Key information about US Number of Registered Vehicles

• US Number of Registered Vehicles was reported at 283,400,986 Unit in Dec 2022.
• This records an increase from the previous number of 282,354,993 Unit for Dec 2021.
• US Number of Registered Vehicles data is updated yearly, averaging 93,949,852 Unit from Dec 1910 to 2022, with 113 observations.
• The data reached an all-time high of 283,400,986 Unit in 2022 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.

Key information about United States Motor Vehicle Production

• United States Motor Vehicle Production was reported at 10,611,555.000 Unit in Dec 2023.
• This records an increase from the previous number of 10,052,958.000 Unit for Dec 2022.
• US Motor Vehicle Production data is updated yearly, averaging 11,292,123.000 Unit from Dec 1997 to 2023, with 27 observations.
• The data reached an all-time high of 13,024,978.000 Unit in 1999 and a record low of 5,731,397.000 Unit in 2009.
• US Motor Vehicle Production 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.MVP: Motor Vehicle Production: by Country.

The graph illustrates the number of registered cars in the United States from 1995 to 2023. The x-axis represents the years, spanning from 1995 to 2023, while the y-axis denotes the number of registered cars, ranging from 1,354 to 999,469. Throughout this period, the number of registered cars shows considerable fluctuations, with the highest count of 96,901,563 in 2022 and the lowest of 1,354 in 2006. Overall, there is a notable upward trend in car registrations over the years, despite intermittent decreases. The data is presented in a line graph format, effectively highlighting the annual changes and long-term growth in the number of registered vehicles in the United States.

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.

Total Vehicle Sales in the United States decreased to 16.10 Million in August from 16.40 Million in July 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.

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.

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 2023, California had the most automobile registrations: almost 13.2 million such vehicles were registered in the most populous U.S. federal state. California also had the highest number of registered motor vehicles overall: nearly 30.4 million registrations.

This dataset shows counts of transactions associated with authorizing vehicles to be used on public roads, commonly referred to as “buying tabs” or “buying tags”. The data includes registration activity by fuel type, county, primary use class, and date. This is comparable to the Fee Distribution Report #13, that is titled "Motor Vehicle Registration By Class and County".

Some 284.6 million vehicles were registered in the United States in 2023. The figures include passenger cars, motorcycles, trucks, buses, and other vehicles. The number of light trucks sold in the U.S. stood at 12.4 million units in 2023. U.S. vehicle registrations The United States is one of the world’s largest automobile markets based on the number of new light vehicle registrations, with more than 15.5 million new light vehicle registrations in 2023. However, domestic production of automobiles stood at around 1.7 million units in 2023, which was under half the output recorded in 2016. At the same time, the United States imports a significant number of vehicles and vehicle parts from various countries, such as Japan, Mexico, and Canada. Leading car manufacturers in the United States The leading car manufacturers overall in the United States include the domestic heavyweights General Motors and Ford. With respect to car brands, the Ford brand clocked in at number one in 2024, selling around 2.1 million vehicles in the United States alone. The brand's holding company is the Ford Motor Company; it was founded by Henry Ford in 1903 in Dearborn, Michigan. The company pioneered in large-scale car manufacturing and introduced production methods such as the assembly line.

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.

Total vehicle registration counts per month by county

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!

Introduction

Welcome to the US English Language In-car Speech Dataset, a comprehensive collection of audio recordings designed to facilitate the development of speech recognition models specifically tailored for in-car environments. This dataset aims to support research and innovation in automotive speech technology, enabling seamless and robust voice interactions within vehicles for drivers and co-passengers.

Speech Data

This dataset comprises over 5,000 high-quality audio recordings collected from various in-car environments. These recordings include scripted wake words and command-type prompts.

Participant Diversity:

- Speakers: 50+ native English speakers from the FutureBeeAI Community.

- Regions: Ensures a balanced representation of United States of America1 accents, dialects, and demographics.

- Participant Profile: Participants range from 18 to 70 years old, representing both males and females in a 60:40 ratio, respectively.

Recording Nature: Scripted wake word and command type of audio recordings.

- Duration: Average duration of 5 to 20 seconds per audio recording.

- Formats: WAV format with mono channels, a bit depth of 16 bits. The dataset contains different data at 16kHz and 48kHz.

Dataset Diversity

Apart from participant diversity, the dataset is diverse in terms of different wake words, voice commands, and recording environments.

Different Automobile Related Wake Words: Hey Mercedes, Hey BMW, Hey Porsche, Hey Volvo, Hey Audi, Hi Genesis, Hey Mini, Hey Toyota, Ok Ford, Hey Hyundai, Ok Honda, Hello Kia, Hey Dodge.

Different Cars: Data collection was carried out in different types and models of cars.

Different Types of Voice Commands:

- Navigational Voice Commands

- Mobile Control Voice Commands

- Car Control Voice Commands

- Multimedia & Entertainment Commands

- General, Question Answer, Search Commands

Recording Time: Participants recorded the given prompts at various times to make the dataset more diverse.

- Morning

- Afternoon

- Evening

Recording Environment: Various recording environments were captured to acquire more realistic data and to make the dataset inclusive of various types of noises. Some of the environment variables are as follows:

- Noise Level: Silent, Low Noise, Moderate Noise, High Noise

- Parking Location: Indoor, Outdoor

- Car Windows: Open, Closed

- Car AC: On, Off

- Car Engine: On, Off

- Car Movement: Stationary, Moving

Metadata

The dataset provides comprehensive metadata for each audio recording and participant:

Participant Metadata: Unique identifier, age, gender, country, state, district, accent, and dialect.

Other Metadata: Recording transcript, recording environment, device details, sample rate, bit depth, file format, recording time.

This metadata is a powerful tool for understanding and characterizing the data, enabling informed decision-making in the development of English voice assistant speech recognition models.

Usage and Applications

This In-car Speech Dataset is a valuable resource for various applications in the field of in-car voice recognition and AI-driven voice technology. This dataset can be leveraged to enhance the performance and functionality of voice-activated systems across different domains.

Speech Recognition Model Training: Provides high-quality audio data for training models to accurately recognize and respond to in-car voice commands.

Safety and Emergency Response: Supports the development of systems that recognize and respond to emergency commands and safety alerts.

Driver Assistance: Facilitates the creation of advanced driver-assistance systems (ADAS) that leverage voice commands for hands-free operation.

Secure and Ethical Collection

Our proprietary data collection platform, “Yugo,” was used throughout the process of this dataset creation.

Throughout the data collection process, the data remained within our secure platform and did not leave our environment, ensuring data security and confidentiality.

The data collection process adhered to strict ethical guidelines, ensuring the privacy and consent of all participants.

It does not include any personally identifiable information about any participant, which makes the dataset safe to use.

Updates and Customization

Understanding the importance of diverse environments for robust voice assistant models, our in-car voice dataset is regularly updated with new audio data captured in various real-world conditions.

Customization & Custom Collection Options:

- Environmental Conditions: Custom collection in specific environmental conditions upon request.

- Sample Rates: Customizable from 8kHz to 48kHz.

- Diverse Pace: Custom collection can be done at a diverse pace upon request.

- Device Specific: Recording can be done with the specific mobile brand or operating system.

License

This US English In-car audio dataset is created by FutureBeeAI and is available for commercial use.

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...

Key information about United States Motor Vehicle Sales: Commercial Cars

• United States Motor Vehicle Sales: Commercial Cars was reported at 12,892,621.000 Unit in Dec 2023.
• This records an increase from the previous number of 11,371,749.000 Unit for Dec 2022.
• US Motor Vehicle Sales: Commercial Cars data is updated yearly, averaging 9,784,346.000 Unit from Dec 2005 to 2023, with 19 observations.
• The data reached an all-time high of 12,892,621.000 Unit in 2023 and a record low of 5,200,478.000 Unit in 2009.
• US Motor Vehicle Sales: Commercial 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: Commercial Vehicle (CV).

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.

Graph and download economic data for Automobile Registrations, Passenger Cars, Total for United States from 1895 to 1944 about car registrations, vehicles, and USA.

Car Registrations in the United States increased to 240.90 Thousand in August from 221.50 Thousand in July of 2025. This dataset provides - United States Car Registrations - actual values, historical data, forecast, chart, statistics, economic calendar and news.