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.

The Motor Vehicle Collisions vehicle table contains details on each vehicle involved in the crash. Each row represents a motor vehicle 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.

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.

📄 Dataset Overview

This dataset contains detailed records of road traffic accidents across multiple districts in the UK, including areas such as Southend-on-Sea, Uttlesford, Chelmsford, Brentwood, Epping Forest, and more.

It includes approximately 300,000 rows of incidents, each capturing environmental, vehicular, and road-related conditions at the time of the accident.

This data is ideal for projects involving accident severity analysis, geospatial visualization, urban planning, and road safety research.

📊 Use Cases

• Traffic accident severity prediction
• District-level accident comparison
• Geospatial accident heatmaps
• Road condition vs. accident analysis
• Time-of-day or weather-related traffic impact studies

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.

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.

Road Safety Statistics releases [missing hyperlink]

Data download tool [missing hyperlink] for bespoke breakdowns of our data.

These files provide detailed road safety data about the circumstances of personal injury road accidents in GB from 1979, the types of vehicles involved and the consequential casualties. The statistics relate only to personal injury accidents on public roads that are reported to the police, and subsequently recorded, using the STATS19 accident reporting form.

There has been an increasing demand for more up to date information on reported road accidents to be made available to the public, stakeholders and researchers. As a result, the Department for Transport made a dataset covering accidents for the first and second quarters of 2018 in Great Britain available for the first time on data.gov.uk. The data released was an un-validated subset and has been superseded by the full accident dataset for 2018, released after validation for the full year.

All the data variables are coded rather than containing textual strings. The lookup tables are available in the "Additional resources" section towards the bottom of the table.

Please note that the 2015 data were revised on the 29th September 2016. Accident, Vehicle and Casualty data for 2005 - 2009 are available in the time series files under 2014. Data for 1979 - 2004 are available as a single download under 2004 below.

Also includes: Results of breath-test screening data from recently introduced digital breath testing devices, as provided by Police Authorities in England and Wales Results of blood alcohol levels (milligrams / 100 millilitres of blood) provided by matching coroners’ data (provided by Coroners in England and Wales and by Procurators Fiscal in Scotland) with fatality data from the STATS19 police data of road accidents in Great Britain. For cases when the Blood Alcohol Levels for a fatality are "unknown" are a consequence of an unsuccessful match between the two data sets.

For each personal injury accident (i.e. an accident on a road open to public traffic, involving at least one vehicle and involving at least one victim requiring treatment), information describing the accident is seized by the police unit (police, gendarmerie, etc.) which intervened at the scene of the accident. These seizures are collected in a sheet entitled ‘Injury Analysis Bulletin’. All these forms constitute the national register of road traffic injuries, known as the ‘BAAC file’, administered by the National Interministerial Observatory for Road Safety (ONISR).

The databases, extracted from the BAAC file, list all road traffic injuries occurring during a specific year in mainland France, in the overseas departments (Guadeloupe, French Guiana, Martinique, Réunion and Mayotte since 2012) and in the other overseas territories (Saint-Pierre-et-Miquelon, Saint-Barthélemy, Saint-Martin, Wallis and Futuna, French Polynesia and New Caledonia; available only from 2019 in open data) with a simplified description. This includes information on the location of the accident, as provided, as well as information on the characteristics of the accident and its location, the vehicles involved and their victims.

Compared to the aggregated databases 2005-2010 and 2006-2011 currently available on the website www.data.gouv.fr, the databases from 2005 to 2023 are now annual and composed of 4 files (Characteristics – Locations – Vehicles – Users) in csv format.

However, those databases conceal certain specific data relating to users and vehicles and their conduct in so far as disclosure of that data would undermine the protection of the privacy of easily identifiable natural persons or reveal the conduct of such persons, whereas disclosure of that conduct could be detrimental to them (CADA opinion – 2 January 2012).

Warning: Data on the classification of injured persons hospitalised since 2018 cannot be compared to previous years following changes in the seizure process of the police. The indicator ‘injured hospitalised’ has no longer been labelled by the public statistics authority since 2019.

The validity of the statistical operations that can be made from this database depends on the verification methods specific to the field of application of road safety and in particular on a precise knowledge of the definitions relating to each variable used. For any operation, it is important to take note in particular of the structure of the attached BAAC sheet and the guide to using the codification of the road traffic accident analysis bulletin.

It should be noted that a number of indicators from this database are labelled by the public statistics authority (Order of 27 November 2019). The list is available at: https://www.onisr.securite-routiere.gouv.fr/statistical tools/labelled indicators

The traffic accident and casualties statistics tabulated in this dataset are compiled and retrieved from the Transport Information System developed and enhanced by the Road Safety and Standards Division. The accidents included are those personal injury accidents reported to the Police and do not include damage-only accidents.

Crash data shows information about each traffic crash on city streets within the City of Chicago limits and under the jurisdiction of Chicago Police Department (CPD). Data are shown as is from the electronic crash reporting system (E-Crash) at CPD, excluding any personally identifiable information. Records are added to the data portal when a crash report is finalized or when amendments are made to an existing report in E-Crash. Data from E-Crash are available for some police districts in 2015, but citywide data are not available until September 2017. About half of all crash reports, mostly minor crashes, are self-reported at the police district by the driver(s) involved and the other half are recorded at the scene by the police officer responding to the crash. Many of the crash parameters, including street condition data, weather condition, and posted speed limits, are recorded by the reporting officer based on best available information at the time, but many of these may disagree with posted information or other assessments on road conditions. If any new or updated information on a crash is received, the reporting officer may amend the crash report at a later time. A traffic crash within the city limits for which CPD is not the responding police agency, typically crashes on interstate highways, freeway ramps, and on local roads along the City boundary, are excluded from this dataset.

All crashes are recorded as per the format specified in the Traffic Crash Report, SR1050, of the Illinois Department of Transportation. The crash data published on the Chicago data portal mostly follows the data elements in SR1050 form. The current version of the SR1050 instructions manual with detailed information on each data elements is available here.

As per Illinois statute, only crashes with a property damage value of $1,500 or more or involving bodily injury to any person(s) and that happen on a public roadway and that involve at least one moving vehicle, except bike dooring, are considered reportable crashes. However, CPD records every reported traffic crash event, regardless of the statute of limitations, and hence any formal Chicago crash dataset released by Illinois Department of Transportation may not include all the crashes listed here.

Change 11/21/2023: We have removed the RD_NO (Chicago Police Department report number) for privacy reasons.

the Ministry of Road Transport and Highways of the Government of India releases annual reports on road accidents and casualties in the country. Additionally, many state governments also release data on road accidents within their jurisdiction. There are many potential causes of road accidents, including: Distracted driving (e.g. using a cell phone, eating, or applying makeup while driving) Impaired driving (e.g. driving under the influence of alcohol or drugs) Reckless or aggressive driving (e.g. speeding, tailgating, or running red lights) Fatigue or drowsy driving Poor road conditions (e.g. potholes, debris, or lack of proper signage) Vehicle defects or malfunctions Poor weather conditions (e.g. rain, snow, or fog) Inadequate infrastructure (e.g. lack of proper lighting, median barriers, or guardrails) Pedestrian or bicycle errors Wildlife crossing the road. There are several datasets available on road accidents, depending on the country and region. Here are a few examples:

In the United States, the National Highway Traffic Safety Administration (NHTSA) provides data on vehicle crashes, including details such as the location, cause, and number of injuries and fatalities. The United Kingdom's Department for Transport provides data on reported road accidents, including information on the type of vehicle, number of casualties, and severity of injuries. The World Health Organization (WHO) also has a Global Status Report on Road Safety, which provides data on road accidents and fatalities for countries around the world. In India, the Ministry of Road Transport and Highways (MoRTH) provides annual data on road accidents and fatalities. The Global Road Safety Partnership (GRSP) also has a wealth of data on road accidents and fatalities, particularly in low- and middle-income countries. It is important to note that these datasets may have different data collection methodologies, and may not include all road accidents that have occurred.

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.

The number of road-traffic related injuries in the United States has decreased by roughly 17 percent between 2019 and 2020, whereas fatalities increased by almost 8 percent. Between 2010 and 2020, road traffic injuries in the United States grew by nearly 34,000 incidents to some 2.28 million road traffic related injuries in 2020. Over the same period, fatalities also increased by about 5,800. This follows two decades of a general decrease in the amount of traffic-related injuries.

Why are traffic injuries increasing? In the United States, male drivers are behind the wheel in the majority of fatal crashes. Though speeding and driving under the influence of alcohol are often to blame, neither have led to a rise in traffic fatalities in the U.S.: instead, cellphones are primarily the cause. Smartphone ownership has become almost omnipresent in the U.S. since 2010, and drivers are likely to be distracted by texting and using social media. Young drivers are the ones accounting for the highest share of cellphone use fatalities.

Changes in mobility Another reason why fatal accidents are rising in number is that non-occupants’ exposure to risk is also increasing. As residents become more encouraged to walk or cycle in cities, the extra time amongst traffic has led to higher rates of fatalities and injuries amongst cyclists and pedestrians. Lastly, poor infrastructure and lack of awareness by motorists is prevalent in large parts of the United States.

This dataset contains information about vehicles (or units as they are identified in crash reports) involved in a traffic crash. This dataset should be used in conjunction with the traffic Crash and People dataset available in the portal. “Vehicle” information includes motor vehicle and non-motor vehicle modes of transportation, such as bicycles and pedestrians. Each mode of transportation involved in a crash is a “unit” and get one entry here. Each vehicle, each pedestrian, each motorcyclist, and each bicyclist is considered an independent unit that can have a trajectory separate from the other units. However, people inside a vehicle including the driver do not have a trajectory separate from the vehicle in which they are travelling and hence only the vehicle they are travelling in get any entry here. This type of identification of “units” is needed to determine how each movement affected the crash. Data for occupants who do not make up an independent unit, typically drivers and passengers, are available in the People table. Many of the fields are coded to denote the type and location of damage on the vehicle. Vehicle information can be linked back to Crash data using the “CRASH_RECORD_ID” field. Since this dataset is a combination of vehicles, pedestrians, and pedal cyclists not all columns are applicable to each record. Look at the Unit Type field to determine what additional data may be available for that record.

The Chicago Police Department reports crashes on IL Traffic Crash Reporting form SR1050. The crash data published on the Chicago data portal mostly follows the data elements in SR1050 form. The current version of the SR1050 instructions manual with detailed information on each data elements is available here.

Change 11/21/2023: We have removed the RD_NO (Chicago Police Department report number) for privacy reasons.

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.

The statistics on road traffic accidents with personal injury (persons injured or killed) records all accidents occurring on roads with public traffic in Austria. The accident data is recorded electronically by the police authorities and an extract relevant for the statistic is transmitted daily to Statistics Austria by the Federal Ministry of the Interior. The objective is to continuously monitor accidents on Austrian roads in order to provide reliable data for research and accident prevention.

The results are published quarterly (preliminary data) and annually (final data).

In 2022, the number of fatalities in road traffic accidents in Indonesia was approximately ***** thousand persons, indicating an increase compared to the previous year. During the time under consideration, the highest number of fatalities was reached in 2017, with over ** thousand persons dying in traffic accidents.

Crashes data includes crash event level details such as location - the Lat/Long of the nearest intersection, A and B street names, with distance and direction of the crash from nearest intersection, etc... It also includes crash level details like weather and roadway conditions, and time of day. Also included are the involved party (vehicle involved with), primary collision factor and severity of injury in terms of fatalities, and severe, moderate and minor injuries per crash.

The vehicles data includes the vehicle level details of the crash such as vehicle types, driver's (vehicle, party) age and sex, driver conditions and violations proceeding the crash, etc...

There is a one to many relationship that needs to be built that relates the crash to the vehicles involved. (i.e. there are an average of 2.07 vehicles/parties involved per crash)

Match the Crash name in vehicle data to the Name in the Crash data to relate the two sets of data.