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Comprehensive Analysis of Indian Road Accident Data to Enrich Road Safety


Pal Chinmoy
Nissan Motor Company, Japan

Nobuhiko Takahashi

Natarajasundaram Balasubramanian, Jeyabharath Manoharan, Narahari Sangolla, Vimalathithan Kulothungan
Renault Nissan Technology Business Center India, India

Padhy Sitikantha


MoRTH 2016 annual report clearly indicated that the number (150,785) of road accident fatalities are increasing every year in India. Also, number of accident severity cases were increased by 7.9% compared to CY2015. Hence, it is an important task to find out the accident characteristics on Indian roads in order to implement appropriate cost effective safety measures to reduce the fatalities. The objective of this study is to properly identify the main road safety issues in India using MoRTH and ADAC, NATRiP accident databases based on a triple-layer approach (i) “Society”: factors related to infra-structure (ii) “Individual”: factors related to Human factors and (iii) “Vehicle”: factors related to Vehicle. At first, macro accident analysis was performed on MoRTH 2016 data and then followed by micro accident analysis carried out with ADAC, NATRiP accident data (National Highway-08). In order to identify the characteristics for those NH-08 accidents, a data mining approach Self-Organizing Maps (SOM) method was applied. Micro-accident analysis results indicate that more signal availability (30%) in urban areas compared to that in rural areas leads to less intersection accidents. Improper driving-manner (30%), improper lane-change (16%), failing to use restraint system (29%) are some of the important elements related to individual. Rear crashes (54%), angled/side crashes at junctions (14%), accidents caused by trucks (48%), and hitting stranded parked-vehicles (24%) are the influential factors related to vehicles. Five basic traffic injury patterns are revealed by SOM analysis within ADAC-NATRiP data and a few countermeasures were proposed for each group separately.

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