Data Dictionary

ID
id
Type
int4
Label
index

ID
year
Type
text
Label
Year

ID
state_name
Type
text
Label
State Name

ID
state_code
Type
text
Label
State Code

ID
road_type
Type
text
Label
Type of Road

ID
cases
Type
numeric
Label
Number of Cases

ID
injured
Type
numeric
Label
Number of Injured

ID
died
Type
numeric
Label
Number of Dead

Additional Information

Field Value
Data last updated February 12, 2026
Metadata last updated February 12, 2026
Created February 12, 2026
Format CSV
License Open Data Commons Attribution License
Data extraction pagehttps://www.ncrb.gov.in/accidental-deaths-suicides-in-india-table-content.html
Data insightsThe Road Classification-wise Number of Road Accidents, Injuries and Deaths dataset provides key insights into how different categories of roads contribute to India’s overall traffic accident burden. Data trends typically show that National and State Highways, while constituting a smaller portion of total road length, account for a disproportionately large share of fatal accidents and injuries due to high traffic volume, speeding, and long-distance transport movement. In contrast, rural and district roads often experience accidents linked to poor infrastructure, lack of lighting, and limited safety measures.Comparative analysis across road types enables policymakers to identify infrastructure and enforcement gaps, such as inadequate signage, unsafe crossings, or weak surveillance on high-speed corridors. These insights are invaluable for formulating evidence-based road safety policies, prioritizing investment in safer road design, and improving emergency response mechanisms.
Data last updated30-09-2025
Data retreival date02-11-2025
Datastore activeTrue
District no0
FrequencyYearly
Gp no0
GranularityState
Has viewsTrue
Ideb39d353-6784-438a-9309-585d1011d86c
Idp readyTrue
Indicators['Number of Cases', 'Number of Injured', 'Number of Dead']
Lgd mappingyes
Mapping status100
MethodologyThe Traffic Accidents in India data are compiled and published by the National Crime Records Bureau (NCRB) under the Ministry of Home Affairs, Government of India. The information is collected annually through a standardized reporting process based on the First Information Reports (FIRs) and related police records maintained at the state and district levels. Each reported traffic accident is recorded by local police authorities and categorized according to cause, type of vehicle involved, number of casualties (injured and deceased), and place of occurrence. State Crime Record Bureaus (SCRBs) and District Crime Record Bureaus (DCRBs) aggregate these data and transmit them to the NCRB, which performs data validation, consistency checks, and compilation to ensure accuracy and comparability across states and years.
No indicators3
Package id086a0183-52bf-4b08-881c-9b69583402a6
Position5
Similar resourcesb068bed3-df55-46fd-ae52-d5d80ef40a20,46000463-50a7-4d2e-90c9-691ec62b3d2d,4aec6071-ae92-4ff8-add2-659e1c7a0f05,4f6bf507-606c-45de-837c-3eaab13f13ee,1dc6abc0-72aa-478c-bc3b-3f1648eb4b70,9fc6f915-f978-465c-b6f2-5ce445dbc621,8952c4b0-9bd3-4ae9-a749-e184484bd148,eb47815b-8b33-4f28-a06d-a0cf253d95cc
Size44.2 KiB
Skuncrb-adsi_road_accidents_classification-st-yr-def
Stateactive
States uts no36
Tehsil no0
Url typeupload
Years covered2018 - 2022
Methodology The Traffic Accidents in India data are compiled and published by the National Crime Records Bureau (NCRB) under the Ministry of Home Affairs, Government of India. The information is collected annually through a standardized reporting process based on the First Information Reports (FIRs) and related police records maintained at the state and district levels. Each reported traffic accident is recorded by local police authorities and categorized according to cause, type of vehicle involved, number of casualties (injured and deceased), and place of occurrence. State Crime Record Bureaus (SCRBs) and District Crime Record Bureaus (DCRBs) aggregate these data and transmit them to the NCRB, which performs data validation, consistency checks, and compilation to ensure accuracy and comparability across states and years.
Indicators ['Number of Cases', 'Number of Injured', 'Number of Dead']
Similar Resources
  1. Cases Reported and Persons Injured and Died
  2. Mode of Transport Wise Number of Persons Died in Road Accidents (2018 - 2020)
  3. Mode of Transport Wise Number of Persons Died in Road Accidents (Onwards 2021)
  4. Month of Occurrence Wise Number of Traffic Accidents
  5. Time of Occurrence Wise Number of Traffic Accidents
  6. Cause Wise Distribution of Road Accidents and Unmanned Railway Crossing Accidents
  7. Place of Occurrence Wise Road Accident Deaths
  8. Classification of Railway Accidents
Granularity Level State
Data Extraction Page https://www.ncrb.gov.in/accidental-deaths-suicides-in-india-table-content.html
Data Retreival Date 02-11-2025
Data Last Updated 30-09-2025
Sku ncrb-adsi_road_accidents_classification-st-yr-def
Dataset Frequency Yearly
Years Covered 2018 - 2022
No of States/UT(s) 36
No of Districts 0
No of Tehsils/blocks 0
No of Gram Panchayats 0
Additional Information
Number of Indicators 3
Insights from the dataset The Road Classification-wise Number of Road Accidents, Injuries and Deaths dataset provides key insights into how different categories of roads contribute to India’s overall traffic accident burden. Data trends typically show that National and State Highways, while constituting a smaller portion of total road length, account for a disproportionately large share of fatal accidents and injuries due to high traffic volume, speeding, and long-distance transport movement. In contrast, rural and district roads often experience accidents linked to poor infrastructure, lack of lighting, and limited safety measures.Comparative analysis across road types enables policymakers to identify infrastructure and enforcement gaps, such as inadequate signage, unsafe crossings, or weak surveillance on high-speed corridors. These insights are invaluable for formulating evidence-based road safety policies, prioritizing investment in safer road design, and improving emergency response mechanisms.
IDP Ready Yes
LGD Mapping Yes
Mapping Status % 100
Geo Columns