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
cause
Type
text
Label
Cause

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 Cause-wise Distribution of Road Accidents and Unmanned Railway Crossing Accidents dataset provides critical insights into the root causes of road traffic and railway crossing accidents, enabling evidence-based approaches to accident prevention. Analysis of national trends reveals that overspeeding and driver negligence are consistently the leading causes of road accidents, contributing to the majority of fatalities and injuries. Drunken driving, mobile phone usage, and fatigue-related incidents also emerge as major behavioral risk factors.At unmanned railway crossings, accidents often result from lack of warning systems, poor visibility, and non-compliance with safety rules, leading to high fatality rates in rural and semi-urban regions. Cause-specific analysis helps identify where to focus enforcement such as stricter speed regulation, awareness campaigns on drunk driving, or conversion of unmanned crossings into manned or automated ones.
Data last updated30-09-2025
Data retreival date02-11-2025
Datastore activeTrue
District no0
FrequencyYearly
Gp no0
GranularityState
Has viewsTrue
Id9fc6f915-f978-465c-b6f2-5ce445dbc621
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
Position6
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,eb39d353-6784-438a-9309-585d1011d86c,8952c4b0-9bd3-4ae9-a749-e184484bd148,eb47815b-8b33-4f28-a06d-a0cf253d95cc
Size201.8 KiB
Skuncrb-adsi_cause_wise_road_accidents_and_unmanned_railway_crossings_accidents-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. Road Classification Wise Number of Road Accidents, Injuries and Deaths
  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_cause_wise_road_accidents_and_unmanned_railway_crossings_accidents-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 Cause-wise Distribution of Road Accidents and Unmanned Railway Crossing Accidents dataset provides critical insights into the root causes of road traffic and railway crossing accidents, enabling evidence-based approaches to accident prevention. Analysis of national trends reveals that overspeeding and driver negligence are consistently the leading causes of road accidents, contributing to the majority of fatalities and injuries. Drunken driving, mobile phone usage, and fatigue-related incidents also emerge as major behavioral risk factors.At unmanned railway crossings, accidents often result from lack of warning systems, poor visibility, and non-compliance with safety rules, leading to high fatality rates in rural and semi-urban regions. Cause-specific analysis helps identify where to focus enforcement such as stricter speed regulation, awareness campaigns on drunk driving, or conversion of unmanned crossings into manned or automated ones.
IDP Ready Yes
LGD Mapping Yes
Mapping Status % 100
Geo Columns