Total Vehicle Sales in the United States increased to 16.41 Million in July from 15.32 Million in June 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.

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.

Autos include all passenger cars, including station wagons. 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.

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.

Car Registrations in the United States increased to 221.20 Thousand in July from 217.20 Thousand in June of 2025. This dataset provides - United States Car Registrations - actual values, historical data, forecast, chart, statistics, economic calendar and news.

Key information about United States Motor Vehicle Sales: Passenger Cars

• United States Motor Vehicle Sales: Passenger Cars was reported at 3,116,647.000 Unit in Dec 2023.
• This records an increase from the previous number of 2,858,575.000 Unit for Dec 2022.
• US Motor Vehicle Sales: Passenger Cars data is updated yearly, averaging 6,089,403.000 Unit from Dec 2005 to 2023, with 19 observations.
• The data reached an all-time high of 7,761,592.000 Unit in 2006 and a record low of 2,858,575.000 Unit in 2022.
• US Motor Vehicle Sales: Passenger Cars data remains active status in CEIC and is reported by International Organization of Motor Vehicle Manufacturers.
• The data is categorized under World Trend Plus’s Association: Automobile Sector – Table RA.OICA.MVS: Motor Vehicle Sales: by Country and Type: Passenger Car (PC).

In 2022, U.S. auto shoppers bought approximately 2.86 million autos. Meanwhile, light trucks accounted for more than 79 percent of light vehicles sold to individual customers and corporate fleets in the United States.

Dataset containing vehicles sold in the US market of 2024-2025 year. Compares horsepower, torque, weight, and ratios of all makes and models sold in the US market of 2024-2025.

Data is taken from manufacturer website and Car & Driver where applicable.

I only compared data with vehicles designed, marketed, and sold as sedans or lower. Wagons were included where applicable. The Mercedes E-class wagon was excluded due to lack of data found. Data excludes vehicles sold and marketed as CUV and above (CUVs, SUVs, Trucks, Vans, etc.)

SpaceKnow uses satellite (SAR) data to capture activity in electric vehicles and automotive factories.

Data is updated daily, has an average lag of 4-6 days, and history back to 2017.

The insights provide you with level and change data that monitors the area which is covered with assembled light vehicles in square meters.

We offer 3 delivery options: CSV, API, and Insights Dashboard

Available companies Rivian (NASDAQ: RIVN) for employee parking, logistics, logistic centers, product distribution & product in the US. (See use-case write up on page 4) TESLA (NASDAQ: TSLA) indices for product, logistics & employee parking for Fremont, Nevada, Shanghai, Texas, Berlin, and Global level Lucid Motors (NASDAQ: LCID) for employee parking, logistics & product in US

Why get SpaceKnow's EV datasets?

Monitor the company’s business activity: Near-real-time insights into the business activities of Rivian allow users to better understand and anticipate the company’s performance.

Assess Risk: Use satellite activity data to assess the risks associated with investing in the company.

Types of Indices Available Continuous Feed Index (CFI) is a daily aggregation of the area of metallic objects in square meters. There are two types of CFI indices. The first one is CFI-R which gives you level data, so it shows how many square meters are covered by metallic objects (for example assembled cars). The second one is CFI-S which gives you change data, so it shows you how many square meters have changed within the locations between two consecutive satellite images.

How to interpret the data SpaceKnow indices can be compared with the related economic indicators or KPIs. If the economic indicator is in monthly terms, perform a 30-day rolling sum and pick the last day of the month to compare with the economic indicator. Each data point will reflect approximately the sum of the month. If the economic indicator is in quarterly terms, perform a 90-day rolling sum and pick the last day of the 90-day to compare with the economic indicator. Each data point will reflect approximately the sum of the quarter.

Product index This index monitors the area covered by manufactured cars. The larger the area covered by the assembled cars, the larger and faster the production of a particular facility. The index rises as production increases.

Product distribution index This index monitors the area covered by assembled cars that are ready for distribution. The index covers locations in the Rivian factory. The distribution is done via trucks and trains.

Employee parking index Like the previous index, this one indicates the area covered by cars, but those that belong to factory employees. This index is a good indicator of factory construction, closures, and capacity utilization. The index rises as more employees work in the factory.

Logistics index The index monitors the movement of materials supply trucks in particular car factories.

Logistics Centers index The index monitors the movement of supply trucks in warehouses.

Where the data comes from: SpaceKnow brings you information advantages by applying machine learning and AI algorithms to synthetic aperture radar and optical satellite imagery. The company’s infrastructure searches and downloads new imagery every day, and the computations of the data take place within less than 24 hours.

In contrast to traditional economic data, which are released in monthly and quarterly terms, SpaceKnow data is high-frequency and available daily. It is possible to observe the latest movements in the EV industry with just a 4-6 day lag, on average.

The EV data help you to estimate the performance of the EV sector and the business activity of the selected companies.

The backbone of SpaceKnow’s high-quality data is the locations from which data is extracted. All locations are thoroughly researched and validated by an in-house team of annotators and data analysts.

Each individual location is precisely defined so that the resulting data does not contain noise such as surrounding traffic or changing vegetation with the season.

We use radar imagery and our own algorithms, so the final indices are not devalued by weather conditions such as rain or heavy clouds.

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Use Case - Rivian:

SpaceKnow uses the quarterly production and delivery data of Rivian as a benchmark. Rivian targeted to produce 25,000 cars in 2022. To achieve this target, the company had to increase production by 45% by producing 10,683 cars in Q4. However the production was 10,020 and the target was slightly missed by reaching total production of 24,337 cars for FY22.

SpaceKnow indices help us to observe the company’s operations, and we are able to monitor if the company is set to meet its forecasts or not. We deliver five different indices for Rivian, and these indices observe logistic centers, employee parking lot, logistics, product, and prod...

This dataset features over 1,000,000 high-quality images of cars, sourced globally from photographers, enthusiasts, and automotive content creators. Optimized for AI and machine learning applications, it provides richly annotated and visually diverse automotive imagery suitable for a wide array of use cases in mobility, computer vision, and retail.

Key Features: 1. Comprehensive Metadata: each image includes full EXIF data and detailed annotations such as car make, model, year, body type, view angle (front, rear, side, interior), and condition (e.g., showroom, on-road, vintage, damaged). Ideal for training in classification, detection, OCR for license plates, and damage assessment.

1. Unique Sourcing Capabilities: the dataset is built from images submitted through a proprietary gamified photography platform with auto-themed competitions. Custom datasets can be delivered within 72 hours targeting specific brands, regions, lighting conditions, or functional contexts (e.g., race cars, commercial vehicles, taxis).

2. Global Diversity: contributors from over 100 countries ensure broad coverage of car types, manufacturing regions, driving orientations, and environmental settings—from luxury sedans in urban Europe to pickups in rural America and tuk-tuks in Southeast Asia.

3. High-Quality Imagery: images range from standard to ultra-HD and include professional-grade automotive photography, dealership shots, roadside captures, and street-level scenes. A mix of static and dynamic compositions supports diverse model training.

4. Popularity Scores: each image includes a popularity score derived from GuruShots competition performance, offering valuable signals for consumer appeal, aesthetic evaluation, and trend modeling.

5. AI-Ready Design: this dataset is structured for use in applications like vehicle detection, make/model recognition, automated insurance assessment, smart parking systems, and visual search. It’s compatible with all major ML frameworks and edge-device deployments.

6. Licensing & Compliance: fully compliant with privacy and automotive content use standards, offering transparent and flexible licensing for commercial and academic use.

Use Cases: 1. Training AI for vehicle recognition in smart city, surveillance, and autonomous driving systems. 2. Powering car search engines, automotive e-commerce platforms, and dealership inventory tools. 3. Supporting damage detection, condition grading, and automated insurance workflows. 4. Enhancing mobility research, traffic analytics, and vision-based safety systems.

This dataset delivers a large-scale, high-fidelity foundation for AI innovation in transportation, automotive tech, and intelligent infrastructure. Custom dataset curation and region-specific filters are available. Contact us to learn more!

The number of new motor vehicles sold. Motor vehicles include all trucks, vans, coaches and buses, minivans, sport utility vehicles, and other passenger cars.

Imports of Automotive Vehicles in the United States increased to 38524 USD Million in February from 37559 USD Million in January of 2024. This dataset includes a chart with historical data for the United States Imports of Automotive Vehicles.

End-Period-Cash-Flow Time Series for Cars.com Inc. Cars.com Inc., an audience-driven technology company, provides solutions for the automotive industry in the United States. The company offers cars commerce platforms, such as Marketplace, allowing OEMs and dealers to merchandise their inventory and allowing consumers to add and save vehicles to virtual garage and track the Cars.com market value of current vehicle, as well as provides reputation management technology and digital financing tools and access to in-market consumers who are ready to trade-in its vehicle for a new one. It also provides website creation and platform hosting; digital retailing solutions; and trade and appraisal product, including AccuTrade, uses real-time market data and diagnostic scans to determine the right trade-in offer for every VIN in minutes. In addition, the company offers Cars Commerce Media Network products comprising Cars Social, allows dealers to target and serve native advertisements displaying real-time inventory to in-market car shoppers on Facebook and Instagram; VIN Performance Media, a machine-learning for media campaign, including audience targeting, real-time inventory, and ad placement across search, social, and display; In-Market Video, provides OEMs and dealers to pinpoint serious, ready-to-buy shoppers geographically; and In-Market Display, enable dealers and OEMs to extend reach and access audience of in-market car shoppers. The company serves local dealers, OEMs, dealer groups, and auto-adjacent companies. Cars.com Inc. was founded in 1998 and is headquartered in Chicago, Illinois.

A Chinese automobile company, Geely Auto, aspires to enter the US market by setting up their manufacturing unit there and producing cars locally to give competition to their US and European counterparts.

They have contracted an automobile consulting company to understand the factors on which the pricing of cars depends. Specifically, they want to understand the factors affecting car pricing in the American market, as they may differ from the Chinese market.

The company wants to know the following things:

Which variables are significant in predicting the price of a car? How well do those variables describe the price of a car? Based on various market surveys, the consulting firm has gathered a large data set of different types of cars across the American market.

Business Goals

You are required to model the price of cars with the available independent variables. The management will use be using this model to understand exactly how the prices vary with the independent variables. Accordingly, they can change the design of the cars, the business strategy, etc., to meet certain price levels. Further, the model will allow the management to understand the pricing dynamics of a new market.

Data Preparation

There is a variable named CarName that comprises two parts: the first word is the name of the car company, and the second is the car model. For example, Chevrolet Impala has ‘Chevrolet’ as the car company name and ‘Impala’ as the car model name. You need to consider only the company name as the independent variable for model building.

Model Evaluation

When you are done with model building and residual analysis and have made predictions on the test set, ensure that you use the following two lines of code to calculate the R-squared score on the test set:

from sklearn.metrics import r2_score r2_score(y_test, y_pred)

Where y_test is the test dataset for the target variable, and y_pred is the variable containing the predicted values of the target variable on the test set.

Do not forget to perform this step as the R-squared score on the test set holds some marks. The variable names inside the ‘r2_score’ function can vary based on your chosen variable names.

Electric Vehicle Sales: ytd: Rivian data was reported at 8,553.000 Unit in Mar 2025. This records a decrease from the previous number of 51,579.000 Unit for Dec 2024. Electric Vehicle Sales: ytd: Rivian data is updated quarterly, averaging 17,087.000 Unit from Dec 2021 (Median) to Mar 2025, with 14 observations. The data reached an all-time high of 51,579.000 Unit in Dec 2024 and a record low of 583.000 Unit in Dec 2021. Electric Vehicle Sales: ytd: Rivian data remains active status in CEIC and is reported by Cox Automotive. The data is categorized under Global Database’s United States – Table US.RA008: Electric Vehicle Sales: by Brand and Model: ytd.

Fuel economy data are the result of vehicle testing done at the Environmental Protection Agency's National Vehicle and Fuel Emissions Laboratory in Ann Arbor, Michigan, and by vehicle manufacturers with oversight by EPA.In 2016, the Department of Justice alleged violations of the Clean Air Act by Volkswagen (including Audi and Porsche) covering all of Volkswagen's 2.0L and 3.0L diesel vehicles sold in the United States since model year 2009. All relevant data from the affected vehicles have been removed from this website until there is an EPA-approved emissions.EPA has issued a Notice of Violation to Fiat Chrysler Automobiles N.V. and FCA US LLC for Model Year 2014-2016 light-duty diesel vehicles (Ram 1500 and Jeep Grand Cherokee). All relevant data from the affected vehicles has been removed from this website until further information is available.

Electric Vehicle Sales: ytd: BMW data was reported at 13,538.000 Unit in Mar 2025. This records a decrease from the previous number of 50,980.000 Unit for Dec 2024. Electric Vehicle Sales: ytd: BMW data is updated quarterly, averaging 12,125.000 Unit from Mar 2021 (Median) to Mar 2025, with 16 observations. The data reached an all-time high of 50,980.000 Unit in Dec 2024 and a record low of 348.000 Unit in Mar 2021. Electric Vehicle Sales: ytd: BMW data remains active status in CEIC and is reported by Cox Automotive. The data is categorized under Global Database’s United States – Table US.RA008: Electric Vehicle Sales: by Brand and Model: ytd.

This dataset shows the Battery Electric Vehicles (BEVs) and Plug-in Hybrid Electric Vehicles (PHEVs) that are currently registered through Washington State Department of Licensing (DOL).

1) Data Introduction • The USA - 2025 - Car Price Dataset includes 13 key characteristics, including vehicle price, brand, model, year, mileage, color, and title status, based on approximately 2,500 used car transaction information in the U.S., allowing you to analyze price trends and brand-specific preferences in the 2025 U.S. used car market.

2) Data Utilization (1) USA - 2025 - Car Price Dataset has characteristics that: • This dataset includes a variety of vehicle and transaction-related characteristics, including vehicle price, brand, model, year, mileage, title status, color, vehicle identification information (vin, lot). (2) USA - 2025 - Car Price Dataset can be used to: • Used Car Price Forecasting Model Development: Using key characteristics such as brand, model, year, mileage, etc., used car price forecasting and valuation models based on machine learning can be built. • Market trends and consumer analysis: Data analysis can be used to understand market trends and consumer preferences, including yearly and brand price changes, popular models, and correlations between mileage and price.