crash analysis in india: data sources and methods
TRANSCRIPT
Crash analysis in India:Data sources and methods
Certificate Course on Road Safety and
Road Safety Audit, IIT Delhi, India
16 March 2021
Rahul Goel
This talk will cover
• Data sources of traffic crash data in India
• Limitations of reported data
• Using police reports for details on crashes
• Case-studies from India and other countries
Traffic crash data recording and reporting process in India
Reporting by public agencies
• National Crime Records Bureau and Ministry of Road Transport and Highways publish annual reports with road traffic statistics
• They provide aggregate statistics of road accidents
• Useful for general trends and comparison across cities or states
• There is a need for crash-level information to do detailed analysis
Accuracy of Police data?
• Fatalities ~ 5% under reported compared to hospital data
• Injuries are 15-20 times under reported
• Large variation between health ministry death registrations and police data
Shortcomings of police data
National level tables(NCRB and MoRTH) for victims are based on “road user causing the accident”, therefore pedestrians and bicyclists numbers are incorrect (lower than actual numbers)
NCRB 2011 Report
These figures are not correct
Four examples of a road crash involving a motorcyclist
Victim Victim
Victim Victim Victim
It is this identification of victim that is not correctly done in NCRB data
Safety outcomes and their limitations
In road safety publications, three outcomes are often reported
1. Accidents
2. Injury accidents and number of people injured
3. Fatal accidents and number of people who died
• Accidents could imply all road crashes, including injury and fatal. Since injury accidents are highly underreported, number of accidents as well as injury accidents are unreliable numbers as reported by NCRB or MORTH
• Injury accidents could be less than or equal to number of people injured
• Similarly, fatal accidents could be less than or equal to number of people who died, as a single accident may have more than one victim
Implications of underreported data on road safety research/analysis• Only number of road deaths are reliable outcomes
• Limits our ability to understand safety problem in India
• Deaths are rare events while injuries and other accidents are more frequent
• For example, if a given set of road sections do not have any road deaths, what can we say about their safety?
• Deaths also result from severe injuries in a crash, but there are many crashes where such injuries do not occur
NCRB reports data for states and for million-plus cities
53 cities36 states and union territories
NCRB reports data for states and for million-plus cities: Table on road deaths and injuries
53 cities36 states and union territories
Injury numbers are highly underreported
Number of deaths are more reliable
Table on monthly number of accidents
Note that “accidents” are underreported
Table on time-of-day of accidents
Note that “accidents” are underreported
Month wise road deaths in Bihar (2015-2019)
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Jan 2015 Dec 2019
Month wise road deaths in Bihar (2015-2019)
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Jan
uar
y20
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Feb
ruar
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Mar
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May
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Jun
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July
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Au
gust
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Sep
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No
vem
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Dec
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Jan
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y20
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Feb
ruar
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Mar
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Jun
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May 2015: 662 deaths
May 2019: 824 deaths
Jan 2015 Dec 2019
Often road deaths peak around May and Nov/Dec- Why?
Road deaths by time of day (urban and rural) in Bihar
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Late nightEarly morning
Rural
Urban
Road deaths by time of day (urban and rural) in Bihar
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Late nightEarly morning
Rural
Urban
What is the reason for such a peak in rural areas but not in urban areas?
Age of people killed
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Less than 18years
18-25 25-35 35-45 45-60 60 andAbove
• 70% of people killed are between 18 and 45 years of age
• This is the most productive time in the lifetime of a person
Metrics of road crash risk
• Number of deaths or injuries alone is a poor indicator of safety
• A large city like Delhi is likely to have greater number of deaths than a smaller city like Visakhapatnam
• Similarly, a vehicle that is used for longer distance will have greater number of accidents than a vehicle that is used for shorter distance
• There is a need to define road deaths that account for different levels of exposure
Road safety indicators
Total number of road deaths in 2011
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Goa and Puducherry report small number of road deaths compared to other large states
Road deaths per capita (per 100,000 people)
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Death rate =𝑁𝑢𝑚𝑏𝑒𝑟 𝑜𝑓 𝑟𝑜𝑎𝑑 𝑑𝑒𝑎𝑡ℎ𝑠 𝑖𝑛 𝑎 𝑦𝑒𝑎𝑟
𝑃𝑜𝑝𝑢𝑙𝑎𝑡𝑖𝑜𝑛 𝑜𝑓 𝑡ℎ𝑒 𝑠𝑡𝑎𝑡𝑒100,000
Death rate is a useful metric for comparison
Goa and Puducherry are now prominent in this graph
Traffic deaths per billion km
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Dea
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mode
Accra
Sao Paulo
Delhi
Bengaluru
• This is an example of road death risk measured per unit distance travelled
• We can compare the risk of different road users across the four cities
• Car drivers are the safest in all the cities
• Delhi and Bengaluru have the highest pedestrian risk
• However, data for distance travelled by modes is often difficult to obtain
• It can be estimated using surveys
Annual deaths divided by annual distance travelled by mode
Road accident data reported by states
• Some states publish their traffic statistics
• These statistics are often reported under Crime statistics reports or Statistical handbooks
• Police departments of some states publish traffic accident data on their websites
• The advantage of this data is that it is reported at district level
• However, the information is often limited to number of deaths, with few exceptions
Road deaths for districts in Rajasthan state
Death rates in districts
Census
ID District
Death rate per
100,000 persons99 Ganganagar 11.4
100 Hanumangarh 10.7101 Bikaner 13.0102 Churu 11.8103 Jhunjhunun 13.3104 Alwar 15.1105 Bharatpur 11.4106 Dhaulpur 12.1107 Karauli 7.6108 Sawai Madhopur 8.8109 Dausa 18.3110 Jaipur 19.0111 Sikar 15.9112 Nagaur 11.0113 Jodhpur 14.8114 Jaisalmer 13.4115 Barmer 10.0116 Jalor 8.3117 Sirohi 21.2118 Pali 18.0119 Ajmer 21.6120 Tonk 15.1121 Bundi 14.2122 Bhilwara 15.0123 Rajsamand 18.7124 Dungarpur 11.6125 Banswara 9.4126 Chittaurgarh 15.4127 Kota 11.5
Districts of Rajasthan• The choropleth maps show the fatality
rates across districts in Rajasthan• The rates vary from 7 to 22 deaths per
100,000• Some districts have consistently high
rates• Some have consistently low rates• We can analyse this data to understand
what factors result in such variation
Satellite images of Delhi-Jaipur highway in Rajasthan
Road death rates across districts in India
• Data collected through state reports and RTI applications
• 640 districts in India according to Census 2011
• Death rate varies from less than 5 to greater than 50 deaths per 100,000
• Regional and sub-regional differences are easily highlighted
• Highlights the problematic areas compared to rest of the country
Levels of data collectionfor safety standards/policies
Epidemiology of fatalcrashes, fixingpriorities
Base
Intermediate
Police Data,
Traffic police
Traffic Data,Injury
coding, specialists
practioners
In-depth multidisciplinary causative
Crash reconstruction
Specialists researchers
traffic management
strategies, road
designs(cross sections)
Vehicle design standards,
road furniture design, crash
barriers
Using crash-level data for safety analysis
• To address the limitations of government reported data we need detailed information of each road crash
• In many high-income countries, such datasets with crash-level information are publicly accessible
• In India, we can use an alternate approach by accessing police files of road crashes
Legal procedure involving traffic crashes
• When the occurrence of a traffic crash is brought to the notice of a police station (by anyone involved in the crash; anyone who knows about the crash; or a police officer who comes to know about the crash) the information reported is recorded in a First Information Report (FIR)
• After an FIR has been filed the contents of the FIR cannot be changed except by a ruling from the High Court or the Supreme Court of India
• After the investigation is complete a case file is prepared which records the details of the crash as determined by the police department (which need not necessarily tally with those in the FIR) and the ‘offending party’ (as determined by the investigation) is charged with offences under provisions of the Indian Penal Code and the Motor Vehicles Act of India 1988 (Ministry of Road Transport and Highways, 1988).
Offences under which traffic crashes are recorded by police• Indian Penal Code (IPC)
1. Section 279. Rash driving or riding on a public way.
2. Section 304A. Causing death by negligence.
3. Section 336. Act endangering life or personal safety of others.
4. Section 337. Causing hurt by act endangering life or personal safety of others.
5. Section 338. Causing grievous hurt by act endangering life or personal safety of others.
• Motor Vehicles Act
1. Section 185. Driving by a drunken person or by a person under the influence of drugs.
2. Section 184. Driving dangerously.
Offences under which traffic crashes are recorded by police• The above provisions are the deciding factor in how a police officer
has to assign blame to one of the participants in a crash (usually one of the drivers)
• This is an important issue, as the ‘cause’ of the crash has to be recorded as a ‘fault’ of a driver under one or more of the above provisions in most cases
• This procedure ensures that 80% or more of the cases get attributed to ‘human error’ and there is no place for understanding crashes as a result of a host of factors including vehicle, road and infrastructure design.
Access FIRs online
• There are FIR copies available online across multiple states
• You need FIR number to download a specific file
• Alternatively, download all the files and check the ones related to traffic crashes
• For this, use IPC and MV act sections to identify the cases
Examples of FIRs
Some examples of IPC sections
Detailed description in FIR
• Often includes information about the victim
• Detail of the traffic crash• The language often reflects the
legal proceedings
Information that can be obtained from reading FIR1. Age and sex: most likely only for the victim and the other individual
involved
2. Types of vehicles or road users involved
3. Date and time-of-day of the crash
4. Location of the crash: though the accuracy can be difficult to determine
5. Type of crash: e.g. head-on crash, sideswipe, overturning, etc.
Important information not available in FIRs
• Use of protective measures e.g. helmet, seat belts, airbags, day-time running lights, etc
• Vehicle technology
• Road features: Often information on road geometry or other features of the road is not available e.g. width of road, number of lanes, whether a median is available or not, speed limit
• Type of injuries of the victims
• Speed of the vehicles
Road death victims in six Indian cities: Vizag, Vadodara, Ludhiana, Bhopal, Amritsar, Agra
• Pedestrians are about 40-50% of all road victims
• Motorcyclists are about 30%
• Cyclists are about 10-15%
Focussing on safety of pedestrians and motorcyclists can bring large benefits in Indian cities
Victims of road deaths in Delhi (2010-2012)
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• Pedestrians and motorised two-wheeler users have the greatest share among road death victims
• Followed by car occupants and cyclists
• This only presents those road users who died in the road crash
• For better understanding, we also need information of other vehicle involved in the crash
Striking vehicles for crashes in which pedestrians or cyclists died
• Cars and trucks (HDV + LDV) have the greatest share
• Motorised two-wheelers are also significantly involved in pedestrian deaths
An example of locating a crash on the map using FIR
First locate the police station
Locate the address on map Searching for ‘Dhaneli Nala’ in google map returns ‘Dhaneli’ village. These are two different things. So we know that this location may not be recorded in google maps
Next, we google Dhaneli Nala and following are the search results
Search gives us a wikimapia link
Following is what we get from that link and there is the geo-location
Now we know our location
Searching the wikimapia coordinates in Google Maps
Now, check the distance between this location and police station– using ‘walk’ mode in google maps is safer
Compare this distance with that reported in FIR
It seems we may be in the right area!
Now we read the description to improve precision of crash location
• Victim was travelling from “Columbia College” and crash occurred when they reached “close to Dhaneli Nala”. Now we know the route and we can use this information to determine the side of the road.
Determining the route that victim took
Zooming in on the location
• Now we have everything that there is in the FIR. We need to make a judgement about the location. The “address” says “Underneath Dhaneli Bridge”. We can use satellite image to see there is a bridge. We finally use this location [21.33627, 81.65009]
Now check the distance of this final location to the police station• It is 5.9 km, making it closer to the distance mentioned in the police
report
Vehicles involved
According to the description, this is a hit-and-run case. The victim was travelling on a scooty(motorised two-wheeler). As she reached close to the bridge near T-junction, she was struck by a truck that was approaching from another approach of the junction.
She was taken to the hospital by an ambulance and was declared dead in the hospital
Road fatality crash map of Patiala city
Road fatality crash map of Agra city
Pedestrian fatality crashes in Bengaluru
https://bengaluru.citizenmatters.in/bengaluru-pedestrian-crashes-deaths-arterial-roads-elderly-speeding-42365
Density map of pedestrian fatal crashes in Delhi
Determinants of safety of vulnerable road users in Delhi Other
modes
Fatality victims
RoundaboutsFlyovers
Traffic volume
59Wards in Delhi
GIS database development
60Geocoding of road infrastructure Geocoding of road accidents
Traffic volume by modes
Population and demographics
Built-up area
Higher safety in wards with:▪ Roundabouts▪ Higher population density▪ Higher literacy rates
Lower safety in wards with:▪ Higher traffic volume▪ Flyovers▪ Bus Stops
Density and fatality risk
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Determinants of safety of vulnerable road users
Impact of alcohol pricing and traffic fines on road crashes in Botswana
Sebego, M., Naumann, R. B., Rudd, R. A., Voetsch, K., Dellinger, A. M., & Ndlovu, C. (2014). The impact of alcohol and road traffic policies on crash rates in Botswana, 2004–2011: a time-series analysis. Accident Analysis & Prevention, 70, 33-39.
• Note that outcome (y-axis) is crash rate
• Here, it is calculated as number of crashes divided by the fuel sales per month
• In this case, fuel sales is the exposure
Impact of child restraint legislation in Chile
Ignacio Nazif-Muñoz, José; Nandi, Arijit; Ruiz-Casares, Mónica (2018). Impact of child restraint policies on child occupant fatalities and injuries in Chile and its regions: An interrupted time-series study. Accident Analysis & Prevention, 120(), 38–45. doi:10.1016/j.aap.2018.07.028
• Note that outcome (y-axis) is child severe injury per one million motor vehicle
• In this case, number of motor vehicle is the exposure
Summary
• NCRB and MORTH reported data is important because they provide consistent reporting of road accident statistics over the years for the same set of states and cities
• Some states also report road deaths for their respective districts
• This data can be used to understand the road safety levels across the country and helps in comparison
• Helps build public pressure to improve safety through media reportage
• However, it cannot be used for detailed crash-level investigation, for example, to assess the safety of a road junction
Summary
• We need alternative sources of data
• We can access FIRs of road crashes from police websites
• Details of each crash along with the location can be extracted
• Still the FIRs of only fatal crashes can be used, as injury related crashes would be underreported
• For the near future, road safety researchers need to rely on such data sources
