The Bureau of Transportation Statistics (BTS) Border Crossing Data provide summary statistics for inbound crossings at the U.S.-Canada and the U.S.-Mexico border at the port level. Data are available for trucks, trains, containers, buses, personal vehicles, passengers, and pedestrians. Border crossing data are collected at ports of entry by U.S. Customs and Border Protection (CBP). The data reflect the number of vehicles, containers, passengers or pedestrians entering the United States. CBP does not collect comparable data on outbound crossings. Users seeking data on outbound counts may therefore want to review data from individual bridge operators, border state governments, or the Mexican and Canadian governments.

The Bureau of Transportation Statistics (BTS) Border Crossing Data provide summary statistics for inbound crossings at the U.S.-Canada and the U.S.-Mexico border at the port level. Data are available for trucks, trains, containers, buses, personal vehicles, passengers, and pedestrians. Border crossing data are collected at ports of entry by U.S. Customs and Border Protection (CBP). The data reflect the number of vehicles, containers, passengers or pedestrians entering the United States. CBP does not collect comparable data on outbound crossings. Users seeking data on outbound counts may therefore want to review data from individual bridge operators, border state governments, or the Mexican and Canadian governments.

The Bikeshare Scooter Systems dataset was compiled on August 10, 2021 and was updated throughout July 2022 from the Bureau of Transportation Statistics (BTS) and is part of the U.S. Department of Transportation (USDOT)/Bureau of Transportation Statistics (BTS) National Transportation Atlas Database (NTAD). It is a list of cities served by a bikeshare and/or e-scooter system collected each year from 2015 to 2021. Some systems serve more than one city. The layer lists just the primary city served. Bikeshare includes systems that are open to the general public, IT-automated, and station based (contain hubs to which users can grab and return a bike) as well as dockless systems. The layer includes a count of the number of docking stations, the number of dockless bikeshare systems, and the number of e-scooter systems serving a city (if applicable) in each year. Counts are for 12/31 of the year.

The Bikeshare Scooter Systems dataset was compiled on August 10, 2021 and was updated throughout July 2022 from the Bureau of Transportation Statistics (BTS) and is part of the U.S. Department of Transportation (USDOT)/Bureau of Transportation Statistics (BTS) National Transportation Atlas Database (NTAD). It is a list of cities served by a bikeshare and/or e-scooter system collected each year from 2015 to 2021. Some systems serve more than one city. The layer lists just the primary city served. Bikeshare includes systems that are open to the general public, IT-automated, and station based (contain hubs to which users can grab and return a bike) as well as dockless systems. The layer includes a count of the number of docking stations, the number of dockless bikeshare systems, and the number of e-scooter systems serving a city (if applicable) in each year. Counts are for 12/31 of the year.

The Bikeshare dataset was compiled on August 10, 2021 and was updated October 19, 2022 from the Bureau of Transportation Statistics (BTS) and is part of the U.S. Department of Transportation (USDOT)/Bureau of Transportation Statistics (BTS) National Transportation Atlas Database (NTAD). The IPCD is a nationwide database of passenger transportation terminals, with data on the availability of connections among the various scheduled public transportation modes at each facility. The IPCD data covers the following types of passenger transportation terminals/stops: 1. Scheduled airline service airports. 2. Intercity bus stations (includes stations served by regular scheduled intercity bus service such as Greyhound, Trailways, code sharing buses such as Amtrak Thruway feeder buses, supplemental buses that provide additional frequencies along rail routes, and airport bus services from locations that are outside of the airport metropolitan area). 3. Intercity and transit ferry terminals. 4. Light-rail transit stations. 5. Heavy-rail transit stations. 6. Passenger-rail stations on the national rail network served by intercity rail and/or commuter rail services. 7. Bike-share stations belonging to bike-share systems that are open to the general public, IT-automated, and station based (contain hubs to which users can grab and return a bike). The data elements describe the location of the above types of terminals as well as the availability of intercity, commuter, and transit rail; scheduled air service; intercity and transit bus; intercity and transit ferry services; and bike-share availability. Transit bus service locations are not specifically included in the database. However, the status of transit bus as a connecting mode is included for each bike-share facility in the database.

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.

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.

Estimates of average weekday household person trips, vehicle trips, person miles traveled, and vehicle miles traveled (per day), for all Census tracts in the United States.

Maps of Value, Tonnage, Ton-Miles and Average Miles per Shipment by State