This statistic depicts the average distance people ride on their way to work with public transport in Latin America as of May 2018. In that period, in Mexico's capital Mexico City people had to commute a distance of *** kilometers on average.

Graph and download economic data for Moving 12-Month Total Vehicle Miles Traveled (M12MTVUSM227NFWA) from Dec 1970 to Sep 2025 about miles, travel, vehicles, and USA.

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.

Daily vehicle miles traveled (VMT) is a distance- and volume-based measure of driving on roadways for all motorized vehicle types—car, bus, motorcycle, and truck—on an average day. Per capita VMT is the same measure divided by the same area's population for the same year. Per vehicle VMT divides VMT by the number of household vehicles available by residents of that geography in the same year. These three value types can be selected in the dropdown in the first chart below. Use the legend items to explore various geographies. The second chart below shows per capita and total personal vehicles available to the region’s households from the American Community Survey.

Normalizing VMT by a county or region's population, or household vehicles, is helpful for context, but does not have complete parity with what is measured in VMT estimates. People and vehicles come into the region from other places, just as people and vehicles leave the region to visit other places. VMT per capita compares all miles traveled on the region's roads to the region's population (for all ages) from the U.S. Census Bureau's latest population estimates. Vehicle counts for VMT are classified by vehicle types, but not by vehicle ownership. In 2017, statewide estimates for VMT by motorcycles, passenger cars, and two-axle single-unit trucks with four wheels made up 88% of Pennsylvania's VMT, and 95% of New Jersey's. These vehicle types are highly likely to be personal vehicles, owned by households, but a small percent could be fleet vehicles of companies or governments. The remaining VMT is made up of vehicle types like school and commercial buses and trucks with more than two axles so they are highly likely to be commercial vehicles.

This table contains data on the annual miles traveled by place of occurrence and by mode of transportation (vehicle, pedestrian, bicycle), for California, its regions, counties, and cities/towns. The ratio uses data from the California Department of Transportation, the U.S. Department of Transportation, and the U.S. Census Bureau. The table is part of a series of indicators in the Healthy Communities Data and Indicators Project of the Office of Health Equity. Miles traveled by individuals and their choice of mode – car, truck, public transit, walking or bicycling – have a major impact on mobility and population health. Miles traveled by automobile offers extraordinary personal mobility and independence, but it is also associated with air pollution, greenhouse gas emissions linked to global warming, road traffic injuries, and sedentary lifestyles. Active modes of transport – bicycling and walking alone and in combination with public transit – offer opportunities for physical activity, which has many documented health benefits. More information about the data table and a data dictionary can be found in the About/Attachments section.

Graph and download economic data for Mean Commuting Time for Workers (5-year estimate) in Fairfield County, CT (B080ACS009001) from 2009 to 2021 about Fairfield County, CT; Bridgeport; commuting time; CT; workers; average; 5-year; and USA.

Context

The San Francisco Bay Area (nine-county) is one of the largest urban areas in the US by population and GDP. It is home to over 7.5 million people and has a GDP of $995 billion (third highest by GDP output and first highest by GDP per capita). Home to Silicon Valley (a global center for high technology and innovation) and San Francisco (the second largest financial center in the US after New York), the Bay Area contains some of the most profitable industries and sophisticated workforces in the world. This dataset describes where these workers live and commute to work in 2018.

Content

This data file includes all needed information as a means to find out more about the different commute patterns, geographical locations, and necessary metrics to make predictions and draw conclusions.

Inspiration

• What can we learn about the different residence and workplace locations? What is the average distance between these locations?
• Which counties contain a high/low concentration of residence and workplace locations? Why?
• What counties do most of the commuters usually commute to work? What counties do most of the commuters call home?
• Are most of these commute patterns county-by-county or within a single county?
• Are there any noticeable outliers (e.g., long commute patterns) in this dataset? What counties contain a high concentration of these outliers?