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
mode_of_transport
Type
text
Label
Mode of Transport

ID
offenders
Type
numeric
Label
Number of Offenders

ID
victims
Type
numeric
Label
Number of Victims

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
Additional infoThis dataset contains data from 2018 to 2020
Data extraction pagehttps://www.ncrb.gov.in/accidental-deaths-suicides-in-india-table-content.html
Data insightsThe Mode of Transport-wise Number of Persons Died in Road Accidents dataset reveals critical insights into India’s road safety dynamics by showing which vehicle categories contribute most to traffic fatalities. Data trends consistently highlight two-wheeler riders as the most vulnerable group, accounting for a significant share of total deaths due to inadequate helmet use, speeding, and limited protection. Pedestrians and cyclists also remain at high risk, particularly in urban areas with mixed traffic conditions and limited pedestrian infrastructure.Heavy vehicles such as trucks and buses are frequently associated with fatal collisions due to their size, load, and higher road exposure, while car and auto rickshaw users face risks tied to speed and congestion in metropolitan regions. This dataset’s state-wise and annual patterns reveal regional variations influenced by road density, enforcement levels, and driver behavior.
Data last updated30-09-2025
Data retreival date02-11-2025
Datastore activeTrue
District no0
FrequencyYearly
Gp no0
GranularityState
Has viewsTrue
Id46000463-50a7-4d2e-90c9-691ec62b3d2d
Idp readyTrue
Indicators['Number of Offenders', 'Number of Victims']
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 indicators2
Package id086a0183-52bf-4b08-881c-9b69583402a6
Position1
Similar resourcesb068bed3-df55-46fd-ae52-d5d80ef40a20,4aec6071-ae92-4ff8-add2-659e1c7a0f05,4f6bf507-606c-45de-837c-3eaab13f13ee,eb39d353-6784-438a-9309-585d1011d86c,1dc6abc0-72aa-478c-bc3b-3f1648eb4b70,9fc6f915-f978-465c-b6f2-5ce445dbc621,eb47815b-8b33-4f28-a06d-a0cf253d95cc,8952c4b0-9bd3-4ae9-a749-e184484bd148
Size81 KiB
Skuncrb-adsi_mode_of_transport_wise_road_accidents-st-yr-def
Stateactive
States uts no36
Tehsil no0
Url typeupload
Years covered2018 - 2020
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 Offenders', 'Number of Victims']
Similar Resources
  1. Cases Reported and Persons Injured and Died
  2. Mode of Transport Wise Number of Persons Died in Road Accidents (Onwards 2021)
  3. Month of Occurrence Wise Number of Traffic Accidents
  4. Road Classification Wise Number of Road Accidents, Injuries and Deaths
  5. Time of Occurrence Wise Number of Traffic Accidents
  6. Cause Wise Distribution of Road Accidents and Unmanned Railway Crossing Accidents
  7. Classification of Railway Accidents
  8. Place of Occurrence Wise Road Accident Deaths
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_mode_of_transport_wise_road_accidents-st-yr-def
Dataset Frequency Yearly
Years Covered 2018 - 2020
No of States/UT(s) 36
No of Districts 0
No of Tehsils/blocks 0
No of Gram Panchayats 0
Additional Information This dataset contains data from 2018 to 2020
Number of Indicators 2
Insights from the dataset The Mode of Transport-wise Number of Persons Died in Road Accidents dataset reveals critical insights into India’s road safety dynamics by showing which vehicle categories contribute most to traffic fatalities. Data trends consistently highlight two-wheeler riders as the most vulnerable group, accounting for a significant share of total deaths due to inadequate helmet use, speeding, and limited protection. Pedestrians and cyclists also remain at high risk, particularly in urban areas with mixed traffic conditions and limited pedestrian infrastructure.Heavy vehicles such as trucks and buses are frequently associated with fatal collisions due to their size, load, and higher road exposure, while car and auto rickshaw users face risks tied to speed and congestion in metropolitan regions. This dataset’s state-wise and annual patterns reveal regional variations influenced by road density, enforcement levels, and driver behavior.
IDP Ready Yes
LGD Mapping Yes
Mapping Status % 100
Geo Columns