18 datasets found
  1. Road traffic fatalities per one million inhabitants in the United States...

    • statista.com
    Updated Dec 18, 2023
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    Statista Research Department (2023). Road traffic fatalities per one million inhabitants in the United States 2014-2029 [Dataset]. https://www.statista.com/topics/3708/road-accidents-in-the-us/
    Explore at:
    Dataset updated
    Dec 18, 2023
    Dataset provided by
    Statistahttp://statista.com/
    Authors
    Statista Research Department
    Area covered
    United States
    Description

    The number of road traffic fatalities per one million inhabitants in the United States was forecast to continuously increase between 2024 and 2029 by in total 18.5 deaths (+13.81 percent). After the tenth consecutive increasing year, the number is estimated to reach 152.46 deaths and therefore a new peak in 2029. Depicted here are the estimated number of deaths which occured in relation to road traffic. They are set in relation to the population size and depicted as deaths per 100,000 inhabitants.The shown data are an excerpt of Statista's Key Market Indicators (KMI). The KMI are a collection of primary and secondary indicators on the macro-economic, demographic and technological environment in up to 150 countries and regions worldwide. All indicators are sourced from international and national statistical offices, trade associations and the trade press and they are processed to generate comparable data sets (see supplementary notes under details for more information).Find more key insights for the number of road traffic fatalities per one million inhabitants in countries like Mexico and Canada.

  2. d

    Motor Vehicle Collisions - Crashes

    • catalog.data.gov
    • nycopendata.socrata.com
    • +3more
    Updated Jul 12, 2025
    + more versions
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    data.cityofnewyork.us (2025). Motor Vehicle Collisions - Crashes [Dataset]. https://catalog.data.gov/dataset/motor-vehicle-collisions-crashes
    Explore at:
    Dataset updated
    Jul 12, 2025
    Dataset provided by
    data.cityofnewyork.us
    Description

    The Motor Vehicle Collisions crash table contains details on the crash event. Each row represents a crash event. 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.For the most accurate, up to date statistics on traffic fatalities, please refer to the NYPD Motor Vehicle Collisions page (updated weekly) or Vision Zero View (updated monthly). 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.

  3. Number of road accidents per one million inhabitants in the United States...

    • statista.com
    Updated Dec 18, 2023
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    Statista Research Department (2023). Number of road accidents per one million inhabitants in the United States 2014-2029 [Dataset]. https://www.statista.com/topics/3708/road-accidents-in-the-us/
    Explore at:
    Dataset updated
    Dec 18, 2023
    Dataset provided by
    Statistahttp://statista.com/
    Authors
    Statista Research Department
    Area covered
    United States
    Description

    The number of road accidents per one million inhabitants in the United States was forecast to continuously decrease between 2024 and 2029 by in total 2,490.4 accidents (-14.99 percent). After the eighth consecutive decreasing year, the number is estimated to reach 14,118.78 accidents and therefore a new minimum in 2029. Depicted here are the estimated number of accidents which occured in relation to road traffic. They are set in relation to the population size and depicted as accidents per one million inhabitants.The shown data are an excerpt of Statista's Key Market Indicators (KMI). The KMI are a collection of primary and secondary indicators on the macro-economic, demographic and technological environment in up to 150 countries and regions worldwide. All indicators are sourced from international and national statistical offices, trade associations and the trade press and they are processed to generate comparable data sets (see supplementary notes under details for more information).Find more key insights for the number of road accidents per one million inhabitants in countries like Mexico and Canada.

  4. US Traffic Fatality Records

    • kaggle.com
    zip
    Updated Mar 20, 2019
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    Department of Transportation (2019). US Traffic Fatality Records [Dataset]. https://www.kaggle.com/datasets/usdot/nhtsa-traffic-fatalities
    Explore at:
    zip(0 bytes)Available download formats
    Dataset updated
    Mar 20, 2019
    Dataset authored and provided by
    Department of Transportation
    License

    https://creativecommons.org/publicdomain/zero/1.0/https://creativecommons.org/publicdomain/zero/1.0/

    Description

    Fatality Analysis Reporting System (FARS) was created in the United States by the National Highway Traffic Safety Administration (NHTSA) to provide an overall measure of highway safety, to help suggest solutions, and to help provide an objective basis to evaluate the effectiveness of motor vehicle safety standards and highway safety programs.

    FARS contains data on a census of fatal traffic crashes within the 50 States, the District of Columbia, and Puerto Rico. To be included in FARS, a crash must involve a motor vehicle traveling on a trafficway customarily open to the public and result in the death of a person (occupant of a vehicle or a non-occupant) within 30 days of the crash. FARS has been operational since 1975 and has collected information on over 989,451 motor vehicle fatalities and collects information on over 100 different coded data elements that characterizes the crash, the vehicle, and the people involved.

    FARS is vital to the mission of NHTSA to reduce the number of motor vehicle crashes and deaths on our nation's highways, and subsequently, reduce the associated economic loss to society resulting from those motor vehicle crashes and fatalities. FARS data is critical to understanding the characteristics of the environment, trafficway, vehicles, and persons involved in the crash.

    NHTSA has a cooperative agreement with an agency in each state government to provide information in a standard format on fatal crashes in the state. Data is collected, coded and submitted into a micro-computer data system and transmitted to Washington, D.C. Quarterly files are produced for analytical purposes to study trends and evaluate the effectiveness highway safety programs.

    Content

    There are 40 separate data tables. You can find the manual, which is too large to reprint in this space, here.

    Querying BigQuery tables

    You can use the BigQuery Python client library to query tables in this dataset in Kernels. Note that methods available in Kernels are limited to querying data. Tables are at bigquery-public-data.nhtsa_traffic_fatalities.[TABLENAME]. Fork this kernel to get started.

    Acknowledgements

    This dataset was provided by the National Highway Traffic Safety Administration.

  5. d

    Motor Vehicle Collisions - Person

    • catalog.data.gov
    • data.cityofnewyork.us
    Updated Jul 12, 2025
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    data.cityofnewyork.us (2025). Motor Vehicle Collisions - Person [Dataset]. https://catalog.data.gov/dataset/motor-vehicle-collisions-person
    Explore at:
    Dataset updated
    Jul 12, 2025
    Dataset provided by
    data.cityofnewyork.us
    Description

    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.

  6. Road Traffic Injuries

    • data.ca.gov
    • data.chhs.ca.gov
    • +3more
    pdf, xlsx, zip
    Updated Aug 29, 2024
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    California Department of Public Health (2024). Road Traffic Injuries [Dataset]. https://data.ca.gov/dataset/road-traffic-injuries
    Explore at:
    zip, xlsx, pdfAvailable download formats
    Dataset updated
    Aug 29, 2024
    Dataset authored and provided by
    California Department of Public Healthhttps://www.cdph.ca.gov/
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    This table contains data on the annual number of fatal and severe road traffic injuries per population and per miles traveled by transport mode, for California, its regions, counties, county divisions, cities/towns, and census tracts. Injury data is from the Statewide Integrated Traffic Records System (SWITRS), California Highway Patrol (CHP), 2002-2010 data from the Transportation Injury Mapping System (TIMS) . The table is part of a series of indicators in the [Healthy Communities Data and Indicators Project of the Office of Health Equity]. Transportation accidents are the second leading cause of death in California for people under the age of 45 and account for an average of 4,018 deaths per year (2006-2010). Risks of injury in traffic collisions are greatest for motorcyclists, pedestrians, and bicyclists and lowest for bus and rail passengers. Minority communities bear a disproportionate share of pedestrian-car fatalities; Native American male pedestrians experience 4 times the death rate as Whites or Asians, 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.

  7. N

    2021 traffic deaths involving pedestrians and cyclists

    • data.cityofnewyork.us
    application/rdfxml +5
    Updated Jul 11, 2025
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    Police Department (NYPD) (2025). 2021 traffic deaths involving pedestrians and cyclists [Dataset]. https://data.cityofnewyork.us/Public-Safety/2021-traffic-deaths-involving-pedestrians-and-cycl/u7dk-udsr
    Explore at:
    application/rssxml, csv, tsv, xml, application/rdfxml, jsonAvailable download formats
    Dataset updated
    Jul 11, 2025
    Authors
    Police Department (NYPD)
    Description

    This is a subset of a larger dataset. This dataset includes pedestrians and cyclists killed in traffic collisions in 2021.

    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.

  8. T

    Vital Signs: Fatalities From Crashes By Metro (2022) DRAFT

    • data.bayareametro.gov
    application/rdfxml +5
    Updated Oct 27, 2022
    + more versions
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    (2022). Vital Signs: Fatalities From Crashes By Metro (2022) DRAFT [Dataset]. https://data.bayareametro.gov/Environment/Vital-Signs-Fatalities-From-Crashes-By-Metro-2022-/c777-6e82
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    application/rdfxml, application/rssxml, tsv, csv, json, xmlAvailable download formats
    Dataset updated
    Oct 27, 2022
    Description

    VITAL SIGNS INDICATOR
    Fatalities From Crashes (EN4)

    FULL MEASURE NAME
    Fatalities from Crashes (traffic collisions)

    LAST UPDATED
    October 2022

    DESCRIPTION
    Fatalities from crashes refers to deaths as a result of fatalities sustained in collisions. The California Highway Patrol includes deaths within 30 days of the collision that are a result of fatalities sustained as part of this metric. This total fatalities dataset includes fatality counts for the region and counties, as well as individual collision data and metropolitan area data.

    DATA SOURCE
    National Highway Safety Administration: Fatality Analysis Reporting System - https://www.nhtsa.gov/file-downloads?p=nhtsa/downloads/FARS/
    1990-2020

    Caltrans: Highway Performance Monitoring System (HPMS) - https://dot.ca.gov/programs/research-innovation-system-information/highway-performance-monitoring-system
    Annual Vehicle Miles Traveled (VMT)
    2001-2020

    California Department of Finance: E-4 Historical Population Estimates for Cities, Counties, and the State - https://dof.ca.gov/forecasting/demographics/estimates/
    1990-2020

    US Census Population and Housing Unit Estimates - https://www.census.gov/programs-surveys/popest.html
    1990-2020

    CONTACT INFORMATION
    vitalsigns.info@bayareametro.gov

    METHODOLOGY NOTES (across all datasets for this indicator)
    Fatalities from crashes data is reported to the National Highway Traffic Safety Administration through the Fatality Analysis Reporting System (FARS) program. Data for individual collisions is reported by the California Highway Patrol (CHP) to the Statewide Integrated Traffic Records System (SWITRS). The data was tabulated using provided categories specifying injury level, individuals involved, causes of collision and location/jurisdiction of collision (for more information refer to the SWITRS codebook - http://tims.berkeley.edu/help/files/switrs_codebook.doc). For case data, latitude and longitude information for each accident is geocoded by SafeTREC’s Transportation Injury Mapping System (TIMS). Fatalities were normalized over historic population data from the US Census Bureau’s population estimates and vehicle miles traveled (VMT) data from the Federal Highway Administration.

    The crash data only include crashes that involved a motor vehicle. Bicyclist and pedestrian fatalities that did not involve a motor vehicle, such as a bicyclist and pedestrian collision or a bicycle crash due to a pothole, are not included in the data.

    For more regarding reporting procedures and injury classification, refer to the CHP Manual - https://www.nhtsa.gov/sites/nhtsa.dot.gov/files/documents/ca_chp555_manual_2_2003_ch1-13.pdf.

  9. a

    Deaths from motor vehicle traffic injuries

    • hub.arcgis.com
    • data-sccphd.opendata.arcgis.com
    Updated Feb 7, 2018
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    Santa Clara County Public Health (2018). Deaths from motor vehicle traffic injuries [Dataset]. https://hub.arcgis.com/datasets/6d4ef035f5d447f0a4f39d8668a72b94
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    Dataset updated
    Feb 7, 2018
    Dataset authored and provided by
    Santa Clara County Public Health
    License

    MIT Licensehttps://opensource.org/licenses/MIT
    License information was derived automatically

    Description

    Age-adjusted rate of deaths from motor vehicle traffic injuries by sex, race/ethnicity, age; trends if available. Source: Santa Clara County Public Health Department, VRBIS, 2007-2016. Data as of 05/26/2017; U.S. Census Bureau; 2010 Census, Tables PCT12, PCT12H, PCT12I, PCT12J, PCT12K, PCT12L, PCT12M; generated by Baath M.; using American FactFinder; Accessed June 20, 2017. METADATA:Notes (String): Lists table title, notes and sourcesYear (String): Year of data; presented as single year or pooled years (2012 to 2016)Category (String): Lists the category representing the data: Santa Clara County is for total population, sex: Male and Female, race/ethnicity: African American, Asian/Pacific Islander, Latino and White (non-Hispanic White only); age categories as follows: 0 to 17, 18 to 44, 45 to 64, 65+; <1, 1 to 4, 5 to 14, 15 to 24, 25 to 34, 35 to 44, 45 to 54, 55 to 64, 65 to 74, 75 to 84, 85+; United States and Healthy People 2020 targetRate per 100,000 people (Numeric): Rate of deaths from motor vehicle traffic injuries. Rates for age groups are reported as age-specific rates per 100,000 people. All other rates are age-adjusted rates per 100,000 people.

  10. w

    Fire statistics data tables

    • gov.uk
    • s3.amazonaws.com
    Updated Jul 10, 2025
    + more versions
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    Ministry of Housing, Communities and Local Government (2025). Fire statistics data tables [Dataset]. https://www.gov.uk/government/statistical-data-sets/fire-statistics-data-tables
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    Dataset updated
    Jul 10, 2025
    Dataset provided by
    GOV.UK
    Authors
    Ministry of Housing, Communities and Local Government
    Description

    On 1 April 2025 responsibility for fire and rescue transferred from the Home Office to the Ministry of Housing, Communities and Local Government.

    This information covers fires, false alarms and other incidents attended by fire crews, and the statistics include the numbers of incidents, fires, fatalities and casualties as well as information on response times to fires. The Ministry of Housing, Communities and Local Government (MHCLG) also collect information on the workforce, fire prevention work, health and safety and firefighter pensions. All data tables on fire statistics are below.

    MHCLG has responsibility for fire services in England. The vast majority of data tables produced by the Ministry of Housing, Communities and Local Government are for England but some (0101, 0103, 0201, 0501, 1401) tables are for Great Britain split by nation. In the past the Department for Communities and Local Government (who previously had responsibility for fire services in England) produced data tables for Great Britain and at times the UK. Similar information for devolved administrations are available at https://www.firescotland.gov.uk/about/statistics/" class="govuk-link">Scotland: Fire and Rescue Statistics, https://statswales.gov.wales/Catalogue/Community-Safety-and-Social-Inclusion/Community-Safety" class="govuk-link">Wales: Community safety and https://www.nifrs.org/home/about-us/publications/" class="govuk-link">Northern Ireland: Fire and Rescue Statistics.

    If you use assistive technology (for example, a screen reader) and need a version of any of these documents in a more accessible format, please email alternativeformats@communities.gov.uk. Please tell us what format you need. It will help us if you say what assistive technology you use.

    Related content

    Fire statistics guidance
    Fire statistics incident level datasets

    Incidents attended

    https://assets.publishing.service.gov.uk/media/686d2aa22557debd867cbe14/FIRE0101.xlsx">FIRE0101: Incidents attended by fire and rescue services by nation and population (MS Excel Spreadsheet, 153 KB) Previous FIRE0101 tables

    https://assets.publishing.service.gov.uk/media/686d2ab52557debd867cbe15/FIRE0102.xlsx">FIRE0102: Incidents attended by fire and rescue services in England, by incident type and fire and rescue authority (MS Excel Spreadsheet, 2.19 MB) Previous FIRE0102 tables

    https://assets.publishing.service.gov.uk/media/686d2aca10d550c668de3c69/FIRE0103.xlsx">FIRE0103: Fires attended by fire and rescue services by nation and population (MS Excel Spreadsheet, 201 KB) Previous FIRE0103 tables

    https://assets.publishing.service.gov.uk/media/686d2ad92557debd867cbe16/FIRE0104.xlsx">FIRE0104: Fire false alarms by reason for false alarm, England (MS Excel Spreadsheet, 492 KB) Previous FIRE0104 tables

    Dwelling fires attended

    https://assets.publishing.service.gov.uk/media/686d2af42cfe301b5fb6789f/FIRE0201.xlsx">FIRE0201: Dwelling fires attended by fire and rescue services by motive, population and nation (MS Excel Spreadsheet, <span class="gem-c-attac

  11. California Commuting Mode Choice

    • kaggle.com
    Updated Jan 12, 2023
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    The Devastator (2023). California Commuting Mode Choice [Dataset]. https://www.kaggle.com/datasets/thedevastator/california-commuting-mode-choice-from-2000-2010
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Jan 12, 2023
    Dataset provided by
    Kagglehttp://kaggle.com/
    Authors
    The Devastator
    License

    Open Database License (ODbL) v1.0https://www.opendatacommons.org/licenses/odbl/1.0/
    License information was derived automatically

    Area covered
    California
    Description

    California Commuting Mode Choice

    Regional Disparities in Risk of Injury and Death

    By Health [source]

    About this dataset

    This dataset contains data on the modes of transportation used by California residents aged 16 and older to commute to work. It includes data from the U.S. Census Bureau, Decennial Census and American Community Survey, covering all regions, counties, cities/towns, and census tracts in California. With each region showing detailed information regarding how its population travels to work (modes of transportation used), this dataset provides vital insight into the development of transport infrastructure in California over the past decade.

    Unlike other states where private cars constitute an overwhelming majority of daily commuters (over 79% nationwide according to a 2015 survey), Californians have built up varied commuting habits – bicycles are commonly reported 5%, public transit stands at 15%, walking alone 4%, and carpooling is at 11%. Commuting plays a significant role on overall health—active modes such as biking or walking lead to healthier lifestyles that lower heart disease risks, obesity rates, diabetes prevalence; passengers on public transport also have a lower chance of injury in collisions compared with pedestrians or cyclists.

    The consequences of inadequate planning for human mobility extend beyond physical health – it can also cause huge disparities between different racial groups such as Native Americans who experience four times higher death rate from pedestrian-car collisions than Whites or Asians; African-Americans and Latinos suffer twice as much as White people do when driving privately in their own cars due to air pollution hazards or lack thereof access to reliable public transportation system that could provide them with healthier alternatives. It is our hope that policymakers will use this dataset prominently stated by the Healthy Communities Data & Indicators Project - part of the Office Of Health Equity - while ensuring every resident’s right for safe mobility no matter their background!

    More Datasets

    For more datasets, click here.

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    • 🚨 Your notebook can be here! 🚨!

    How to use the dataset

    This dataset contains information on the percent of Californians aged 16 and older who use different modes of transportation to get to work. The data is collected from the U.S. Census Bureau and American Community Survey, and covers all counties, cities/towns and census tracts in California.

    In this dataset, there are several columns of data such as mode (mode of transport), race_eth_name (name of the race/ethnicity), region_code (code for the region) and pop_total (total population). This makes it possible to look at relations between transportation choice and demographic factors like gender or ethnicity, or comparison between regions within California regarding commuting habits.

    The purpose of this dataset is to provide information on how Californians travel to their jobs with respect to both geographical area as well as demographic characteristics. It allows studies into why certain areas might have higher usage rates for specific types of transport compared with others, how gender affects travel decisions, or which regions have access issues with public transit compared with driving for example.

    To use this dataset you should start by familiarizing yourself with descriptive statistics such as percentages, hazard ratios etc., in order to understand each variable's contribution towards commuting trends more effectively. It might also help if you filter data by geographic area or personal characteristics first before performing more detailed analysis for more insightful results that can be used in policy-making when planning effective infrastructure investments related to transportation options over time or among differing populations within California state population levels noted here year-by-year across a decade period provided here

    Research Ideas

    • Creating interactive maps to visualize and compare the transportation methods of different race/ethnicities in California.
    • Analyzing the transportation trends across regions, counties, cities/towns, and census tracts to forecast and plan for infrastructure investments.
    • Comparing the risk ratio of pedestrian-car fatalities across different ethnic groups in order to address safety issues within underserved populations

    Acknowledgements

    If you use this dataset in your research, please credit the original authors. Data Source

    License

    **License: [Open Database License (ODbL) v1.0](https://opendatacommons.org/lice...

  12. Drivers involved in fatal crashes in U.S. road traffic by sex 1996-2021

    • statista.com
    Updated Nov 17, 2023
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    Statista (2023). Drivers involved in fatal crashes in U.S. road traffic by sex 1996-2021 [Dataset]. https://www.statista.com/statistics/192074/drivers-in-fatal-crashes-in-us-road-traffic-by-gender-since-1992/
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    Dataset updated
    Nov 17, 2023
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United States
    Description

    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.

  13. T

    Tesla Fire

    • tesla-fire.com
    • search.dataone.org
    • +2more
    csv
    Updated Feb 19, 2024
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    I Capulet (2024). Tesla Fire [Dataset]. http://doi.org/10.5281/zenodo.5520568
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    csvAvailable download formats
    Dataset updated
    Feb 19, 2024
    Dataset provided by
    TSLAQ
    Authors
    I Capulet
    License

    Attribution-NonCommercial-ShareAlike 4.0 (CC BY-NC-SA 4.0)https://creativecommons.org/licenses/by-nc-sa/4.0/
    License information was derived automatically

    Time period covered
    Apr 2, 2013 - Present
    Variables measured
    fires
    Description

    A digital record of all Tesla fires - including cars and other products, e.g. Tesla MegaPacks - that are corroborated by news articles or confirmed primary sources. Latest version hosted at https://www.tesla-fire.com.

  14. Data from: Minimum Legal Drinking Age and Crime in the United States,...

    • catalog.data.gov
    • s.cnmilf.com
    • +1more
    Updated Mar 12, 2025
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    National Institute of Justice (2025). Minimum Legal Drinking Age and Crime in the United States, 1980-1987 [Dataset]. https://catalog.data.gov/dataset/minimum-legal-drinking-age-and-crime-in-the-united-states-1980-1987-9bd49
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    Dataset updated
    Mar 12, 2025
    Dataset provided by
    National Institute of Justicehttp://nij.ojp.gov/
    Area covered
    United States
    Description

    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.

  15. Transportation to Work

    • data.ca.gov
    • data.chhs.ca.gov
    • +4more
    pdf, xlsx, zip
    Updated Aug 29, 2024
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    California Department of Public Health (2024). Transportation to Work [Dataset]. https://data.ca.gov/dataset/transportation-to-work
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    xlsx, zip, pdfAvailable download formats
    Dataset updated
    Aug 29, 2024
    Dataset authored and provided by
    California Department of Public Healthhttps://www.cdph.ca.gov/
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    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.

  16. T

    Office of Traffic Safety Crash Data for Napa County and Selected Cities

    • data.countyofnapa.org
    application/rdfxml +5
    Updated Jul 11, 2023
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    (2023). Office of Traffic Safety Crash Data for Napa County and Selected Cities [Dataset]. https://data.countyofnapa.org/Health-Outcomes-and-Health-Behaviors/Office-of-Traffic-Safety-Crash-Data-for-Napa-Count/c7ub-ipet
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    application/rdfxml, csv, application/rssxml, tsv, json, xmlAvailable download formats
    Dataset updated
    Jul 11, 2023
    Area covered
    Napa County
    Description

    Data Source: California Office of Traffic Safety

    This data biography shares the how, who, what, where, when, and why about this dataset. We, the epidemiology team at Napa County Health and Human Services Agency, Public Health Division, created it to help you understand where the data we analyze and share comes from. If you have any further questions, we can be reached at epidemiology@countyofnapa.org.

    Data dashboard featuring this data: https://data.countyofnapa.org/stories/s/abqu-wcty

    Why was the data collected?  California Office of Traffic Safety (OTS) ranking metric is a tool used to compare similarly sized cities on traffic safety statistics. A smaller the assigned number means that the city is ranked higher, and a higher ranking means the city has worse traffic safety compared to similar locations.

    How was the data collected? Crash data comes from Statewide Traffic Records System (SWITRS). This system collects and processes data gathered from a collision scene. Population estimates come from California Department of Finance (DoF), which are based on changes in births, deaths, domestic migration, and international migration. Estimates are developed using aggregate data from a variety of sources, including birth and death counts provided by the Department of Public Health, driver's license data from the Department of Motor Vehicles, housing unit data from local governments, school enrollment data from the Department of Education, and federal income tax return data from the U.S. Internal Revenue Service. Daily Vehicle Miles Traveled (DVMT) come from California Department of Transportation (Caltrans). The Traffic Data Branch at Caltrans estimates the number of vehicle miles that motorists traveled on California State Highways using a sampling of up to 20 traffic monitoring sites and reports on that data. Crash rankings are based on a ranking method that assigns statistical weights to categories including observed crash counts, population, and vehicle miles traveled. Counties are assigned statewide rankings, while cities are assigned population group rankings. DUI arrests data comes from the Department of Justice.

    Who was included and excluded from the data & Where was the data collected? Data for the rankings is taken from Incorporated cities only. This includes local streets and state highways within city limits that share jurisdiction with the CHP. DUI arrest data is only available for cities that report it to the Department of Justice. Data from the OTS crash was sources specifically for Napa County, the City of Napa, American Canyon, Calistoga, St. Helena and Yountville.

    When was the data collected? 2017-2022

    Where can I learn more about this data? Office of traffic safety: https://www.ots.ca.gov/media-and-research/crash-rankings/ Methodology: https://rosap.ntl.bts.gov/view/dot/24410

  17. Number of homicide victims, by method used to commit the homicide

    • www150.statcan.gc.ca
    • beta.data.urbandatacentre.ca
    • +3more
    Updated Jul 25, 2024
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    Government of Canada, Statistics Canada (2024). Number of homicide victims, by method used to commit the homicide [Dataset]. http://doi.org/10.25318/3510006901-eng
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    Dataset updated
    Jul 25, 2024
    Dataset provided by
    Statistics Canadahttps://statcan.gc.ca/en
    Area covered
    Canada
    Description

    Number of homicide victims, by method used to commit the homicide (total methods used; shooting; stabbing; beating; strangulation; fire (burns or suffocation); other methods used; methods used unknown), Canada, 1974 to 2023.

  18. O

    Real-Time Traffic Incident Reports

    • data.austintexas.gov
    • datahub.austintexas.gov
    • +1more
    Updated Jul 14, 2025
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    City of Austin, Texas - data.austintexas.gov (2025). Real-Time Traffic Incident Reports [Dataset]. https://data.austintexas.gov/Transportation-and-Mobility/Real-Time-Traffic-Incident-Reports/dx9v-zd7x
    Explore at:
    csv, tsv, application/rssxml, application/rdfxml, xml, kml, application/geo+json, kmzAvailable download formats
    Dataset updated
    Jul 14, 2025
    Dataset authored and provided by
    City of Austin, Texas - data.austintexas.gov
    Description

    This dataset contains traffic incident information from the Austin-Travis County traffic reports collected from the various Public Safety agencies through a data feed from the Combined Transportation, Emergency, and Communications Center (CTECC).

    For further context, see: - Active Incidents: Map and Context - https://data.austintexas.gov/stories/s/Austin-Travis-County-Traffic-Report-Page/9qfg-4swh/ - Data Trends and Analysis - https://data.austintexas.gov/stories/s/48n7-m3me

    The dataset is updated every 5 minutes with the latest snapshot of active traffic incidents.

  19. Not seeing a result you expected?
    Learn how you can add new datasets to our index.

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Statista Research Department (2023). Road traffic fatalities per one million inhabitants in the United States 2014-2029 [Dataset]. https://www.statista.com/topics/3708/road-accidents-in-the-us/
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Road traffic fatalities per one million inhabitants in the United States 2014-2029

Explore at:
14 scholarly articles cite this dataset (View in Google Scholar)
Dataset updated
Dec 18, 2023
Dataset provided by
Statistahttp://statista.com/
Authors
Statista Research Department
Area covered
United States
Description

The number of road traffic fatalities per one million inhabitants in the United States was forecast to continuously increase between 2024 and 2029 by in total 18.5 deaths (+13.81 percent). After the tenth consecutive increasing year, the number is estimated to reach 152.46 deaths and therefore a new peak in 2029. Depicted here are the estimated number of deaths which occured in relation to road traffic. They are set in relation to the population size and depicted as deaths per 100,000 inhabitants.The shown data are an excerpt of Statista's Key Market Indicators (KMI). The KMI are a collection of primary and secondary indicators on the macro-economic, demographic and technological environment in up to 150 countries and regions worldwide. All indicators are sourced from international and national statistical offices, trade associations and the trade press and they are processed to generate comparable data sets (see supplementary notes under details for more information).Find more key insights for the number of road traffic fatalities per one million inhabitants in countries like Mexico and Canada.

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