Understanding road traffic crashes in India through a data-driven approach.

Transcription

1 1 November 22-23, 2017 New Delhi Understanding road traffic crashes in India through a data-driven approach. Ravishankar Rajaraman, JP Research India Pvt. Ltd.

2 Road Accident Sampling System - India 2 On-site crash investigation and in-depth data collection. Initiated in 2011 by a consortium of OEMs.

3 Road Accident Sampling System - India 3

4 Road Accident Sampling System - India 4

5 Road Accident Sampling System - India 5 IN-DEPTH CRASH DATA ACCIDENT VEHICLE PEDESTRIAN / OCCUPANT INJURIES CRASH FILES Summary GPS Road Structure Pre-crash event Kind of Accident Crash Configuration Specifications Deformation Intrusions Contacts Safety Systems Pre-crash events Speeds Legal compliance Age/Gender Role Activity Ejection Entrapment Seat Position Safety System Use EMS Data Injury description AIS Injury Source Field Data Forms Pictures Crash Scene Vehicles Scene Diagram PC Crash

6 Improving crash data reporting 6

7 Identify contributing factors Haddon Matrix 7

8 Let s investigate a crash! 8 CAR Crash time: 01:15 hrs One occupant of car fatal. The occupant was entrapped. Evacuation took hours. TRUCK

9 Crash Scene Examination 9 Car Travel direction of tipper Identification and marking of vehicle trajectories (skid/brake marks), point of impact and final resting positions. Documenting with photographs.

10 Crash Scene Diagram (To scale) 10

11 Crash Vehicle Examination 11

12 CCTV Footage 12

13 CCTV Footage Speed Calculation for Tipper 13 Time - 1:45:705 (m:ss:ms) Time - 1:47:278 (m:ss:ms) Distance : 17.4m for tipper

14 CCTV Footage Speed Calculation for Car 14 Time - 1:45:685 (m:ss:ms) Time - 1:47:269 (m:ss:ms) Distance : 9m for car

15 Vehicle Average Speed Calculations 15 Vehicles Values Average Speed (kmph) V = distance / time (m/s) x 3.6 Tipper d = 17.4 m t = s 40 Car d = 9 m t = s 18

16 Crash Reconstruction Accident View Tipper driver view 16 Sight distance is low for both vehicles due to median plantation and fencing.

17 Apply Haddon Matrix to tipper-car crash 17 Car - Violation of right of way Truck - Overloading Vision obstruction due to median plantation Car - Passenger compartment intrusion Car Occupant Entrapment Car Occupant Evacuation

18 Road Safety Priorities and Low Hanging Fruits 18 Based on crashes investigated over a period of time, the contributing factors identified for all crashes can help in determining: Priorities Top contributing factors that need to be addressed. Low hanging fruits Quick and low cost implementations with high ROI.

19 Road Safety Priorities and Low Hanging Fruits Using crash data from: Urban Areas (Kolkata and Ahmedabad) 2. Rural Roads, NH and SH (Coimbatore Rural District) 3. Expressways (Mumbai Pune Expressway)

20 Urban Areas Who is Affected? 20 Pedestrians account for nearly 60% of fatalities in Kolkata. Poor walking and road crossing infrastructure a major contributing factor.

21 Urban Areas Accident Types 21 Source: JPRI Kolkata Fatal Accident Study Report

22 Urban Areas Contributing Factors 22 Infrastructure Poor pedestrian infrastructure (100%) Road marking and signage and intersection design (100%) Vehicle Bus/Truck run overs (34%) Self fall of 2-wheelers (33%) Vision obstruction due to vehicle interiors (8%) Human Speeding over 30 kmph at an intersection (77%) Helmet not used (52%) Driver inattention/distraction (8%) Source: JPRI Kolkata Fatal Accident Study Report 2016, Ahmedabad Urban Accident Study

23 Rural Roads, NH, SH Who is affected? 23 Source: JPRI Coimbatore Rural Road Accident Study 2016

24 Rural Roads, NH, SH Accident Types 24 Source: JPRI Kolkata Fatal Accident Study Report 2016, Ahmedabad Urban Accident Study

25 Rural Roads, NH, SH Contributing Factors 25 Infrastructure Undivided roads (35%) Poor lighting, pedestrian infrastructure and intersection design(16%) Impacts with road side objects (6%) Vehicle Bus/Truck run overs (12%) Passenger compartment intrusion (9%) Seatbelts not available/usable (6%) Human Overtaking on undivided roads (24%) Helmet, Seatbelt not used (59%, 11%) Improper lane change/lane usage (15%) Source: JPRI Kolkata Fatal Accident Study Report 2016, Ahmedabad Urban Accident Study

26 Expressways Who is affected? 26 Source: JPRI Mumbai-Pune Expressway Road Accident Study Report 2016

27 Expressways Accident Types 27 Source: JPRI Mumbai-Pune Expressway Road Accident Study Report 2016

28 Expressways Contributing Factors 28 Infrastructure Impacts with road side objects (26%) Narrow or No shoulders and sharp road curvatures (16%) Inadequate warning about breakdown/accident/parked vehicle (4%) Vehicle Passenger compartment intrusion (66%) Occupant ejections (20%) Seat belts not available/ usable (18%) Human Improper lane change or speeding over 80 kmph (59%) Seatbelt not used (57%) Driver sleep/fatigue (27%) Source: JPRI Mumbai-Pune Expressway Road Accident Study Report 2016

29 Low hanging fruits Take your pick 29 Infrastructure Road marking and signage Pedestrian infrastructure Safer roadside barriers Breakdown/Accident Assistance Vehicle Bus/Truck run overs and driver vision improvements Make seatbelts usable Underrun protection devices Human Helmet/Seatbelt usage Speed limit enforcement Low cost solutions available. Fastest ROI. Vehicle design changes. Long term ROI. Most difficult to enforce. ROI depends on sustained efforts.

30 Safer guardrail designs on Mumbai Pune Expressway 30 X Zero Fatality Corridor Project Intervention Guardrail end-tapers removed and replaced with bull nose. Guardrail run-out length increased from 30 meters to over 60 meters.

31 THANK YOU! 31