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.

Comprehensive dataset of 85,152 Trucking companies in United States as of July, 2025. Includes verified contact information (email, phone), geocoded addresses, customer ratings, reviews, business categories, and operational details. Perfect for market research, lead generation, competitive analysis, and business intelligence. Download a complimentary sample to evaluate data quality and completeness.

The North American Transborder Freight Database, available since April 1993, contains freight flow data by commodity type and by mode of transportation (rail, truck, pipeline, air, vessel, and other) for U.S. exports to and imports from Canada and Mexico.

This table contains 140 series, with data for years 2009 - 2010 (not all combinations necessarily have data for all years), and was last released on 2015-02-06. This table contains data described by the following dimensions (Not all combinations are available): Geography (14 items: Canada; Newfoundland and Labrador; Prince Edward Island; New Brunswick; ...), Fleet and equipment statistics (10 items: Total powered units; Straight trucks; Road tractors; All other powered units ...).

United States ASS: Exp: TW: Truck: Long-Distance Trucking Freight Truckload data was reported at 88.165 USD bn in 2016. This records an increase from the previous number of 86.697 USD bn for 2015. United States ASS: Exp: TW: Truck: Long-Distance Trucking Freight Truckload data is updated yearly, averaging 78.682 USD bn from Dec 2004 (Median) to 2016, with 13 observations. The data reached an all-time high of 88.165 USD bn in 2016 and a record low of 65.489 USD bn in 2009. United States ASS: Exp: TW: Truck: Long-Distance Trucking Freight Truckload data remains active status in CEIC and is reported by US Census Bureau. The data is categorized under Global Database’s USA – Table US.H021: Annual Services Survey: Employer Firms Expense.

Comprehensive dataset of 3,161 Trucking companies in New York, United States as of June, 2025. Includes verified contact information (email, phone), geocoded addresses, customer ratings, reviews, business categories, and operational details. Perfect for market research, lead generation, competitive analysis, and business intelligence. Download a complimentary sample to evaluate data quality and completeness.

The Truck Stop Parking dataset was compiled on April 09, 2019 from the Federal Highway Administration (FHWA) and is part of the U.S. Department of Transportation (USDOT)/Bureau of Transportation Statistics (BTS) National Transportation Atlas Database (NTAD). The truck parking data was collected as part of the Jason's Law Truck Parking Survey requirement of MAP-21 (PL 112-141) to provide a "national priority on addressing the shortage of long-term parking for commercial motor vehicles on the National Highway System to improve the safety of motorized and non-motorized users and for commercial motor vehicle operators." Jason's Law required the USDOT to conduct a survey and comparative assessment in consultation with relevant State motor carrier representatives to: 1. Evaluate the capability of the State to provide adequate parking and rest facilities for commercial motor vehicles engaged in interstate transportation; 2. Assess the volume of commercial motor vehicle traffic in the State; and 3. Develop a system of metrics to measure the adequacy of commercial motor vehicle parking facilities in the State. A data dictionary, or other source of attribute information, is accessible at https://doi.org/10.21949/1529087

Summary

Geojson files used to visualize geospatial layers relevant to identifying and assessing trucking fleet decarbonization opportunities with the MIT Climate & Sustainability Consortium's Geospatial Trucking Industry Decarbonization Explorer (Geo-TIDE) tool.

Relevant Links

Link to the online version of the tool (requires creation of a free user account).

Link to GitHub repo with source code to produce this dataset and deploy the Geo-TIDE tool locally.

Funding

This dataset was produced with support from the MIT Climate & Sustainability Consortium.

Original Data Sources

These geojson files draw from and synthesize a number of different datasets and tools. The original data sources and tools are described below:

Filename(s) Description of Original Data Source(s) Link(s) to Download Original Data License and Attribution for Original Data Source(s)

faf5_freight_flows/*.geojson

trucking_energy_demand.geojson

highway_assignment_links_*.geojson

infrastructure_pooling_thought_experiment/*.geojson

Regional and highway-level freight flow data obtained from the Freight Analysis Framework Version 5. Shapefiles for FAF5 region boundaries and highway links are obtained from the National Transportation Atlas Database. Emissions attributes are evaluated by incorporating data from the 2002 Vehicle Inventory and Use Survey and the GREET lifecycle emissions tool maintained by Argonne National Lab.

Shapefile for FAF5 Regions

Shapefile for FAF5 Highway Network Links

FAF5 2022 Origin-Destination Freight Flow database

FAF5 2022 Highway Assignment Results

Attribution for Shapefiles: United States Department of Transportation Bureau of Transportation Statistics National Transportation Atlas Database (NTAD). Available at: https://geodata.bts.gov/search?collection=Dataset.

License for Shapefiles: This NTAD dataset is a work of the United States government as defined in 17 U.S.C. § 101 and as such are not protected by any U.S. copyrights. This work is available for unrestricted public use.

Attribution for Origin-Destination Freight Flow database: National Transportation Research Center in the Oak Ridge National Laboratory with funding from the Bureau of Transportation Statistics and the Federal Highway Administration. Freight Analysis Framework Version 5: Origin-Destination Data. Available from: https://faf.ornl.gov/faf5/Default.aspx. Obtained on Aug 5, 2024. In the public domain.

Attribution for the 2022 Vehicle Inventory and Use Survey Data: United States Department of Transportation Bureau of Transportation Statistics. Vehicle Inventory and Use Survey (VIUS) 2002 [supporting datasets]. 2024. https://doi.org/10.21949/1506070

Attribution for the GREET tool (original publication): Argonne National Laboratory Energy Systems Division Center for Transportation Research. GREET Life-cycle Model. 2014. Available from this link.

Attribution for the GREET tool (2022 updates): Wang, Michael, et al. Summary of Expansions and Updates in GREET® 2022. United States. https://doi.org/10.2172/1891644

grid_emission_intensity/*.geojson

Emission intensity data is obtained from the eGRID database maintained by the United States Environmental Protection Agency.

eGRID subregion boundaries are obtained as a shapefile from the eGRID Mapping Files database.

eGRID database

Shapefile with eGRID subregion boundaries

Attribution for eGRID data: United States Environmental Protection Agency: eGRID with 2022 data. Available from https://www.epa.gov/egrid/download-data. In the public domain.

Attribution for shapefile: United States Environmental Protection Agency: eGRID Mapping Files. Available from https://www.epa.gov/egrid/egrid-mapping-files. In the public domain.

US_elec.geojson

US_hy.geojson

US_lng.geojson

US_cng.geojson

US_lpg.geojson

Locations of direct current fast chargers and refueling stations for alternative fuels along U.S. highways. Obtained directly from the Station Data for Alternative Fuel Corridors in the Alternative Fuels Data Center maintained by the United States Department of Energy Office of Energy Efficiency and Renewable Energy.

US_elec.geojson

US_hy.geojson

US_lng.geojson

US_cng.geojson

US_lpg.geojson

Attribution: U.S. Department of Energy, Energy Efficiency and Renewable Energy. Alternative Fueling Station Corridors. 2024. Available from: https://afdc.energy.gov/corridors. In the public domain.

These data and software code ("Data") are provided by the National Renewable Energy Laboratory ("NREL"), which is operated by the Alliance for Sustainable Energy, LLC ("Alliance"), for the U.S. Department of Energy ("DOE"), and may be used for any purpose whatsoever.

daily_grid_emission_profiles/*.geojson

Hourly emission intensity data obtained from ElectricityMaps.

Original data can be downloaded as csv files from the ElectricityMaps United States of America database

Shapefile with region boundaries used by ElectricityMaps

License: Open Database License (ODbL). Details here: https://www.electricitymaps.com/data-portal

Attribution for csv files: Electricity Maps (2024). United States of America 2022-23 Hourly Carbon Intensity Data (Version January 17, 2024). Electricity Maps Data Portal. https://www.electricitymaps.com/data-portal.

Attribution for shapefile with region boundaries: ElectricityMaps contributors (2024). electricitymaps-contrib (Version v1.155.0) [Computer software]. https://github.com/electricitymaps/electricitymaps-contrib.

gen_cap_2022_state_merged.geojson

trucking_energy_demand.geojson

Grid electricity generation and net summer power capacity data is obtained from the state-level electricity database maintained by the United States Energy Information Administration.

U.S. state boundaries obtained from this United States Department of the Interior U.S. Geological Survey ScienceBase-Catalog.

Annual electricity generation by state

Net summer capacity by state

Shapefile with U.S. state boundaries

Attribution for electricity generation and capacity data: U.S. Energy Information Administration (Aug 2024). Available from: https://www.eia.gov/electricity/data/state/. In the public domain.

electricity_rates_by_state_merged.geojson

Commercial electricity prices are obtained from the Electricity database maintained by the United States Energy Information Administration.

Electricity rate by state

Attribution: U.S. Energy Information Administration (Aug 2024). Available from: https://www.eia.gov/electricity/data.php. In the public domain.

demand_charges_merged.geojson

demand_charges_by_state.geojson

Maximum historical demand charges for each state and zip code are derived from a dataset compiled by the National Renewable Energy Laboratory in this this Data Catalog.

Historical demand charge dataset

The original dataset is compiled by the National Renewable Energy Laboratory (NREL), the U.S. Department of Energy (DOE), and the Alliance for Sustainable Energy, LLC ('Alliance').

Attribution: McLaren, Joyce, Pieter Gagnon, Daniel Zimny-Schmitt, Michael DeMinco, and Eric Wilson. 2017. 'Maximum demand charge rates for commercial and industrial electricity tariffs in the United States.' NREL Data Catalog. Golden, CO: National Renewable Energy Laboratory. Last updated: July 24, 2024. DOI: 10.7799/1392982.

eastcoast.geojson

midwest.geojson

la_i710.geojson

h2la.geojson

bayarea.geojson

saltlake.geojson

northeast.geojson

Highway corridors and regions targeted for heavy duty vehicle infrastructure projects are derived from a public announcement on February 15, 2023 by the United States Department of Energy.

The shapefile with Bay area boundaries is obtained from this Berkeley Library dataset.

The shapefile with Utah county boundaries is obtained from this dataset from the Utah Geospatial Resource Center.

Shapefile for Bay Area country boundaries

Shapefile for counties in Utah

Attribution for public announcement: United States Department of Energy. Biden-Harris Administration Announces Funding for Zero-Emission Medium- and Heavy-Duty Vehicle Corridors, Expansion of EV Charging in Underserved Communities (2023). Available from https://www.energy.gov/articles/biden-harris-administration-announces-funding-zero-emission-medium-and-heavy-duty-vehicle.

Attribution for Bay area boundaries: San Francisco (Calif.). Department Of Telecommunications and Information Services. Bay Area Counties. 2006. In the public domain.

Attribution for Utah boundaries: Utah Geospatial Resource Center & Lieutenant Governor's Office. Utah County Boundaries (2023). Available from https://gis.utah.gov/products/sgid/boundaries/county/.

License for Utah boundaries: Creative Commons 4.0 International License.

incentives_and_regulations/*.geojson

State-level incentives and regulations targeting heavy duty vehicles are collected from the State Laws and Incentives database maintained by the United States Department of Energy's Alternative Fuels Data Center.

Data was collected manually from the State Laws and Incentives database.

Attribution: U.S. Department of Energy, Energy Efficiency and Renewable Energy, Alternative Fuels Data Center. State Laws and Incentives. Accessed on Aug 5, 2024 from: https://afdc.energy.gov/laws/state. In the public domain.

These data and software code ("Data") are provided by the National Renewable Energy Laboratory ("NREL"), which is operated by the Alliance for Sustainable Energy, LLC ("Alliance"), for the U.S. Department of Energy ("DOE"), and may be used for any purpose whatsoever.

costs_and_emissions/*.geojson

diesel_price_by_state.geojson

trucking_energy_demand.geojson

Lifecycle costs and emissions of electric and diesel trucking are evaluated by adapting the model developed by Moreno Sader et al., and calibrated to the Run on Less dataset for the Tesla Semi collected from the 2023 PepsiCo Semi pilot by the North American Council for Freight Efficiency.

In

United States ASS: Exp: TW: Truck: Long-Distance Trucking Freight Less Truckload data was reported at 37.816 USD bn in 2016. This records a decrease from the previous number of 38.366 USD bn for 2015. United States ASS: Exp: TW: Truck: Long-Distance Trucking Freight Less Truckload data is updated yearly, averaging 36.060 USD bn from Dec 2004 (Median) to 2016, with 13 observations. The data reached an all-time high of 38.767 USD bn in 2014 and a record low of 27.888 USD bn in 2004. United States ASS: Exp: TW: Truck: Long-Distance Trucking Freight Less Truckload data remains active status in CEIC and is reported by US Census Bureau. The data is categorized under Global Database’s USA – Table US.H021: Annual Services Survey: Employer Firms Expense.

The Intermodal Freight Facilities - Pipeline Terminals dataset was compiled on February 02, 2021 and was updated on April 21, 2021 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). Pipeline terminals interface between pipeline mode and other transportation modes. They have the ability to receive or deliver freight commodities via pipeline and truck/rail/water. The data consists of location information, truck/rail/water mode connections, storage capacity, and a list of commodities handled at the terminal. Geographical coverage includes the United States and U.S. territories. This dataset is one of several layers in the Bureau of Transportation Statistics (BTS) Intermodal Freight Facility Database. A data dictionary, or other source of attribute information, is accessible at https://doi.org/10.21949/1529033

Data Quality identifies FMCSA resources for evaluating, monitoring, and improving the quality of data submitted by States to the Motor Carrier Management Information System (MCMIS).

The T-100 Domestic Market and Segment Data dataset was downloaded on April 08, 2025 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 database includes data obtained from a 100 percent census of BTS Form 41 schedule submissions by large certificated air carriers. It shows 2024 statistics for all domestic airports operated by US carriers, and all information are totals for the year. This dataset is a combination of both T-100 Market and T-100 Segments datasets. The T-100 Market includes enplanement data, and T-100 Segment data includes arrivals, departures, freight, and mail. Data is by origin airport. A data dictionary, or other source of attribute information, is accessible at https://doi.org/10.21949/1529081

Records for all 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). See dataset attachment "FMCSA Dataset Description and Data Definitions - Select Datasets" for more information.

Graph and download economic data for Employment for Transportation and Warehousing: General Freight Trucking, Long-Distance (NAICS 48412) in the United States (IPUIN48412W010000000) from 1987 to 2024 about general, freight, warehousing, trucks, NAICS, transportation, employment, and USA.

This dataset consists of truck size and weight enforcement data including number of trucks weighed, number of violations, and number of oversize/overweight permits, as reported by the States in their annual certification to FHWA.

This data is from an FMCSA Comprehensive Safety Analysis (CSA) monthly data run, which contains the FMCSA registration data of all active Interstate and Intrastate Hazmat Motor Carriers of property and/or passengers. Contains the USDOT Number, company names, addresses, contacts, telephone and fax numbers, e-mail, HazMat flag, passenger carrier flag, number of power units, number of drivers, mileage, mileage year, operation, and classification registration information. File is comma delimited. One carrier per row.

Contains data on large trucks and buses involved in Federally reportable crashes as per Title 49 U.S.C. Part 390.5 (crashes involving a commercial motor vehicle, and that either involve a fatalities, injury requiring treatmentaway from the scene of the crash, or a tow-away due to disabling damage). This information is reported by the States to FMCSA.

United States Employment: NF: TW: General Freight Trucking (GFT) data was reported at 1,012.200 Person th in May 2018. This records an increase from the previous number of 1,007.300 Person th for Apr 2018. United States Employment: NF: TW: General Freight Trucking (GFT) data is updated monthly, averaging 947.400 Person th from Jan 1990 (Median) to May 2018, with 341 observations. The data reached an all-time high of 1,028.800 Person th in Aug 2000 and a record low of 778.700 Person th in Feb 1992. United States Employment: NF: TW: General Freight Trucking (GFT) data remains active status in CEIC and is reported by Bureau of Labor Statistics. The data is categorized under Global Database’s USA – Table US.G024: Current Employment Statistics Survey: Employment: Non Farm.

United States AHE: sa: PW: TW: General Freight Trucking data was reported at 31.030 USD in Mar 2025. This records an increase from the previous number of 30.840 USD for Feb 2025. United States AHE: sa: PW: TW: General Freight Trucking data is updated monthly, averaging 17.700 USD from Jan 1990 (Median) to Mar 2025, with 423 observations. The data reached an all-time high of 31.030 USD in Mar 2025 and a record low of 13.230 USD in Nov 1990. United States AHE: sa: PW: TW: General Freight Trucking data remains active status in CEIC and is reported by U.S. Bureau of Labor Statistics. The data is categorized under Global Database’s United States – Table US.G: Current Employment Statistics: Average Hourly Earnings: Production Workers: Seasonally Adjusted.

The FMCSA Crash File contains data from state police crash reports involving drivers and vehicles of motor carriers operating in the U.S. Each report contains about 80 data elements pertaining to the motor carrier, driver, vehicles, and circumstances of a crash. Due to sensitive and/or privacy restrictions, driver, and hazardous materials data are not included in any crash files released to the public.

The Crash File may contain multiple records for a crash. Separate reports are entered for each commercial motor vehicle involved in a crash. These multiple reports can be distinguished by the Crash Report Number field.