Over the course of the 20th century, the number of operational motor vehicles in the United States grew significantly, from just 8,000 automobiles in the year 1900 to more than 183 million private and commercial vehicles in the late 1980s. Generally, the number of vehicles increased in each year, with the most notable exceptions during the Great Depression and Second World War.

Key information about US Number of Registered Vehicles

• US Number of Registered Vehicles was reported at 284,614,269 Unit in Dec 2023.
• This records an increase from the previous number of 283,400,986 Unit for Dec 2022.
• US Number of Registered Vehicles data is updated yearly, averaging 93,949,852 Unit from Dec 1910 to 2023, with 114 observations.
• The data reached an all-time high of 284,614,269 Unit in 2023 and a record low of 468,500 Unit in 1910.
• US Number of Registered Vehicles data remains active status in CEIC and is reported by CEIC Data.
• The data is categorized under World Trend Plus’s Global Economic Monitor – Table: No of Registered Vehicles: Annual.

This dataset provides a comprehensive, state-level view of the key factors influencing electric vehicle (EV) adoption across the United States. Compiled from authoritative sources such as the US Census Bureau, Department of Energy, National Renewable Energy Laboratory (NREL), and others, it includes annual data on EV registrations, socioeconomic indicators, infrastructure availability, policy incentives, and energy prices from multiple years.

The dataset is designed to support research and analysis on the drivers of EV adoption, enabling users to explore questions around policy effectiveness, infrastructure planning, and market dynamics.

Context & Motivation The transition to electric vehicles is a cornerstone of US climate and energy policy, yet EV adoption rates remain highly uneven across states. While states like California lead with robust infrastructure and incentives, other regions-particularly in the Midwest and South-lag behind. Understanding what drives these differences is crucial for policymakers, automakers, and energy providers.

This dataset was created as part of a research project investigating the determinants of EV adoption. By making this data publicly available, I hope to empower further research, foster data-driven policy decisions, and encourage innovation in sustainable transportation.

Data Sources EV Registrations: National Renewable Energy Laboratory (NREL)

Socioeconomic Indicators: US Census Bureau (population, income, education, labor force, unemployment)

Charging Infrastructure & Incentives: Alternative Fuels Data Center (AFDC)

Fuel Economy & Vehicle Registrations: Bureau of Transportation Statistics

Gasoline Prices: American Automobile Association (AAA)

Electricity Prices: Energy Information Administration (EIA)

CO2 Emissions: Bureau of Transportation Statistics Variables Included

Car Production in the United States increased to 11.04 Million Units in August from 10.42 Million Units in July of 2025. This dataset provides - United States Car Production- actual values, historical data, forecast, chart, statistics, economic calendar and news.

Second-Hand (SH) vehicle imports from the US comprise nearly 30 percent of Mexico’s light-duty vehicles. As US electric vehicle (EV) adoption progresses, SH EVs will increasingly enter Mexico. SH EVs could speed vehicle electrification, but also present environmental and economic risks because they are larger and reach retirement faster than new EVs. Understanding future flows of used and new EVs into Mexico’s fleet, and their expected retirement, is needed to understand if SH EVs provide a net benefit. This research uses system dynamics modeling to project future EV adoption and SH vehicle trade between the US and Mexico. Results show EVs will comprise nearly 50% of Mexico’s fleet and up to 99% of SH imports by 2050, and SH EV batteries disproportionately contribute to the stock of spent EV batteries. Policies to ensure SH vehicle trade provides net benefits for the region include import and export battery state-of-health restrictions. Methods The multiple background datasets used in the study were collected from official sources in both the United States and Mexico. For Mexico, data on second-hand (SH) vehicle imports was obtained from the National Customs Agency (ANAM), and historical vehicle fleet and sales data were sourced from the National Institute for Statistics and Geography (INEGI). For the U.S., vehicle sales projections were based on the U.S. Energy Information Administration’s (EIA) forecasts, with additional adjustments made to align with government policy goals, such as the White House’s target for EV adoption. These datasets were integrated into a multi-region stock turnover model, and further refined using optimization techniques to align the model's outputs with historical records. Then, the model incorporated battery characterization data from BatPaC v5.0 (Argonne National Laboratory) to estimate the recoverable amounts of various materials per battery pack type at their end-of-life, including lithium, nickel, cobalt, manganese, aluminum, copper, and steel. The aim was to estimate the battery mass of critical battery materials associated with used EV exports.

Total Vehicle Sales in the United States decreased to 15.30 Million in October from 16.40 Million in September of 2025. This dataset provides the latest reported value for - United States Total Vehicle Sales - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

Around ******* battery electric vehicles were sold in the Americas in 2021, according to data provided by EV-Volumes. This was a year-on-year rise of almost ** percent. The battery electric vehicle sales in the region made up just over ***** percent of the total plug-in electric vehicle sales worldwide.

The U.S. auto industry sold nearly ************* cars in 2024. That year, total car and light truck sales were approximately ************ in the United States. U.S. vehicle sales peaked in 2016 at roughly ************ units. Pandemic impact The COVID-19 pandemic deeply impacted the U.S. automotive market, accelerating the global automotive semiconductor shortage and leading to a drop in demand during the first months of 2020. However, as demand rebounded, new vehicle supply could not keep up with the market. U.S. inventory-to-sales ratio dropped to its lowest point in February 2022, as Russia's war on Ukraine lead to gasoline price hikes. During that same period, inflation also impacted new and used car prices, pricing many U.S. consumers out of a market with increasingly lower car stocks. Focus on fuel economy The U.S. auto industry had one of its worst years in 1982 when customers were beginning to feel the effects of the 1973 oil crisis and the energy crisis of 1979. Since light trucks would often be considered less fuel-efficient, cars accounted for about ** percent of light vehicle sales back then. Thanks to improved fuel economy for light trucks and cheaper gas prices, this picture had completely changed in 2020. That year, prices for Brent oil dropped to just over ** U.S. dollars per barrel. The decline occurred in tandem with lower gasoline prices, which came to about **** U.S. dollars per gallon in 2020 - and cars only accounted for less than one-fourth of light vehicle sales that year. Four years on, prices are dropping again, after being the highest on record since 1990 in 2022.

In the third quarter of 2025, over ******* battery-electric vehicles were sold in the United States. This was a year-over-year increase of over ***percent compared to the sales recorded in the third quarter of 2024. The third quarter of 2025 also recorded a hike in sales compared to the second quarter of that same year, making it the best quarter for BEV sales in the country ever. The stark increase in sales in the third quarter of 2025 is tied to the elimination of EV purchase incentives by the U.S. government. The fourth quarter of 2025 could very well see a decrease in sales. Global EV Race - Where does the U.S. stand? Over the last few years, consumers have perceived Electric Vehicles (EVs) as a far more appealing option due to their increased range, battery life, variety of models, and affordability. Therefore, the EV market has grown fast in recent years and is forecast to expand to ****billion U.S. dollars in 2029. Though the global demand for electric cars has been escalating, American sales lag behind Europe and the Asia-Pacific regions. In 2024, Chinese customers bought around **** million plug-in EVs, considerably more than American customers' purchases, around *** million that year. China leads the global EV race, with a substantial **** percent growth in sales year-on-year in 2024. However, given the market share of electric vehicles in the global automotive industry, this still can be anyone's race. Outlook of the U.S. market There is still a lack of interest in electric vehicles among American buyers compared to European and Asian consumers. In the first half of 2021, the share of the battery electric vehicle was **** percentage points more in Norway than in the U.S. One of the main reasons is that American consumers still anticipate that EVs are more expensive than gasoline vehicles and diesel internal combustion engine cars (ICE). This perception is partially true in the U.S. since the battery production market is highly concentrated in Asia, where the companies have logistical advantages, leading automotive makers to offer better prices. On the other hand, high licensing fees for electric vehicles are another factor affecting the consumption behaviors of automobile purchasers. In many states, the licensing fees for electric cars are considerably higher than their ICE counterparts. EV licensing fees were around *** U.S. dollars compared to ** U.S. dollars for standard vehicles in Georgia in 2021. Together, these factors significantly impact the individual perception of electric cars in the United States.

This layer shows household size by number of vehicles available. This is shown by tract, county, and state centroids. This service is updated annually to contain the most currently released American Community Survey (ACS) 5-year data, and contains estimates and margins of error. There are also additional calculated attributes related to this topic, which can be mapped or used within analysis. This layer is symbolized to show the count and percentage of households with no vehicle available. To see the full list of attributes available in this service, go to the "Data" tab, and choose "Fields" at the top right. Current Vintage: 2019-2023ACS Table(s): B08201 Data downloaded from: Census Bureau's API for American Community Survey Date of API call: December 12, 2024National Figures: data.census.govThe United States Census Bureau's American Community Survey (ACS):About the SurveyGeography & ACSTechnical DocumentationNews & UpdatesThis ready-to-use layer can be used within ArcGIS Pro, ArcGIS Online, its configurable apps, dashboards, Story Maps, custom apps, and mobile apps. Data can also be exported for offline workflows. For more information about ACS layers, visit the FAQ. Please cite the Census and ACS when using this data.Data Note from the Census:Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see Accuracy of the Data). The effect of nonsampling error is not represented in these tables.Data Processing Notes:This layer is updated automatically when the most current vintage of ACS data is released each year, usually in December. The layer always contains the latest available ACS 5-year estimates. It is updated annually within days of the Census Bureau's release schedule. Click here to learn more about ACS data releases.Boundaries come from the US Census TIGER geodatabases, specifically, the National Sub-State Geography Database (named tlgdb_(year)_a_us_substategeo.gdb). Boundaries are updated at the same time as the data updates (annually), and the boundary vintage appropriately matches the data vintage as specified by the Census. These are Census boundaries with water and/or coastlines erased for cartographic and mapping purposes. For census tracts, the water cutouts are derived from a subset of the 2020 Areal Hydrography boundaries offered by TIGER. Water bodies and rivers which are 50 million square meters or larger (mid to large sized water bodies) are erased from the tract level boundaries, as well as additional important features. For state and county boundaries, the water and coastlines are derived from the coastlines of the 2023 500k TIGER Cartographic Boundary Shapefiles. These are erased to more accurately portray the coastlines and Great Lakes. The original AWATER and ALAND fields are still available as attributes within the data table (units are square meters).The States layer contains 52 records - all US states, Washington D.C., and Puerto RicoCensus tracts with no population that occur in areas of water, such as oceans, are removed from this data service (Census Tracts beginning with 99).Percentages and derived counts, and associated margins of error, are calculated values (that can be identified by the "_calc_" stub in the field name), and abide by the specifications defined by the American Community Survey.Field alias names were created based on the Table Shells file available from the American Community Survey Summary File Documentation page.Negative values (e.g., -4444...) have been set to null, with the exception of -5555... which has been set to zero. These negative values exist in the raw API data to indicate the following situations:The margin of error column indicates that either no sample observations or too few sample observations were available to compute a standard error and thus the margin of error. A statistical test is not appropriate.Either no sample observations or too few sample observations were available to compute an estimate, or a ratio of medians cannot be calculated because one or both of the median estimates falls in the lowest interval or upper interval of an open-ended distribution.The median falls in the lowest interval of an open-ended distribution, or in the upper interval of an open-ended distribution. A statistical test is not appropriate.The estimate is controlled. A statistical test for sampling variability is not appropriate.The data for this geographic area cannot be displayed because the number of sample cases is too small.

The dataset is an extensive compendium of data pertaining to the selling of automobiles. This dataset, which was compiled via questionnaires, provides insightful information about numerous facets of the retail car sector. It covers a wide variety of automobile models and their characteristics, providing insight into market trends and customer preferences. The dataset is described in the following manner:

The following columns are included in the dataset:

Date: The date when the data were collected, giving the dataset a temporal component.

Car_Model: This field specifies the kind of car model, which may be one of many subcategories, including Sedan, SUV, Truck, Hatchback, and Sports Car.

Manufacturing_Location: This specifies where the automobile was made, including Germany, the United States, Japan, and South Korea.

Production_Quantity: Indicates the quantity of automobiles produced for a certain date and model.

Sales_Price: This figure depicts the selling price of the autos and offers information on pricing tactics.

Cost_Price: This number represents the cost involved in making the automobiles.

Profit_Percent: Provides profitability insights by displaying the profit margin as a percentage of the cost price.

Market_Share: Represents each automobile model's proportion of the market, demonstrating how competitive they are.

Customer_Satisfaction: Reflects client satisfaction ratings, providing insight into the calibre of the product and the opinions of customers.

The fuel type used by the vehicle is specified, including petrol, diesel, and electric.

Engine_Size (cc): This value, which might affect performance, indicates the engine size in cubic centimetres (cc).

Mileage (km/l): Shows the amount of miles per litre, which is an important aspect of fuel economy.

The warranty time offered for each automobile model is specified by the field Warranty_Period (months).

Provides safety ratings for the vehicles, an important factor for customers.

Colour: Illustrates the many car-color possibilities.

The term "transmission" designates the kind of transmission, either automatic or manual.

Country_of_Origin: Indicates the nation from which the particular automobile model is derived.

Reflects monthly advertising costs and provides information on marketing initiatives.

Dealership_Location: Indicates where a dealership is located, classifying it as either urban, suburban, or rural.

For the analysis and comprehension of the dynamics of the vehicle retail business, including market trends, customer behaviour, pricing tactics, and product features, this dataset is an invaluable resource. It may be used in the automobile industry for a variety of analytical and forecasting reasons.

Graph and download economic data for Combined Inputs Costs for Manufacturing: Motor Vehicle Manufacturing (NAICS 3361) in the United States (IPUEN3361M021000000) from 1988 to 2022 about cost, NAICS, IP, vehicles, manufacturing, and USA.

This is the Car sales data set which include information about different car sales dealers and the model of the cars they sold across different region of United States . In this we have to see two things First we have to see which region in US have highest percentage of car sales in US Secondly we have which dealer tops the chart in car sales in particular region

Imports of Autos and Parts in the United States increased to 38133 USD Million in February from 37845 USD Million in January of 2024. This dataset includes a chart with historical data for the United States Imports of Autos And Parts.

In 2024, the auto industry in the United States sold approximately 15.9 million light vehicle units. This figure includes retail sales of about three million passenger cars and just under 12.9 million light trucks. Lower fuel consumption There are many kinds of light vehicles available in the United States. Light-duty vehicles are popular for their utility and improved fuel economy, making them an ideal choice for savvy consumers. As of Model Year 2023, the light vehicle manufacturer with the best overall miles per gallon was Kia, with one gallon of gas allowing for 30.4 miles on the road. Higher brand satisfaction When asked about light vehicle satisfaction, consumers in the United States were most satisfied with Toyota, Subaru, Tesla, and Mercedes-Benz models. Another survey conducted in 2018 and quizzing respondents on their stance regarding the leading car brands indicated that Lexus was among the most dependable brands based on the number of problems reported per 100 vehicles.

When asked about "Car features", most U.S. respondents pick "Wireless smartphone connection" as an answer. ** percent did so in our online survey in 2023.Find this and more survey data on car features in our Consumer Insights tool. Filter by countless demographics, drill down to your own, hand-tailored target audience, and compare results across countries worldwide.

From Esri Demographics:This layer shows household size by number of vehicles available. This is shown by tract, county, and state boundaries. This service is updated annually to contain the most currently released American Community Survey (ACS) 5-year data, and contains estimates and margins of error. There are also additional calculated attributes related to this topic, which can be mapped or used within analysis. This layer is symbolized to show the percentage of households with no vehicle available. To see the full list of attributes available in this service, go to the "Data" tab, and choose "Fields" at the top right. Current Vintage: 2019-2023ACS Table(s): B08201Data downloaded from: Census Bureau's API for American Community Survey Date of API call: December 12, 2024National Figures: data.census.gov The United States Census Bureau's American Community Survey (ACS):About the Survey Geography & ACS Technical Documentation News & Updates This ready-to-use layer can be used within ArcGIS Pro, ArcGIS Online, its configurable apps, dashboards, Story Maps, custom apps, and mobile apps. Data can also be exported for offline workflows. For more information about ACS layers, visit the FAQ. Please cite the Census and ACS when using this data. Data Note from the Census: Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see Accuracy of the Data). The effect of nonsampling error is not represented in these tables. Data Processing Notes:This layer is updated automatically when the most current vintage of ACS data is released each year, usually in December. The layer always contains the latest available ACS 5-year estimates. It is updated annually within days of the Census Bureau's release schedule. Click here to learn more about ACS data releases. Boundaries come from the US Census TIGER geodatabases, specifically, the National Sub-State Geography Database (named tlgdb_(year)_a_us_substategeo.gdb). Boundaries are updated at the same time as the data updates (annually), and the boundary vintage appropriately matches the data vintage as specified by the Census. These are Census boundaries with water and/or coastlines erased for cartographic and mapping purposes. For census tracts, the water cutouts are derived from a subset of the 2020 Areal Hydrography boundaries offered by TIGER. Water bodies and rivers which are 50 million square meters or larger (mid to large sized water bodies) are erased from the tract level boundaries, as well as additional important features. For state and county boundaries, the water and coastlines are derived from the coastlines of the 2023 500k TIGER Cartographic Boundary Shapefiles. These are erased to more accurately portray the coastlines and Great Lakes. The original AWATER and ALAND fields are still available as attributes within the data table (units are square meters).The States layer contains 52 records - all US states, Washington D.C., and Puerto RicoCensus tracts with no population that occur in areas of water, such as oceans, are removed from this data service (Census Tracts beginning with 99).Percentages and derived counts, and associated margins of error, are calculated values (that can be identified by the "_calc_" stub in the field name), and abide by the specifications defined by the American Community Survey.Field alias names were created based on the Table Shells file available from the American Community Survey Summary File Documentation page. Negative values (e.g., -4444...) have been set to null, with the exception of -5555... which has been set to zero. These negative values exist in the raw API data to indicate the following situations:The margin of error column indicates that either no sample observations or too few sample observations were available to compute a standard error and thus the margin of error. A statistical test is not appropriate.Either no sample observations or too few sample observations were available to compute an estimate, or a ratio of medians cannot be calculated because one or both of the median estimates falls in the lowest interval or upper interval of an open-ended distribution. The median falls in the lowest interval of an open-ended distribution, or in the upper interval of an open-ended distribution. A statistical test is not appropriate.The estimate is controlled. A statistical test for sampling variability is not appropriate. The data for this geographic area cannot be displayed because the number of sample cases is too small.

United States Exports of motor cars and vehicles for transporting persons to Canada was US$15.53 Billion during 2024, according to the United Nations COMTRADE database on international trade. United States Exports of motor cars and vehicles for transporting persons to Canada - data, historical chart and statistics - was last updated on December of 2025.

Graph and download economic data for Labor Productivity for Manufacturing: Motor Vehicle Transmission and Power Train Parts Manufacturing (NAICS 336350) in the United States (IPUEN336350L001000000) from 1988 to 2021 about trains, power transmission, productivity, parts, NAICS, IP, vehicles, labor, manufacturing, and USA.

Graph and download economic data for Percent Loaded of Total Freight Car-Miles, Class I Railroads for United States (M03043USM156NNBR) from Jan 1920 to Dec 1942 about railroad, freight, percent, and USA.