 p.m . . . . . . . . . . . . . 9,270 6.7 –

4:00 p.m. to 11:59 p.m . . . . . . . . . . . . . 9,150 6.6 –

Travel Time to Work3

Less than 10 minutes . . . . . . . . . . . . . 18,565 13.4 0.1

10 to 14 minutes . . . . . . . . . . . . . . . . . 19,328 13.9 0.1

15 to 19 minutes . . . . . . . . . . . . . . . . . 20,775 15.0 0.1

20 to 24 minutes . . . . . . . . . . . . . . . . . 19,559 14.1 0.1

25 to 29 minutes . . . . . . . . . . . . . . . . . 8,040 5.8 –

30 to 34 minutes . . . . . . . . . . . . . . . . . 17,874 12.9 –

35 to 44 minutes . . . . . . . . . . . . . . . . . 8,321 6.0 –

45 to 59 minutes . . . . . . . . . . . . . . . . . 9,834 7.1 –

60 to 89 minutes . . . . . . . . . . . . . . . . . 7,160 5.2 –

90 or more minutes . . . . . . . . . . . . . . . 3,218 2.3 –

Mean travel time to work (minutes) . . . 25.1 – 0.1

– Represents or rounds to zero.

1

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

interval around the estimate. 2

 Workers 16 years and over. 3

 Workers 16 years and over who did not work at home.

Note: Because of sampling error, the estimates in this table may not be significantly different 

from one another.

Source: U.S. Census Bureau, American Community Survey, 2009.
U.S. Census Bureau 3

• Hispanic workers carpooled 

at a rate of 16.4 percent, 

compared with 9.5 percent for 

non-Hispanic workers.

• The rate of public transportation 

usage among the foreign-born 

population was 10.8 percent, 

more than twice that of the 

native-born population, at 

4.1 percent.

• Suburban workers drove alone at 

a rate of 81.5 percent, compared 

with 72.1 percent for workers 

living inside of a principal city.

• The New York-Northern New 

Jersey-Long Island, NY-NJ-PA 

Metro Area had the longest average commute, at 34.6 minutes.

• The 10 metro areas with the 

shortest average commute times 

have populations of fewer than 

300,000 people.

As communities change, the 

information collected in the ACS 

provides timely and relevant data 

upon which transportation planning decisions may be made. A 

major advantage of the ACS is its 

rich array of sociodemographic 

information. The ability to link 

information about commuting to 

sociodemographic characteristics 

and geography allows planners to 

forecast local peak travel demand 

and address unmet transportation 

needs more accurately.

A NATIONAL COMMUTING 

OVERVIEW FOR 2009

Table 1 shows that, among workers 16 years and over, 86.1 percent 

commuted in a car, truck, or van 

in 2009, and 76.1 percent drove 

to work alone. About 5 percent 

of workers commuted by public 

transportation, and about 3 percent 

walked to work. All other transportation modes were used by less 

than 1 percent of workers who did 

not work at home. 

The private automobile’s dominance among travel modes used for 

the commute represents a longstanding pattern. The 1960 Census 

was the first to include questions 

specifically related to commuting. 

Figure 2 shows that the number of 

workers who commuted by private 

automobile increased continuously between 1960 and 2009, 

from about 41 million to about 

120 million.5

5 Figure 2 includes workers 16 years 

and over. All subsequent tables and figures 

include workers 16 years and over who did 

not work at home.

Information about when workers 

leave their homes for work plays 

an integral role in the regional 

transportation planning process by 

contributing to an understanding of 

traffic flow patterns on the nation’s 

roads and public transportation 

infrastructure. Table 1 shows that 

over half of the nation’s workers 

left their homes for work between 

6:00 a.m. and 8:59 a.m. The 

30-minute period with the highest 

percentage of departures (14.1 percent) occurred between 7:00 a.m. 

and 7:29 a.m. Less than 25 percent 

of the nation’s workers left for work 

between 9:00 a.m. and 11:59 p.m. 

Source: U.S. Census Bureau, . 

Figure 2.

Means of Transportation: 1960 to 2009

(Workers 16 years and over. For information on confidentiality 

protection, sampling error, nonsampling error, and definitions, 

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

Sources: U.S. Census Bureau, Decennial Census, 1960, 1970, 1980, 1990, 2000; 

U.S. Census Bureau, American Community Survey, 2009.

Millions

0

20

40

60

80

100

120

140 All other 

means

Walked

Public

transportation

Private

automobile

2009

ACS

2000

Census

1990

Census

1980

Census

1970

Census

1960

Census
4 U.S. Census Bureau

Figure 3 shows mean travel time 

since 1980, the first year the census collected travel-time information. The mean travel time for 

workers was just under 22 minutes 

in 1980, then increased between 

1980 and 2000 to about 25 minutes, where it remained in 2009. 

Just over 2 percent of workers took 

90 minutes or more to get to work 

in 2009 (see Table 1). The questionnaires prior to Census 2000 permitted respondents to mark no more 

than two digits for their travel time, 

limiting reported travel time to 99 

minutes. Three digits were made 

available in the Census 2000 questionnaire, which allowed results to 

show a greater range of extremely 

long commutes. 

The amount of time workers 

spend commuting is an important 

indicator of shifts in the spatial 

distribution of workers’ residences 

and their places of work. Traveltime shifts may also provide insight 

into other important community 

characteristics such as changes in 

workforce participation rates and 

shifts in the availability and usage 

of different transportation modes. 

Table 1 provides a broad overview 

of key commuting patterns in the 

United States, but commuting 

patterns vary considerably across 

geographic scales and population 

subsets. Subsequent sections of 

this report illustrate these variations, beginning with a focus on 

differences in means of transportation across groups and regions.

MEANS OF TRANSPORTATION 

TO WORK 

The 2009 ACS question related 

to means of transportation asked 

respondents in the workforce, 

“How did this person usually get 

to work LAST WEEK?” (see Figure 1, 

Question 31). Although commutes 

may involve multiple transportation modes (for example, driving 

to a train station and then taking 

a train), respondents are restricted 

to indicating the single travel mode 

used for the longest distance. 

Tracking changes in the distribution of means of transportation to 

work is important to the regional 

planning process for gauging the 

utility of transportation policy and 

budget decisions. This information 

also contributes to understanding 

unmet commuting needs for local 

populations, integral for addressing 

policy concerns related to mobility. 

The characteristics of the communities to and from which workers commute have a great deal of 

influence on commuting choices, 

including the means of transportation used. For example, automobile 

congestion and the quality and 

availability of public transportation, 

sidewalks, and bicycle routes influence the relative utility and attractiveness of different transportation 

modes. These characteristics may 

vary considerably across and within 

places, especially when contrasting principal cities and suburbs.6

This section takes a closer look at 

differences in how people get to 

work across several socioeconomic 

characteristics.7

6 For more information about the definition 

of principal city, see the U.S. Office of Management and Budget document entitled “Update 

of Statistical Area Definitions and Guidance on 

Their Uses” at <www.whitehouse.gov/omb

/assets/bulletins/b10-02.pdf>. 7 Much of the information presented 

in this section comes from Supplemental 

Table A, Means of Transportation by Selected 

Characteristics: 2009, accessible online at 

<www.census.gov/hhes/commuting/>. This 

table presents the means of transportation 

for the work commute by several social, 

economic, and housing characteristics. 

Figure 3.

Average Travel Time for Workers: 1980 to 2009

(Workers 16 years and over. For information on confidentiality 

protection, sampling error, nonsampling error, and definitions, 

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

Minutes (one way)

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

U.S. Census Bureau, American Community Survey, 2009.

0

18

19

20

21

22

23

24

25

26

27

28

29

30

1980 Census 1990 Census 2000 Census 2009 ACS
U.S. Census Bureau 5

Racial/Ethnic Differences

The percentage of non-Hispanic 

White workers who drove alone to 

work (83.5 percent) was about 10 

percentage points higher than that 

of any other racial or ethnic group 

(see Figure 4).8 The percentage of 

Hispanic and non-Hispanic Asian 

workers who drove alone did not 

exceed 70 percent. The comparatively low rate of Hispanic workers 

who drove alone was accompanied by a carpooling rate of 16.4 

percent, notably higher than that 

of any other racial or ethnic group. 

Non-Hispanic Black workers had 

the highest rate of public transportation usage at 11.5 percent, more 

than three times higher than that 

of non-Hispanic White workers, at 

3.2 percent. The rate of walking to 

work varied little across race and 

Hispanic origin groups, ranging 

between 2.8 and 4.4 percent.

Foreign-Born and Native-Born 

Differences 

Figure 5 shows differences in 

commuting mode by nativity. The 

foreign-born population carpooled 

at a rate of 16.0 percent, compared 

with 9.4 percent for the native-born 

8 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 single-race concept) or as those who 

reported Asian regardless of whether they 

also reported another race (the race-aloneor-in-combination concept). The body of this 

report (text, figures, and tables) shows data 

using the first approach (race alone). Use of 

the single-race 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>. This report may refer 

to the White-alone population as White, the 

Black-alone population as Black, the Asianalone population as Asian, and the Whitealone-non-Hispanic population as White, 

non-Hispanic. Because Hispanics may be any 

race, data in this report for Hispanics overlap 

with data for racial groups. 

population.9 The rate of public 

transportation usage among the 

foreign-born population was more 

than twice that of the native-born 

population (10.8 percent compared 

to 4.1 percent, respectively). Higher 

rates of carpooling and public transit usage among the foreign born 

may reflect differences between 

the foreign-born and native-born 

populations in sociodemographic 

characteristics related to travel 

behavior. For example, in 2009 the 

foreign-born population was more 

9 “Native” or “native-born” includes people 

born in the United States, Puerto Rico, or 

U.S. Island Areas, or people born abroad of an 

American parent or parents.

likely than the native-born population to live in families with incomes 

at or below the poverty level and 

in households with no available 

vehicle.10

How Home and Work 

Characteristics Affect the 

Commute

The percentage of workers living in 

renter-occupied units who commuted to work by public transportation (9.9 percent) was more 

than three times higher than that 

of workers in owner-occupied units 

10 See Table S0501 from the 2009 ACS 

data on American FactFinder at 

<http://factfinder.census.gov>.

Figure 4.

Means of Transportation by Race and 

Hispanic Origin: 2009

(Workers 16 years and over. 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, 2009.

Percent

0

10

20

30

40

50

60

70

80

90

100

All other

means

Walked

Public

transportation

Carpooled

Drove alone

Hispanic or

 Latino (of

any race)...

Some other

race or

Two or

more races,

 non-Hispanic

Asian,

non-Hispanic

Black or

African

American,

non-Hispanic

White,

non-Hispanic
6 U.S. Census Bureau

(3.1 percent). At 46.7 percent, the 

percentage of workers living in 

noninstitutionalized group quarters, including (but not limited to) 

those living in college or university 

student housing, military barracks, 

and group homes walked to work 

at a rate considerably higher than 

any other group.11

11 See Supplemental Table A, Means 

of Transportation by Selected Characteristics: 

2009, at <www.census.gov/hhes

/commuting/>. 

There were notable differences 

in mode choice between workers 

residing in the suburbs and those 

living in the city (see Table 2). 

Suburban workers (those who lived 

in a metropolitan area and outside 

of a principal city) drove alone at 

a rate of 81.5 percent, compared 

with 72.1 percent for workers 

who lived inside of a principal city. 

Respondents who lived inside of 

a principal city in a metro area 

walked to work at a rate of 4.4 percent, higher than that of workers 

who lived outside of a principal city 

in a metro area or outside of any 

metro area. Workers who lived in 

a principal city and worked in the 

metro area of residence had the 

highest public transportation usage 

rate, at 10.9 percent.

A Closer Look at Public 

Transportation 

In several regions, transportationplanning efforts aimed at relieving 

congestion and increasing mobility 

have shifted from strategies that 

favor road-building to those that 

favor multimodal solutions. Investment in new and existing public 

transportation infrastructure has 

played a crucial role in this effort.

At the national level, 5 percent of 

commuters used public transportation in 2009, but public transportation represents the second most 

common means of transportation after the private automobile. 

“Public transportation” includes 

bus, trolley, streetcar, subway, 

elevated rail, railroad, or ferry. 

Although these modes collectively 

account for only a small portion of 

the nation’s overall commutes, they 

play prominent transportation roles 

within several of the nation’s largest metro areas. 

Figure 6 shows workers who 

commuted by any form of public 

transportation in the 50 largest 

metro areas in 2009.12 The rate of 

public transportation usage was 

less than the national average of 

5 percent for many of these metro 

areas, illustrating the concentration of public transportation trips 

among a handful of the nation’s 

large and densely populated 

12 The 50 most populous metropolitan 

statistical areas are based on population 

estimates as of July 1, 2009. 

Figure 5.

Means of Transportation by Nativity: 2009

(Percent distribution of workers 16 years and over. 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, 2009.

0

10

20

30

40

50

60

70

80

90

100

All other means

Walked

Public transportation

Carpooled

Drove alone

Native born Foreign born

Percent
U.S. Census Bureau 7

regions. The New York-Northern 

New Jersey-Long Island, NY-NJ-PA 

Metro Area had the highest percentage of workers who commuted by public transportation 

(30.5 percent), followed by the 

San Francisco-Oakland-Fremont, CA 

(14.6 percent), and the WashingtonArlington-Alexandria, DC-VA-MD-WV 

(14.1 percent) Metro Areas. 

Figure 7 shows the percentage of 

workers who commuted by public 

transportation for all 366 metro 

areas in 2009. The percentage of 

public transportation commuters 

exceeded 10 percent in only five 

metro areas in 2009.13 Although 

13 For the following metro areas, the 

percentage of workers who commuted by 

public transportation in 2009 exceeded and 

was statistically different from 10 percent: 

New York-Northern New Jersey-Long Island, 

NY-NJ-PA; San Francisco-Oakland-Fremont, 

CA; Boston-Cambridge-Quincy, MA-NH; and 

Chicago-Naperville-Joliet, IL-IN-WI.

public transportation usage is generally higher in large metro areas, 

several relatively small metro areas 

with large universities also showed 

comparatively high rates of public 

transportation usage. For example, 

Ithaca, NY, and Ames, IA, had public transportation usage rates of 6.9 

and 6.1 percent, respectively. 

In several large metro areas, subway or elevated rail systems are 

integral components of the overall 

regional transportation system. The 

highest rate of subway or elevated 

rail commuting in 2009 occurred 

in the New York-Northern New 

Jersey-Long Island, NY-NJ-PA Metro 

Area, where about 19 percent of all 

workers used one of these modes, 

followed by the WashingtonArlington-Alexandria, DC-VA-MDWV, and Boston-Cambridge-Quincy, 

MA-NH Metro Areas, at 8.4 and 6.3 

percent, respectively.14

Commuting by Bicycle and 

Walking 

Creating new infrastructure and 

altering existing infrastructure to 

accommodate bicycling and walking has become a goal for several 

metropolitan planning organizations across the United States.15

Tables 3 and 4 show the 10 metro 

areas with the highest percentage of workers who commuted by 

bicycle and walked in 2009. Due 

14 See Table B08006 from the 2009 ACS 

data on American FactFinder at 

<http://factfinder.census.gov>. 15 For example, the Cities for Cycling 

Program is a project of the National 

Association of City Transportation Officials 

that focuses on gathering and disseminating 

information about best practices for implementing bicycle-friendly infrastructure at the 

local level.

Table 2. 

Place of Work by Means of Transportation for Metropolitan Statistical Area Level: 2009

(Numbers in thousands. For information on confidentiality protection, sampling error, nonsampling error, and definitions, 

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

Metropolitan statistical area level

Total

Drove alone Carpooled Public 

transportation Walked All other means

Percent

Margin 

of error1

(±) Percent

Margin 

of error1

(±) Percent

Margin 

of error1

(±) Percent

Margin 

of error1

(±) Percent

Margin 

of error1

(±)

Workers who lived inside

principal city in metro area2 . . . . . . . 44,239 72.1 0.1 10.5 0.1 10.6 0.1 4.4 0.1 2.4 –

Worked inside metro area of residence . 41,838 72.0 0.1 10.2 0.1 10.9 0.1 4.6 0.1 2.3 –

Worked inside different metro area . . . . 1,914 75.7 0.5 14.1 0.4 4.9 0.3 1.6 0.1 3.7 0.3

Worked outside any metro area3 . . . . . . 486 68.7 1.3 16.0 1.1 8.2 0.8 2.9 0.4 4.2 0.5

Workers who lived outside principal 

city in metro area2 . . . . . . . . . . . . . . . 43,164 81.5 0.1 10.3 0.1 3.9 – 2.6 – 1.6 –

Worked inside metro area of residence . 36,684 81.5 0.1 9.9 0.1 4.2 0.1 2.9 0.1 1.4 –

Worked inside different metro area . . . . 5,108 82.0 0.3 11.8 0.3 2.6 0.1 1.0 0.1 2.6 0.1

Worked outside any metro area3 . . . . . . 1,372 81.5 0.5 13.2 0.5 1.0 0.2 1.6 0.2 2.7 0.2

Workers who lived outside

any metro area2, 3 . . . . . . . . . . . . . . . . 45,271 84.8 0.1 10.7 0.1 1.2 – 1.9 – 1.4 –

Worked in metro area . . . . . . . . . . . . . . 3,147 83.9 0.3 13.4 0.3 0.6 0.1 0.6 0.1 1.6 0.1

Worked outside any metro area3 . . . . . . 42,123 84.9 0.1 10.5 0.1 1.2 – 2.0 – 1.4 –

– Represents or rounds to zero.

1 This number, when added to or subtracted from the estimate, represents the 90 percent confidence interval around the estimate. 2

 Workers 16 years and over who did not work at home. 3

 Outside any metropolitan statistical areas includes micropolitan statistical areas.

Note: Because of sampling error, the estimates in this table may not be significantly different from one another.

Source: U.S. Census Bureau, American Community Survey, 2009.
8 U.S. Census Bureau

Figure 6.

Public Transportation Usage for the 50 Largest Metropolitan Statistical Areas: 2009

(Workers 16 years and over. 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, 2009.

Percent of workers

0 5 10 15 20 25 30 35

Oklahoma City, OK

Birmingham-Hoover, AL

Raleigh-Cary, NC

Indianapolis-Carmel, IN

Nashville–Davidson-Murfreesboro–Franklin, TN

Jacksonville, FL

Kansas City, MO-KS

Columbus, OH

Tampa-St. Petersburg-Clearwater, FL

Virginia Beach-Norfolk-Newport News, VA-NC

Memphis, TN-MS-AR

Dallas-Fort Worth-Arlington, TX

Detroit-Warren-Livonia, MI

Riverside-San Bernardino-Ontario, CA

Orlando-Kissimmee, FL

Charlotte-Gastonia-Concord, NC-SC

Richmond, VA

Houston-Sugar Land-Baytown, TX

Phoenix-Mesa-Scottsdale, AZ

San Antonio, TX

Louisville/Jefferson County, KY-IN

Cincinnati-Middletown, OH-KY-IN

St. Louis, MO-IL

New Orleans-Metairie-Kenner, LA

Sacramento–Arden-Arcade–Roseville, CA

Providence-New Bedford-Fall River, RI-MA

Hartford-West Hartford-East Hartford, CT

Austin-Round Rock, TX

Salt Lake City, UT

San Diego-Carlsbad-San Marcos, CA

San Jose-Sunnyvale-Santa Clara, CA

Las Vegas-Paradise, NV

Miami-Fort Lauderdale-Pompano Beach, FL

Buffalo-Niagara Falls, NY

Atlanta-Sandy Springs-Marietta, GA

Milwaukee-Waukesha-West Allis, WI

Cleveland-Elyria-Mentor, OH

Denver-Aurora-Broomfield, CO

Minneapolis-St. Paul-Bloomington, MN-WI

Pittsburgh, PA

Portland-Vancouver-Beaverton, OR-WA

Los Angeles-Long Beach-Santa Ana, CA

Baltimore-Towson, MD

Seattle-Tacoma-Bellevue, WA

Philadelphia-Camden-Wilmington, PA-NJ-DE-MD

Chicago-Naperville-Joliet, IL-IN-WI

Boston-Cambridge-Quincy, MA-NH

Washington-Arlington-Alexandria, DC-VA-MD-WV

San Francisco-Oakland-Fremont, CA

New York-Northern New Jersey-Long Island, NY-NJ-PA
U.S. Census Bureau

9

0 100 Miles

Metropolitan statistical areas defined by the Office of 

Management and Budget as of November 2008.

Source: U.S. Census Bureau, American Community Survey, 2009.

0 100 Miles

0 100 Miles

Percentage of Workers Who Commuted by Public Transby Metropolitan Statistical Area: 2009

10.0 or h5.0 to 9.2.0 to 4.Less tha

U.S. workers 

public transp

(Workers 16 years and over. For information on confidentiality protection, samplin

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

Figure 7.

Percent
10 U.S. Census Bureau

to relatively small sample sizes for 

estimates, the margins of error for 

both the top biking metro areas 

and the top walking metro areas 

tend to be large and, as a result, 

estimates for some metro areas 

may not be statistically different 

from others on the list. 

Some common characteristics stand 

out among the metro areas featured in Tables 3 and 4. Each metro 

area had a population of less than 

500,000 in 2009. Several were also 

home to at least one large college 

or university and had high proportions of college-aged students. 

For example, 18- to 24-year-olds 

accounted for about 17 percent of 

the population of the Missoula, MT 

Metro Area in 2009, and about 25 

percent of the population of the 

Corvallis, OR Metro Area, compared with about 10 percent in 

this age category for the nation 

(not shown).16 Corvallis is the only 

metro area to appear on both the 

bicycle and walking lists. Oregon is 

also notable because the PortlandVancouver-Beaverton, OR-WA Metro 

Area, with a bicycle commuting 

rate of 2.3 percent, was the only 

metro area with a population of 

over 1 million with a bicycle commuting rate of at least 2 percent.

16 See Table S0101 from the 2009 ACS 

data on American FactFinder at <http://

factfinder.census.gov>.

Table 3.

Top Ten Metro Areas for Commutes to Work by Bicycle: 2009

(Numbers in thousands. For information on confidentiality protection, sampling error, 

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

Metropolitan statistical area Commuted by bicycle1

Percent Margin of error2 (±)

Corvallis, OR . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9.3 3.1

Eugene-Springfield, OR . . . . . . . . . . . . . . . . . . . . . . 6.0 1.2

Fort Collins-Loveland, CO . . . . . . . . . . . . . . . . . . . . 5.6 2.1

Boulder, CO . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.4 1.2

Missoula, MT . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.0 1.8

Santa Barbara-Santa Maria-Goleta, CA . . . . . . . . . . 4.0 0.9

Gainesville, FL . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.3 1.2

Logan, UT-ID . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.3 1.4

Chico, CA . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.0 1.2

Bellingham, WA . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.0 1.3

1

 Workers 16 years and over.

2

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

interval around the estimate.

Note: Because of sampling error, the estimates in this table may not be significantly different 

from one another.

Source: U.S. Census Bureau, American Community Survey, 2009.

Table 4.

Top Ten Metro Areas for Commutes to Work by Walking: 2009

(Numbers in thousands. For information on confidentiality protection, sampling error, 

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

Metropolitan statistical area

Walked to work1

Percent Margin of error2 (±)

Ithaca, NY . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15.1 3.2

Corvallis, OR . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11.2 3.0

Ames, IA . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10.4 2.9

Champaign-Urbana, IL . . . . . . . . . . . . . . . . . . . . . . . 9.0 1.5

Manhattan, KS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8.5 2.4

Ocean City, NJ . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8.4 2.9

Iowa City, IA . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8.2 1.4

Hinesville-Fort Stewart, GA . . . . . . . . . . . . . . . . . . . 8.2 5.1

Jacksonville, NC . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8.1 3.0

State College, PA . . . . . . . . . . . . . . . . . . . . . . . . . . . 8.0 2.0

1

 Workers 16 years and over.

2 This number, when added to or subtracted from the estimate, represents the 90 percent confidence 

interval around the estimate.

Note: Because of sampling error, the estimates in this table may not be significantly different 

from one another.

Source: U.S. Census Bureau, American Community Survey, 2009.
U.S. Census Bureau 11

TIME OF DEPARTURE 

FOR WORK

Information about when workers 

leave for work plays an integral 

role in the regional transportation 

planning process, especially by 

contributing to an understanding of 

congestion patterns on the nation’s 

roads and public transportation 

infrastructure. Table 1 suggests 

that the volume of commuter 

travel occurring on the nation’s 

transportation infrastructure varies 

considerably during a typical day. 

The majority of all U.S. workers 

depart in the morning, but there 

are important differences in the 

distribution of departures across 

sociodemographic subgroups, 

means of transportation, and 

subsequent mean travel time. The 

following section highlights these 

differences.17

17 See Supplemental Table B, Time of 

Departure to Work by Selected Characteristics: 2009, at <www.census.gov/hhes

/commuting/>. 

Mean Travel Time by Time of 

Departure and by Means of 

Transportation

Figure 8 shows mean travel time 

by time of departure and means of 

transportation for the United States 

in 2009. The longest average travel 

times were associated with earlymorning departures, and travel 

time decreased as the morning progresses. This trend suggests that 

many workers who depart for work 

relatively early may do so to compensate for long work commutes. 

Figure 8.

Mean Travel Time by Means of Transportation by Time of Departure

(Workers 16 years and over. 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, 2009.

0

10

20

30

40

50

60

70

8:00 a.m. to 8:59 a.m. 9:00 a.m. to 11:59 a.m. 12:00 p.m. to 3:59 p.m. 4:00 p.m. to 11:59 p.m.

12:00 a.m. to 4:59 a.m. 5:00 a.m to 5:59 a.m. 6:00 a.m. to 6:59 a.m. 7:00 a.m. to 7:59 a.m.

Total Drove alone Carpooled Public transportation Walked Other means

Minutes
12 U.S. Census Bureau

Those who relied on public transportation had the longest commutes across all departure-time 

categories, especially in the earliest 

departure categories. Compared 

with all other modes, workers who 

walked to work had the shortest 

mean travel time for every departure-time category. Workers who 

carpooled took longer to get to 

work than those who drove alone. 

This difference was largest for the 

12:00 a.m. to 4:59 a.m. period, 

where mean travel time for carpool 

commuters was 45.1 minutes, 

compared with 30.8 minutes for 

workers who drove alone.

Men Left for Work Earlier 

Than Women

The most common time of departure for both male and female 

workers was between 7:00 a.m. 

and 7:59 a.m. Male workers were 

more likely to leave for work before 

7:00 a.m. than their female counterparts. Almost 40 percent of men 

left before 7:00 a.m., compared 

with less than 25 percent of women 

(see Figure 9). All departure time 

categories from 7:00 a.m. through 

3:59 p.m. included a greater percentage of women than men.

Source: U.S. Census Bureau, . 

Source: U.S. Census Bureau, American Community Survey, 2009.

0

5

10

15

20

25

30

35

4:00 p.m. to

11:59 p.m.

12:00 p.m. to

3:59 p.m.

9:00 a.m. to

11:59 a.m.

8:00 a.m. to

8:59 a.m.

7:00 a.m. to

7:59 a.m.

6:00 a.m. to

 6:59 a.m.

5:00 a.m. to

5:59 a.m.

12:00 a.m. to

 4:59 a.m.

Percent

Female

Male

— Female

Male —

Figure 9.

Time of Departure by Sex of Worker: 2009

(Workers 16 years and over. For information on confidentiality protection, sampling error, nonsampling error, 

and definitions, see www.census.gov/acs/www/)
U.S. Census Bureau 13

Departure Times Varied by 

Occupation

Figure 10 shows that at 10.5 

percent, workers in production, 

transportation, and material 

moving occupations were more 

likely to depart for work between 

12:00 a.m. and 4:59 a.m. than any 

other occupational category. At 

1.9 percent, those in managerial, 

professional, and related occupations had the lowest percentage 

of departures between 12:00 a.m. 

and 4:59 a.m. Over one third of all 

workers in management, professional, and related occupations left 

for work between 7:00 a.m. and 

8:00 a.m. Departures for service 

workers were more evenly distributed across the day compared with 

other occupation categories. For 

service workers, no time of departure category exceeded 20 percent. 

TRAVEL TIME TO WORK 

The ACS asks respondents in the 

workforce how many minutes it 

usually takes them to get from 

home to work (see Figure 1, 

Question 34). Changes in average 

commuting times at the community 

level may reflect several factors 

working in concert, including 

changes in the community’s population and infrastructure, as well 

as shifts in regional labor market 

patterns. As communities change, 

the ACS provides an important 

tool for understanding the social 

and economic forces that influence 

travel time. The 2009 ACS reveals 

that average commute times in 

large metro areas were generally 

longer than those in smaller metro 

areas and that commute times also 

varied across sociodemographic 

characteristics, as discussed in this 

section.18

18 Unless otherwise stated, the travel-time 

information provided in subsequent sections 

is based on Supplemental Table C, Mean 

Travel Time to Work by Means of Transportation and Selected Characteristics: 2009, 

available online at <www.census.gov/hhes

/commuting/>.

Figure 10.

Time of Departure by Occupation: 2009

(Workers 16 years and over. 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, 2009.

0

5

10

15

20

25

30

35

40

8:00 a.m. to 8:59 a.m. 9:00 a.m. to 11:59 a.m. 12:00 p.m. to 3:59 p.m. 4:00 p.m. to 11:59 p.m.

12:00 a.m. to 4:59 a.m. 5:00 a.m. to 5:59 a.m. 6:00 a.m. to 6:59 a.m. 7:00 a.m. to 7:59 a.m.

Production, Armed Forces

transportation, and

material moving

occupations

Construction and

extraction and 

maintenance

occupations

Farming, fishing, and

forestry occupations

Sales and office

 occupations

Management, Service occupations

professional, and

related occupations

Percent
14 U.S. Census Bureau

Men Took Longer to Get to 

Work Than Women 

Overall, the mean travel time for 

male workers was significantly 

longer than for female workers (see 

Figure 11). Men took an average 

of 26.7 minutes to get to work, 

compared with 23.4 minutes for 

women. For all transportation 

modes except walking, the mean 

travel time for women was significantly shorter than it was for men. 

For both male and female workers, 

the average travel time for workers 

who commuted by public transportation was over 20 minutes longer 

than that of their counterparts who 

drove alone.

Demographic Variation in 

Travel Time 

Figure 12 shows mean travel time 

by race and Hispanic origin. NonHispanic White workers had the 

shortest mean travel times for the 

categories of walking and driving 

alone. Non-Hispanic Black workers 

who commuted to work by public transportation had the longest 

average travel time, at 50.0 minutes, although this is not statistically different from that of workers 

of some other race or two or more 

races. Non-Hispanic Black workers 

also had the longest average walking travel time, at about 14 minutes. Hispanic or Latino workers 

had the longest mean travel time 

when carpooling (29.0 minutes), 

but the shortest mean travel time 

for public transportation usage 

(46.0 minutes). 

For all workers combined, public 

transportation commuters averaged 

over 20 minutes longer getting to 

work than those who drove alone.19

Mean travel time also varied by 

nativity status. The average travel 

time for foreign-born workers was 

28.1 minutes, compared with 24.9 

minutes for native-born workers. 

Average Commute Time 

Across Metro Areas and 

Their Components

Table 5 presents mean travel time 

for workers who lived in metropolitan areas for different commute 

types. For example, workers who 

lived in a metro area and worked 

outside any metro area had the 

longest average commute times, at 

43.4 minutes, followed by workers 

who lived outside a principal city 

(in a metropolitan area) and worked 

inside a principal city, who traveled 

an average of 30.4 minutes. For 

each home-to-work trip combination, public transportation commuters had the longest mean travel 

19 See Supplemental Table C, Mean Travel 

Time to Work by Means of Transportation and Selected Characteristics: 2009, at 

<www.census.gov/hhes/commuting/>.

Figure 11.

Mean Travel Time and Means of Transportation 

by Sex: 2009

(In minutes. Workers 16 years and over. 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, 2009.

Female

Male

All other means

Walked

Public

transportation

Carpooled

Drove alone

Total

26.7

23.4

25.3

22.0

30.8

24.6

48.3

47.1

11.2

11.3

28.6

23.7

0 10 20 30 40 50 60
U.S. Census Bureau 15

time, while walkers had the shortest. Workers who took public transportation, lived in a metro area, 

and worked outside any metro area 

had the longest average commute 

time at 71.1 minutes. Workers 

who walked to work and lived and 

worked in a metro area, but outside 

of a principal city, had the shortest 

mean travel time, at 9.6 minutes. 

Table 6 provides ranked lists of 

the metropolitan statistical areas 

with the shortest and longest commutes. Metropolitan area size has 

a considerable bearing on mean 

travel time. The 10 metro areas 

with the shortest mean travel times 

have populations of fewer than 

300,000 people. The Great Falls, 

MT Metro Area had the shortest 

mean travel time at 14.2 minutes, 

although this estimate was not statistically different from that of three 

other metro areas.20

Among the 10 metro areas with 

the longest travel times, several are among the nation’s most 

populous. For example, the New 

York-Northern New Jersey-Long 

Island NY-NJ-PA Metro Area had 

the longest average travel time 

at 34.6 minutes, followed by the 

Washington-Arlington-Alexandria, 

DC-VA-MD-WV Metro Area, with 

an average travel time of 33.4 

minutes. 

20 The travel-time estimate for the Great 

Falls, MT Metro Area is not statistically different from Lewiston, ID-WA; Grand Forks, 

ND-MN; and Cheyenne, WY.

Also among the 10 metro areas 

with the longest commutes are 

several smaller metro areas located 

near a much larger one. For example, the Poughkeepsie-NewburghMiddletown, NY Metro Area had 

the third-longest average commute 

time at 32.2 minutes, which was 

influenced by a substantial percentage of its residents commuting to 

the New York-Northern New JerseyLong Island NY-NJ-PA Metro Area.21

Figure 13 shows the variation in 

mean travel time across metro 

areas in 2009.

21 The travel-time estimate for the 

Poughkeepsie-Newburgh-Middletown, NY 

Metro Area is not statistically different from 

Bremerton-Silverdale, WA.

Figure 12.

Mean Travel Time by Race and Hispanic Origin: 2009

(Workers 16 years and over. 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, 2009.

0

10

20

30

40

50

60

Drove alone Carpooled Public transportation Walked All other means

Some other

race or two or

more races,

non-Hispanic

Asian,

non-Hispanic

Black or

African American, 

non-Hispanic

White, 

non-Hispanic

Hispanic or Latino

(of any race)

Minutes
16 U.S. Census Bureau

Table 5. 

Means of Transportation and Mean Travel Time to Work for Workers Living in 

Metro Areas: 2009

(Travel time to work is in minutes. For information on confidentiality protection, sampling error, nonsampling error, 

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

and 

Place

Total Drove alone Carpooled Public 

transportation Walked All other means

Mean 

travel 

Margin 

of error1

Mean 

travel 

Margin 

of error1

Mean 

travel 

Margin of 

error1

Mean 

travel 

Margin 

of error1

Mean 

travel 

Margin

of error1

Mean 

travel 

Margin 

of error1

time (±) time (±) time (±) time (±) time (±) time (±)

Workers 16 years and over 

 who did not work at home . . . . . 25 .7 – 24 .2 – 28 .0 0 .1 47 .8 0 .2 11 .9 0 .1 27 .5 0 .4

Lived and worked inside same 

 metro area . . . . . . . . . . . . . . . . . . . 24 .2 – 22 .7 – 25 .7 0 .1 47 .0 0 .2 12 .0 0 .1 22 .6 0 .4

 Lived and worked inside 

 same principal city . . . . . . . . . . . 21 .1 0 .1 17 .6 0 .1 20 .8 0 .2 42 .5 0 .2 13 .0 0 .2 19 .4 0 .4

 Lived and worked inside 

 different principal cities . . . . . . . . 28 .6 0 .2 26 .5 0 .2 29 .4 0 .5 49 .9 0 .7 16 .5 1 .5 29 .1 1 .4

 Lived inside principal city, 

 worked outside principal city . . . 26 .1 0 .1 24 .4 0 .1 27 .9 0 .3 53 .3 0 .9 16 .1 1 .0 27 .2 1 .5

 Lived outside principal city, 

 worked inside principal city . . . . 30 .4 0 .1 28 .2 0 .1 32 .0 0 .2 57 .8 0 .4 16 .7 1 .4 30 .9 1 .0

 Lived and worked outside 

 principal city . . . . . . . . . . . . . . . . 21 .9 0 .1 21 .7 0 .1 24 .3 0 .2 42 .9 0 .8 9 .6 0 .2 21 .4 0 .6

Lived in metro area and 

 worked outside metro area . . . . . 43 .4 0 .2 41 .2 0 .2 49 .7 0 .7 71 .1 1 .3 11 .0 0 .7 62 .0 1 .8

– Represents or rounds to zero .

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

Note: Because of sampling error, the estimates in this table may not be significantly different from one another .

Source: U .S . Census Bureau, American Community Survey, 2009 .

Table 6.

Metro Areas With the Longest and Shor

(In minutes. For information on confidentiality protection,

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

test

 s

 C

ampling

omm

 er

utes:

ror, no

 2009

nsampling 

Metropolitan statistical area Mean travel 

time to work1

Margin of error2 

(±)

Ten Longest Commutes

New York-Northern New Jersey-Long Island, NY-NJ-PA . . . 34 .6 0 .1

Washington-Arlington-Alexandria, DC-VA-MD-WV . . . . . . . 33 .4 0 .3

Poughkeepsie-Newburgh-Middletown, NY . . . . . . . . . . . . . . . 32 .2 1 .0

Bremerton-Silverdale, WA . . . . . . . . . . . . . . . . . . . . . . . . . . 30 .8 1 .4

Chicago-Naperville-Joliet, IL-IN-WI3 . . . . . . . . . . . . . . . . . . 30 .7 0 .2

Winchester, VA-WV . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30 .3 2 .1

Atlanta-Sandy Springs-Marietta, GA . . . . . . . . . . . . . . . . . . 30 .1 0 .3

Riverside-San Bernardino-Ontario, CA . . . . . . . . . . . . . . . . 30 .0 0 .4

Stockton, CA . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29 .8 1 .2

Baltimore-Towson, MD . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29 .7 0 .3

Ten Shortest Commutes

Great Falls, MT . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14 .2 0 .8

Lewiston, ID-WA . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14 .7 1 .5

Grand Forks, ND-MN . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15 .1 1 .1

Lubbock, TX . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15 .5 0 .8

Missoula, MT . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15 .8 1 .0

San Angelo, TX . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15 .9 1 .3

Cheyenne, WY . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15 .9 1 .8

Midland, TX . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16 .0 0 .7

Lawton, OK . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16 .0 0 .8

Decatur, IL . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16 .5 0 .9

1

 Workers 16 years and over who did not work at home . 

2

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

interval around the estimate . 3

 The mean travel time for workers in the San Juan-Caguas-Guaynabo, Puerto Rico metropolitan area 

was 30 .8 minutes, the fifth highest among metropolitan areas in the United States and its territories . 

Note: Because of sampling error, the estimates in this table may not be significantly different 

from one another .

Source: U .S . Census Bureau, American Community Survey, 2009 .
U.S. Census Bureau 170 100 Miles Metropolitan statistical areas defined by the Office of Management and Budget as of November 2008. Source: U.S. Census Bure au, American Community Survey, 2009. 0 100 Miles 0 100 Miles Mean Travel Time for Metro Areas: 2009 Mea

MeUn

Figure 13. (Workers 16 years and over. For information on confidentiality protection, samp

error and definitions, see www.census.gov/acs/www)
18 U.S. Census Bureau

SUMMARY

Commuting in the United States 

is dominated by private automobile travel, as is evidenced by the 

large proportion (86.1 percent) of 

workers 16 years and over who 

commuted by car, truck, or van 

in 2009. About three-quarters of 

workers drove to work alone in that 

year. The dominance of the automobile at the national level should 

not obscure the considerable 

variation in modal usage across 

geographic areas. This report 

highlights metro areas with comparatively high usages of transportation modes other than the private 

automobile.

Several smaller metropolitan areas 

have high proportions of workers who commute by walking or 

bicycle, and transit commuters are 

concentrated within a small number of large metropolitan areas. 

Differences in average travel times 

also vary geographically. The metro 

areas with the shortest travel times 

tend to have smaller populations, 

while the longest commutes are 

associated with the nation’s largest 

metro areas.

Some of the most striking categorical differences in commuting 

behavior are found among characteristics associated with race, 

ethnicity, and sex. For example, 

non-Hispanic White workers drove 

alone at a rate of about 10 percentage points higher than that of 

any other racial or ethnic group. 

Hispanic workers carpooled at a 

rate much higher than non-Hispanic 

workers. And non-Hispanic Black 

workers who commuted by public transportation had the longest 

average travel time. Regardless 

of transportation mode (with the 

exception of walking), women generally had shorter travel times and 

later commutes than men. 

Changes in the socioeconomic 

and demographic landscapes of 

communities are accompanied by 

changes in commuting patterns. 

Timely information about commuting patterns enables planners and 

policy makers to make informed 

decisions about investment in the 

nation’s infrastructure, enables 

researchers to identify unmet transportation needs, and provides the 

tools necessary for working toward 

more efficient and equitable transportation solutions. 

ADDITIONAL SOURCES FOR 

COMMUTING DATA 

Additional ACS information related 

to the work commute or place of 

work is available on the Census 

Bureau’s American FactFinder Web 

site at <http://factfinder.census

.gov>. American FactFinder allows 

users to view data for several 

sociodemographic characteristics at 

various geographies. 

The National Household Travel 

Survey (NHTS) is the nation’s largest survey focusing specifically on 

travel. It collects household data 

on daily trips and is not limited to 

the commute. The NHTS provides 

a valuable contribution to understanding national-level travel patterns. More information about the 

NHTS can be found at 

<http://nhts.ornl.gov/>.

Several special tabulations related 

to commuting are available from 

the Census Transportation Planning Products (CTPP). The CTPP is 

a collaborative effort among the 

U.S. Census Bureau and several 

transportation-related agencies 

to produce a set of tabulations 

designed for transportation planners. The CTPP contains residence 

data summarizing worker and 

household characteristics, place 

of work data summarizing worker 

characteristics, and commuting 

flow data. The most recent CTPP 

tabulations are based on the ACS 

3-year data from 2006 to 2008. 

Visit <http://ctpp.transportation

.org> to access CTPP data. 

The Longitudinal EmployerHousehold Dynamics (LEHD) 

dataset relates where people live 

to where they work using quarterly census of employment and 

wages (ES-202) data derived from 

reports filed by all employers 

subject to unemployment compensation laws. LEHD is a project of 

the Census Bureau that combines 

federal and state administrative 

data on employers and employees 

with the rich array of sociodemographic information from decennial 

censuses and the ACS. The LEHD 

dataset potentially provides an 

alternative source of place of work 

and flow data because it is built 

from administrative records, not 

the ACS survey. More information 

about LEHD can be found at 

<http://lehd.did.census.gov/led/>. 

SOURCE OF THE DATA 

AND ACCURACY OF THE 

ESTIMATES

The American Community 

Survey

Many of the findings presented 

in this report were based on the 

American Community Survey (ACS)

data collected in 2009. These data 

were based on the population living in either households or group 
U.S. Census Bureau 19

quarters (which include correctional facilities, nursing homes, 

college dormitories, group homes, 

and overnight shelters) that were 

included in the ACS sample. The 

U.S. Census Bureau is both the 

sponsor and the collector of the 

American Community Survey. The 

2009 ACS is based on a sample of 

just under 3 million housing unit 

addresses and a separate sample of 

just under 200 thousand people living in group quarters. ACS figures 

are estimates based on this sample 

and approximate the actual figures 

that would have been obtained by 

interviewing the entire household 

and group quarters populations 

using the same methodology. The 

estimates from the 2009 ACS sample may also differ from estimate 

based on other survey samples of 

housing units and group quarters 

and the people living within those 

housing units and group quarters.

SAMPLING AND 

NONSAMPLING ERROR

Sampling error occurs when the 

characteristics of a sample are measured instead of those of the entire 

population (as from a census). Note 

that sample-based estimates will 

vary depending on the particular 

sample selected from the population, but all attempt to approximate 

the actual figures. Measures of 

the magnitude of sampling error 

reflect the variation in the estimates over all possible samples 

that could have been selected from 

the population using the same 

sampling, data collection, and 

processing methods. Estimates of 

the magnitude of sampling errors 

are provided in the form of margins 

of error for all key ACS estimates 

included in this report. The Census 

Bureau recommends that data users 

incorporate this information into 

their analyses, as sampling error in 

survey estimates could impact the 

conclusions drawn from the results. 

All comparative statements in this 

report have undergone statistical 

testing, and comparisons are significant at the 90 percent confidence 

level unless noted otherwise. This 

means the 90 percent confidence 

interval for the difference between 

the estimates being compared does 

not include zero. In addition to 

sampling error, nonsampling errors 

may be introduced during any 

phase of data collection or processing. For example, operations such 

as editing, reviewing, or keying 

data from questionnaires may 

introduce error into the estimates. 

The primary source of nonsampling 

error and the processes instituted 

to control error in the 2009 ACS 

are described in further detail in 

the 2009 ACS Accuracy of the Data 

document (see Web link below).

Title 13, U.S. Code, Section 9, 

prohibits the Census Bureau from 

publishing results from which the 

identity of an individual survey 

respondent could be determined. 

For more information on how the 

Census Bureau protects the confidentiality of data, see the 2009 ACS 

Accuracy of the Data document, 

available at <www.census.gov

/acs/www/Downloads/data

_documentation/Accuracy/ACS

_Accuracy_of_Data_2009.pdf>.

FOR MORE INFORMATION

Further information from the 2009 

ACS is available on the Census 

Bureau’s Web site, at <www.census

.gov/acs/www/>. 

Measures of ACS quality—including 

sample size and number of interviews, response and nonresponse 

rates, coverage rates, and item 

allocation rates—are available at

<www.census.gov/acs/www

/methodology/methodology

_main/>. For more information 

about commuting, go to the 

U.S. Census Bureau’s Commuting 

(Journey to Work) Web site, at 

<www.census.gov/hhes

/commuting/>.

CONTACT

Contact U.S. Census Bureau 

Customer Services Center at 

1-800-923-8282 (toll free) or visit 

<ask.census.gov> for further 

information.

SUGGESTED CITATION

McKenzie, Brian, and Melanie 

Rapino. 2011. Commuting in the 

United States: 2009, American 

Community Survey Reports, 

ACS-15. U.S. Census Bureau, 

Washington, DC.

For additional questions or comments, contact Brian McKenzie 

<brian.mckenzie@census.gov> or 

Melanie Rapino <melanie.rapino

@census.gov> at 301-763-2454.