Registration information on interstate, intrastate non-hazmat, and intrastate truck and bus companies that operate in the United States and have registered with FMCSA. Contains contact information and demographic information (number of drivers, vehicles, commodities carried, etc).

This is a "daily difference" dataset. See dataset attachment "FMCSA Dataset Description and Data Definitions - Select Datasets" for more information. Records for carriers/brokers/freight forwarders with active, inactive, or pending authorities (common or contract). It includes the DOT number and MC/FF/MX number for the carrier/broker/freight forwarder, along with company census data, e.g., types of authority, address, types of insurance on file, and amounts of insurance on file.

United States Department of Transportation Public Data Listing. The file is formatted to comply with project open data common core metadata requirements (http://project-open-data.github.io/schema/) and conforms to schema version 1.1

This dataset is a list of Department of Transportation (DOT) Artificial Intelligence (AI) use cases. Artificial intelligence (AI) promises to drive the growth of the United States economy and improve the quality of life of all Americans. Pursuant to Section 5 of Executive Order (EO) 13960, "Promoting the Use of Trustworthy Artificial Intelligence in the Federal Government," Federal agencies are required to inventory their AI use cases and share their inventories with other government agencies and the public. In accordance with the requirements of EO 13960, this spreadsheet provides the mechanism for federal agencies to create their inaugural AI use case inventories. https://www.federalregister.gov/documents/2020/12/08/2020-27065/promoting-the-use-of-trustworthy-artificial-intelligence-in-the-federal-government

This dataset provides lane closure occurrences within the Texas Department of Transportation (TxDOT) highway system in a tabular format. A continuously updating archive of the TxDOT WZDx feed data can be found at ITS WorkZone Raw Data Sandbox and the ITS WorkZone Semi-Processed Data Sandbox. The live feed is currently compliant with the Work Zone Data Exchange (WZDx) Specification version 2.0.

About Transportation Services Index

The Transportation Services Index (TSI), created by the U.S. Department of Transportation (DOT), Bureau of Transportation Statistics (BTS), measures the movement of freight and passengers. The index, which is seasonally adjusted, combines available data on freight traffic, as well as passenger travel, that have been weighted to yield a monthly measure of transportation services output.

For charts and discussion on the relationship of the TSI to the economy, see our Transportation as an Economic Indicator: Transportation Services Index page (https://data.bts.gov/stories/s/TET-indicator-1/9czv-tjte)

For release schedule see: https://www.bts.gov/newsroom/transportation-services-index-release-schedule

About seasonally-adjusted data

Statisticians use the process of seasonal-adjustment to uncover trends in data. Monthly data, for instance, are influenced by the number of days and the number of weekends in a month as well as by the timing of holidays and seasonal activity. These influences make it difficult to see underlying changes in the data. Statisticians use seasonal adjustment to control for these influences.

Controlling of seasonal influences allows measurement of real monthly changes; short and long term patterns of growth or decline; and turning points. Data for one month can be compared to data for any other month in the series and the data series can be ranked to find high and low points. Any observed differences are “real” differences; that is, they are differences brought about by changes in the data and not brought about by a change in the number of days or weekends in the month, the occurrence or non-occurrence of a holiday, or seasonal activity.

This data set contains information about the Department of Transportation's cybersecurity incident response tickets, incident response metrics, incident response time, vulnerability data, and remediation recommendations broken down by OA. The CSMC owns maintains, collects, and operates this data as a service for the entire department.

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 mobility statistics program.

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.

These data are made available under a public domain license. Data should be attributed to the "Maryland Transportation Institute and Center for Advanced Transportation Technology Laboratory at the University of Maryland and the United States Bureau of Transportation Statistics."

Daily data for a given week will be uploaded to the BTS website within 9-10 days of the end of the week in question (e.g., data for Sunday September 17-Saturday September 23 would be updated on Tuesday, October 3). All BTS visualizations and tables that rely on these data will update at approximately 10am ET on days when new data are received, processed, and uploaded.

The methodology used to develop these data can be found at: https://rosap.ntl.bts.gov/view/dot/67520.

14 Global import shipment records of Dot with prices, volume & current Buyer's suppliers relationships based on actual Global export trade database.

National Address DatabaseThis National Geospatial Data Asset (NGDA) dataset, shared as a U.S. Department of Transportation (USDOT) feature layer, displays address data in the United States. Per USDOT, "The U.S. Department of Transportation (USDOT) and its partners from all levels of government recognize the need for a National Address Database (NAD). Accurate and up-to-date addresses are critical to transportation safety and are a vital part of Next Generation 9-1-1. They are also essential for a broad range of government services, including mail delivery, permitting, and school siting. To meet this need, USDOT partners with address programs from state, local, and tribal governments to compile their authoritative data into the NAD."District of Columbia (DC) Residential AddressesData currency: Current federal service (Address Points from National Address Database)NGDAID: 196 (National Address Database (NAD))For more information: Getting to know the National Address Database (NAD); National Address DatabaseFor feedback, please contact: Esri_US_Federal_Data@esri.comNGDA Data SetThis data set is part of the NGDA Transportation Theme Community. Per the Federal Geospatial Data Committee (FGDC), Transportation is defined as the "means and aids for conveying persons and/or goods. The transportation system includes both physical and non-physical components related to all modes of travel that allow the movement of goods and people between locations".For other NGDA Content: Esri Federal Datasets

This dataset details the ages of guideway elements for each applicable agency reporting to the National Transit Database in the 2022 and 2023 report years. Guideway elements include elements, structures, or facilities dedicated specifically to transit use, such as track, subway structures, tunnels, bridges, and propulsion power systems.

NTD Data Tables organize and summarize data from the 2022 and 2023 National Transit Database in a manner that is more useful for quick reference and summary analysis. This dataset is based on the 2022 and 2023 Transit Way Mileage database files.

In years 2015-2021, you can find this data in the "Track and Roadway" data table on NTD Program website, at https://transit.dot.gov/ntd/ntd-data.

In versions of the data tables from before 2015, you can find data on vehicles in the file called "Transit Way Mileage - Rail Modes."

If you have any other questions about this table, please contact the NTD Help Desk at NTDHelp@dot.gov.

This dataset details service and cost efficiency metrics for agencies reporting to the National Transit Database in the 2022 and 2023 report years.

Only Full Reporters report data on Passenger Miles. The columns containing ratios have been calculated as the average across all reporting modes, not as the ratio of summed data. Thus, each transit agency received equal weight, regardless of that agency's total ridership.

NTD Data Tables organize and summarize data from the 2022 and 2023 National Transit Database in a manner that is more useful for quick reference and summary analysis. This dataset is based on the 2022 and 2023 Federal Funding Allocation, Operating Expenses, and Service database files.

In years 2015-2021, you can find this data in the "Metrics" data table on NTD Program website, at https://transit.dot.gov/ntd/ntd-data.

In versions of the NTD data tables from before 2014, you can find data on metrics in the files called "Fare per Passenger and Recovery Ratio" and "Service Supplied and Consumed Ratios."

If you have any other questions about this table, please contact the NTD Help Desk at NTDHelp@dot.gov.

335 Global import shipment records of Dot To Dot with prices, volume & current Buyer's suppliers relationships based on actual Global export trade database.

This dataset contains information about designated user-facilities and R&D equipment funded by the U.S. Department of Transportation and accessible to the private sector. These facilities reside throughout the United States and are meant to advance scientific research and accelerated technology commercialization.

Provides agency-wide totals for capital expenses that were applied to Rehabilitation, Reconstruction, Replacement, or other improvements to existing service, as reported to the National Transit Database in the 2022 and 2023 report years. This view is based off of the "2022 - 2023 NTD Annual Data - Capital Expenses (by Capital Use)" dataset, which displays capital expense data for all expense types. This view filters the parent dataset to show only expenses toward Existing Service.

NTD Data Tables organize and summarize data from the 2022 and 2023 National Transit Database in a manner that is more useful for quick reference and summary analysis. The parent dataset is based on the 2022 and 2023 Capital Use database files.

In years 2015-2021, you can find this data in the "Capital Expenses" data table on NTD Program website, at https://transit.dot.gov/ntd/ntd-data.

If you have any other questions about this table, please contact the NTD Help Desk at NTDHelp@dot.gov.

This dataset details funding sources for each applicable agency reporting to the National Transit Database in the 2022 and 2023 report years, split by fund expenditure type: capital and operating.

NTD Data Tables organize and summarize data from the 2022 and 2023 National Transit Database in a manner that is more useful for quick reference and summary analysis. This dataset is based on the 2022 and 2023 Revenue Sources database files.

In years 2015-2021, you can find this data in the "Funding Sources" data table on NTD Program website, at https://transit.dot.gov/ntd/ntd-data.

If you have any other questions about this table, please contact the NTD Help Desk at NTDHelp@dot.gov.

The Fataility Analysis Reporting System (FARS) dataset is as of July 1, 2017, and is part of the U.S. Department of Transportation (USDOT)/Bureau of Transportation Statistics's (BTS's) National Transportation Atlas Database (NTAD). One of the primary objectives of the National Highway Traffic Safety Administration (NHTSA) is to reduce the staggering human toll and property damage that motor vehicle traffic crashes impose on our society. FARS is a census of fatal motor vehicle crashes with a set of data files documenting all qualifying fatalities that occurred within the 50 States, the District of Columbia, and Puerto Rico since 1975. To qualify as a FARS case, the crash had to involve a motor vehicle traveling on a trafficway customarily open to the public, and must have resulted in the death of a motorist or a non-motorist within 30 days of the crash. This data file contains information about crash characteristics and environmental conditions at the time of the crash. There is one record per crash. Please note: 207 records in this database were geocoded to latitude and logtitude of 0,0 due to lack of location information or errors in the reported locations. FARS data are made available to the public in Statistical Analysis System (SAS) data files as well as Database Files (DBF). Over the years changes have been made to the type of data collected and the way the data are presented in the SAS data files. Some data elements have been dropped and new ones added, coding of individual data elements has changed, and new SAS data files have been created. Coding changes and the years for which individual data items are available are shown in the “Data Element Definitions and Codes” section of this document. The FARS Coding and Editing Manual contains a detailed description of each SAS data elements including coding instructions and attribute definitions. The Coding Manual is published for each year of data collection. Years 2001 to current are available at: http://www-nrd.nhtsa.dot.gov/Cats/listpublications.aspx?Id=J&ShowBy=DocType Note: In this manual the word vehicle means in-transport motor vehicle unless otherwise noted.

This dataset details stations for each agency and mode for stations reported to the National Transit Database in report years 2022 and 2023. These data include the type of facility and the decade in which it was built.

In many cases, stations are reported by each mode and type of service that uses them. For example, a single station used by bus - directly operated, bus - purchased transportation, and commuter bus - directly operated would be reported three times. For more detail, please see the NTD Policy Manual.

Rural reporters do not report passenger stations and are not included in this file. Modes Demand Response, Demand Response - Taxi, Vanpool, and Publico also do not report stations and are also excluded.

NTD Data Tables organize and summarize data from the 2022 and 2023 National Transit Database in a manner that is more useful for quick reference and summary analysis. This dataset is based on the 2022 and 2023 Facility Inventory database files.

In years 2015-2021, you can find this data in the "Stations" data table on NTD Program website, at https://transit.dot.gov/ntd/ntd-data.

If you have any other questions about this table, please contact the NTD Help Desk at NTDHelp@dot.gov.

This dataset provides information about the number of properties, residents, and average property values for Dot Sears Drive cross streets in Grandy, NC.

Sidewalk Management System is used to track and organize inspections, volitions and the status of New York City sidewalks. Identifies a Notice of Violation has been issued for a sidewalk defect. For more information please visit NYC DOT website: www.nyc.gov/sidewalks