Road Safety Statistics releases [missing hyperlink]

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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 The data released was an un-validated subset and has been superseded by the full accident dataset for 2018, released after validation for the full year.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.

This data has moved and is now published on the Road Safety Data page. Road casualty publications and data tools can be found on the statistical collection page.

In 2023, Poland observed an overall improvement in the accidents, deaths, and casualties in road safety compared to the previous year. However, collisions had increased by around *** percent.

Detailed data about personal injury accidents on public roads in York that are reported to the police and subsequently recorded, using the STATS19 accident reporting form, from 2005 onwards. The Accident_Index attribute gives a unique index for each accident and links to Vehicle and Casualty data. Casualties are linked to vehicles by the “VEHREF” attribute. The Longitude and Latitude data is based on WGS 1984. The key for all of the coded values of the data is provided within the "Road Safety Key" resource. For more information such as casualties, details on vehicles or breath-test or blood alcohol content, please visit Road Safety data for GB Data extracted from publication by Department for Transport, licensed under Open Government Licence

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.

Overview:

Information on location and characteristics of crashes in Queensland for all reported Road Traffic Crashes occurred from 1 January 2001 to 31 Dec 2024.

Fatal, Hospitalisation, Medical treatment and Minor injury:

This dataset contains information on crashes reported to the police which resulted from the movement of at least 1 road vehicle on a road or road related area. Crashes listed in this resource have occurred on a public road and meet one of the following criteria:

• a person is killed or injured, or
• at least 1 vehicle was towed away, or
• the value of the property damage meets the appropriate criteria listed below.

Property damage:

1. $2500 or more damage to property other than vehicles (after 1 December 1999)
2. $2500 or more damage to vehicle and/or other property (after 1 December 1991 and before 1 December 1999)
3. value of property damage is greater than $1000 (before December 1991).

Please note:

• This data has been extracted from the Queensland Road Crash Database.
• Information held in the Road Crash Database on events occurring within the last 12 months is considered preliminary as investigations into crashes can take up to 1 year to finalise.
• Property damage only crashes ceased to be reported/recorded by Queensland Police Service after 31 December 2010.
• These crash location coordinates reference the current Australian geodetic datum is GDA2020 (previously it was GDA94).

This data has been consolidated from Victoria Police reports and Hospital injury information, then validated and enriched to provide a comprehensive and detailed view of road crashes and injuries across Victoria. The data provides users with information about Victorian fatal and injury road crash data based on time, location, conditions, crash type, road user type, and other relevant attributes. Data Currency This information will be updated on a monthly basis but with a 7 month lag in order to provide a comprehensive view of incidents during that time period. Data Structure The CSV data is split across multiple tables with attributes to facilitate joins between the information. This has been captured as part of the supporting documentation in the metadata. The tables and attributes include: - accident (basic accident details, time, severity, location) - person (person based details, age, gender etc) - vehicle (vehicle based data, vehicle type, make etc) - accident_event (sequence of events e.g. left road, rollover, caught fire) - road_surface_cond (whether road was wet, dry, icy etc) - atmospheric_cond (rain, winds etc) - sub_dca (detailed codes describing accident) - accident_node (master location table - NB subset of accident table) - Node Table with Lat/Long references There is also a lite Victoria Road Crash .csv dataset is a single flat file containing a subset of the attributes from the other CSV files. It provides a single set of attributes for each road crash that has occurred within Victoria. Supporting documentation in the metadata will provide further details of the attributes. This used to be a .GeoJSON file however due to feedback from a significant number of Open Data users, this was changed to a .csv file. Disclaimer No claim is made as to the accuracy or currency of the content on this site at any time, there will be instances where attributes relating to a crash are amended over time. This data is provided on the basis that users undertake responsibility for assessing the relevance and accuracy of its content. Data relating to fatal crashes that have occurred recently are provisional and are subject to change or removal. They will have a high level of incompleteness and details will be amended before they are finalised. The Victorian Government and Department of Transport and Planning accept no liability to any person or group for the data or advice (or the use of such data or advice) which is provided or incorporated into it by reference.

This dataset captures detailed statistics about road accidents in Glasgow from 2014 to 2021. The data relate to the location, built environment and level of injury for each accident, along with numbers of casualties and vehicles involved. 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. Data are released via the UK Department for Transport and can be found at the UK Government Data portal data.gov.uk.

In 2022, the total number of road traffic accidents in Indonesia was roughly ****** thousand cases, indicating a significant increase compared to the previous year. Indonesia has a high traffic fatality number, approximately ***** thousand fatalities happened on the streets and roadways of Indonesia in that year.

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.

🌍 Dataset Description

This dataset contains detailed information on traffic accidents across various regions and time periods. It includes various metrics such as accident date, weather conditions, lighting conditions, crash types, injuries, and vehicle involvement. The data spans multiple locations and accident types, offering a comprehensive view of traffic incidents and their causes.

📊 Columns:

• crash_date: The date the accident occurred.
• traffic_control_device: The type of traffic control device involved (e.g., traffic light, sign).
• weather_condition: The weather conditions at the time of the accident.
• lighting_condition: The lighting conditions at the time of the accident.
• first_crash_type: The initial type of the crash (e.g., head-on, rear-end).
• trafficway_type: The type of roadway involved in the accident (e.g., highway, local road).
• alignment: The alignment of the road where the accident occurred (e.g., straight, curved).
• roadway_surface_cond: The condition of the roadway surface (e.g., dry, wet, icy).
• road_defect: Any defects present on the road surface.
• crash_type: The overall type of the crash.
• intersection_related_i: Whether the accident was related to an intersection.
• damage: The extent of the damage caused by the accident.
• prim_contributory_cause: The primary cause contributing to the crash.
• num_units: The number of vehicles involved in the accident.
• most_severe_injury: The most severe injury sustained in the crash.
• injuries_total: The total number of injuries reported.
• injuries_fatal: The number of fatal injuries resulting from the accident.
• injuries_incapacitating: The number of incapacitating injuries.
• injuries_non_incapacitating: The number of non-incapacitating injuries.
• injuries_reported_not_evident: The number of injuries reported but not visibly evident.
• injuries_no_indication: The number of cases with no indication of injury.
• crash_hour: The hour the accident occurred.
• crash_day_of_week: The day of the week the accident occurred.
• crash_month: The month the accident occurred.

🔍 Use Cases:

• Accident Analysis: Analyze accident trends, types, and the severity of injuries across different locations, time periods, and conditions.
• Traffic Safety: Understand the factors contributing to accidents (e.g., weather, lighting, road conditions) to inform traffic safety measures.
• Predictive Modeling: Use the dataset to forecast accident hotspots, potential injuries, and the impact of various factors on crash severity.

Nearly ***** road fatalities were recorded on French roads in 2023, down from around ***** deaths in 2022. Road fatalities had fluctuated in France, with the COVID-19 pandemic and related lockdowns helping to bring down the fatality rate in 2020. Alcohol- and speed-related offenses in France Yet, according to a survey conducted by the French National Inter-Ministerial Road Safety Observatory in 2014, ** percent of the respondents believed that not enough was done to prevent and control drink driving. Further, ** percent of those surveyed also believed that police enforcement against drug consumption on the road was lacking. Nevertheless, the same institution reported that, in 2015, ten percent of all the road offenses recorded more than 100 times were related to alcohol. Offenses related to speed control accounted for almost ** percent of all the road offenses. The European perception of road fatalities On the other side of the Rhine, in Germany, where the consumption of alcohol seems to be more widespread – with around 137 liters of alcoholic beverage per capita in 2014 - the authorities seem to have managed to reduce the number of road traffic fatalities more efficiently. It went from ***** deaths reported in 2006 to ***** deaths in 2022. From a European perspective, ** percent of Europeans believed that driving under alcohol or drugs influence was the main general cause of fatal accidents on the road in their respective countries.

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.

This is the number of people of all ages killed or seriously injured (KSI) in road traffic accidents, in an area, adjusted. This indicator includes only casualties who are fatally or seriously injured and these categories are defined as follows:

Fatal casualties are those who sustained injuries which caused death less than 30 days after the accident; confirmed suicides are excluded.

Seriously injured casualties are those who sustained an injury for which they are detained in hospital as an in-patient, or any of the following injuries, whether or not they are admitted to hospital: fractures, concussion, internal injuries, crushings, burns (excluding friction burns), severe cuts and lacerations, severe general shock requiring medical treatment and injuries causing death 30 or more days after the accident.

An injured casualty is recorded as seriously or slightly injured by the police on the basis of information available within a short time of the collision. This generally will not reflect the results of a medical examination, but may be influenced according to whether the casualty is hospitalised or not. Hospitalisation procedures will vary regionally.

Slight injuries are excluded from the total, such as a sprain (including neck whiplash injury), bruise or cut which are not judged to be severe, or slight shock requiring roadside attention.

Police forces use one of two systems for recording reported road traffic collisions; the CRaSH (Collision Recording and Sharing) or COPA (Case Overview Preparation Application). Estimates are calculated from figures which are as reported by police. Since 2016, changes in severity reporting systems for a large number of police forces mean that serious injury figures, and to a lesser extent slight injuries, are not comparable with earlier years. As a result, both adjusted and unadjusted killed or seriously injured statistics are available. Further information about the reporting systems can be found here.

Areas with low resident populations but have high inflows of people or traffic may have artificially high rates because the at-risk resident population is not an accurate measure of exposure to transport. This is likely to affect the results for employment centres e.g. City of London and sparsely populated rural areas which have high numbers of visitors or through traffic. Counts for Heathrow Airport are included in the London Region and England totals only.

From the publication of the 2023 statistics onwards, casualty rates shown in table RAS0403 to include rates based on motor vehicle traffic only. This is because the department does not consider pedal cycle traffic to be robust at the local authority level.

Data is Powered by LG Inform Plus and automatically checked for new data on the 3rd of each month.

This dataset can be used for the following tasks : 1) Understanding Accident Severity for Effective Road Management 2) Exploring Geographic and Temporal Aspects of Road Incidents 3) A Comprehensive Dataset for Traffic Incident Research 4) Impacts of Weather and Road Conditions on Accident Rates 5) Identifying Hotspots and Risk Factors in Road Safety 6) Data-driven Approaches to Reduce Road Accidents 7) Traffic Collision Analysis for Urban Planning Strategies 8) Patterns of Driver Behavior and Their Influence on Accidents

In 2024, Japan recorded around 2.66 thousand fatalities in road traffic accidents, down from about 4.12 thousand in 2015. Consequently, the number of fatalities on Japanese streets continued their decline.