Statistic crash records within State of California

***The Los Angeles Police Department (LAPD) has transitioned traffic collision reporting to our new Records Management System (RMS) as part of our ongoing efforts to modernize data collection and comply with the FBI’s National Incident-Based Reporting System (NIBRS). This transition will improve the accuracy and detail of reported traffic-related incidents.

During this process, there will be a delay in the availability of new traffic collision datasets while they are being developed for the new system. In the meantime, users will continue to see only historical data from the retired system. We appreciate your patience as we complete this transition. ***

This dataset reflects traffic collision incidents in the City of Los Angeles dating back to 2010. This data is transcribed from original traffic reports that are typed on paper and therefore there may be some inaccuracies within the data. Some location fields with missing data are noted as (0°, 0°). Address fields are only provided to the nearest hundred block in order to maintain privacy. This data is as accurate as the data in the database. Please note questions or concerns in the comments.

The Crash Data On California State Highways Report is produced by the California Department of Transportation (Caltrans) to provide high level summaries of road miles, travel, crashes and crash rates on the California State Highway System.

This table lists statewide vehicle travel expressed in Million Vehicle Miles (MVM), road miles, and one and three year crash rates and fatality rates based on lane types and population codes.

While crash rates for total crash and fatal + injury crashes are calculated per MVM, fatality rates are expressed per 100 MVM.

The Crash Data On California State Highways Report is produced annually by the California Department of Transportation (Caltrans) to provide high level summaries of road miles, travel, crashes and crash rates on the California State Highway System. This table lists statewide vehicle travel expressed in Million Vehicle Miles (MVM), road miles, and one and three year crash rates and fatality rates based on lane types and population codes. While crash rates for total crash and fatal + injury crashes are calculated per MVM, fatality rates are expressed per 100 MVM.

National Collision Database (NCDB) – a database containing all police-reported motor vehicle collisions on public roads in Canada. Selected variables (data elements) relating to fatal and injury collisions for the collisions from 1999 to the most recent available data.

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

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.

Statewide Integrated Traffic Records System (SWITRS) location point data, containing combined reports on collision crashes, parties, and victims in Orange County, California for 2012-2024 (Data from January 01, 2012 to December 31, 2024). The data are collected and maintained by the California Highway Patrol (CHP), from incidents reported by local and government agencies. Original tabular datasets are provided by the Transportation Injury Mapping System (TIMS). Only records with reported locational GPS attributes in Orange County are included in the spatial database (either from X and Y geocoded coordinates, or the longitude and latitude coordinates generated by the CHP officer on site). Incidents without valid coordinates are omitted from this spatial dataset representation. Last Updated on June 12, 2025

In 2024, the state of California reported ***** motor-vehicle deaths, an increase from the year before. Death from motor-vehicles remains a relevant problem across the United States. Motor-vehicle deaths in the United States In the United States, a person’s lifetime odds of dying in a motor vehicle accident is around * in **. Death rates from motor vehicles have decreased in recent years and are significantly lower than the rates recorded in the ***** and *****. This is due to a mass improvement in car safety standards and features. For example, all states, with the exception of New Hampshire, have laws against not wearing safety belts. Drinking and driving One of the biggest causes of motor-vehicle deaths is driving while under the influence of alcohol. The state with the highest number of fatalities due to alcohol-impaired driving in 2022 was Texas, followed by California and Florida. Light trucks are the vehicle type most often involved in fatal crashes caused by alcohol-impaired drivers, with around ***** such accidents in the United States in 2022.

VITAL SIGNS INDICATOR Fatalities From Crashes (EN4-6)

FULL MEASURE NAME Fatalities from crashes (traffic collisions)

LAST UPDATED May 2022

DESCRIPTION Fatalities from crashes refers to deaths as a result of injuries sustained in collisions. The California Highway Patrol includes deaths within 30 days of the collision that are a result of injuries 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

CONTACT INFORMATION vitalsigns.info@bayareametro.gov

METHODOLOGY NOTES (across all datasets for this indicator) The data is reported by the California Highway Patrol (CHP) to the Statewide Integrated Traffic Records System (SWITRS), which was accessed via SafeTREC’s Transportation Injury Mapping System (TIMS). The data was tabulated using provided categories specifying injury level, individuals involved, causes of collision, and location/jurisdiction of collision (for more: http://tims.berkeley.edu/help/files/switrs_codebook.doc).

For more regarding reporting procedures and injury classification, see the California Highway Patrol Manual (https://one.nhtsa.gov/nhtsa/stateCatalog/states/ca/docs/CA_CHP555_Manual_2_2003_ch1-13.pdf).

A. SUMMARY This table contains all victims (parties who are injured) involved in a traffic crash resulting in an injury in the City of San Francisco. Fatality year-to-date crash data is obtained from the Office of the Chief Medical Examiner (OME) death records, and only includes those cases that meet the San Francisco Vision Zero Fatality Protocol maintained by the San Francisco Department of Public Health (SFDPH), San Francisco Police Department (SFPD), and San Francisco Municipal Transportation Agency (SFMTA). Injury crash data is obtained from SFPD’s Interim Collision System for 2018 to YTD, Crossroads Software Traffic Collision Database (CR) for years 2013-2017 and the Statewide Integrated Transportation Record System (SWITRS) maintained by the California Highway Patrol for all years prior to 2013. Only crashes with valid geographic information are mapped. All geocodable crash data is represented on the simplified San Francisco street centerline model maintained by the Department of Public Works (SFDPW). Collision injury data is queried and aggregated on a quarterly basis. Crashes occurring at complex intersections with multiple roadways are mapped onto a single point and injury and fatality crashes occurring on highways are excluded.

The crash, party, and victim tables have a relational structure. The traffic crashes table contains information on each crash, one record per crash. The party table contains information from all parties involved in the crashes, one record per party. Parties are individuals involved in a traffic crash including drivers, pedestrians, bicyclists, and parked vehicles. The victim table contains information about each party injured in the collision, including any passengers. Injury severity is included in the victim table.

For example, a crash occurs (1 record in the crash table) that involves a driver party and a pedestrian party (2 records in the party table). Only the pedestrian is injured and thus is the only victim (1 record in the victim table).

B. HOW THE DATASET IS CREATED Traffic crash injury data is collected from the California Highway Patrol 555 Crash Report as submitted by the police officer within 30 days after the crash occurred. All fields that match the SWITRS data schema are programmatically extracted, de-identified, geocoded, and loaded into TransBASE. See Section D below for details regarding TransBASE.

C. UPDATE PROCESS After review by SFPD and SFDPH staff, the data is made publicly available approximately a month after the end of the previous quarter (May for Q1, August for Q2, November for Q3, and February for Q4).

D. HOW TO USE THIS DATASET This data is being provided as public information as defined under San Francisco and California public records laws. SFDPH, SFMTA, and SFPD cannot limit or restrict the use of this data or its interpretation by other parties in any way. Where the data is communicated, distributed, reproduced, mapped, or used in any other way, the user should acknowledge TransBASE.sfgov.org as the source of the data, provide a reference to the original data source where also applicable, include the date the data was pulled, and note any caveats specified in the associated metadata documentation provided. However, users should not attribute their analysis or interpretation of this data to the City of San Francisco. While the data has been collected and/or produced for the use of the City of San Francisco, it cannot guarantee its accuracy or completeness. Accordingly, the City of San Francisco, including SFDPH, SFMTA, and SFPD make no representation as to the accuracy of the information or its suitability for any purpose and disclaim any liability for omissions or errors that may be contained therein. As all data is associated with methodological assumptions and limitations, the City recommends that users review methodological documentation associated with the data prior to its analysis, interpretation, or communication.

This dataset can also be queried on the TransBASE Dashboard. TransBASE is a geospatially enabled database maintained by SFDPH that currently includes over 200 spatially referenced variables from multiple agencies and across a range of geographic scales, including infrastructure, transportation, zoning, sociodemographic, and collision data, all linked to an intersection or street segment. TransBASE facilitates a data-driven approach to understanding and addressing transportation-related health issues, informed by a large and growing evidence base regarding the importance of transportation system design and land use decisions for health. TransBASE’s purpose is to inform public and private efforts to improve transportation system safety, sustainability, community health and equity in San Francisco.

E. RELATED DATASETS Traffic Crashes Resulting in Injury Traffic Crashes Resulting in Injury: Parties Involved TransBASE Dashboard iSWITRS TIMS

A. SUMMARY This table contains all fatalities resulting from a traffic crash in the City of San Francisco. Fatality year-to-date crash data is obtained from the Office of the Chief Medical Examiner (OME) death records, and only includes those cases that meet the San Francisco Vision Zero Fatality Protocol maintained by the San Francisco Department of Public Health (SFDPH), San Francisco Police Department (SFPD), and San Francisco Municipal Transportation Agency (SFMTA). Injury crash data is obtained from SFPD’s Interim Collision System for 2018 to YTD, Crossroads Software Traffic Collision Database (CR) for years 2013-2017 and the Statewide Integrated Transportation Record System (SWITRS) maintained by the California Highway Patrol for all years prior to 2013. Only crashes with valid geographic information are mapped. All geocodable crash data is represented on the simplified San Francisco street centerline model maintained by the Department of Public Works (SFDPW). Collision injury data is queried and aggregated on a quarterly basis. Crashes occurring at complex intersections with multiple roadways are mapped onto a single point and injury and fatality crashes occurring on highways are excluded. The fatality table contains information about each party injured or killed in the collision, including any passengers. B. HOW THE DATASET IS CREATED Traffic crash injury data is collected from the California Highway Patrol 555 Crash Report as submitted by the police officer within 30 days after the crash occurred. All fields that match the SWITRS data schema are programmatically extracted, de-identified, geocoded, and loaded into TransBASE. See Section D below for details regarding TransBASE. This table is filtered for fatal traffic crashes. C. UPDATE PROCESS After review by SFPD and SFDPH staff, the data is made publicly available approximately a month after the end of the previous quarter (May for Q1, August for Q2, November for Q3, and February for Q4). D. HOW TO USE THIS DATASET This data is being provided as public information as defined under San Francisco and California public records laws. SFDPH, SFMTA, and SFPD cannot limit or restrict the use of this data or its interpretation by other parties in any way. Where the data is communicated, distributed, reproduced, mapped, or used in any other way, the user should acknowledge the Vision Zero initiative and the TransBASE database as the source of the data, provide a reference to the original data source where also applicable, include the date the data was pulled, and note any caveats specified in the associated metadata documentation provided. However, users should not attribute their analysis or interpretation of this data to the City of San Francisco. While the data has been collected and/or produced for the use of the City of San Francisco, it cannot guarantee its accuracy or completeness. Accordingly, the City of San Francisco, including SFDPH, SFMTA, and SFPD make no representation as to the accuracy of the information or its suitability for any purpose and disclaim any liability for omissions or errors that may be contained therein. As all data is associated with methodological assumptions and limitations, the City recommends that users review methodological documentation associated with the data prior to its analysis, interpretation, or communication. TransBASE is a geospatially enabled database maintained by SFDPH that currently includes over 200 spatially referenced variables from multiple agencies and across a range of geographic scales, including infrastructure, transportation, zoning, sociodemographic, and collision data, all linked to an intersection or street segment. TransBASE facilitates a data-driven approach to understanding and addressing transportation-related health issues, informed by a large and growing evidence base regarding the importance of transportation system design and land u

This data comes from the California Highway Patrol and covers collisions from January 1st, 2001 until mid-October, 2020. I have requested full database dumps from the CHP four times, once in 2016, 2017, 2018, 2020, and 2021. I have combined these datasets into the one presented here. For additional details, see my post: Introducing the SWITRS SQLite Hosted Dataset

There are three main tables:

• collisions: Contains information about the collision, where it happened, what vehicles were involved.
• parties: Contains information about the groups people involved in the collision including age, sex, and sobriety.
• victims: Contains information about the injuries of specific people involved in the collision.

There is also a table called case_ids which I used to build the other tables. It tells you which of the four original datasets each row came from.

Redirect Notice: The website https://transbase.sfgov.org/ is no longer in operation. Visitors to Transbase will be redirected to this page where they can view, visualize, and download Traffic Crash data.

A. SUMMARY This table contains all crashes resulting in an injury in the City of San Francisco. Fatality year-to-date crash data is obtained from the Office of the Chief Medical Examiner (OME) death records, and only includes those cases that meet the San Francisco Vision Zero Fatality Protocol maintained by the San Francisco Department of Public Health (SFDPH), San Francisco Police Department (SFPD), and San Francisco Municipal Transportation Agency (SFMTA). Injury crash data is obtained from SFPD’s Interim Collision System for 2018 through the current year-to-date, Crossroads Software Traffic Collision Database (CR) for years 2013-2017 and the Statewide Integrated Transportation Record System (SWITRS) maintained by the California Highway Patrol for all years prior to 2013. Only crashes with valid geographic information are mapped. All geocodable crash data is represented on the simplified San Francisco street centerline model maintained by the Department of Public Works (SFDPW). Collision injury data is queried and aggregated on a quarterly basis. Crashes occurring at complex intersections with multiple roadways are mapped onto a single point and injury and fatality crashes occurring on highways are excluded.

The crash, party, and victim tables have a relational structure. The traffic crashes table contains information on each crash, one record per crash. The party table contains information from all parties involved in the crashes, one record per party. Parties are individuals involved in a traffic crash including drivers, pedestrians, bicyclists, and parked vehicles. The victim table contains information about each party injured in the collision, including any passengers. Injury severity is included in the victim table.

For example, a crash occurs (1 record in the crash table) that involves a driver party and a pedestrian party (2 records in the party table). Only the pedestrian is injured and thus is the only victim (1 record in the victim table).

To learn more about the traffic injury datasets, see the TIMS documentation

B. HOW THE DATASET IS CREATED Traffic crash injury data is collected from the California Highway Patrol 555 Crash Report as submitted by the police officer within 30 days after the crash occurred. All fields that match the SWITRS data schema are programmatically extracted, de-identified, geocoded, and loaded into TransBASE. See Section D below for details regarding TransBASE.

C. UPDATE PROCESS After review by SFPD and SFDPH staff, the data is made publicly available approximately a month after the end of the previous quarter (May for Q1, August for Q2, November for Q3, and February for Q4).

D. HOW TO USE THIS DATASET This data is being provided as public information as defined under San Francisco and California public records laws. SFDPH, SFMTA, and SFPD cannot limit or restrict the use of this data or its interpretation by other parties in any way. Where the data is communicated, distributed, reproduced, mapped, or used in any other way, the user should acknowledge TransBASE.sfgov.org as the source of the data, provide a reference to the original data source where also applicable, include the date the data was pulled, and note any caveats specified in the associated metadata documentation provided. However, users should not attribute their analysis or interpretation of this data to the City of San Francisco. While the data has been collected and/or produced for the use of the City of San Francisco, it cannot guarantee its accuracy or completeness. Accordingly, the City of San Francisco, including SFDPH, SFMTA, and SFPD make no representation as to the accuracy of the information or its suitability for any purpose and disclaim any liability for omissions or errors that may be contained therein. As all data is associated with methodological assumptions and limitations, the City recommends that users review methodological documentation associated with the data prior to its analysis, interpretation, or communication.

This dataset can also be queried on the TransBASE Dashboard. TransBASE is a geospatially enabled database maintained by SFDPH that currently includes over 200 spatially referenced variables from multiple agencies and across a range of geographic scales, including infrastructure, transportation, zoning, sociodemographic, and collision data, all linked to an intersection or street segment. TransBASE facilitates a data-driven approach to understanding and addressing transportation-related health issues, informed by a large and growing evidence base regarding the importance of transportation system design and land use decisions for health. TransBASE’s purpose is to inform public and private efforts to improve transportation system safety, sustainability, community health and equity in San Francisco.

E. RELATED DATASETS Traffic Crashes Resulting in Injury: Parties Involved Traffic Crashes Resulting in Injury: Victims Involved TransBASE Dashboard iSWITRS TIMS

The Crash Data On California State Highways Report is produced annually by the California Department of Transportation (Caltrans) to provide high level summaries of road miles, travel, crashes and crash rates on the California State Highway System.

This table lists statewide vehicle travel expressed in Million Vehicle Miles (MVM), road miles, and one and three year crash rates and fatality rates based on lane types and population codes.

While crash rates for total crash and fatal + injury crashes are calculated per MVM, fatality rates are expressed per 100 MVM.

The project needs data for macroscopic statistical modeling, which are OTS rankings and historical crash data. OTS crash ranking data California Office of Traffic Safety (OTS) provides a crash ranking dataset that was developed so that individual cities could compare their city’s traffic safety statistics to those of other cities with similar-sized populations. The OTS crash rankings are based on the Empirical Bayesian Ranking Method. It adds weights to different crash statistical categories including observed crash counts, population and daily vehicle miles traveled (DVMT). In addition, the OTS crash rankings include different types of crashes with larger percentages of total victims and areas of focus for the OTS grant program. In conjunction with the research context, two types of crash rankings are focused on, namely pedestrians and bicyclists. SWITRS crash data The Transportation Injury Mapping System (TIMS) to provide the project quick, easy, and free access to California crash d..., The Safe Transportation Research and Education Center (SafeTREC) at the University of California, Berkeley, develops the Transportation Injury Mapping System (TIMS) to provide a quick, easy and free access to California crash data provided by the Statewide Integrated Traffic Records System (SWITRS). We collect five-year-long crash data, which are from 01/01/2014 to 12/31/2018. The crash data includes bicyclist and pedestrian collisions with vehicles resulting in injuries across four types of crash severity: fatal, severe injury, visible injury, and complaint of injury. The data consists of three tables including the collision dataset, the involved parties dataset, and the victims dataset. In particular, we use the collision and parties datasets that contain enough information for modeling. The rows in the crash data are built based on each case of a crash and includes information such as weather, road surface, road condition, control device, and lighting. The parties dataset includes in..., The data files can be viewed by Excel.Â

​Traffic collision data includes time, location, severity, cause, type, party information​

Vital Signs: Injuries From Crashes – By Case (2022) DRAFT

VITAL SIGNS INDICATOR Injuries From Crashes (EN7-9)

FULL MEASURE NAME Serious injuries from crashes (traffic collisions)

LAST UPDATED May 2022

DESCRIPTION Injuries from crashes refers to serious but not fatal injuries sustained in a collision. The California Highway Patrol classifies a serious injury as any combination of the following: broken bones; dislocated or distorted limbs; severe lacerations; skull, spinal, chest or abdominal injuries that go beyond visible injuries; unconsciousness at or when taken from the scene; or severe burns. This injuries dataset includes serious injury counts for the region and counties, as well as individual collision data.

DATA SOURCE California Highway Patrol: Statewide Integrated Traffic Records System

CONTACT INFORMATION vitalsigns.info@bayareametro.gov

METHODOLOGY NOTES (across all datasets for this indicator) The data is reported by the California Highway Patrol (CHP) to the Statewide Integrated Traffic Records System (SWITRS), which was accessed via SafeTREC’s Transportation Injury Mapping System (TIMS). The data was tabulated using provided categories specifying injury level, individuals involved, causes of collision, and location/jurisdiction of collision (for more: http://tims.berkeley.edu/help/files/switrs_codebook.doc).

For more regarding reporting procedures and injury classification, see the California Highway Patrol Manual (https://one.nhtsa.gov/nhtsa/stateCatalog/states/ca/docs/CA_CHP555_Manual_2_2003_ch1-13.pdf).

Context

I curate a dataset of California traffic collisions, which you can find here: Kaggle: California Traffic Collision Data from SWITRS.

However, I made certain decisions about how to clean and process the data, which others might disagree with. This dataset contains the raw data, allowing you to make your own cleaning decisions!

Content

This data comes from the California Highway Patrol and covers collisions from January 1st, 2001 until mid-December, 2020. I have requested full database dumps from the CHP four times, once in 2016, 2017, 2018, 2020, 2021. These are the raw files as provided by the CHP with no post-processing

Acknowledgements

This data would not exist without the California Highway Patrol compiling it, thanks!

The Crash Data On California State Highways Report is produced annually by the California Department of Transportation (Caltrans) to provide high level summaries of road miles, travel, crashes and crash rates on the California State Highway System. This table lists statewide vehicle travel expressed in Million Vehicle Miles (MVM), road miles, and one and three year crash rates and fatality rates based on lane types and population codes. While crash rates for total crash and fatal + injury crashes are calculated per MVM, fatality rates are expressed per 100 MVM.