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Daily vehicle miles traveled (VMT) is a distance- and volume-based measure of driving on roadways for all motorized vehicle types—car, bus, motorcycle, and truck—on an average day. Per capita VMT is the same measure divided by the same area's population for the same year. Per vehicle VMT divides VMT by the number of household vehicles available by residents of that geography in the same year. These three value types can be selected in the dropdown in the first chart below. Use the legend items to explore various geographies. The second chart below shows per capita and total personal vehicles available to the region’s households from the American Community Survey.
Normalizing VMT by a county or region's population, or household vehicles, is helpful for context, but does not have complete parity with what is measured in VMT estimates. People and vehicles come into the region from other places, just as people and vehicles leave the region to visit other places. VMT per capita compares all miles traveled on the region's roads to the region's population (for all ages) from the U.S. Census Bureau's latest population estimates. Vehicle counts for VMT are classified by vehicle types, but not by vehicle ownership. In 2017, statewide estimates for VMT by motorcycles, passenger cars, and two-axle single-unit trucks with four wheels made up 88% of Pennsylvania's VMT, and 95% of New Jersey's. These vehicle types are highly likely to be personal vehicles, owned by households, but a small percent could be fleet vehicles of companies or governments. The remaining VMT is made up of vehicle types like school and commercial buses and trucks with more than two axles so they are highly likely to be commercial vehicles.
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Graph and download economic data for Moving 12-Month Total Vehicle Miles Traveled (M12MTVUSM227NFWA) from Dec 1970 to Sep 2025 about miles, travel, vehicles, and USA.
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TwitterThe number of vehicle-miles traveled on all roads in the United States decreased by some 1.55 percent to approximately 3.17 trillion in 2022. Records for 2019 reported the highest annual level on record, at just under 3.3 trillion vehicle-miles traveled.
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United States Ave Vehicle Miles Traveled per Household: 1 Person data was reported at 7,100.000 Mile in 2009. This records a decrease from the previous number of 7,500.000 Mile for 2001. United States Ave Vehicle Miles Traveled per Household: 1 Person data is updated yearly, averaging 7,500.000 Mile from Dec 1991 (Median) to 2009, with 3 observations. The data reached an all-time high of 11,400.000 Mile in 1991 and a record low of 7,100.000 Mile in 2009. United States Ave Vehicle Miles Traveled per Household: 1 Person 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.TA005: Vehicles Miles Traveled per Household.
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TwitterNTS0901: https://assets.publishing.service.gov.uk/media/68a35b1e50939bdf2c2b5e64/nts0901.ods">Annual mileage of cars by ownership, fuel type and trip purpose: England, 2002 onwards (ODS, 13.1 KB)
NTS0904: https://assets.publishing.service.gov.uk/media/68a35b3550939bdf2c2b5e65/nts0904.ods">Annual mileage band of cars: England, 2002 onwards (ODS, 14.3 KB)
NTS0905: https://assets.publishing.service.gov.uk/media/68a35b5df49bec79d23d2983/nts0905.ods">Average car or van occupancy and lone driver rate by trip purpose: England, 2002 onwards (ODS, 19 KB)
NTS0908: https://assets.publishing.service.gov.uk/media/68a35b7150939bdf2c2b5e66/nts0908.ods">Where vehicle parked overnight by rural-urban classification of residence: England, 2002 onwards (ODS, 15.9 KB)
NTS0909: https://assets.publishing.service.gov.uk/media/68a35add32d2c63f869343bc/nts0909.ods">Cars by fuel type and transmission: England, 2019 onwards (ODS, 9.82 KB)
National Travel Survey statistics
Email mailto:national.travelsurvey@dft.gov.uk">national.travelsurvey@dft.gov.uk
To hear more about DfT statistical publications as they are released, follow us on X at https://x.com/dftstats">DfTstats.
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平均每户行车里程:1人在12-01-2009达7,100.000Mile,相较于12-01-2001的7,500.000Mile有所下降。平均每户行车里程:1人数据按年更新,12-01-1991至12-01-2009期间平均值为7,500.000Mile,共3份观测结果。该数据的历史最高值出现于12-01-1991,达11,400.000Mile,而历史最低值则出现于12-01-2009,为7,100.000Mile。CEIC提供的平均每户行车里程:1人数据处于定期更新的状态,数据来源于Center for Transportation Analysis,数据归类于全球数据库的美国 – 表US.TA005:每户行车里程。
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Vehicle Roadside Assistance Market size was valued at USD 30 Billion in 2024 and is projected to reach USD 45 Billion by 2032, growing at a CAGR of 5.6% from 2026 to 2032Vehicle Roadside Assistance Market Key DriversThe Vehicle Roadside Assistance Market is experiencing significant growth, primarily driven by a global surge in vehicle ownership and usage. As per-capita income rises, particularly in burgeoning economies across the Asia-Pacific region, more consumers are purchasing both passenger and commercial vehicles. This expanding vehicle fleet directly correlates with a higher probability of mechanical failures, accidents, and breakdowns, thereby escalating the demand for professional roadside assistance. The increase in vehicle miles traveled, fueled by longer commutes and a rise in travel and tourism, further contributes to wear and tear, making services like towing, tire replacement, and battery assistance essential. This trend is especially pronounced in urban and semi-urban areas, where dense traffic and complex road networks amplify the need for swift and reliable support, as businesses and individuals alike seek to minimize downtime and disruption.Aging Vehicle Fleet: Another critical driver for the market is the increasing average age of vehicles on the road, particularly in mature markets like North America and Europe. Older vehicles are inherently more susceptible to mechanical and electrical failures, including engine trouble, battery issues, and worn-out components. This demographic shift in the vehicle fleet creates a steady and predictable demand for roadside assistance services. As owners of older cars opt to repair rather than replace their vehicles, the need for emergency services and minor on-the-spot repairs grows. This trend is a key revenue generator for roadside assistance providers, who can capitalize on the recurring service needs of these vehicles, ensuring a stable customer base and supporting the continued expansion of their service networks.Technological Advances: The integration of advanced technologies is fundamentally reshaping and propelling the vehicle roadside assistance market. The widespread adoption of telematics, connected car systems, IoT, and mobile apps has revolutionized service delivery. These technologies enable faster and more accurate breakdown detection, allowing for optimized dispatch and improved customer experience through features like real-time GPS tracking and service request platforms. Additionally, the rise of predictive maintenance, leveraging data from in-vehicle diagnostics, allows service providers to proactively anticipate potential failures and offer pre-emptive assistance. The use of AI and machine learning algorithms further enhances efficiency by optimizing routes, reducing response times, and streamlining the entire assistance process, setting a new standard for speed and convenience that customers now expect.
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BUS0415: https://assets.publishing.service.gov.uk/media/691f4af0d3a80970b766f11a/bus0415.ods">Local bus fares index by metropolitan area status and country, quarterly: Great Britain (ODS, 21.9 KB)
This spreadsheet includes breakdowns by country, region, metropolitan area status, urban-rural classification and Local Authority. It also includes data per head of population, and concessionary journeys.
BUS01: https://assets.publishing.service.gov.uk/media/692591b82945773cf12dd01a/bus01.ods"> Local bus passenger journeys (ODS, 152 KB)
Limited historic data is available
These spreadsheets include breakdowns by country, region, metropolitan area status, urban-rural classification and Local Authority, as well as by service type. Vehicle distance travelled is a measure of levels of service provision.
BUS02_mi: https://assets.publishing.service.gov.uk/media/692591b89fd433badebc3141/bus02_mi.ods">Vehicle distance travelled (miles) (ODS, 126 KB)
BUS02_km: https://assets.publishing.service.gov.uk/media/692591b847904590c9da2cc8/bus02_km.ods">Vehicle distance travelled (kilometres) (ODS, 118 KB)
Limited historic data is available
Following a review of the methodology, table BUS03 has been fully revised back to 2005.
This spreadsheet includes breakdowns by country and metropolitan area status, as well as average occupancy data.
BUS03: https://assets.publishing.service.gov.uk/media/692591b833d088f6d5da2cce/bus03.ods">Passenger distance travelled (miles and kilometres) (ODS, 18.4 KB)
Limited historic data is available
These spreadsheets include breakdowns by country and metropolitan area status, as well as revenue and costs per passenger journey and vehicle mile/kilometre.
BUS04i: https://assets.publishing.service.gov.uk/media/692591b847904590c9da2cc9/bus04i.ods">Costs, fares and revenue in current prices (ODS, 41 KB)
BUS04ii: https://assets.publishing.service.gov.uk/media/692591b822424e25e6bc313c/bus04ii.ods"> Costs, fares and revenue in constant prices (ODS, <span class="gem-c-attachment-link_a
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The global cold chain logistics vehicle market is experiencing robust growth, driven by the increasing demand for temperature-sensitive goods across various sectors like food and beverages, pharmaceuticals, and healthcare. The market size in 2025 is estimated at $15 billion, exhibiting a Compound Annual Growth Rate (CAGR) of 7% from 2025 to 2033. This growth is fueled by several key factors: the expanding e-commerce sector requiring efficient last-mile delivery solutions for perishable goods; stringent regulatory compliance regarding food safety and pharmaceutical transportation; and the rising adoption of advanced technologies like IoT sensors and telematics for improved tracking and monitoring of shipments. The market is segmented by vehicle type (New Energy Cold Chain Logistics Vehicle and Fuel Cold Chain Logistics Vehicle) and application (Food and Beverages, Medical, and Other), with the food and beverage sector currently dominating the market share due to the significant volume of perishable products transported globally. Significant growth is also expected in the medical segment driven by the increased demand for temperature-sensitive pharmaceuticals and vaccines. The market's expansion is also being influenced by regional variations. North America and Europe currently hold significant market shares due to established cold chain infrastructure and high per capita consumption of temperature-sensitive goods. However, Asia-Pacific is projected to witness the fastest growth rate during the forecast period, driven by rapid economic development, expanding middle class, and increasing urbanization in countries like China and India. While factors like high initial investment costs for specialized vehicles and fluctuating fuel prices pose challenges, the overall market outlook remains positive. The ongoing development and adoption of more sustainable and efficient cold chain logistics vehicles, such as electric and hybrid options, are further accelerating market growth and shaping its future trajectory. Key players in the market include established trailer manufacturers and commercial vehicle producers, continuously innovating to meet the evolving demands of the industry.
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Turkey TR: Road Fatalities: Per One Million Vehicle-km data was reported at 15.204 Ratio in 2022. This records a decrease from the previous number of 16.269 Ratio for 2021. Turkey TR: Road Fatalities: Per One Million Vehicle-km data is updated yearly, averaging 19.949 Ratio from Dec 2015 (Median) to 2022, with 8 observations. The data reached an all-time high of 29.999 Ratio in 2015 and a record low of 15.204 Ratio in 2022. Turkey TR: Road Fatalities: Per One Million Vehicle-km data remains active status in CEIC and is reported by Organisation for Economic Co-operation and Development. The data is categorized under Global Database’s Turkey – Table TR.OECD.ITF: Road Traffic and Road Accident Fatalities: OECD Member: Annual. [COVERAGE] ROAD FATALITIES A road fatality is any person killed immediately or dying within 30 days as a result of an injury accident, excluding suicides. A killed person is excluded if the competent authority declares the cause of death to be suicide, i.e. a deliberate act to injure oneself resulting in death. For countries that do not apply the threshold of 30 days, conversion coefficients are estimated so that comparison on the basis of the 30-day definition can be made. ROAD TRAFFIC Road traffic is any movement of a road vehicle on a given road network. When a road vehicle is being carried on another vehicle, only the movement of the carrying (active mode) is considered. [COVERAGE] ROAD TRAFFIC Data come from odometer readings and include all motor vehicle movements on the territory, irrespective of the country of registration.
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Daily vehicle miles traveled (VMT) is a distance- and volume-based measure of driving on roadways for all motorized vehicle types—car, bus, motorcycle, and truck—on an average day. Per capita VMT is the same measure divided by the same area's population for the same year. Per vehicle VMT divides VMT by the number of household vehicles available by residents of that geography in the same year. These three value types can be selected in the dropdown in the first chart below. Use the legend items to explore various geographies. The second chart below shows per capita and total personal vehicles available to the region’s households from the American Community Survey.
Normalizing VMT by a county or region's population, or household vehicles, is helpful for context, but does not have complete parity with what is measured in VMT estimates. People and vehicles come into the region from other places, just as people and vehicles leave the region to visit other places. VMT per capita compares all miles traveled on the region's roads to the region's population (for all ages) from the U.S. Census Bureau's latest population estimates. Vehicle counts for VMT are classified by vehicle types, but not by vehicle ownership. In 2017, statewide estimates for VMT by motorcycles, passenger cars, and two-axle single-unit trucks with four wheels made up 88% of Pennsylvania's VMT, and 95% of New Jersey's. These vehicle types are highly likely to be personal vehicles, owned by households, but a small percent could be fleet vehicles of companies or governments. The remaining VMT is made up of vehicle types like school and commercial buses and trucks with more than two axles so they are highly likely to be commercial vehicles.