The graph illustrates the number of car accidents in the United States from 2013 to 2023. The x-axis represents the years, abbreviated from '13 to '23, while the y-axis displays the annual number of crashes. Over this 11-year period, the number of accidents ranges from a low of 5,251,006 in 2020 to a high of 6,821,129 in 2016. Other notable figures include 6,756,084 crashes in 2019 and 5,686,891 in 2013. The data exhibits significant fluctuations, with a peak in 2016, a sharp decline in 2020, and subsequent variations in the following years. This information is presented in a line graph format, effectively highlighting the yearly changes and overall variability in car accidents across the United States.

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.

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.

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.

The graph displays the number of car accident fatalities by type in the United States from 2010 to 2022. The x-axis represents the years, labeled from '10 to '22, while the y-axis indicates the number of fatalities. Each year includes data points for four categories: Passenger Vehicle, Pedestrian, Two-Wheeled Vehicle, and Large Truck fatalities. Passenger Vehicle fatalities range from a low of 21,076 in 2014 to a high of 26,650 in 2021. Pedestrian fatalities increase from 4,300 in 2010 to a peak of 7,467 in 2022. Two-Wheeled Vehicle fatalities vary between 5,022 in 2014 and 7,287 in 2022. Large Truck fatalities are the lowest among the categories, ranging from 346 in 2010 to 533 in 2022. The data reveals an overall upward trend in fatalities across all categories, particularly notable in the years 2021 and 2022.

The Measurement template document is available at the archived version of this page on the UK Government Web Archive.

DfT Business plan

Geographical coverage: Great Britain

Information broken down by: Accident site. Data are available by geographical area, age, gender and type of road user.

Latest data

In 2013:

• 1,713 people were killed in reported road traffic accidents in Great Britain, 2% (41) fewer than in 2012. This is the lowest number of fatalities since national records began in 1926. The total number of people killed in 2013 was 39% lower than the 2005-09 baseline average
• the number of fatalities decreased for pedestrians, pedal cyclists and car occupants, by 5%, 8% and 2% respectively, but increased for motorcycle users by 1%. Over the same period motor vehicle traffic remained broadly stable, with a small increase of 0.4% between 2012 and 2013
• with the exception of 2011, road deaths have fallen every year since 2004. Adverse weather (heavy snow falls) experienced in the first and last quarters of 2010 but not in 2011, is likely to be the main factor behind the increase in fatalities recorded in 2011

Year	Road accident fatalities	% change from previous year
2000	3,409	-0.4
2001	3,450	1.2
2002	3,431	-0.6
2003	3,508	2.2
2004	3,221	-8.2
2005	3,201	-0.6
2006	3,175	-0.9
2007	2,946	-7.1
2008	2,538	-13.8
2009	2,222	-12.5
2010	1,850	-16.7
2011	1,901	2.8
2012	1,754	-7.7
2013	1,713	-2.3

The complete set of data is available for download.

Background information

The indicator can be broken down by any geographical area (eg country, region, local authority) since a grid reference is collected for each accident. Information is also available by age, gender, type of road user and road type. Numbers will be relatively small for more detailed breakdowns of the total and may therefore fluctuate from year to year. This needs to be taken into account when assessing trends.

• publishing schedule: annual
• last updated: September 2014
• next update: July 2015

Other related data and information

More detailed analysis and time series can be found in Reported road casualties Great Britain: annual report.

Record level data on accidents and casualties can be found in http://data.gov.uk/dataset/road-accidents-safety-data/">Record level data

Further information

• Business Plan 2012 to 2015
• Input and impact indicators
• Analyst contact: Anil Bhagat, roadacc.stats@dft.gsi.gov.uk

Some 44,800 road traffic fatalities occurred in the United States in 2023, and projections estimate 2024 fatalities could drop to 44,700. Motor vehicle crashes and drug overdoses are the leading causes of death among those under the age of 55 in the United States.

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.

In 2022, over 4.5 million light trucks were involved in U.S. traffic crashes, accounting for 43.2 percent of the overall total. The second highest were passenger cars, being involved in four million car crashes and accounting for 38.1 percent of the total. Motor vehicle crashes are among the leading causes of death among those under the age of 55 in the United States.

The State of Michigan’s criteria for a crash is a motor vehicle that was in transport and on the roadway, that resulted in death, injury, or property damage of $1,000 or more. Traffic crashes in this dataset are derived from SEMCOG’s Open Data Portal. Each row in the dataset represents a traffic crash that includes data about when and where the crash occurred, road conditions, number of individuals involved in the crash, and various factors that apply to the crash (Train, Bus, Deer, etc.). Also included is the number of injuries and fatalities that are associated with the crash.

Panama No. of Traffic Accidents data was reported at 4,303.000 Number in Dec 2024. This records an increase from the previous number of 4,061.000 Number for Nov 2024. Panama No. of Traffic Accidents data is updated monthly, averaging 3,811.000 Number from Jan 2019 (Median) to Dec 2024, with 72 observations. The data reached an all-time high of 4,474.000 Number in Mar 2019 and a record low of 1,067.000 Number in Apr 2020. Panama No. of Traffic Accidents data remains active status in CEIC and is reported by National Institute of Statistics and Census. The data is categorized under Global Database’s Panama – Table PA.TA008: Number of Traffic Accidents and Deaths: by Province. [COVID-19-IMPACT]

Traffic Accident Prediction Dataset

This dataset contains data designed to predict the occurrence and severity of traffic accidents based on various factors affecting road conditions, driver behavior, and traffic situations.

Features:

Weather: The impact of weather conditions on the likelihood of accidents.

• Clear: No adverse weather conditions.
• Rainy: Rainy conditions increase the chance of accidents.
• Foggy: Foggy conditions reduce visibility, increasing accident chances.
• Snowy: Snow can cause slippery roads and higher accident probability.
• Stormy: Stormy weather can create hazardous driving conditions.

Road_Type: The type of road, influencing the probability of accidents.

• Highway: High-speed roads with higher chances of severe accidents.
• City Road: Roads within city limits, typically with more traffic and lower speeds.
• Rural Road: Roads outside urban areas, often with fewer vehicles and lower speeds.
• Mountain Road: Roads with curves and elevation changes, increasing accident risk.

Time_of_Day: The time of day when the accident occurs.

• Morning: The period between sunrise and noon.
• Afternoon: The period between noon and evening.
• Evening: The period just before sunset.
• Night: The nighttime, often associated with reduced visibility and higher risk.

Traffic_Density: The level of traffic on the road.

• 0: Low density (few vehicles).
• 1: Moderate density.
• 2: High density (many vehicles).

Speed_Limit: The maximum allowed speed on the road.

Number_of_Vehicles: The number of vehicles involved in the accident, ranging from 1 to 5.

Driver_Alcohol: Whether the driver consumed alcohol.

• 0: No alcohol consumption.
• 1: Alcohol consumption (which increases the likelihood of an accident).

Accident_Severity: The severity of the accident.

• Low: Minor accident.
• Moderate: Moderate accident with some damage or injuries.
• High: Severe accident with significant damage or injuries.

Road_Condition: The condition of the road surface.

• Dry: Dry roads with minimal risk.
• Wet: Wet roads due to rain, increasing the risk of accidents.
• Icy: Ice on the road, significantly increasing the risk of accidents.
• Under Construction: Roads under construction, which may have obstacles or poor road quality.

Vehicle_Type: The type of vehicle involved in the accident.

• Car: A regular passenger car.
• Truck: A large vehicle used for transporting goods.
• Motorcycle: A two-wheeled motor vehicle.
• Bus: A large vehicle used for public transportation.

Driver_Age: The age of the driver. Values range from 18 to 70 years old.

Driver_Experience: The years of experience the driver has. Values range from 0 to 50 years of experience.

Road_Light_Condition: The lighting conditions on the road.

• Daylight: Daytime, when visibility is typically good.
• Artificial Light: Road is illuminated with streetlights.
• No Light: Road is not illuminated, typically during the night in poorly lit areas.

Notes: This dataset can be used to train classification models to predict whether an accident will occur based on these factors. You can apply machine learning algorithms such as logistic regression, random forests, gradient boosting, or neural networks to build a predictive model.

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.

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.

Explore the Saudi Arabia Traffic Accidents and Casualties dataset to find information on the number of casualties (injured and dead) and accidents in the country for the year 2008.

No. of Casualties - Injured, No. of Accidents, No. of Casualties - Dead, Traffic, Accidents

Saudi ArabiaFollow data.kapsarc.org for timely data to advance energy economics research..

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.

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.

Motor Vehicle Collisions - Crashes Metadata Updated: August 19, 2023

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.

License: No license information was provided.

In 2023, the number of deaths caused by traffic accidents amounted to approximately 11,628 cases in Vietnam. This indicated a decrease from the previous year. From 2013 to 2021, the number of traffic deaths has gradually declined, then increased dramatically in 2022, with the number of deaths due to crashes double than that in 2021.