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 the fourth quarter of 2024, there were around ***** million vehicles operating on roads throughout the United States. Almost **** million used vehicles changed owners in the U.S. between the fourth quarter of 2023 and the fourth quarter of 2024, while new registrations of vehicles came to about **** million units during that period. Automotive market disparities The number of licensed drivers had been steadily increasing up to just under ******* in 2023, but the automotive market has been impacted by economic developments over the past few years. The U.S. vehicle fleet is aging, reflected by the slow increase in the average vehicle age from **** years in 2018 to over ** years in 2024. This is in part due to market disparities. The average selling price of new vehicles has been increasing to nearly ****** U.S. dollars in 2024, up from under ****** in 2016. Used car prices have been declining after the chip shortages linked to the COVID-19 pandemic, reaching around ****** U.S. dollars in 2024. The majority of U.S. car owners earned more than ****** U.S. dollars per years, with the ****** to ****** income group owning over ** percent of the vehicles in use. The boom of the used vehicle market Close to ************* of new car buyers were born between 1946 and 1981, with Gen X being the leading consumers by age group for both the new and used vehicle market. Used light vehicle sales have been steadily increasing since 2010, representing well over double the size of the new light vehicle market in 2024. With a product range priced below new vehicle prices, used vehicles are gaining momentum in the United States. The average American household spends some ***** U.S. dollars on vehicle purchases annually, with consumers in income groups earning above 100,000 U.S. dollars per year spending above ***** dollars annually on car buying. Used vehicle financing options are naturally more affordable than new vehicle financing options, with an average monthly payment over *** dollars for loan payments for new vehicles.

The Stanford Cars dataset consists of 196 classes of cars with a total of 16,185 images, taken from the rear. The data is divided into almost a 50-50 train/test split with 8,144 training images and 8,041 testing images. Categories are typically at the level of Make, Model, Year. The images are 360×240.

Worldwide car sales grew to around ** million automobiles in 2024, up from around **** million units in 2023. Throughout 2020 and 2021, the sector experienced a downward trend on the back of a slowing global economy, while COVID-19 and the Russian war on Ukraine contributed to shortages in the automotive semiconductor industry and further supply chain disruptions in 2022. Despite these challenges, 2023 and 2024 sales surpassed pre-pandemic levels and are forecast to keep rising through 2025. Covid-19 hits car demand It had been estimated pre-pandemic that international car sales were on track to reach ** million. While 2023 sales are still far away from that goal, this was the first year were car sales exceeded pre-pandemic values. The automotive market faced various challenges in 2023, including supply shortages, automotive layoffs, and strikes in North America. However, despite these hurdles, the North American market was among the fastest-growing regions in 2024, along with Eastern Europe and Asia, as auto sales in these regions increased year-on-year. Chinese market recovers After years of double-digit growth, China's economy began to lose steam in 2022, and recovery has been slow through 2023. China was the largest automobile market based on sales with around **** million units in 2023. However, monthly car sales in China were in free-fall in April 2022 partly due to shortages, fears over a looming recession, and the country grappling with the COVID-19 pandemic. By June of that same year, monthly sales in China were closer to those recorded in 2021.

Total Vehicle Sales in the United States decreased to 15.65 Million in May from 17.27 Million in April 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.

Statistical analysis of the vehicle fleet for passenger cars by province and year of registration of the vehicle. Vehicle fleet statistics are prepared from data in open format made available on the portal of the Automobile Club of Italy (ACI - https://www.aci.it/laci/studies-and-research/data-e-statistics/self-portrait.html). The data were cut out for the Piedmont Region only and completed with the provincial ISTAT codes, for easy reading and possible comparison with other datasets. The data, taken from the Ente’s archives (primary source of the statistics concerning the vehicle fleet is the Pra, Pubblico vehicle register) and from the analysis of the vehicle fleet, in this case in Piedmont, may be of interest both to the world of the economy and the environment, both for land management and for surveys of a social nature. The publication shall take place by the ACI by October of each year with data relating to 31 December of the previous year.

Morocco MA: Passenger Cars: per One Thousand Inhabitants data was reported at 84.725 Ratio in 2019. This records an increase from the previous number of 81.880 Ratio for 2018. Morocco MA: Passenger Cars: per One Thousand Inhabitants data is updated yearly, averaging 76.029 Ratio from Dec 2013 (Median) to 2019, with 7 observations. The data reached an all-time high of 84.725 Ratio in 2019 and a record low of 68.662 Ratio in 2013. Morocco MA: Passenger Cars: per One Thousand Inhabitants data remains active status in CEIC and is reported by Organisation for Economic Co-operation and Development. The data is categorized under Global Database’s Morocco – Table MA.OECD.ITF: Motor Vehicles Statistics: Non OECD Member: Annual. PASSENGER CARS The stock of road motor vehicles is the number of road motor vehicles registered at a given date in a country and licenced to use roads open to public traffic. This includes road vehicles exempted from annual taxes or licence fee; it also includes imported second-hand vehicles and other road vehicles according to national practices. It should not include military vehicles.; PASSENGER CARS A passenger car is a road motor vehicle, other than a moped or a motorcycle, intended for the carriage of passengers and designed to seat no more than nine people (including the driver). It refers to category M1 of the UN Consolidated Resolution on the Construction of Vehicles. Passenger cars, vans designed and used primarily for transport of passengers, taxis, hire cars, ambulances and motor homes are not included. Light goods road vehicles, motor-coaches and buses and mini-buses/mini-coaches are not included. Microcars (needing no permit to be driven), taxis and passenger hire cars, provided that they have fewer than ten seats, are included.

Aerial Cars

## Overview

Aerial Cars is a dataset for object detection tasks - it contains Cars annotations for 153 images.

## Getting Started

You can download this dataset for use within your own projects, or fork it into a workspace on Roboflow to create your own model.

  ## License

  This dataset is available under the [Public Domain license](https://creativecommons.org/licenses/Public Domain).

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.

→ Reach out to get a free trial

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...

Over the past few years, Tesla has expanded its efforts to build fully autonomous road vehicles. This has resulted in them holding the major share of operational cars that are collecting data for autonomous driving use, at a total of 2.7 million. This could be data regarding recorded road accidents or problems with the autopilot system. The second most significant participant in data collection was Xpeng with 270,000 cars. Finally, Waymo, Baidu, Pony and Cruise show significantly smaller fleet sizes collecting data, ranging from 1,000 to as low as 300 cars.

This table contains figures on traffic performance (vehicle-kilometres) of passenger cars, delivery vans, lorries, semi-trailers, special purpose vehicles and buses. Vehicle-kilometres of Dutch vehicles have been broken down by Dutch vehicles on Dutch territory and Dutch vehicles on foreign territory.

In addition, there are figures on the total distance covered on Dutch territory. A distinction is made between kilometres covered by Dutch vehicles and kilometres by foreign vehicles.

The vehicle population used to estimate the kilometres is based on the vehicle fleet statistics. The population of the figures in this table is based on the new selection method of the vehicle fleet. The difference between the old and the new selection method is described in a methodological report, see paragraph 4. The data series of vehicle kilometres estimated for the new population is available starting from 2018. The data series based on the old population ends with 2020. The way in which the vehicle kilometres are estimated has not changed, only the population.

For the 2020 data a correction factor was implemented to correct for the ‘smoothing effect’ caused by the method. The smoothing effect smoothes out yearly variation in the data and this results in a distorted picture of periods of time when mobility patterns suddenly change drastically, like happened in 2020 due to COVID-19.

Data available from:2018

Status of the figures: The figures in this table up to and including 2021 are definitive. Figures over 2022 and 2023 have a provisional status.

Changes as of 21 October 2024: Figures of 2023 have been added.

When will new figures be published? New figures are expected to be released by end of 2025.

The Comprehensive Cars (CompCars) dataset contains data from two scenarios, including images from web-nature and surveillance-nature. The web-nature data contains 163 car makes with 1,716 car models. There are a total of 136,726 images capturing the entire cars and 27,618 images capturing the car parts. The full car images are labeled with bounding boxes and viewpoints. Each car model is labeled with five attributes, including maximum speed, displacement, number of doors, number of seats, and type of car. The surveillance-nature data contains 50,000 car images captured in the front view.

The dataset can be used for the tasks of:

Fine-grained classification Attribute prediction Car model verification

The dataset can be also used for other tasks such as image ranking, multi-task learning, and 3D reconstruction.

NCAP rates vehicles to determine crash worthiness and rollover safety. The safety ratings are gathered during controlled crash and rollover tests conducted at NHTSA research facilities. Vehicles with a rating of five stars indicate the highest safety rating, whereas a one star indicates the lowest rating.

The given dataset provides information about vehicles, including their identification, location, specifications, and other relevant details. It contains several columns, each representing a specific aspect of the vehicles.

The "VIN(1-10)" column contains the unique Vehicle Identification Number assigned to each vehicle. The "Country" column indicates the country where the vehicle is registered, while the "City" and "State" columns specify the city and state of the vehicle's location. The "Postal code" column provides the postal code of the vehicle's location.

The dataset also includes information about the vehicle's characteristics. The "Model Year" column denotes the manufacturing year of the vehicle model, while the "Make" and "Model" columns indicate the manufacturer and model name, respectively. The "Electric Vehicle Type" column categorizes the vehicles based on their electric propulsion, such as a battery-powered or plug-in hybrid.

Additionally, the dataset includes columns related to eligibility for Clean Alternative Fuel Vehicle (CAFV) incentives, electric range, base MSRP (Manufacturer's Suggested Retail Price), legislative district, and DOL Vehicle ID. The "Vehicle Location" column specifies the precise location or address of the vehicle.

Furthermore, the dataset provides information about the electric utility company that services the vehicles and the 2022 Census Tract associated with their location.

Overall, this dataset offers a comprehensive overview of vehicles, their characteristics, and relevant details that can be used for various analyses and insights related to electric vehicles, location-specific information, and other aspects of the vehicles' attributes.

Tasks :

• Get all the cars and their types that do not qualify for clean alternative fuel vehicle
• Get all TESLA cars with the model year, and model type made in Bothell City.
• Get all the cars that have an electric range of more than 100, and were made after 2015
• Draw plots to show the distribution between city and electric vehicle types

First Registrations of Brand New Passenger Cars data was reported at 746,788.000 Number in Dec 2024. This records an increase from the previous number of 738,592.000 Number for Sep 2024. First Registrations of Brand New Passenger Cars data is updated quarterly, averaging 747,191.500 Number from Mar 2020 (Median) to Dec 2024, with 20 observations. The data reached an all-time high of 1,044,835.000 Number in Jun 2021 and a record low of 652,191.000 Number in Dec 2021. First Registrations of Brand New Passenger Cars data remains active status in CEIC and is reported by Organisation for Economic Co-operation and Development. The data is categorized under Global Database’s United States – Table US.OECD.ITF: Motor Vehicles Statistics: OECD Member: Quarterly. [COVERAGE] A passenger car is a road motor vehicle, other than a motorcycle, intended for the carriage of passengers and designed to seat no more than nine persons (including the driver). The term 'passenger car' therefore covers microcars (need no permit to be driven), taxis and hired passenger cars, provided that they have fewer than ten seats. This category may also include pick-ups. [COVERAGE] Data do not include light trucks. [STAT_CONC_DEF] Until 2008, data are not available. Quarterly and monthly data are not available. Since 2022, data are not yet available.

Our automotive datasets provide comprehensive insights into the global vehicle market, covering a wide range of data points related to car listings, pricing trends, vehicle specifications, and market demand. These datasets are ideal for businesses, analysts, and developers looking to enhance automotive research, optimize pricing strategies, or improve vehicle inventory management.

Key Features:

  Vehicle Listings & Specifications: Access detailed information on cars, trucks, SUVs, motorcycles, and electric vehicles, 
    including make, model, year, trim, mileage, fuel type, and transmission.
  Pricing & Market Trends: Analyze historical and real-time pricing data to track market fluctuations, assess vehicle depreciation, 
    and optimize pricing strategies.
  Dealer & Private Seller Insights: Gain visibility into vehicle listings from dealerships and private sellers, including contact details, 
    location, and availability.
  Vehicle Condition & Features: Identify key attributes such as accident history, service records, safety features, and additional specifications.
  Regional & Global Coverage: Access datasets segmented by country, state, or city to analyze local and international automotive markets.


Use Cases:

  Market Research & Competitive Analysis: Monitor automotive trends, track competitor pricing, and assess consumer demand.
  Pricing Optimization: Adjust vehicle pricing based on real-time market data to maximize profitability and sales efficiency.
  Inventory & Fleet Management: Improve vehicle sourcing, inventory tracking, and fleet management for dealerships and rental companies.
  Automotive AI & Machine Learning: Train predictive models for vehicle valuation, demand forecasting, and fraud detection.
  Consumer Insights & Lead Generation: Identify potential buyers, analyze purchasing behavior, and enhance targeted marketing efforts.



  Our automotive datasets are available in multiple formats (JSON, CSV, Excel) and can be delivered via 
  API, cloud storage (AWS, Google Cloud, Azure), or direct download. 
  Gain valuable insights into the automotive industry with high-quality, structured data tailored to your needs.

Snapshot img

US Used Car Market Size 2025-2029

The us used car market size is forecast to increase by USD 40.2 billion at a CAGR of 4.3% between 2024 and 2029.

The used car market in the US exhibits robust growth, driven by the excellent value proposition that pre-owned vehicles offer to consumers. This market trend is further bolstered by the increasing penetration of online platforms dedicated to selling used cars, providing greater convenience and accessibility for buyers. However, the market faces regulatory challenges as stricter emission regulations limit the sale of non-compliant used cars, necessitating investments in upgrading inventory and adhering to regulatory frameworks. These hurdles, while significant, can be navigated through strategic partnerships with emission testing centers and ongoing investment in fleet modernization. Companies that effectively address these challenges and leverage the opportunities presented by the growing demand for used cars and the digital shift in sales channels will thrive in this dynamic market.

What will be the size of the US Used Car Market during the forecast period?

Request Free Sample

In the dynamic used car market, consumers face various challenges such as car scams and fraudulent activities. To mitigate risks, car buyers turn to comprehensive car buying guides and car detailing services. A VIN number check is essential for vehicle identification and history assessment, while emissions testing ensures environmental compliance. Car sharing and subscription services offer flexible mobility solutions. Vehicle registration and title transfer processes can be streamlined through digital means, and car refurbishment and connected car technology enhance safety and convenience. Blind spot monitoring and adaptive cruise control are popular safety features, while collision avoidance systems and lane departure warning systems provide added protection. Used car logistics and online financing applications simplify the purchasing process, and extended warranties offer peace of mind. Wireless charging, smartphone integration, and vehicle diagnostics are essential features for modern cars. Sustainable mobility and car comparison tools cater to eco-conscious consumers, while car maintenance schedules and roadside assistance ensure long-term vehicle care. Remote vehicle inspection and car care tips help maintain a car's resale value, and car subscription services offer flexible ownership alternatives. Used car fraud prevention and vehicle identification technologies protect buyers from potential risks. Car safety ratings and vehicle identification numbers are crucial tools for informed decision-making.

How is this market segmented?

The market research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD billion' for the period 2025-2029, as well as historical data from 2019-2023 for the following segments. Distribution Channel3P channel salesOEM channel salesProductMid sizeFull sizeCompact sizeVendor TypeOrganizedUnorganizedFuel TypeDieselPetrolGeographyNorth AmericaUS

By Distribution Channel Insights

The 3p channel sales segment is estimated to witness significant growth during the forecast period.

The used car market in the US is a dynamic and significant sector, with numerous entities shaping its activity. Used car buyers continuously seek value, leading to a high demand for pre-owned vehicles. Search engine optimization and online advertising play crucial roles in connecting buyers with sellers, whether they're private parties or car dealerships. Wholesale car lots and auctions provide inventory for dealerships, ensuring a steady supply of used cars. Fleet vehicles, often traded in for newer models, contribute to the used car inventory. Maintenance records and vehicle history reports are essential for buyers, influencing their purchasing decisions. Safety features, infotainment systems, and driver assistance are increasingly desired in used cars, especially among budget-conscious consumers and luxury car buyers. Electric and hybrid vehicles are gaining popularity, driving the demand for used models in these categories. Car negotiation, fuel economy, and vehicle valuation are essential factors in used car selling. Digital marketing, including social media, mobile apps, and data analytics, helps sellers reach a wider audience. Certified pre-owned vehicles, reconditioned cars, and consignment sales offer buyers additional options and peace of mind. Car financing, vehicle inspections, and warranties are essential components of the used car buying process. Autonomous driving technology and car pricing trends continue to evolve, impacting the used car market. As the average ownership cycle shortens, the market will see an increase in the availability of used cars, making it an exciting and ever-changing landscape for both buyers and sellers.

D

This dataset provides values for TOTAL VEHICLE SALES reported in several countries. The data includes current values, previous releases, historical highs and record lows, release frequency, reported unit and currency.

Description:

This dataset contains the latest information on car prices in Australia for the year 2023. It covers various brands, models, types, and features of cars sold in the Australian market. It provides useful insights into the trends and factors influencing the car prices in Australia. The dataset includes information such as brand, year, model, car/suv, title, used/new, transmission, engine, drive type, fuel type, fuel consumption, kilometres, colour (exterior/interior), location, cylinders in engine, body type, doors, seats, and price. The dataset has over 16,000 records of car listings from various online platforms in Australia.

Key Features:

• Brand: Name of the car manufacturer
• Year: Year of manufacture or release
• Model: Name or code of the car model
• Car/Suv: Type of the car (car or suv)
• Title: Title or description of the car
• UsedOrNew: Condition of the car (used or new)
• Transmission: Type of transmission (manual or automatic)
• Engine: Engine capacity or power (in litres or kilowatts)
• DriveType: Type of drive (front-wheel, rear-wheel, or all-wheel)
• FuelType: Type of fuel (petrol, diesel, hybrid, or electric)
• FuelConsumption: Fuel consumption rate (in litres per 100 km)
• Kilometres: Distance travelled by the car (in kilometres)
• ColourExtInt: Colour of the car (exterior and interior)
• Location: Location of the car (city and state)
• CylindersinEngine: Number of cylinders in the engine
• BodyType: Shape or style of the car body (sedan, hatchback, coupe, etc.)
• Doors: Number of doors in the car
• Seats: Number of seats in the car
• Price: Price of the car (in Australian dollars)

Potential Use Cases:

• Price prediction: Predict the price of a car based on its features and location using machine learning models.
• Market analysis: Explore the market trends and demand for different types of cars in Australia using descriptive statistics and visualization techniques.
• Feature analysis: Identify the most important features that affect the car prices and how they vary across different brands, models, and locations using correlation and regression analysis.

If you find this dataset useful, your support through an upvote would be greatly appreciated ❤️🙂
Thank you