Contains locations and information about every crash incident reported to the police in Allegheny County from 2004 to 2022. Fields include injury severity, fatalities, information about the vehicles involved, location information, and factors that may have contributed to the crash. Data is provided by PennDOT and is subject to PennDOT's data privacy restrictions, which are noted in the metadata information section below.

This dataset contains crash information from the last five years to the current date. The data is based on the National Incident Based Reporting System (NIBRS). The data is dynamic, allowing for additions, deletions and modifications at any time, resulting in more accurate information in the database. Due to ongoing and continuous data entry, the numbers of records in subsequent extractions are subject to change.About Crash DataThe Cary Police Department strives to make crash data as accurate as possible, but there is no avoiding the introduction of errors into this process, which relies on data furnished by many people and that cannot always be verified. As the data is updated on this site there will be instances of adding new incidents and updating existing data with information gathered through the investigative process.Not surprisingly, crash data becomes more accurate over time, as new crashes are reported and more information comes to light during investigations.This dynamic nature of crash data means that content provided here today will probably differ from content provided a week from now. Likewise, content provided on this site will probably differ somewhat from crime statistics published elsewhere by the Town of Cary, even though they draw from the same database.About Crash LocationsCrash locations reflect the approximate locations of the crash. Certain crashes may not appear on maps if there is insufficient detail to establish a specific, mappable location.This dataset is updated daily.

This dataset provides information on motor vehicle operators (drivers) involved in traffic collisions occurring on county and local roadways. The dataset reports details of all traffic collisions occurring on county and local roadways within Montgomery County, as collected via the Automated Crash Reporting System (ACRS) of the Maryland State Police, and reported by the Montgomery County Police, Gaithersburg Police, Rockville Police, or the Maryland-National Capital Park Police. This dataset shows each collision data recorded and the drivers involved.

Please note that these collision reports are based on preliminary information supplied to the Police Department by the reporting parties. Therefore, the collision data available on this web page may reflect:

-Information not yet verified by further investigation -Information that may include verified and unverified collision data -Preliminary collision classifications may be changed at a later date based upon further investigation -Information may include mechanical or human error

This dataset can be joined with the other 2 Crash Reporting datasets (see URLs below) by the State Report Number. * Crash Reporting - Incidents Data at https://data.montgomerycountymd.gov/Public-Safety/Crash-Reporting-Incidents-Data/bhju-22kf * Crash Reporting - Non-Motorists Data at https://data.montgomerycountymd.gov/Public-Safety/Crash-Reporting-Non-Motorists-Data/n7fk-dce5

Update Frequency : Weekly

This dataset contains all traffic crashes reported to CSPD . This dataset may be tied to the Tickets and Citations dataset by ticket number.

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.

Vision Zero Boston is our commitment to focus the city’s resources on proven strategies to eliminate fatal and serious traffic crashes in the city by 2030. We are inspired by the belief that even one fatality is too many. Learn more about about the Vision Zero Boston program at https://www.boston.gov/departments/transportation/vision-zero.

This dataset, provided as part of the Vision Zero Boston program, contains records of the date, time, location, and type of crash for incidents requiring public safety response which may involve injuries or fatalities. All records are compiled by the Department of Innovation and Technology from the City's Computer-Aided Dispatch (911) system and verified as having required a response from a public safety agency. To protect the privacy of individuals involved in these incidents, we do not indicate the severity of specific crashes or whether medical care was provided in any specific case.

Additional notes:

• Each incident is included only once regardless of the number of individuals involved.
• The date and time of an incident reflects when public safety response was dispatched to the location, not the crash itself.
• Records are typically updated on a monthly basis, but because the verification process involves manual confirmation of incidents, exact posting schedules may vary.
• Records may be updated after their initial posting if new information becomes available.
• Data on pedestrian and bicycle incidents is now available through December 31, 2024. Motor Vehicle incident data for July 1, 2024 to December 31, 2024 is delayed due to a change in the reporting system.

The NHTSA Vehicle Crash Test Database contains engineering data measured during various types of research, the New Car Assessment Program (NCAP), and compliance crash tests. Information in this database refers to the performance and response of vehicles and other structures in impacts. This database is not intended to support general consumer safety issues. For general consumer information please see the NHTSA's information on buying a safer car.

Crash Statistics are summarized crash statistics for large trucks and buses involved in fatal and non-fatal Crashes that occurred in the United States. These statistics are derived from two sources: the Fatality Analysis Reporting System (FARS) and the Motor Carrier Management Information System (MCMIS). Crash Statistics contain information that can be used to identify safety problems in specific geographical areas or to compare state statistics to the national crash figures.

The main source of the crash data is owned and maintained by the Virginia Department of Motor Vehicle (DMV). DMV’s Traffic Records Electronic Data System (TREDS) is a state-of-the-art data system maintained by the DMV Highway Safety Office (HSO) that automates and centralizes all crash data in Virginia. Per data sharing use agreement with DMV, VDOT publishes the non-privileged crash data through Virginia Roads data portal. In providing this data, VDOT assumes no responsibility for the accuracy and completeness of the data. In the process of recording and compiling the data, some deletions and/or omissions of data may occur and VDOT is not responsible for any such occurrences. The most recent data contained in this dataset is preliminary and subject to change.

Please be advised that, under Title 23 United State Code – Section 407, this crash information cannot be used in discovery or as evidence in a Federal or State court proceeding or considered for other purposes in any action for damages against VDOT or the State of Virginia arising from any occurrence at the location identified.

All users shall comply with and be subject to all applicable laws and regulations, whether federal or state, in connection with any of the receipt and use of DMV data including, but not limited to, (1) the Federal Drivers Privacy Protection Act (18 U.S.C. § 2721 et seq.), (2) the Government Data Collection and Dissemination Practices Act (Va. Code § 2.2-3800 et seq.), (3) the Virginia Computer Crimes Act (Va. Code § 18.2-152.1 et seq.), (4) the provisions of Va. Code §§ 46.2-208 and 58.1-3, and (5) any successor rules, regulations, or guidelines adopted by DMV with regard to disclosure or dissemination of any information obtained from DMV records or files.

Attributes about each crash case which may consist of a single or multiple reports occurring during the year.

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.

Context

The aviation accident database throughout the world, from 1908-2019.

• All civil and commercial aviation accidents of scheduled and non-scheduled passenger airliners worldwide, which resulted in a fatality (including all U.S. Part 121 and Part 135 fatal accidents)
• All cargo, positioning, ferry and test flight fatal accidents.
• All military transport accidents with 10 or more fatalities.
• All commercial and military helicopter accidents with greater than 10 fatalities.
• All civil and military airship accidents involving fatalities.
• Aviation accidents involving the death of famous people.
• Aviation accidents or incidents of noteworthy interest.

There are similar dataset available on Kaggle. This dataset is cleaned versioned and source code is available on github.

Content

Data is scraped from planecrashinfo.com. Below you can find the dataset column descriptions:

• Date: Date of accident, in the format - January 01, 2001
• Time: Local time, in 24 hr. format unless otherwise specified
• Airline/Op: Airline or operator of the aircraft
• Flight #: Flight number assigned by the aircraft operator
• Route: Complete or partial route flown prior to the accident
• AC Type: Aircraft type
• Reg: ICAO registration of the aircraft
• cn / ln: Construction or serial number / Line or fuselage number
• Aboard: Total aboard (passengers / crew)
• Fatalities: Total fatalities aboard (passengers / crew)
• Ground: Total killed on the ground
• Summary: Brief description of the accident and cause if known

Acknowledgements

The original data is from the Plane Crash info website (http://www.planecrashinfo.com/database.htm). Dataset is scraped with Python. Source code is also public on Github

Inspiration

Find the root cause of plane crashes. Find any insights from dataset such as - Which operators are the worst - Which aircrafts are the worst

Overview:

Information on location and characteristics of crashes in Queensland for all reported Road Traffic Crashes occurred from 1 January 2001 to 30 November 2023. Fatal crashes to 30 November 2023. Non-fatal, hospitalisation, medical treatment and minor injury crashes to 30 June 2023 and property damage only crashes to 31 December 2010.

_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 database that can be used for macro-level analysis of road accidents on interurban roads in Europe. Through the variables it contains, road accidents can be explained using variables related to economic resources invested in roads, traffic, road network, socioeconomic characteristics, legislative measures and meteorology. This repository contains the data used for the analysis carried out in the papers:

1. Calvo-Poyo F., Navarro-Moreno J., de Oña J. (2020) Road Investment and Traffic Safety: An International Study. Sustainability 12:6332. https://doi.org/10.3390/su12166332

2. Navarro-Moreno J., Calvo-Poyo F., de Oña J. (2022) Influence of road investment and maintenance expenses on injured traffic crashes in European roads. Int J Sustain Transp 1–11. https://doi.org/10.1080/15568318.2022.2082344

3. Navarro-Moreno, J., Calvo-Poyo, F., de Oña, J. (2022) Investment in roads and traffic safety: linked to economic development? A European comparison. Environ. Sci. Pollut. Res. https://doi.org/10.1007/s11356-022-22567

The file with the database is available in excel.

DATA SOURCES

The database presents data from 1998 up to 2016 from 20 european countries: Austria, Belgium, Croatia, Czechia, Denmark, Estonia, Finland, France, Germany, Ireland, Italy, Latvia, Netherlands, Poland, Portugal, Slovakia, Slovenia, Spain, Sweden and United Kingdom. Crash data were obtained from the United Nations Economic Commission for Europe (UNECE) [2], which offers enough level of disaggregation between crashes occurring inside versus outside built-up areas.

With reference to the data on economic resources invested in roadways, deserving mention –given its extensive coverage—is the database of the Organisation for Economic Cooperation and Development (OECD), managed by the International Transport Forum (ITF) [1], which collects data on investment in the construction of roads and expenditure on their maintenance, following the definitions of the United Nations System of National Accounts (2008 SNA). Despite some data gaps, the time series present consistency from one country to the next. Moreover, to confirm the consistency and complete missing data, diverse additional sources, mainly the national Transport Ministries of the respective countries were consulted. All the monetary values were converted to constant prices in 2015 using the OECD price index.

To obtain the rest of the variables in the database, as well as to ensure consistency in the time series and complete missing data, the following national and international sources were consulted:

• Eurostat [3]
• Directorate-General for Mobility and Transport (DG MOVE). European Union [4]
• The World Bank [5]
• World Health Organization (WHO) [6]
• European Transport Safety Council (ETSC) [7]
• European Road Safety Observatory (ERSO) [8]
• European Climatic Energy Mixes (ECEM) of the Copernicus Climate Change [9]
• EU BestPoint-Project [10]
• Ministerstvo dopravy, República Checa [11]
• Bundesministerium für Verkehr und digitale Infrastruktur, Alemania [12]
• Ministerie van Infrastructuur en Waterstaat, Países Bajos [13]
• National Statistics Office, Malta [14]
• Ministério da Economia e Transição Digital, Portugal [15]
• Ministerio de Fomento, España [16]
• Trafikverket, Suecia [17]
• Ministère de l’environnement de l’énergie et de la mer, Francia [18]
• Ministero delle Infrastrutture e dei Trasporti, Italia [19–25]
• Statistisk sentralbyrå, Noruega [26-29]
• Instituto Nacional de Estatística, Portugal [30]
• Infraestruturas de Portugal S.A., Portugal [31–35]
• Road Safety Authority (RSA), Ireland [36]

DATA BASE DESCRIPTION

The database was made trying to combine the longest possible time period with the maximum number of countries with complete dataset (some countries like Lithuania, Luxemburg, Malta and Norway were eliminated from the definitive dataset owing to a lack of data or breaks in the time series of records). Taking into account the above, the definitive database is made up of 19 variables, and contains data from 20 countries during the period between 1998 and 2016. Table 1 shows the coding of the variables, as well as their definition and unit of measure.

Table. Database metadata

| Code | Variable and unit | | fatal_pc_km | Fatalities per billion passenger-km | | fatal_mIn | Fatalities per million inhabitants | | accid_adj_pc_km | Accidents per billion passenger-km | | p_km | Billions of passenger-km | | croad_inv_km | Investment in roads construction per kilometer, €/km (2015 constant prices) | | croad_maint_km | Expenditure on roads maintenance per kilometer €/km (2015 constant prices) | | prop_motorwa | Proportion of motorways over the total road network (%) | | populat | Population, in millions of inhabitants | | unemploy | Unemployment rate (%) | | petro_car | Consumption of gasolina and petrol derivatives (tons), per tourism | | alcohol | Alcohol consumption, in liters per capita (age > 15) | | mot_index | Motorization index, in cars per 1,000 inhabitants | | den_populat | Population density, inhabitants/km2 | | cgdp | Gross Domestic Product (GDP), in € (2015 constant prices) | | cgdp_cap | GDP per capita, in € (2015 constant prices) | | precipit | Average depth of rain water during a year (mm) | | prop_elder | Proportion of people over 65 years (%) | | dps | Demerit Point System, dummy variable (0: no; 1: yes) | | freight | Freight transport, in billions of ton-km |

ACKNOWLEDGEMENTS

This database was carried out in the framework of the project “Inversión en carreteras y seguridad vial: un análisis internacional (INCASE)”, financed by: FEDER/Ministerio de Ciencia, Innovación y Universidades–Agencia Estatal de Investigación/Proyecto RTI2018-101770-B-I00, within Spain´s National Program of R+D+i Oriented to Societal Challenges.

Moreover, the authors would like to express their gratitude to the Ministry of Transport, Mobility and Urban Agenda of Spain (MITMA), and the Federal Ministry of Transport and Digital Infrastructure of Germany (BMVI) for providing data for this study.

REFERENCES

1. International Transport Forum OECD iLibrary | Transport infrastructure investment and maintenance.

2. United Nations Economic Commission for Europe UNECE Statistical Database Available online: https://w3.unece.org/PXWeb2015/pxweb/en/STAT/STAT_40-TRTRANS/?rxid=18ad5d0d-bd5e-476f-ab7c-40545e802eeb (accessed on Apr 28, 2020).

3. European Commission Database - Eurostat Available online: https://ec.europa.eu/eurostat/data/database (accessed on Apr 28, 2021).

4. Directorate-General for Mobility and Transport. European Commission EU Transport in figures - Statistical Pocketbooks Available online: https://ec.europa.eu/transport/facts-fundings/statistics_en (accessed on Apr 28, 2021).

5. World Bank Group World Bank Open Data | Data Available online: https://data.worldbank.org/ (accessed on Apr 30, 2021).

6. World Health Organization (WHO) WHO Global Information System on Alcohol and Health Available online: https://apps.who.int/gho/data/node.main.GISAH?lang=en (accessed on Apr 29, 2021).

7. European Transport Safety Council (ETSC) Traffic Law Enforcement across the EU - Tackling the Three Main Killers on Europe’s Roads; Brussels, Belgium, 2011;

8. Copernicus Climate Change Service Climate data for the European energy sector from 1979 to 2016 derived from ERA-Interim Available online: https://cds.climate.copernicus.eu/cdsapp#!/dataset/sis-european-energy-sector?tab=overview (accessed on Apr 29, 2021).

9. Klipp, S.; Eichel, K.; Billard, A.; Chalika, E.; Loranc, M.D.; Farrugia, B.; Jost, G.; Møller, M.; Munnelly, M.; Kallberg, V.P.; et al. European Demerit Point Systems : Overview of their main features and expert opinions. EU BestPoint-Project 2011, 1–237.

10. Ministerstvo dopravy Serie: Ročenka dopravy; Ročenka dopravy; Centrum dopravního výzkumu: Prague, Czech Republic;

11. Bundesministerium für Verkehr und digitale Infrastruktur Verkehr in Zahlen 2003/2004; Hamburg, Germany, 2004; ISBN 3871542946.

12. Bundesministerium für Verkehr und digitale Infrastruktur Verkehr in Zahlen 2018/2019. In Verkehrsdynamik; Flensburg, Germany, 2018 ISBN 9783000612947.

13. Ministerie van Infrastructuur en Waterstaat Rijksjaarverslag 2018 a Infrastructuurfonds; The Hague, Netherlands, 2019; ISBN 0921-7371.

14. Ministerie van Infrastructuur en Milieu Rijksjaarverslag 2014 a Infrastructuurfonds; The Hague, Netherlands, 2015; ISBN 0921- 7371.

15. Ministério da Economia e Transição Digital Base de Dados de Infraestruturas - GEE Available online: https://www.gee.gov.pt/pt/publicacoes/indicadores-e-estatisticas/base-de-dados-de-infraestruturas (accessed on Apr 29, 2021).

16. Ministerio de Fomento. Dirección General de Programación Económica y Presupuestos. Subdirección General de Estudios Económicos y Estadísticas Serie: Anuario estadístico; NIPO 161-13-171-0; Centro de Publicaciones. Secretaría General Técnica. Ministerio de Fomento: Madrid, Spain;

17. Trafikverket The Swedish Transport Administration Annual report: 2017; 2018; ISBN 978-91-7725-272-6.

18. Ministère de l’Équipement, du T. et de la M. Mémento de statistiques des transports 2003; Ministère de l’environnement de l’énergie et de la mer, 2005;

19. Ministero delle Infrastrutture e dei Trasporti Conto Nazionale delle Infrastrutture e dei Trasporti Anno 2000; Istituto Poligrafico e Zecca dello Stato: Roma, Italy, 2001;

20. Ministero delle Infrastrutture e dei Trasporti Conto nazionale dei trasporti 1999. 2000.

21. Generale, D.; Informativi, S. delle Infrastrutture e dei Trasporti Anno 2004.

22. Ministero delle Infrastrutture e dei Trasporti *Conto Nazionale delle Infrastrutture e dei

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.

This dataset contains traffic crash records for crashes which have occurred in Austin, TX in the last ten years. It is one of two datasets which power our Vision Zero Viewer dashboard, available here: https://visionzero.austin.gov/viewer.

Crash data may take several weeks to be submitted, reviewed, and finalized for inclusion in this dataset. To provide the most accurate information as possible, we only provide crash data as recent as two weeks old. Please also note that some crash records may take even longer to appear in this dataset, depending on the circumstances of the crash and the ensuing law enforcement investigation.

Crash data is obtained from the Texas Department of Transportation (TxDOT) Crash Record Information System (CRIS) database, which is populated by reports submitted by Texas Peace Officers throughout the state, including Austin Police Department (APD).

The data and information on this website is for informational purposes only. While we seek to provide accurate information, please note that errors may be present and information presented may not be complete.

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 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.

SerialNumber - The serial number for each crash incident and is applied to each unit involved. Use this field as the dissolve field to update Raw_Crash_Dissolve.PMID - A unique ID field used to summarize crashes per segment to join to the model network.

List of crashes involving motor vehicles, bicycles and/or pedestrians reported in the City of Cambridge since 2015.

Any data or text that may identify specific persons or companies has been omitted. Please see attached MassTRAC documentation for additional explanation about crash reporting data elements.

Note: crashes involving pedestrians are indicated in the “P1 Non Motorist Desc” and “P2 Mon Motorist Desc” columns. When using Socrata's built in visualization tools to map crashes, please use the geocoded "Location" column. The column "May involve cyclist" specifies whether a given incident may involve a bicycle operator.