In 2021, more than 44,000 male drivers were involved in fatal crashes in U.S. road traffic, which accounted for 72.3 percent of the total, while female drivers were involved in about 15,100 fatal crashes. The number of drivers who were involved in fatal crashes has shown an increase of about 16.2 percent from 2016.

The Motor Vehicle Collisions person table contains details for people involved in the crash. Each row represents a person (driver, occupant, pedestrian, bicyclist,..) involved in a crash. The data in this table goes back to April 2016 when crash reporting switched to an electronic system. The Motor Vehicle Collisions data tables contain information from all police reported motor vehicle collisions in NYC. The police report (MV104-AN) is required to be filled out for collisions where someone is injured or killed, or where there is at least $1000 worth of damage (https://www.nhtsa.gov/sites/nhtsa.dot.gov/files/documents/ny_overlay_mv-104an_rev05_2004.pdf). It should be noted that the data is preliminary and subject to change when the MV-104AN forms are amended based on revised crash details. Due to success of the CompStat program, NYPD began to ask how to apply the CompStat principles to other problems. Other than homicides, the fatal incidents with which police have the most contact with the public are fatal traffic collisions. Therefore in April 1998, the Department implemented TrafficStat, which uses the CompStat model to work towards improving traffic safety. Police officers complete form MV-104AN for all vehicle collisions. The MV-104AN is a New York State form that has all of the details of a traffic collision. Before implementing Trafficstat, there was no uniform traffic safety data collection procedure for all of the NYPD precincts. Therefore, the Police Department implemented the Traffic Accident Management System (TAMS) in July 1999 in order to collect traffic data in a uniform method across the City. TAMS required the precincts manually enter a few selected MV-104AN fields to collect very basic intersection traffic crash statistics which included the number of accidents, injuries and fatalities. As the years progressed, there grew a need for additional traffic data so that more detailed analyses could be conducted. The Citywide traffic safety initiative, Vision Zero started in the year 2014. Vision Zero further emphasized the need for the collection of more traffic data in order to work towards the Vision Zero goal, which is to eliminate traffic fatalities. Therefore, the Department in March 2016 replaced the TAMS with the new Finest Online Records Management System (FORMS). FORMS enables the police officers to electronically, using a Department cellphone or computer, enter all of the MV-104AN data fields and stores all of the MV-104AN data fields in the Department’s crime data warehouse. Since all of the MV-104AN data fields are now stored for each traffic collision, detailed traffic safety analyses can be conducted as applicable.

How many people are staying at home? How far are people traveling when they don’t stay home? Which states and counties have more people taking trips? The Bureau of Transportation Statistics (BTS) now provides answers to those questions through our mobility statistics program.

The "Trips by Distance" data and number of people staying home and not staying home are estimated for the Bureau of Transportation Statistics by the Maryland Transportation Institute and Center for Advanced Transportation Technology Laboratory at the University of Maryland. The travel statistics are produced from an anonymized national panel of mobile device data from multiple sources. All data sources used in the creation of the metrics contain no personal information. Data analysis is conducted at the aggregate national, state, and county levels. A weighting procedure expands the sample of millions of mobile devices, so the results are representative of the entire population in a nation, state, or county. To assure confidentiality and support data quality, no data are reported for a county if it has fewer than 50 devices in the sample on any given day.

Trips are defined as movements that include a stay of longer than 10 minutes at an anonymized location away from home. Home locations are imputed on a weekly basis. A movement with multiple stays of longer than 10 minutes before returning home is counted as multiple trips. Trips capture travel by all modes of transportation. including driving, rail, transit, and air.

The daily travel estimates are from a mobile device data panel from merged multiple data sources that address the geographic and temporal sample variation issues often observed in a single data source. The merged data panel only includes mobile devices whose anonymized location data meet a set of data quality standards, which further ensures the overall data quality and consistency. The data quality standards consider both temporal frequency and spatial accuracy of anonymized location point observations, temporal coverage and representativeness at the device level, spatial representativeness at the sample and county level, etc. A multi-level weighting method that employs both device and trip-level weights expands the sample to the underlying population at the county and state levels, before travel statistics are computed.

These data are experimental and may not meet all of our quality standards. Experimental data products are created using new data sources or methodologies that benefit data users in the absence of other relevant products. We are seeking feedback from data users and stakeholders on the quality and usefulness of these new products. Experimental data products that meet our quality standards and demonstrate sufficient user demand may enter regular production if resources permit.

These data are made available under a public domain license. Data should be attributed to the "Maryland Transportation Institute and Center for Advanced Transportation Technology Laboratory at the University of Maryland and the United States Bureau of Transportation Statistics."

Daily data for a given week will be uploaded to the BTS website within 9-10 days of the end of the week in question (e.g., data for Sunday September 17-Saturday September 23 would be updated on Tuesday, October 3). All BTS visualizations and tables that rely on these data will update at approximately 10am ET on days when new data are received, processed, and uploaded.

The methodology used to develop these data can be found at: https://rosap.ntl.bts.gov/view/dot/67520.

United States Ave Vehicle Miles Traveled per Household: 3 Licensed Drivers data was reported at 37,700.000 Mile in 2009. This records a decrease from the previous number of 37,900.000 Mile for 2001. United States Ave Vehicle Miles Traveled per Household: 3 Licensed Drivers data is updated yearly, averaging 37,700.000 Mile from Dec 1991 (Median) to 2009, with 3 observations. The data reached an all-time high of 37,900.000 Mile in 2001 and a record low of 29,400.000 Mile in 1991. United States Ave Vehicle Miles Traveled per Household: 3 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.TA005: Vehicles Miles Traveled per Household.

United States US: Road Passenger Transport: Passenger Cars data was reported at 5,286,161.874 Person-km mn in 2022. This records a decrease from the previous number of 5,586,348.601 Person-km mn for 2021. United States US: Road Passenger Transport: Passenger Cars data is updated yearly, averaging 4,298,629.006 Person-km mn from Dec 1970 (Median) to 2022, with 37 observations. The data reached an all-time high of 6,060,622.152 Person-km mn in 2019 and a record low of 2,817,796.000 Person-km mn in 1970. United States US: Road Passenger Transport: Passenger Cars data remains active status in CEIC and is reported by Organisation for Economic Co-operation and Development. The data is categorized under Global Database’s United States – Table US.OECD.ITF: Passenger Transport by Mode of Transport: OECD Member: Annual. [STAT_CONC_DEF] Road passenger transport: any movement of passengers using a road vehicle on a given road network. National road passenger transport: road passenger transport between two places (a place of loading/embarkation and a place of unloading/disembarkation) located in the same country irrespective of the country in which the road motor vehicle is registered. It may involve transit through a second country. International road passenger transport: road passenger transport between a place of loading/embarkation or unloading/disembarkation in the declaring country and a place of loading/embarkation or unloading/disembarkation in another country. Such transport may involve transit through one or more additional countries. Road passenger: any person who makes a journey by a road vehicle. Drivers of passenger cars, excluding taxi drivers, are counted as passengers. Road passenger-kilometre: unit of measurement representing the transport of one passenger by road over one kilometre. [STAT_CONC_DEF] Since 2000, the definition of passenger car is determined by the size of the wheel base. In 2009, there was a change in passenger car occupancy factor, that creates a break in the series. Transport by buses and coaches by the American Public Transportation Association (APTA). [COVERAGE] Data should include urban transport.

We provide high-quality, real-time vehicle data collected from a fleet of over 150,000 vehicles, offering granular insights into driving behavior, battery health, and charging patterns. All of our data is collected with 100% informed driver consent, ensuring full transparency and compliance with privacy standards. This consent allows us to gather telemetry and identity data through direct connections to the vehicles via APIs or installed hardware, providing accurate, actionable insights for various industries.

Our data stands out for its granularity and real-time nature, which is critical for applications that require precise, up-to-date information. Unlike aggregated data sources, our direct vehicle connections ensure accuracy and help eliminate the need for assumptions, making our dataset ideal for applications in sectors like energy optimization, insurance, and autonomous vehicle development.

For energy companies, our data provides insights into optimal charging locations, battery life cycles, and energy consumption, enabling more efficient management of EV charging infrastructure. In the insurance sector, the data allows for usage-based insurance (UBI) models that personalize premiums based on real-world driving habits, reducing the risk for insurers and incentivizing safer driving. For autonomous vehicle (AV) development, our data helps train AI models by offering real-time insights into driving behavior and environmental factors, enhancing the safety and reliability of AV systems.

Moreover, our platform also enables fleet management, smart city planning, and urban mobility solutions by providing data on traffic patterns, vehicle usage, and congestion points. This helps transportation agencies and departments of transportation make data-driven decisions for public infrastructure improvements and sustainability efforts.

The ability to collect and process data with informed consent ensures that all participants understand how their data is used, maintaining trust and compliance with data privacy regulations. With our direct connections to vehicles and real-time data processing, we provide the most accurate and actionable insights available for industries looking to optimize operations, enhance customer experiences, and drive smarter, more efficient solutions.

Graph and download economic data for Moving 12-Month Total Vehicle Miles Traveled (M12MTVUSM227NFWA) from Dec 1970 to Jan 2025 about miles, travel, vehicles, and USA.

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US Car Wash Services Market Size 2024-2028

The us car wash services market size is forecast to increase by USD 1.38 billion at a CAGR of 3.4% between 2023 and 2028.

The car wash services market In the US is witnessing significant growth due to several key factors. One of the primary drivers is the increasing need for water-efficient car washing products. With water scarcity becoming a major concern in various regions, there is a growing demand for car washing solutions that minimize water usage. Additionally, there is a rising trend towards the adoption of environment-friendly vehicle wash systems. As consumers become more conscious of their carbon footprint, they are opting for eco-friendly car washing options. Furthermore, there is a growing concern over vehicle damage during the washing process. Car owners want to ensure their vehicles are not only cleaned but also protected from scratches and other damages.These factors are expected to drive the growth of the car wash services market In the US over the forecast period.

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

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The car wash services market In the US is a significant industry, catering to various segments, including residential car washing, professional car washes, corporate fleets, and automobile maintenance. Car wash technology continues to evolve, with touchless car washing and hybrid car washing gaining popularity due to water conservation concerns and environmental restrictions. In drought-prone areas and regions with water scarcity, water recycling and eco-friendly solutions are essential. Economic uncertainties and labor costs have led to automation and factory closures in some instances. Convenience remains a crucial factor, with many car owners opting for on-demand, drive-through services. Environmental regulations and growing awareness of sustainability have influenced the market, with an increasing focus on reducing water usage and minimizing environmental impact.Vehicle wash services remain essential for maintaining the appearance and longevity of vehicles, making this market a resilient and evolving sector.

How is this market segmented and which is the largest segment?

The market research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD billion' for the period 2024-2028, as well as historical data from 2018-2022 for the following segments. TypeExteriorInteriorMethodCloth friction car washingTouchless car washingGeographyUS

By Type Insights

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

Exterior car wash services In the US are predominantly provided through gantry systems, conveyor tunnel wash, and self-service options. Gantry car washes, also known as rollover systems, enable customers to drive their vehicles into the wash bay for cleaning. These systems offer touch-free, friction, or hybrid cleaning methods, ensuring a comprehensive exterior wash. Customers typically pay via automated point-of-sale systems at the wash bay entrance. Environmental restrictions have led to the adoption of touchless and hybrid car washing technologies, reducing water usage. Residential car washing and professional washes cater to various segments, including corporate fleets, autowash, and vehicle wash services.Urbanization and densely populated areas have given rise to on-demand services, subscription models, and loyalty programs. Car wash technology continues to evolve, integrating water recycling systems and eco-friendly solutions. Strategic acquisitions and a focus on customer experience have become essential for both small and large operators. Water scarcity concerns and water conservation regulations impact car wash facilities in drought-prone areas, leading to factory closures and economic uncertainties. Car owners seek convenience, automation, and personalized washing services, driving the market's growth.

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The Exterior segment was valued at USD 4.50 billion in 2018 and showed a gradual increase during the forecast period.

Market Dynamics

Our researchers analyzed the data with 2023 as the base year, along with the key drivers, trends, and challenges. A holistic analysis of drivers will help companies refine their marketing strategies to gain a competitive advantage.

What are the key market drivers leading to the rise in adoption of US Car Wash Services Market?

Growing need for water-efficient car washing products is the key driver of the market.

The car wash services market In the US is witnessing significant growth due to increasing environmental restrictions and the need for water conservation. With water scarcity being a major concern in many regions, the use of water-efficient car washing technologies i

THIS DATASET IS UPDATED SEVERAL TIMES PER DAY. TLC Driver application status check for applicants who had applied for a new TLC driver’s license. For questions, please email newdriverapp@tlc.nyc.gov and visit www.nyc.gov/newdriver for more detailed information.

For historical/archived data of past application statuses, please see- https://data.cityofnewyork.us/Transportation/Historical-Driver-Application-Status/p32s-yqxq

This data were collected during the Safety Pilot Model Deployment (SPMD). The data sets that these entities will provide include basic safety messages (BSM), vehicle trajectories, and various driver-vehicle interaction data, as well as contextual data that describes the circumstances under which the Model Deployment data was collected. Large portion of the data contained in this environment is obtained from on board vehicle devices and roadside units. This legacy dataset was created before data.transportation.gov and is only currently available via the attached file(s). Please contact the dataset owner if there is a need for users to work with this data using the data.transportation.gov analysis features (online viewing, API, graphing, etc.) and the USDOT will consider modifying the dataset to fully integrate in data.transportation.gov.

Feature layer of electric vehicle registrations in Pennsylvania by United States Postal Service ZIP code. Data is provided by Pennsylvania Department of Transportation Driver and Vehicle Services and updated on a quarterly basis. ZIP code areas are based on U.S. Census Bureau data and adjusted to match PennDOT boundaries where possible. This data includes the following types of vehicles: battery electric, plug-in hybrid electric, hybrid electric and fuel cell.

For more information on this layer, you can use the Data Dictionary available here.

This data details the _location of the Taxi and For Hire Vehicle(FHV) stands and the number of spaces provided. Taxi and FHV relief stands allow drivers to park their vehicles for up to one hour. This gives drivers the opportunity to leave their vehicles and take care of personal needs. TNOTE: Taxi and FHV relief stands should not be confused with taxi stands. Taxi stands allow drivers to wait in their cars to pick up passengers.

Subscribers can find out export and import data of 23 countries by HS code or product’s name. This demo is helpful for market analysis.

PLEASE NOTE: This dataset, which includes all TLC licensed for-hire vehicles which are in good standing and able to drive, is updated every day in the evening between 4-7pm. Please check the 'Last Update Date' field to make sure the list has updated successfully. 'Last Update Date' should show either today or yesterday's date, depending on the time of day. If the list is outdated, please download the most recent list from the link below. http://www1.nyc.gov/assets/tlc/downloads/datasets/tlc_for_hire_vehicle_active_and_inactive.csv

TLC authorized For-Hire vehicles that are active. This list is accurate to the date and time represented in the Last Date Updated and Last Time Updated fields. For inquiries about the contents of this dataset, please email licensinginquiries@tlc.nyc.gov.

Opah labs 3227 specializes in providing third-party software solutions for last-mile delivery services in North America, excluding the United States. Established in 2015, their primary focus is on business-to-business (B2B) services. Their platform streamlines delivery operations, overseeing orders, drivers, and historical data, including Ecommerce data. They have a database containing 5,632,203 records spanning from August 5, 2021, to March 23, 2022, with no duplicates. They serve 1,134,167 unique users, with an 82.30% similarity rate. Their mission is to enhance last-mile delivery efficiency through software and data-driven solutions.

The data is sourced from an application that facilitates various deliveries, acting as a backend for providers. The company offers ETL services and can adjust delivery frequency, including daily collection. It has data coverage for Ozempic, Saxenda, Orlistat, and Hydrogel.

The dataset includes prescription delivery data and consumer goods data for users. This information offers insights into geographical transactions at a consumer level, with implications for consumer behavior and publicly traded companies.

Restaurant & Food Delivery Transaction Data is part of Opah 3227's comprehensive dataset, providing valuable insights into the dynamics of the food delivery industry. | Volume and Stats | Industry records undergo an unmatched refresh every two weeks. Many prominent sales and marketing platforms rely on curating firsthand data.

Delivery formats: JSON, XLS, CSV

| Data Points | With an impressive average of over 1,255,918 unique users. Key fields include Location, Payment Method, transit times, branch locations, and products.

| Use Cases | Pharma, Restaurant & Food Delivery Transaction, Ecommerce Pharma Data pertaining to the pharmaceutical industry. Restaurant & Food Delivery Transaction Details of transactions in the restaurant and food delivery sector. Ecommerce Online transactions, including products, purchases, and customer behavior, vital for optimizing online retail operations.

| Data Use Cases | Understand consumer purchasing and delivery behavior within the Mexico market

Data provides insights into pharmaceutical usage within the Mexico Market Insights into food consumption and food delivery usage

Insights into delivery applications transactions within the Mexico market, Rappi, Uber Eats, Ivoy, etc

Verified delivery consumer, email address, address information, etc

Geospatial, latitude, longitude, ping data coordinate values for consumers with timestamps

Geospatial, latitude, longitude, ping data coordinate values for delivery drivers

Insights into Mexico Farmacia brands delivery transactions

Insights to build targeted marketing campaigns for Mexico market consumers

| Delivery Options | Choose from various delivery options such as flat files, databases, APIs, and more, tailored to your needs.

| Other key features | Free data samples

Tags: Third-party software, On-Demand delivery, Last-mile, Drivers, Transit times, Branch locations, Products, Payments, Customer data, Food delivery, E-commerce, Pharmacy, Prescription action, Order processing, Efficiency, Customer behavior, Demand forecasting, Route optimization.

This table contains data on the annual miles traveled by place of occurrence and by mode of transportation (vehicle, pedestrian, bicycle), for California, its regions, counties, and cities/towns. The ratio uses data from the California Department of Transportation, the U.S. Department of Transportation, and the U.S. Census Bureau. The table is part of a series of indicators in the Healthy Communities Data and Indicators Project of the Office of Health Equity. Miles traveled by individuals and their choice of mode – car, truck, public transit, walking or bicycling – have a major impact on mobility and population health. Miles traveled by automobile offers extraordinary personal mobility and independence, but it is also associated with air pollution, greenhouse gas emissions linked to global warming, road traffic injuries, and sedentary lifestyles. Active modes of transport – bicycling and walking alone and in combination with public transit – offer opportunities for physical activity, which has many documented health benefits. More information about the data table and a data dictionary can be found in the About/Attachments section.

This collection focuses on how changes in the legal drinking age affect the number of fatal motor vehicle accidents and crime rates. The principal investigators identified three areas of study. First, they looked at blood alcohol content of drivers involved in fatal accidents in relation to changes in the drinking age. Second, they looked at how arrest rates correlated with changes in the drinking age. Finally, they looked at the relationship between blood alcohol content and arrest rates. In this context, the investigators used the percentage of drivers killed in fatal automobile accidents who had positive blood alcohol content as an indicator of drinking in the population. Arrests were used as a measure of crime, and arrest rates per capita were used to create comparability across states and over time. Arrests for certain crimes as a proportion of all arrests were used for other analyses to compensate for trends that affect the probability of arrests in general. This collection contains three parts. Variables in the Federal Bureau of Investigation Crime Data file (Part 1) include the state and year to which the data apply, the type of crime, and the sex and age category of those arrested for crimes. A single arrest is the unit of analysis for this file. Information in the Population Data file (Part 2) includes population counts for the number of individuals within each of seven age categories, as well as the number in the total population. There is also a figure for the number of individuals covered by the reporting police agencies from which data were gathered. The individual is the unit of analysis. The Fatal Accident Data file (Part 3) includes six variables: the FIPS code for the state, year of accident, and the sex, age group, and blood alcohol content of the individual killed. The final variable in each record is a count of the number of drivers killed in fatal motor vehicle accidents for that state and year who fit into the given sex, age, and blood alcohol content grouping. A driver killed in a fatal accident is the unit of analysis.

Taxi fleets, for-hire vehicle bases, and industry associations have been welcoming TLC into their establishments to discuss Vision Zero and traffic safety. TLC staff use a presentation to guide this discussion, and at the end of the session drivers sign the TLC Safe Driver Pledge.

For a complete list of Vision Zero maps, please follow this link

Federal and State field enforcement staff performs Inspections on Interstate and Intrastate Motor Carriers and Hazardous Materials carriers. Violations of the Federal Motor Carrier Safety Regulations (FMCSRs) severe enough may result in a vehicle and/or driver being placed "out-of-service." The data collected from inspection activity is collected and stored in the FMCSA Motor Carrier Management Information System (MCMIS) Inspection Data Files.

Due to privacy restrictions, driver information is not included in any inspection files released to the public.