The graph illustrates the average number of cars per household in the United States from 1969 to 2022. The x-axis represents the years, labeled from '69 to '22, while the y-axis displays the average number of cars per household. Over this period, the average increased from 1.16 cars per household in 1969 to a peak of 1.89 in 2001. The lowest recorded average was 1.16 in 1969, and the highest was 1.89 in 2001. After 2001, the average slightly decreased to 1.83 in 2022. The data indicates an overall upward trend in the average number of cars per household over the decades, with a slight decline in recent years.

United States Average Vehicles per Household: 4 or More Licensed Drivers data was reported at 4.100 Unit in 2017. This records an increase from the previous number of 3.900 Unit for 2009. United States Average Vehicles per Household: 4 or More Licensed Drivers data is updated yearly, averaging 3.850 Unit from Dec 1991 (Median) to 2017, with 4 observations. The data reached an all-time high of 4.100 Unit in 2017 and a record low of 3.800 Unit in 2001. United States Average Vehicles per Household: 4 or More Licensed Drivers data remains active status in CEIC and is reported by Center for Transportation Analysis. The data is categorized under Global Database’s United States – Table US.TA003: Number of Vehicles per Household.

The Household Size by Vehicles Available dataset was compiled using information from December 31, 2023 and updated December 12, 2024 from the Bureau of Transportation Statistics (BTS) and is part of the U.S. Department of Transportation (USDOT)/Bureau of Transportation Statistics (BTS) National Transportation Atlas Database (NTAD). The Household Size by Vehicles Available table from the 2023 American Community Survey (ACS) 5-year estimates was joined to 2023 tract-level geographies for all 50 States, District of Columbia and Puerto Rico provided by the Census Bureau. A new file was created that combines the demographic variables from the former with the cartographic boundaries of the latter. The national level census tract layer contains data on the number and percentage of households by household size by number of vehicles available.

United States Average Vehicles per Household: w/ Children data was reported at 2.200 Unit in 2009. This stayed constant from the previous number of 2.200 Unit for 2001. United States Average Vehicles per Household: w/ Children data is updated yearly, averaging 2.200 Unit from Dec 1991 (Median) to 2009, with 3 observations. The data reached an all-time high of 2.200 Unit in 2009 and a record low of 2.200 Unit in 2009. United States Average Vehicles per Household: w/ Children data remains active status in CEIC and is reported by Center for Transportation Analysis. The data is categorized under Global Database’s USA – Table US.TA003: Number of Vehicles per Household.

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.

The US Consumer Auto package includes every vehicle available in a household and is tied to the full US Consumer database.

Although the American Community Survey (ACS) produces population, demographic and housing unit estimates, it is the Census Bureau's Population Estimates Program that produces and disseminates the official estimates of the population for the nation, states, counties, cities, and towns and estimates of housing units for states and counties..Supporting documentation on code lists, subject definitions, data accuracy, and statistical testing can be found on the American Community Survey website in the Technical Documentation section.Sample size and data quality measures (including coverage rates, allocation rates, and response rates) can be found on the American Community Survey website in the Methodology section..Source: U.S. Census Bureau, 2017-2021 American Community Survey 5-Year Estimates.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 roughly 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 ACS Technical Documentation). The effect of nonsampling error is not represented in these tables..Workers include members of the Armed Forces and civilians who were at work last week..The 2017-2021 American Community Survey (ACS) data generally reflect the March 2020 Office of Management and Budget (OMB) delineations of metropolitan and micropolitan statistical areas. In certain instances, the names, codes, and boundaries of the principal cities shown in ACS tables may differ from the OMB delineation lists due to differences in the effective dates of the geographic entities..Estimates of urban and rural populations, housing units, and characteristics reflect boundaries of urban areas defined based on Census 2010 data. As a result, data for urban and rural areas from the ACS do not necessarily reflect the results of ongoing urbanization..Explanation of Symbols:- The estimate could not be computed because there were an insufficient number of sample observations. For a ratio of medians estimate, one or both of the median estimates falls in the lowest interval or highest interval of an open-ended distribution. For a 5-year median estimate, the margin of error associated with a median was larger than the median itself.N The estimate or margin of error cannot be displayed because there were an insufficient number of sample cases in the selected geographic area. (X) The estimate or margin of error is not applicable or not available.median- The median falls in the lowest interval of an open-ended distribution (for example "2,500-")median+ The median falls in the highest interval of an open-ended distribution (for example "250,000+").** The margin of error could not be computed because there were an insufficient number of sample observations.*** The margin of error could not be computed because the median falls in the lowest interval or highest interval of an open-ended distribution.***** A margin of error is not appropriate because the corresponding estimate is controlled to an independent population or housing estimate. Effectively, the corresponding estimate has no sampling error and the margin of error may be treated as zero.

When asked about "Car ownership", * percent of U.S. respondents answer "Yes, a company car". This online survey was conducted in 2025, among ****** consumers. Looking to gain valuable insights about car owners across the globe? Check out our reports about consumers of car brands worldwide. These reports provide readers with a detailed understanding of car owners: their identities, preferences, opinions, and how to effectively engage with them.

United States Average Vehicles per Household: Rural data was reported at 2.400 Unit in 2009. This records an increase from the previous number of 2.300 Unit for 2001. United States Average Vehicles per Household: Rural data is updated yearly, averaging 2.300 Unit from Dec 1991 (Median) to 2009, with 3 observations. The data reached an all-time high of 2.400 Unit in 2009 and a record low of 2.100 Unit in 1991. United States Average Vehicles per Household: Rural data remains active status in CEIC and is reported by Center for Transportation Analysis. The data is categorized under Global Database’s USA – Table US.TA003: Number of Vehicles per Household.

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.

United States Average Vehicles per Household: 2 Persons data was reported at 2.000 Unit in 2009. This stayed constant from the previous number of 2.000 Unit for 2001. United States Average Vehicles per Household: 2 Persons data is updated yearly, averaging 2.000 Unit from Dec 1991 (Median) to 2009, with 3 observations. The data reached an all-time high of 2.000 Unit in 2009 and a record low of 1.900 Unit in 1991. United States Average Vehicles per Household: 2 Persons data remains active status in CEIC and is reported by Center for Transportation Analysis. The data is categorized under Global Database’s USA – Table US.TA003: Number of Vehicles per Household.

This layer contains 2010-2014 American Community Survey (ACS) 5-year data, and contains estimates and margins of error. The layer shows household size by number of vehicles available. This is shown by tract, county, and state boundaries. 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. Vintage: 2010-2014ACS Table(s): B08201 Data downloaded from: Census Bureau's API for American Community Survey Date of API call: November 11, 2020National 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 has associated layers containing the most recent ACS data available by the U.S. Census Bureau. Click here to learn more about ACS data releases and click here for the associated boundaries layer. The reason this data is 5+ years different from the most recent vintage is due to the overlapping of survey years. It is recommended by the U.S. Census Bureau to compare non-overlapping datasets.Boundaries come from the US Census TIGER geodatabases. Boundary vintage (2014) appropriately matches the data vintage as specified by the Census. These are Census boundaries with water and/or coastlines clipped for cartographic purposes. For census tracts, the water cutouts are derived from a subset of the 2010 AWATER (Area Water) boundaries offered by TIGER. For state and county boundaries, the water and coastlines are derived from the coastlines of the 500k TIGER Cartographic Boundary Shapefiles. 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.

Annual average net outlays for vehicle purchases came to above ***** U.S. dollars for all U.S. consumers in 2023, ranging between around ***** U.S. dollars for those in the lowest income bracket to nearly ****** U.S. dollars for consumers in the highest income group.

United States Average Vehicles per Household: 2 Licensed Drivers data was reported at 2.200 Unit in 2009. This stayed constant from the previous number of 2.200 Unit for 2001. United States Average Vehicles per Household: 2 Licensed Drivers data is updated yearly, averaging 2.200 Unit from Dec 1991 (Median) to 2009, with 3 observations. The data reached an all-time high of 2.200 Unit in 2009 and a record low of 2.100 Unit in 1991. United States Average Vehicles per Household: 2 Licensed Drivers data remains active status in CEIC and is reported by Center for Transportation Analysis. The data is categorized under Global Database’s USA – Table US.TA003: Number of Vehicles per Household.

The census is undertaken by the Office for National Statistics every 10 years and gives us a picture of all the people and households in England and Wales. The most recent census took place in March of 2021.The census asks every household questions about the people who live there and the type of home they live in. In doing so, it helps to build a detailed snapshot of society. Information from the census helps the government and local authorities to plan and fund local services, such as education, doctors' surgeries and roads.Key census statistics for Leicester are published on the open data platform to make information accessible to local services, voluntary and community groups, and residents. There is also a dashboard published showcasing various datasets from the census allowing users to view data for Leicester and compare this with national statistics.Further information about the census and full datasets can be found on the ONS website - https://www.ons.gov.uk/census/aboutcensus/censusproductsCar availabilityThis dataset provides Census 2021 estimates on the number of cars or vans available to members of households for England and Wales. The estimates are as at Census Day, 21 March 2021.Definition: The number of cars or vans owned or available for use by household members.Vehicles included:pick-ups, camper vans and motor homesvehicles that are temporarily not working vehicles that have failed their MOTvehicles owned or used by a lodgercompany cars or vans if they're available for private useVehicles not included:motorbikes, trikes, quad bikes or mobility scootersvehicles that have a Statutory Off Road Notification (SORN)vehicles owned or used only by a visitor vehicles that are kept at another address or not easily accessedThe number of cars or vans in an area relates only to households. Cars or vans used by communal establishment residents are not counted.Households with 10 to 20 cars or vans are counted as having only 10.Households with more than 20 cars or vans were treated as invalid and a value imputed.This dataset includes data for Leicester city and England overall.

Some of the most vulnerable populations don’t have the network or the financial means necessary to evacuate themselves during a catastrophic disaster. Understanding where these people are is critical information for first responders so that they can provide the necessary support and aid to everyone. This is extremely important if these individuals are living in isolated areas that are difficult to access; if residents have no way of evacuating themselves (no vehicle available); or if the residents have special transportation needs due to disability or medical issues.This map shows counts and percents of households that have no vehicle available by state, county, and tract. Vehicles include passenger cars, vans, and pickup or panel trucks kept at home and available for use of household members. Motorcycles, other recreational vehicles, dismantled or immobile vehicles, and vehicles used only for business purposes are excluded. Map starts in New Orleans, but zoom, pan, or use the search bar to get to your city, county, or neighborhood. Hover over the bar chart in the pop-up to see information about household size.This map uses these hosted feature layers containing the most recent American Community Survey data. These layers are part of the ArcGIS Living Atlas, and are updated every year when the American Community Survey releases new estimates, so values in the map always reflect the newest data available. Other uses of this data:When the data is used in conjunction with place-of-work and journey-to-work data, the information can provide insight into vehicle travel and aid in forecasting future travel and its effect on transportation systems. The data also serve to aid in forecasting future energy consumption and needs.

Alesco Data's Automotive records are updated monthly from millions of proprietary sourced vehicle transactions. These incoming transactions are processed through compilation rules and are either added as new, incremental records to our file, or contribute to validating existing records.

Our recent focus is on compiling new vehicle ownership, and the file includes over 14.2 million late model vehicle owners (2020-2025).

In addition, we append our Persistent ID, telephone numbers, and demographics for a complete file that can support your direct mail and email marketing, lead validation, and identity verification needs. A Persistent ID is assigned to each vehicle record and tracks consumers as they change addresses or phone numbers, and vehicles as they change owners.

The database is not derived from state motor vehicle databases and therefore not subject to the Shelby Act also known as the Driver's Privacy Protection Act (DPPA) of 2000. The data is deterministic and sources include sales and service data, warranty data and notifications, aftermarket repair and maintenance facilities, and scheduled maintenance records.

Fields Included: -Make -Model -Year -VIN -Vehicle Class Code (crossover, SUV, full-size, mid-size, small) -Vehicle Fuel Code (gas, flex, hybrid) -Vehicle Style Code (sport, pickup, utility, sedan) -Mileage -Number of Vehicles per Household -First seen date -Last seen date -Email

This paper examines the association between the Great Recession and real assets among families with young children. Real assets such as homes and cars are key indicators of economic well-being that may be especially valuable to low-income families. Using longitudinal data from the Fragile Families and Child Wellbeing Study (N = 4,898), we investigate the association between the city unemployment rate and home and car ownership and how the relationship varies by family structure (married, cohabiting, and single parents) and by race/ethnicity (White, Black, and Hispanic mothers). Using mother fixed-effects models, we find that a one percentage point increase in the unemployment rate is associated with a -0.5 percentage point decline in the probability of home ownership and a -0.7 percentage point decline in the probability of car ownership. We also find that the recession was associated with lower levels of home ownership for cohabiting families and for Hispanic families, as well as lower car ownership among single mothers and among Black mothers, whereas no change was observed among married families or White households. Considering that homes and cars are the most important assets among middle and low-income households in the U.S., these results suggest that the rise in the unemployment rate during the Great Recession may have increased household asset inequality across family structures and race/ethnicities, limiting economic mobility, and exacerbating the cycle of poverty.

The increasing diversity of vehicle type holdings and growing demand for BEVs and PHEVs have serious policy implications for travel demand and air pollution. Consequently, it is important to accurately predict or estimate the preference for vehicle holdings of households as well as the vehicle miles traveled by vehicle body and fuel type to project future VMT changes and mobile source emission levels. The current report presents the application of a utility-based model for multiple discreteness that combines multiple vehicle types with usage in an integrated model, specifically the MDCEV model. We use the 2019 California Vehicle Survey data here that allows us to analyze the driving behavior associated with more recent EV models (with potentially longer ranges). Important findings from the model include:

Household characteristics like size or having children have an expected impact on vehicle preference: larger vehicles are preferred. College education, rooftop solar ownership, and the number of employed workers in a household affect the preference for BEVs and PHEVs in the small car segment dominated by the Leaf, Bolt, Prius-Plug-in and the Volt often used as a commuter car. Among built environment factors, population density and the walkability index of a neighborhood have a statistically significant impact on the type of vehicle choice and VMT. It is observed that a 10% increase in population density reduces the preference for ICEV pickup trucks by 0.34% and VMT by 0.4%. However, if the increase in population density is 25%, the reduction in preference for pickup trucks is 8.4% and VMT is 8.6%. The other built environment factor we consider is the walkability index. If the walkability index of a neighborhood increases by 25%, it reduces the preference for ICEV pickup trucks by 15% and their VMT by 16%. Overall, these results suggest that if policies encourage mixed development of neighborhoods and increase density, it can have an important impact on ownership and usage of gas guzzlers like pickup trucks and help in the process of electrification of the transportation sector.

Methods The dataset used in this report was created using the following public data sources:

2019 California Vehicle Survey: "Transportation Secure Data Center." ([2019]). National Renewable Energy Laboratory. Accessed [04/26/2023]: www.nrel.gov/tsdc. The Smart Mapping Tool by EPA: https://www.epa.gov/smartgrowth/smart-location-mapping

American Community Survey: https://www.census.gov/programs-surveys/acs

Estimates of average weekday household person trips, vehicle trips, person miles traveled, and vehicle miles traveled (per day), for all Census tracts in the United States for 2009.

For latest data (2017), see https://data.bts.gov/Research-and-Statistics/Local-Area-Transportation-Characteristics-by-House/va72-z8hz

For methodology, see attachments