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 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 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.

The graph displays speeding-related accident statistics in Missouri from 2013 to 2023. The x-axis represents the years, ranging from '13 to '23, while the y-axis indicates the number of crashes where speeding was a contributing factor. Over this 11-year period, the number of speeding-related crashes ranges from a high of 16,238 in 2019 to a low of 10,273 in 2023. A notable decline is observed after 2019, with the figures steadily dropping through 2023. The data is presented in a line graph format to illustrate the yearly fluctuations and trends in speeding-related accidents.

Highways Statistics: Traffic Accidents: Wounded Victims: Paraná data was reported at 5,601.000 Unit in 2017. This records a decrease from the previous number of 5,764.000 Unit for 2016. Highways Statistics: Traffic Accidents: Wounded Victims: Paraná data is updated yearly, averaging 6,512.500 Unit from Dec 1998 (Median) to 2017, with 20 observations. The data reached an all-time high of 7,098.000 Unit in 2012 and a record low of 2,884.000 Unit in 1998. Highways Statistics: Traffic Accidents: Wounded Victims: Paraná data remains active status in CEIC and is reported by Brazilian Association of Highway Concessionaires. The data is categorized under Brazil Premium Database’s Automobile Sector – Table BR.RAW008: Highways Statistics: Traffic Accidents. The Brazilian Association of Highway Concessionaires-ABCR represents the highway concession sector.

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 data contains information about people involved in a crash and if any injuries were sustained. This dataset should be used in combination with the traffic Crash and Vehicle dataset. Each record corresponds to an occupant in a vehicle listed in the Crash dataset. Some people involved in a crash may not have been an occupant in a motor vehicle, but may have been a pedestrian, bicyclist, or using another non-motor vehicle mode of transportation. Injuries reported are reported by the responding police officer. Fatalities that occur after the initial reports are typically updated in these records up to 30 days after the date of the crash. Person data can be linked with the Crash and Vehicle dataset using the “CRASH_RECORD_ID” field. A vehicle can have multiple occupants and hence have a one to many relationship between Vehicle and Person dataset. However, a pedestrian is a “unit” by itself and have a one to one relationship between the Vehicle and Person table. 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.

In 2022, the number of fatalities in road traffic accidents in Indonesia was approximately 27.53 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 30 thousand persons dying in traffic accidents.

Highways Statistics: Traffic Accidents: Vehicles Involved: Federal data was reported at 119,277.000 Unit in 2017. This records an increase from the previous number of 114,897.000 Unit for 2016. Highways Statistics: Traffic Accidents: Vehicles Involved: Federal data is updated yearly, averaging 76,397.000 Unit from Dec 2000 (Median) to 2017, with 17 observations. The data reached an all-time high of 119,277.000 Unit in 2017 and a record low of 21,694.000 Unit in 2002. Highways Statistics: Traffic Accidents: Vehicles Involved: Federal data remains active status in CEIC and is reported by Brazilian Association of Highway Concessionaires. The data is categorized under Brazil Premium Database’s Automobile Sector – Table BR.RAW008: Highways Statistics: Traffic Accidents. The Brazilian Association of Highway Concessionaires-ABCR represents the highway concession sector.

Provide information on traffic accidents that resulted in injuries or fatalities exceeding 24 hours (Category A2).

This dataset contains traffic violation information from all electronic traffic violations issued in the County. Any information that can be used to uniquely identify the vehicle, the vehicle owner or the officer issuing the violation will not be published. Update Frequency: Daily

The statistics refer to casualties resulting from personal injury accidents on public roads reported to the police and forwarded to the Welsh Government. Road Accident Data contains details of the accident, the number of vehicles involved and information on casualties. Accident data contains: the description and location, the number of casualties and vehicles, severity of accident, type of road and contributory factors. Vehicle description: includes details of vehicle type, age of driver/rider. Casualty description: provides details of the severity of casualty, casualty class and age. The Data Dictionary provides a detailed breakdown description of the variables that are included in all three categories.

Brazil Highways Statistics: Traffic Accidents: Vehicles Involved data was reported at 200,303.000 Unit in 2017. This records an increase from the previous number of 195,017.000 Unit for 2016. Brazil Highways Statistics: Traffic Accidents: Vehicles Involved data is updated yearly, averaging 112,260.000 Unit from Dec 1998 (Median) to 2017, with 20 observations. The data reached an all-time high of 211,279.000 Unit in 2012 and a record low of 22,317.000 Unit in 1998. Brazil Highways Statistics: Traffic Accidents: Vehicles Involved data remains active status in CEIC and is reported by Brazilian Association of Highway Concessionaires. The data is categorized under Brazil Premium Database’s Automobile Sector – Table BR.RAW008: Highways Statistics: Traffic Accidents. The Brazilian Association of Highway Concessionaires-ABCR represents the highway concession sector.

1. Data source: Road Safety Information Inquiry Network: Traffic accident statistics at a glance https://roadsafety.tw 2. Statistical conditions: All drivers (cars, motorcycles, power machinery, slow vehicles) drink-driving (exceeding 0.15mg by breath test) /L) accident, resulting in the number of deaths and injuries (including all drivers, passengers, and pedestrians affected by the incident).

• Statistical data on traffic accidents by vehicle type of the perpetrator and the victim driver (the number of accidents, the number of fatalities, the number of serious injuries, the number of light injuries, the number of reported injuries)
  • Statistics on traffic accidents investigated and handled by the police, counting only accidents with human damage
  • Based on data from Traffic Accident Analysis System (http://taas.koroad.or.kr)

Sample Data: https://cloud.drivertechnologies.com/shared?s=146&t=4:03&token=0f469c88-d578-4b4f-80b2-f53f195683b2

At Driver Technologies, we are dedicated to harnessing advanced technology to gather anonymized critical driving data through our innovative dash cam app, which operates seamlessly on end users' smartphones. Our Speed Over Limit Driver Behavior Data offering is a key resource for understanding driver behavior and improving safety on the roads, making it an essential tool for various industries.

What Makes Our Data Unique? Our Speed Over Limit Driver Behavior Data is distinguished by its real-time collection capabilities, utilizing our built-in computer vision technology to identify and capture instances where a driver nearly gets into an accident. This data reflects critical safety events that are indicative of potential risks and non-compliance with traffic regulations. By providing data on these significant events, our dataset empowers clients to perform in-depth analysis.

How Is the Data Generally Sourced? Our data is sourced directly from users who utilize our dash cam app, which harnesses the smartphone’s camera and sensors to record during a trip. This direct sourcing method ensures that our data is unbiased and represents a wide variety of conditions and environments. The data is not only authentic and reflective of current road conditions but is also abundant in volume, offering millions of miles of recorded trips that cover diverse scenarios. For our Speed Over Limit Driver Behavior Data, we leverage computer vision models to read speed limit signs as the driver drives past them, then compare that to speed data captured using the phone's sensor.

Primary Use-Cases and Verticals Driver Behavior Analysis: Organizations can leverage our dataset to analyze driving habits and identify trends in driver behavior. This analysis can help in understanding patterns related to rule compliance and potential risk factors.

Training Computer Vision Models: Clients can utilize our annotated data to develop and refine their own computer vision models for applications in autonomous vehicles, ensuring better decision-making capabilities in complex driving environments.

Improving Risk Assessment: Insurers can utilize our dataset to refine their risk assessment models. By understanding the frequency and context of significant events, they can better evaluate driver risk profiles, leading to more accurate premium pricing and improved underwriting processes.

Integration with Our Broader Data Offering The Speed Over Limit Driver Behavior Data is a crucial component of our broader data offerings at Driver Technologies. It complements our extensive library of driving data collected from various vehicles and road users, creating a comprehensive data ecosystem that supports multiple verticals, including insurance, automotive technology, and smart city planning.

In summary, Driver Technologies' Speed Over Limit Driver Behavior Data provides a unique opportunity for data buyers to access high-quality, actionable insights that drive innovation across mobility. By integrating our Speed Over Limit Driver Behavior Data with other datasets, clients can gain a holistic view of transportation dynamics, enhancing their analytical capabilities and decision-making processes.

Traffic Accidents: Coahuila data was reported at 11.000 Number in Dec 2017. This records a decrease from the previous number of 16.000 Number for Nov 2017. Traffic Accidents: Coahuila data is updated monthly, averaging 24.000 Number from Jan 2012 (Median) to Dec 2017, with 72 observations. The data reached an all-time high of 48.000 Number in Dec 2016 and a record low of 10.000 Number in Aug 2017. Traffic Accidents: Coahuila data remains active status in CEIC and is reported by Secretary of Communications and Transportations. The data is categorized under Global Database’s Mexico – Table MX.TA011: Traffic Accidents: by State.

All accidents, injuries and illnesses reported by mine operators and contractors. Obtained from the Mine Accident, Injury and Illness Report form (MSHA Form 7000-1). Document number is the unique key for this data. It provides information about the accident/injury/illness such as type, mine location, lost days and the degree of injury.

General Road Accident Statistics in Malaysia