This table shows the number and percent of people in the United States potentially exposed to different levels of noise from road sources.

Bikeshare ridership by system, year, month, and hour the trip ended at for bikeshare systems with docking stations. Data available by month starting in January 2019. Months are rearranged to include the same number of days of the week across years (see below). Data designed to show the impacts of COVID-19 on bikeshare ridership as featured at https://maps.dot.gov/BTS/dockedbikeshare-COVID/

Ridership data not available for all docked bikeshare systems. Only docked bikeshare systems with ridership data shown. Some systems included in the data permit users to leave a bicycle outside of a docking station; these trips are indicated by the trip type. Trips defined as rides from point A to B. If user makes trip from B to A on same day, counted as a second trip. Trips labeled as round trips in Metro Bike Share and Indego trip files counted as 2 trips. Trips with no trip time are not counted. For trips starting and ending at a docking station or on systems where only docked trips are permitted, trips with no start station identifier and/or end station id are not counted in totals. Trips shorter than 1 minute or greater than 2 hours excluded. Days aligned to include the same days of weeks in 2019 and 2020. Days included in each month are as follows:

Days included in each month are as follows:
Jan 2019 (01/02/19 through 02/02/19); Jan 2020 (01/01/20 through 02/01/20); Jan 2021 (12/30/20 through 01/30/21); Jan 2022 (12/29/2021 through 01/29/22)
Feb 2019 (02/03/19 through 03/02/19); Feb 2020 (02/02/20 through 02/29/20); Feb 2021 (01/31/21 through 02/27/21); Feb 2022 (01/30/22 through 02/26/22)
Mar 2019 (03/03/19 through 03/30/19); Mar 2020 (03/01/20 through 03/28/20); Mar 2021 (02/28/21 through 03/29/21); Mar 2022 (02/27/22) through 03/26/22)
Apr 2019 (03/31/19 through 05/04/19); Apr 2020 (03/29/20 through 05/02/20); Apr 2021 (03/28/21 through 05/01/21); Apr 2022 (03/27/22 through 04/30/22)
May 2019 (05/05/19 through 06/01/19); May 2020 (05/03/20 through 05/30/20); May 2021 (05/02/21 through 05/29/21); May 2022 (05/01/22 through 05/28/22)
Jun 2019 (06/02/19 through 06/29/19); Jun 2020 (05/31/20 through 06/27/20); Jun 2021 (05/30/21 through 06/26/21); Jun 2022 (05/29/22 through 06/25/22)
Jul 2019 (06/30/19 through 08/03/19); Jul 2020 (06/28/20 through 08/01/20); Jul 2021 (06/27/21 through 07/31/21); Jul (06/26/22 through 07/30/22)
Aug 2019 (08/04/19 through 08/31/19); Aug 2020 (08/02/20 through 08/29/20); Aug 2021 (08/01/21 through 08/28/21); Aug (07/31/22 through 08/27/22)
Sep 2019 (09/01/19 through 10/05/19); Sep 2020 (08/30/20 through 10/03/20); Sep 2021 (08/29/21 through 10/02/21); Sep 2022 (08/28/22 through 10/01/22)
Oct 2019 (10/06/19 through 11/02/19); Oct 2020 (10/04/20 through 10/31/20); Oct 2021 (10/03/21 through 10/30/21); Oct 2022 (10/02/22 through 10/29/22)
Nov 2019 (11/03/19 through 11/30/19); Nov 2020 (11/01/20 through 11/28/20); Nov 2021 (10/31/21 through 11/27/21); Nov 2022 (10/30/22 through 11/26/22)
Dec 2019 (12/01/19 through 12/31/19); Dec 2020 (11/29/20 through 12/29/20); Dec 2021 (11/28/21 through 12/28/21); Dec 2022 (11/27/22 through 12/27/22)

Trips beginning on 12/31/2019 but ending on 01/01/2020 not included in totals.

Interactive map application featuring data: https://maps.dot.gov/BTS/dockedbikeshare-COVID/

How many people are staying at home? How far are people traveling when they don’t stay home? Which states and counties have more people taking trips? The Bureau of Transportation Statistics (BTS) now provides answers to those questions through our new mobility statistics.

The Trips by Distance data and number of people staying home and not staying home are estimated for the Bureau of Transportation Statistics by the Maryland Transportation Institute and Center for Advanced Transportation Technology Laboratory at the University of Maryland. The travel statistics are produced from an anonymized national panel of mobile device data from multiple sources. All data sources used in the creation of the metrics contain no personal information. Data analysis is conducted at the aggregate national, state, and county levels. A weighting procedure expands the sample of millions of mobile devices, so the results are representative of the entire population in a nation, state, or county. To assure confidentiality and support data quality, no data are reported for a county if it has fewer than 50 devices in the sample on any given day.

Trips are defined as movements that include a stay of longer than 10 minutes at an anonymized location away from home. Home locations are imputed on a weekly basis. A movement with multiple stays of longer than 10 minutes before returning home is counted as multiple trips. Trips capture travel by all modes of transportation. including driving, rail, transit, and air.

The daily travel estimates are from a mobile device data panel from merged multiple data sources that address the geographic and temporal sample variation issues often observed in a single data source. The merged data panel only includes mobile devices whose anonymized location data meet a set of data quality standards, which further ensures the overall data quality and consistency. The data quality standards consider both temporal frequency and spatial accuracy of anonymized location point observations, temporal coverage and representativeness at the device level, spatial representativeness at the sample and county level, etc. A multi-level weighting method that employs both device and trip-level weights expands the sample to the underlying population at the county and state levels, before travel statistics are computed.

These data are experimental and may not meet all of our quality standards. Experimental data products are created using new data sources or methodologies that benefit data users in the absence of other relevant products. We are seeking feedback from data users and stakeholders on the quality and usefulness of these new products. Experimental data products that meet our quality standards and demonstrate sufficient user demand may enter regular production if resources permit.

Heavy trucks include trucks with more than 14,000 pounds gross vehicle weight. Prior to the 2003 Benchmark Revision heavy trucks were more than 10,000 pounds. The U.S. Bureau of Economic Analysis releases auto and truck sales data, which are used in the preparation of estimates of personal consumption expenditures.

Labor force participation rate is the percent of persons classified as employed or unemployed as a percent of the civilian noninstitutional population. The Bureau of Labor Statistics produces industry estimates of nonfarm payroll employment as part of the Current Population Survey. Employment data are seasonally adjusted to remove the effects of normal seasonal variation.