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.

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.

This layer shows household size by number of vehicles available. This is shown by tract, county, and state boundaries. This service is updated annually to contain the most currently released American Community Survey (ACS) 5-year data, and contains estimates and margins of error. There are also additional calculated attributes related to this topic, which can be mapped or used within analysis. This layer is symbolized to show the percentage of households with no vehicle available. To see the full list of attributes available in this service, go to the "Data" tab, and choose "Fields" at the top right. Current Vintage: 2018-2022ACS Table(s): B08201 Data downloaded from: Census Bureau's API for American Community Survey Date of API call: December 7, 2023The 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 2022 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.

Graph and download economic data for Expenditures: Vehicle Purchases: Cars and Trucks, Used by Deciles of Income Before Taxes: Fourth 10 Percent (31st to 40th Percentile) (CXUUSEDCARSLB1505M) from 2014 to 2023 about used, purchase, trucks, percentile, tax, vehicles, expenditures, income, and USA.

The percentage of households that do not have a personal vehicle available for use out of all households in an area. Source: American Community Survey Years Available: 2007-2011, 2008-2012, 2009-2013, 2010-2014, 2011-2015, 2012-2016, 2013-2017, 2014-2018, 2015-2019, 2016-2020, 2017-2021, 2018-2022

This table contains data on the percent of residents aged 16 years and older mode of transportation to work for California, its regions, counties, cities/towns, and census tracts. Data is from the U.S. Census Bureau, Decennial Census and American Community Survey. The table is part of a series of indicators in the Healthy Communities Data and Indicators Project of the Office of Health Equity. Commute trips to work represent 19% of travel miles in the United States. The predominant mode – the automobile - offers extraordinary personal mobility and independence, but it is also associated with health hazards, such as air pollution, motor vehicle crashes, pedestrian injuries and fatalities, and sedentary lifestyles. Automobile commuting has been linked to stress-related health problems. Active modes of transport – bicycling and walking alone and in combination with public transit – offer opportunities for physical activity, which is associated with lowering rates of heart disease and stroke, diabetes, colon and breast cancer, dementia and depression. Risk of injury and death in collisions are higher in urban areas with more concentrated vehicle and pedestrian activity. Bus and rail passengers have a lower risk of injury in collisions than motorcyclists, pedestrians, and bicyclists. Minority communities bear a disproportionate share of pedestrian-car fatalities; Native American male pedestrians experience four times the death rate Whites or Asian pedestrians, and African-Americans and Latinos experience twice the rate as Whites or Asians. More information about the data table and a data dictionary can be found in the About/Attachments section.

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.

Sales of used light vehicles in the United States came to around 38.9 million units in the third quarter of 2024. The same period, approximately 15.6 million new light trucks and automobiles were sold here. Declining availability of vehicles In the fourth quarter of 2023, about 288.5 million vehicles were in operation in the United States, an increase of under one percent year-over-year. The rising demand for vehicles paired with an overall price inflation lead to a rise in new vehicle prices. In contrast, used vehicle prices slightly decreased. E-commerce: a solution for the bumpy road ahead? Financial reports have revealed how the outbreak of the coronavirus pandemic has triggered a shift in vehicle-buying behavior. With many consumer goods and services now bought online due to COVID-19, the automobile industry has also started to digitally integrate its services online to reach consumers with a preference for contactless test driving amid the global crisis. Several dealers and automobile companies had already begun to tap into online car sales before the pandemic, some of them being Carvana and Tesla.

Graph and download economic data for Consumer Unit Characteristics: At Least One Vehicle Owned or Leased by Income Before Taxes: $40,000 to $49,999 (CXU980350LB0208M) from 1984 to 2023 about owned, consumer unit, leases, tax, vehicles, percent, income, and USA.

DESCRIPTION This table contains data on the percent of residents aged 16 years and older mode of transportation to work for ...

SUMMARY This table contains data on the percent of residents aged 16 years and older mode of transportation to work for California, its regions, counties, cities/towns, and census tracts. Data is from the U.S. Census Bureau, Decennial Census and American Community Survey. The table is part of a series of indicators in the Healthy Communities Data and Indicators Project of the Office of Health Equity. Commute trips to work represent 19% of travel miles in the United States. The predominant mode – the automobile - offers extraordinary personal mobility and independence, but it is also associated with health hazards, such as air pollution, motor vehicle crashes, pedestrian injuries and fatalities, and sedentary lifestyles. Automobile commuting has been linked to stress-related health problems. Active modes of transport – bicycling and walking alone and in combination with public transit – offer opportunities for physical activity, which is associated with lowering rates of heart disease and stroke, diabetes, colon and breast cancer, dementia and depression. Risk of injury and death in collisions are higher in urban areas with more concentrated vehicle and pedestrian activity. Bus and rail passengers have a lower risk of injury in collisions than motorcyclists, pedestrians, and bicyclists. Minority communities bear a disproportionate share of pedestrian-car fatalities; Native American male pedestrians experience four times the death rate Whites or Asian pedestrians, and African-Americans and Latinos experience twice the rate as Whites or Asians. More information about the data table and a data dictionary can be found in the About/Attachments section.

ind_id - Indicator ID ind_definition - Definition of indicator in plain language reportyear - Year that the indicator was reported race_eth_code - numeric code for a race/ethnicity group race_eth_name - Name of race/ethnic group geotype - Type of geographic unit geotypevalue - Value of geographic unit geoname - Name of a geographic unit county_name - Name of county that geotype is in county_fips - FIPS code of the county that geotype is in region_name - MPO-based region name; see MPO_County list tab region_code - MPO-based region code; see MPO_County list tab mode - Mode of transportation short name mode_name - Mode of transportation long name pop_total - denominator pop_mode - numerator percent - Percent of Residents Mode of Transportation to Work,
Population Aged 16 Years and Older LL_95CI_percent - The lower limit of 95% confidence interval UL_95CI_percent - The lower limit of 95% confidence interval percent_se - Standard error of the percent mode of transportation percent_rse - Relative standard error (se/value) expressed as a percent CA_decile - California decile CA_RR - Rate ratio to California rate version - Date/time stamp of a version of data

Graph and download economic data for Consumer Unit Characteristics: At Least One Vehicle Owned or Leased: All Consumer Units (CXU980350LB0101M) from 1984 to 2023 about owned, consumer unit, leases, vehicles, percent, and USA.

Snapshot img

Automotive Connected Car Platform Market Size 2024-2028

The automotive connected car platform market size is forecast to increase by USD 6.57 billion at a CAGR of 13.11% between 2023 and 2028.

The connected car platform market is experiencing significant growth due to the increased focus of Original Equipment Manufacturers (OEMs) on the development of autonomous and connected vehicles. This trend is driven by the desire to enhance vehicle safety, improve customer experience, and provide real-time traffic and navigation information. Rental companies are also adopting connected car platforms to attract customers and offer value-added services. However, the design complexity and technological challenges associated with connected car technologies pose significant hurdles for market growth. These challenges include ensuring secure data transmission, integrating multiple sensors and systems, and complying with regulatory requirements. Despite these challenges, the market is expected to continue its growth trajectory as technological advancements and increasing consumer demand drive innovation In the connected car space.

What will be the Size of the Automotive Connected Car Platform Market During the Forecast Period?

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The market is experiencing significant growth due to the increasing demand for vehicle infotainment systems and advanced driver assistance features. Autonomous cars represent a key trend in this market, with V2V communication enabling vehicles to exchange data and improve road safety. According to Canalys, the production of connected cars is projected to reach 100 million units by 2024. Comfort, convenience, performance, and safety are primary drivers for consumers, with sensors and processors playing crucial roles in delivering these benefits. OEMs are partnering with telecommunication companies to provide 3G/4G services for data transfer, ensuring fast and reliable connectivity. Maintenance costs are also a consideration, with some manufacturers exploring the use of lightweight suspension systems, such as those employing sensors and advanced algorithms, to improve vehicle performance and reduce production costs.

How is this Automotive Connected Car Platform Industry segmented and which is the largest segment?

The automotive connected car platform industry research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD million' for the period 2024-2028, as well as historical data from 2018-2022 for the following segments.

Service

  Infotainment services
  Telematics services


Technology

  Integrated solution
  Embedded solutions
  Tethered solutions


Geography

  North America

    Canada
    US


  Europe

    Germany
    UK


  APAC

    China


  South America



  Middle East and Africa

By Service Insights

The infotainment services segment is estimated to witness significant growth during the forecast period.

In the automotive industry, connected car platforms have become a significant focus for Original Equipment Manufacturers (OEMs) seeking to differentiate their offerings and meet customer demand for advanced infotainment systems. These platforms integrate various technologies such as telematics, remote control access, GPS tracking, and internet services, often utilizing smartphones for seamless connectivity. IoT companies, like Trak N Tell, a subsidiary of Bits N Bytes Soft Private Limited, play a crucial role in this market by providing GPS-enabled technology products to OEMs, fleet customers, and automotive aftermarkets. For instance, Trak N Tell introduced three variants of its IntelliPlay 4G SIM-enabled Android-based car infotainment system in June 2022.

This system offers features like news, weather, social networking, and audio/video streaming, enhancing the overall driving experience for consumers.

Get a glance at the Automotive Connected Car Platform Industry report of share of various segments Request Free Sample

The Infotainment services segment was valued at USD 4.82 billion in 2018 and showed a gradual increase during the forecast period.

Regional Analysis

APAC is estimated to contribute 59% to the growth of the global market during the forecast period.

Technavio's analysts have elaborately explained the regional trends and drivers that shape the market during the forecast period.

For more insights on the market share of various regions, Request Free Sample

The North American connected car market is experiencing significant growth due to the region's demographic trends. With an average car buyer age of 52 years and a large population of senior citizens, there is a heightened demand for enhanced comfort and safety features. Moreover, luxury car owners In the US have a median annual income of USD99,364, making the market attractive for automotive companies. Connected

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.

This table contains data on the percent of residents aged 16 years and older mode of transportation to work for California, its regions, counties, cities/towns, and census tracts. Data is from the U.S. Census Bureau, Decennial Census and American Community Survey. The table is part of a series of indicators in the Healthy Communities Data and Indicators Project of the Office of Health Equity. Commute trips to work represent 19% of travel miles in the United States. The predominant mode – the automobile - offers extraordinary personal mobility and independence, but it is also associated with health hazards, such as air pollution, motor vehicle crashes, pedestrian injuries and fatalities, and sedentary lifestyles. Automobile commuting has been linked to stress-related health problems. Active modes of transport – bicycling and walking alone and in combination with public transit – offer opportunities for physical activity, which is associated with lowering rates of heart disease and stroke, diabetes, colon and breast cancer, dementia and depression. Risk of injury and death in collisions are higher in urban areas with more concentrated vehicle and pedestrian activity. Bus and rail passengers have a lower risk of injury in collisions than motorcyclists, pedestrians, and bicyclists. Minority communities bear a disproportionate share of pedestrian-car fatalities; Native American male pedestrians experience four times the death rate Whites or Asian pedestrians, and African-Americans and Latinos experience twice the rate as Whites or Asians. More information about the data table and a data dictionary can be found in the About/Attachments section.

Snapshot img

Automotive Communication Protocols Market Size 2025-2029

The automotive communication protocols market size is forecast to increase by USD 758.7 million at a CAGR of 7.9% between 2024 and 2029.

The market is witnessing significant growth due to the increasing electrification in vehicles. As electric vehicles and hybrid vehicles gain popularity, the need for advanced communication systems to manage power distribution and vehicle performance becomes crucial. Another trend driving market growth is the use of Ethernet to create the backbone network of vehicles. This technology enables faster data transfer and improved connectivity between various vehicle systems. However, the additional cost to manage rough operating conditions of automotive networks poses a challenge to market growth. Extreme temperatures, vibrations, and electromagnetic interference can damage communication components and require costly repairs. Despite these challenges, the market is expected to continue growing as automakers prioritize safety and efficiency In their vehicle designs.

What will be the Size of the Market During the Forecast Period?

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The market is experiencing significant growth as the global automotive industry shifts towards connected vehicles and smart mobility solutions. This market encompasses various communication technologies, including vehicle-to-everything (V2X), Wi-Fi, and cellular connectivity, enabling real-time data exchange between vehicles, infrastructure, and other devices. The architecture of these systems prioritizes data privacy and security, ensuring the protection of sensitive vehicle information. Adoption of connected vehicle technology is increasing in light duty vehicles, leading to the development of advanced features such as predictive maintenance, remote diagnostics, and real-time traffic management. The implementation of 5G for automotive applications is poised to revolutionize the market, offering faster data transfer rates and lower latency.
The automotive cybersecurity landscape is also evolving, with a focus on vehicle-to-infrastructure communication and connected infrastructure. As the ecosystem expands, automotive cloud platforms and vehicle-to-vehicle communication are becoming essential components, enabling vehicle data analytics and smart mobility solutions. The market's direction is towards a more interconnected and autonomous driving future, where communication protocols play a crucial role in ensuring seamless and secure data exchange.

How is this Automotive Communication Protocols Industry segmented and which is the largest segment?

The automotive communication protocols industry research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD million' for the period 2025-2029, as well as historical data from 2019-2023 for the following segments.

Application

  Passenger cars
  Commercial vehicles


Type

  LIN
  CAN
  Flexray
  MOST
  Ethernet


Component

  Hardware
  Software
  Services


End-user

  Powertrain
  Infotainment and communication
  Safety and ADAS
  Body control and comfort
  Others


Geography

  APAC

    China
    India
    Japan
    South Korea


  Europe

    Germany
    UK
    France


  North America

    Canada
    US


  South America



  Middle East and Africa

By Application Insights

The passenger cars segment is estimated to witness significant growth during the forecast period.

The automotive industry is experiencing significant advancements in safety, connectivity, and electrification, leading to a growing demand for strong communication protocols. Over the past decade, passenger vehicles have seen the integration of numerous features, including Advanced Driver-Assistance Systems (ADAS), autonomous driving, infotainment systems, and vehicle-to-everything (V2X) communication. These innovations are driven by increasing consumer expectations, OEM competition, and regulatory requirements. Communication protocols such as Controller Area Network (CAN), Local Interconnect Network (LIN), FlexRay, Ethernet, CAN FD, and Wireless Connectivity (Bluetooth, Wi-Fi, and Cellular) are essential for enabling seamless conversations between various vehicle systems and infrastructure. Moreover, the integration of Intelligent Transport Systems (ITS), 5G networks, and cloud services necessitates advanced communication protocols for over-the-air configuration changes, privacy, security, and emergency services conversations.

Get a glance at the market report of share of various segments Request Free Sample

The passenger cars segment was valued at USD 1.14 billion in 2019 and showed a gradual increase during the forecast period.

Regional Analysis

APAC is estimated to contribute 58% to the growth of the global market during the forecast period.

Technavio's analysts have elaborately exp

Graph and download economic data for Consumer Unit Characteristics: At Least One Vehicle Owned or Leased by Hispanic or Latino Origin: Hispanic or Latino (CXU980350LB1002M) from 1994 to 2023 about owned, consumer unit, leases, vehicles, latino, hispanic, percent, and USA.

The data is based upon traffic volume trends data collected by the United States Department of Transportation data from January 1971 to February 2013.Since June 2005, vehicle miles driven have fallen 8.75 percent. This decline has remained steady for the past 92 months. There are several reasons that may be causing this steady downward trend. It has been suggested that due to rising gas prices, the Great Recession, an aging population led by the Baby Boom generation which is comprised of Americans over the age of 55 who tend to drive less, and quite possibly younger Americans choosing to drive less. Between 2001 and 2009, the average yearly number of miles driven by 16- to 34-year-olds has dropped 23 percent.Researchers indicate that this trend may be linked to five principal factors:The cost of Driving has increasedThe recent recessionIt is harder to get a license in many statesMore younger people are choosing to live in transit-oriented areas andTechnology is making it easier to go car-freeData Source Information: Traffic Volume Trends is a monthly report based on hourly traffic count data reported by the States. These data are collected at approximately 4,000 continuous traffic counting locations nationwide and are used to estimate the percent change in traffic for the current month compared with the same month in the previous year. Estimates are re-adjusted annually to match the vehicle miles of travel from the Highway Performance Monitoring System and are continually updated with additional data.

Supporting documentation on code lists, subject definitions, data accuracy, and statistical testing can be found on the American Community Survey website in the Data and 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..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..Explanation of Symbols:An ''**'' entry in 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..An ''-'' entry in the estimate column indicates that 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..An ''-'' following a median estimate means the median falls in the lowest interval of an open-ended distribution..An ''+'' following a median estimate means the median falls in the upper interval of an open-ended distribution..An ''***'' entry in the margin of error column indicates that the median falls in the lowest interval or upper interval of an open-ended distribution. A statistical test is not appropriate..An ''*****'' entry in the margin of error column indicates that the estimate is controlled. A statistical test for sampling variability is not appropriate. .An ''N'' entry in the estimate and margin of error columns indicates that data for this geographic area cannot be displayed because the number of sample cases is too small..An ''(X)'' means that the estimate is not applicable or not available..Estimates of urban and rural population, housing units, and characteristics reflect boundaries of urban areas defined based on Census 2000 data. Boundaries for urban areas have not been updated since Census 2000. As a result, data for urban and rural areas from the ACS do not necessarily reflect the results of ongoing urbanization..While the 2007-2011 American Community Survey (ACS) data generally reflect the December 2009 Office of Management and Budget (OMB) definitions 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 definitions due to differences in the effective dates of the geographic entities..Workers include members of the Armed Forces and civilians who were at work last week..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 Accuracy of the Data). The effect of nonsampling error is not represented in these tables..Source: U.S. Census Bureau, 2007-2011 American Community Survey

The U.S. auto industry sold nearly three million cars in 2024. That year, total car and light truck sales were approximately 15.9 million in the United States. U.S. vehicle sales peaked in 2016 at roughly 17.5 million 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 77 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 40 U.S. dollars per barrel. The decline occurred in tandem with lower gasoline prices, which came to about 2.17 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.

Graph and download economic data for Consumer Unit Characteristics: At Least One Vehicle Owned or Leased by Region: Residence in the Northeast Census Region (CXU980350LB1102M) from 1984 to 2023 about Northeast Census Region, owned, consumer unit, leases, vehicles, residents, percent, and USA.