According to the Statista Consumer Insights, for the period between October 2023 and September 2024, around of U.S. American workers spent an average of **** an hour or less commuting to work. In the period between 2019 and 2024, the share of workers commuting less than ** minutes dropped by ***** percentage points to ** percent, while the share of workers commuting over **** an hour decreased from ** to ** percent. Rise of hybrid work models The transformation in commute times coincides with a surge in hybrid work arrangements. By the second quarter of 2024, ** percent of U.S. workers reported adopting a hybrid work model, blending remote and on-site work. This shift, initially sparked by the COVID-19 pandemic, has reshaped how Americans balance their professional and personal lives, offering increased flexibility and potentially reducing overall commute times for many. Driving remains most common form of commuting Among those workers who continue to travel to their place of work, driving remained the most popular mode. Over ********** of U.S. Americans drove to work by car, truck or van in 2022 and an additional nearly **** percent used a carpool to get to their job. Public transportation, meanwhile, was only used by *** percent of workers.
When asked about "Duration of daily commute", ** percent of U.S. respondents answer "15 to ** minutes". This online survey was conducted in 2025, among ****** consumers.
According to the Statista Consumer Insights, for the period between October 2022 and September 2023, just over half of Brazilian workers had an average daily commute time of less than half an hour. Between 2019 and 2023, the share of workers commuting 15 to 19 minutes increased by four percentage points, while the share of workers who commuted 60 to 119 minutes decreased by three percentage points.
Mean travel time to work (minutes) DP03_0025E County and State values are from the ACS 1 Year Survey.
https://www.census.gov/data/developers/about/terms-of-service.htmlhttps://www.census.gov/data/developers/about/terms-of-service.html
Average commute time in each U.S. county in minutes.
This product uses the Census Bureau Data API but is not endorsed or certified by the Census Bureau.
The Travel Time to Work indicator compares the mean, or average, commute time for Champaign County residents to the mean commute time for residents of Illinois and the United States as a whole. On its own, mean travel time of all commuters on all mode types could be reflective of a number of different conditions. Congestion, mode choice, changes in residential patterns, changes in the location of major employment centers, and changes in the transit network can all impact travel time in different and often conflicting ways. Since the onset of the COVID-19 pandemic in 2020, the workplace location (office vs. home) is another factor that can impact the mean travel time of an area. We don’t recommend trying to draw any conclusions about conditions in Champaign County, or anywhere else, based on mean travel time alone.
However, when combined with other indicators in the Mobility category (and other categories), mean travel time to work is a valuable measure of transportation behaviors in Champaign County.
Champaign County’s mean travel time to work is lower than the mean travel time to work in Illinois and the United States. Based on this figure, the state of Illinois has the longest commutes of the three analyzed areas.
The year-to-year fluctuations in mean travel time have been statistically significant in the United States since 2014, and in Illinois in 2021 and 2022. Champaign County’s year-to-year fluctuations in mean travel time were statistically significant from 2021 to 2022, the first time since this data first started being tracked in 2005.
Mean travel time data was sourced from the U.S. Census Bureau’s American Community Survey (ACS) 1-Year Estimates, which are released annually.
As with any datasets that are estimates rather than exact counts, it is important to take into account the margins of error (listed in the column beside each figure) when drawing conclusions from the data.
Due to the impact of the COVID-19 pandemic, instead of providing the standard 1-year data products, the Census Bureau released experimental estimates from the 1-year data in 2020. This includes a limited number of data tables for the nation, states, and the District of Columbia. The Census Bureau states that the 2020 ACS 1-year experimental tables use an experimental estimation methodology and should not be compared with other ACS data. For these reasons, and because data is not available for Champaign County, no data for 2020 is included in this Indicator.
For interested data users, the 2020 ACS 1-Year Experimental data release includes a dataset on Travel Time to Work.
Sources: U.S. Census Bureau; American Community Survey, 2023 American Community Survey 1-Year Estimates, Table S0801; generated by CCRPC staff; using data.census.gov; (16 October 2024).; U.S. Census Bureau; American Community Survey, 2022 American Community Survey 1-Year Estimates, Table S0801; generated by CCRPC staff; using data.census.gov; (10 October 2023).; U.S. Census Bureau; American Community Survey, 2021 American Community Survey 1-Year Estimates, Table S0801; generated by CCRPC staff; using data.census.gov; (17 October 2022).; U.S. Census Bureau; American Community Survey, 2019 American Community Survey 1-Year Estimates, Table S0801; generated by CCRPC staff; using data.census.gov; (29 March 2021).; U.S. Census Bureau; American Community Survey, 2018 American Community Survey 1-Year Estimates, Table S0801; generated by CCRPC staff; using data.census.gov; (29 March 2021).; U.S. Census Bureau; American Community Survey, 2017 American Community Survey 1-Year Estimates, Table S0801; generated by CCRPC staff; using American FactFinder; (13 September 2018).; U.S. Census Bureau; American Community Survey, 2016 American Community Survey 1-Year Estimates, Table S0801; generated by CCRPC staff; using American FactFinder; (14 September 2017).; U.S. Census Bureau; American Community Survey, 2015 American Community Survey 1-Year Estimates, Table S0801; generated by CCRPC staff; using American FactFinder; (19 September 2016).; U.S. Census Bureau; American Community Survey, 2014 American Community Survey 1-Year Estimates, Table S0801; generated by CCRPC staff; using American FactFinder; (16 March 2016).; U.S. Census Bureau; American Community Survey, 2013 American Community Survey 1-Year Estimates, Table S0801; generated by CCRPC staff; using American FactFinder; (16 March 2016).; U.S. Census Bureau; American Community Survey, 2012 American Community Survey 1-Year Estimates, Table S0801; generated by CCRPC staff; using American FactFinder; (16 March 2016).; U.S. Census Bureau; American Community Survey, 2011 American Community Survey 1-Year Estimates, Table S0801; generated by CCRPC staff; using American FactFinder; (16 March 2016).; U.S. Census Bureau; American Community Survey, 2010 American Community Survey 1-Year Estimates, Table S0801; generated by CCRPC staff; using American FactFinder; (16 March 2016).; U.S. Census Bureau; American Community Survey, 2009 American Community Survey 1-Year Estimates, Table S0801; generated by CCRPC staff; using American FactFinder; (16 March 2016).; U.S. Census Bureau; American Community Survey, 2008 American Community Survey 1-Year Estimates, Table S0801; generated by CCRPC staff; using American FactFinder; (16 March 2016).; U.S. Census Bureau; American Community Survey, 2007 American Community Survey 1-Year Estimates, Table S0801; generated by CCRPC staff; using American FactFinder; (16 March 2016).; U.S. Census Bureau; American Community Survey, 2006 American Community Survey 1-Year Estimates, Table S0801; generated by CCRPC staff; using American FactFinder; (16 March 2016).; U.S. Census Bureau; American Community Survey, 2005 American Community Survey 1-Year Estimates, Table S0801; generated by CCRPC staff; using American FactFinder; (16 March 2016).
https://fred.stlouisfed.org/legal/#copyright-public-domainhttps://fred.stlouisfed.org/legal/#copyright-public-domain
Graph and download economic data for Mean Commuting Time for Workers (5-year estimate) in Dallas County, TX (B080ACS048113) from 2009 to 2023 about Dallas County, TX; commuting time; Dallas; workers; average; TX; 5-year; and USA.
VITAL SIGNS INDICATOR
Commute Time (T3)
FULL MEASURE NAME
Commute time by residential location
LAST UPDATED
January 2023
DESCRIPTION
Commute time refers to the average number of minutes a commuter spends traveling to work on a typical day. The dataset includes metropolitan area, county, city, and census tract tables by place of residence.
DATA SOURCE
U.S. Census Bureau: Decennial Census (1980-2000) - via MTC/ABAG Bay Area Census - http://www.bayareacensus.ca.gov/transportation.htm
U.S. Census Bureau: American Community Survey - https://data.census.gov/
2006-2021
Form C08136
Form C08536
Form B08301
Form B08301
Form B08301
CONTACT INFORMATION
vitalsigns.info@bayareametro.gov
METHODOLOGY NOTES (across all datasets for this indicator)
For the decennial Census datasets, breakdown of commute times was unavailable by mode; only overall data could be provided on a historical basis.
For the American Community Survey (ACS) datasets, 1-year rolling average data was used for all metros, region and county geographic levels, while 5-year rolling average data was used for cities and tracts. This is due to the fact that more localized data is not included in the 1-year dataset across all Bay Area cities. Similarly, modal data is not available for every Bay Area city or census tract, even when the 5-year data is used for those localized geographies.
Regional commute times were calculated by summing aggregate county travel times and dividing by the relevant population; similarly, modal commute times were calculated using aggregate times and dividing by the number of communities choosing that mode for the given geography.
Census tract data is not available for tracts with insufficient numbers of residents. The metropolitan area comparison was performed for the nine-county San Francisco Bay Area in addition to the primary metropolitan statistical areas (MSAs) for the nine other major metropolitan areas.
This statistic illustrates the average daily commute times in various countries of the European Union (EU) in 2014 in minutes and by gender. While the average daily commuting time of men in the EU increases if they have children, the average commuting time of women with children decreases.
VITAL SIGNS INDICATOR Commute Time (T4)
FULL MEASURE NAME Commute time by employment location
LAST UPDATED April 2020
DESCRIPTION Commute time refers to the average number of minutes a commuter spends traveling to work on a typical day. The dataset includes metropolitan area, county, city, and census tract tables by place of residence.
DATA SOURCE U.S. Census Bureau: Decennial Census (1980-2000) - via MTC/ABAG Bay Area Census http://www.bayareacensus.ca.gov/transportation.htm
U.S. Census Bureau: American Community Survey Table B08536 (2018 only; by place of employment) Table B08601 (2018 only; by place of employment) www.api.census.gov
CONTACT INFORMATION vitalsigns.info@bayareametro.gov
METHODOLOGY NOTES (across all datasets for this indicator) For the decennial Census datasets, breakdown of commute times was unavailable by mode; only overall data could be provided on a historical basis.
For the American Community Survey datasets, 1-year rolling average data was used for all metros, region, and county geographic levels, while 5-year rolling average data was used for cities and tracts. This is due to the fact that more localized data is not included in the 1-year dataset across all Bay Area cities. Similarly, modal data is not available for every Bay Area city or census tract, even when the 5-year data is used for those localized geographies.
Regional commute times were calculated by summing aggregate county travel times and dividing by the relevant population; similarly, modal commute time were calculated using aggregate times and dividing by the number of communities choosing that mode for the given geography. Census tract data is not available for tracts with insufficient numbers of residents.
The metropolitan area comparison was performed for the nine-county San Francisco Bay Area in addition to the primary MSAs for the nine other major metropolitan areas.
https://www.usa.gov/government-works/https://www.usa.gov/government-works/
AGGREGATE TRAVEL TIME TO WORK (IN MINUTES) OF WORKERS BY TRAVEL TIME TO WORK Survey/Program: American Community Survey Universe: Workers 16 years and over who did not work at home TableID: B08135 Product: 2019: ACS 1-Year Estimates Detailed Tables
VITAL SIGNS INDICATOR
Commute Time (T3)
FULL MEASURE NAME
Commute time by residential location
LAST UPDATED
January 2023
DESCRIPTION
Commute time refers to the average number of minutes a commuter spends traveling to work on a typical day. The dataset includes metropolitan area, county, city, and census tract tables by place of residence.
DATA SOURCE
U.S. Census Bureau: Decennial Census (1980-2000) - via MTC/ABAG Bay Area Census - http://www.bayareacensus.ca.gov/transportation.htm
U.S. Census Bureau: American Community Survey - https://data.census.gov/
2006-2021
Form C08136
Form C08536
Form B08301
Form B08301
Form B08301
CONTACT INFORMATION
vitalsigns.info@bayareametro.gov
METHODOLOGY NOTES (across all datasets for this indicator)
For the decennial Census datasets, breakdown of commute times was unavailable by mode; only overall data could be provided on a historical basis.
For the American Community Survey (ACS) datasets, 1-year rolling average data was used for all metros, region and county geographic levels, while 5-year rolling average data was used for cities and tracts. This is due to the fact that more localized data is not included in the 1-year dataset across all Bay Area cities. Similarly, modal data is not available for every Bay Area city or census tract, even when the 5-year data is used for those localized geographies.
Regional commute times were calculated by summing aggregate county travel times and dividing by the relevant population; similarly, modal commute times were calculated using aggregate times and dividing by the number of communities choosing that mode for the given geography.
Census tract data is not available for tracts with insufficient numbers of residents. The metropolitan area comparison was performed for the nine-county San Francisco Bay Area in addition to the primary metropolitan statistical areas (MSAs) for the nine other major metropolitan areas.
Open Government Licence - Canada 2.0https://open.canada.ca/en/open-government-licence-canada
License information was derived automatically
Data on the main mode of commuting by commuting duration, distance (straight-line) from home to work and time leaving for work.
The average time spent traveling in Italy peaked at 67 minutes per capita in 2008. The lowest time was found in 2020 when Italians, on average, spent about 48 minutes per capita commuting, in part caused by the travel restrictions during the COVID-19 pandemic.
When asked about "Duration of daily commute", ** percent of Indonesian respondents answer "15 to ** minutes". This online survey was conducted in 2024, among ***** consumers.As an element of Statista Consumer Insights, our Consumer Insights Global survey offers you up-to-date market research data from over ** countries and territories worldwide.
Open Government Licence - Canada 2.0https://open.canada.ca/en/open-government-licence-canada
License information was derived automatically
This table provides statistical information about people in Canada by their demographic, social and economic characteristics as well as provide information about the housing units in which they live.
On average, it took the respondents around ** minutes to travel about five to ten kilometers in the urban cities across India for work and education according to a survey. Walking was the most preferred mode of transportation by urban dwellers for their weekly needs, followed by personal motorbike in the south Asian country.
https://data.go.kr/ugs/selectPortalPolicyView.dohttps://data.go.kr/ugs/selectPortalPolicyView.do
The average daily travel time is the average time that public transportation users spend moving during the day, and is an important indicator for evaluating the efficiency and user convenience of public transportation services. This data is used for traffic demand management, congestion relief, policy establishment for shortening travel times, adjustment of dispatch intervals, route optimization, etc., and also contributes to regional traffic congestion analysis and improvement of public transportation service quality. It is also actively used as basic data for urban transportation infrastructure planning and environmental improvement strategy establishment. The scope of provision is the average travel time for daily/monthly/annual travel.
VITAL SIGNS INDICATOR
Commute Time (T3)
FULL MEASURE NAME
Commute time by residential location
LAST UPDATED
January 2023
DESCRIPTION
Commute time refers to the average number of minutes a commuter spends traveling to work on a typical day. The dataset includes metropolitan area, county, city, and census tract tables by place of residence.
DATA SOURCE
U.S. Census Bureau: Decennial Census (1980-2000) - via MTC/ABAG Bay Area Census - http://www.bayareacensus.ca.gov/transportation.htm
U.S. Census Bureau: American Community Survey - https://data.census.gov/
2006-2021
Form C08136
Form C08536
Form B08301
Form B08301
Form B08301
CONTACT INFORMATION
vitalsigns.info@bayareametro.gov
METHODOLOGY NOTES (across all datasets for this indicator)
For the decennial Census datasets, breakdown of commute times was unavailable by mode; only overall data could be provided on a historical basis.
For the American Community Survey (ACS) datasets, 1-year rolling average data was used for all metros, region and county geographic levels, while 5-year rolling average data was used for cities and tracts. This is due to the fact that more localized data is not included in the 1-year dataset across all Bay Area cities. Similarly, modal data is not available for every Bay Area city or census tract, even when the 5-year data is used for those localized geographies.
Regional commute times were calculated by summing aggregate county travel times and dividing by the relevant population; similarly, modal commute times were calculated using aggregate times and dividing by the number of communities choosing that mode for the given geography.
Census tract data is not available for tracts with insufficient numbers of residents. The metropolitan area comparison was performed for the nine-county San Francisco Bay Area in addition to the primary metropolitan statistical areas (MSAs) for the nine other major metropolitan areas.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
This table contains information regarding the mobility of the residents of the Netherlands aged 6 or older in private households, so excluding residents of institutions and homes. The table contains per person per day /year an overview of the average number of trips, the average distance travelled and the average time travelled. These are regular trips on Dutch territory, including domestic holiday mobility. The distance travelled is based on stage information. Excluded in this table is mobility based on series of calls trips. The mobility behaviour is broken down by modes of travel, purposes of travel, population and region characteristics. The data used are retrieved from The Dutch National travel survey named Onderweg in Nederland (ODiN). Data available from: 2018
Status of the figures: The figures in this table are final.
Changes as of 4 July 2024: The figures for year 2023 are added.
When will new figures be published? Figures for the 2024 research year will be published in mid-2025
According to the Statista Consumer Insights, for the period between October 2023 and September 2024, around of U.S. American workers spent an average of **** an hour or less commuting to work. In the period between 2019 and 2024, the share of workers commuting less than ** minutes dropped by ***** percentage points to ** percent, while the share of workers commuting over **** an hour decreased from ** to ** percent. Rise of hybrid work models The transformation in commute times coincides with a surge in hybrid work arrangements. By the second quarter of 2024, ** percent of U.S. workers reported adopting a hybrid work model, blending remote and on-site work. This shift, initially sparked by the COVID-19 pandemic, has reshaped how Americans balance their professional and personal lives, offering increased flexibility and potentially reducing overall commute times for many. Driving remains most common form of commuting Among those workers who continue to travel to their place of work, driving remained the most popular mode. Over ********** of U.S. Americans drove to work by car, truck or van in 2022 and an additional nearly **** percent used a carpool to get to their job. Public transportation, meanwhile, was only used by *** percent of workers.