Padmanaban, J., Rajaraman, R., Narayan, S., Arjun, C. et al., "RASSI: A Systematic Approach for On-site Crash Investigations and In-depth Accident Data Collection in India," SAE Technical Paper 2013-26-0031, 2013, doi:10.4271/2013-26-0031.
India's growing trend of serious road accidents has created an urgent need to understand the primary factors involved in these crashes and in the resulting severe injuries and fatalities. In order to improve the safety of highways and automobiles for all road users, a consortium of safety researchers and vehicle manufacturers has come together to collect first-hand, detailed and consistent crash and injury data for traffic accidents on Indian roads. After three years of pilot studies, a methodology, called Road Accident Sampling System - India (RASSI), has been developed for conducting on-site crash investigations and collecting in-depth accident data on road accidents in India.The processes developed under RASSI to investigate onsite crashes and collect quality accident data suitable for detailed analysis are described. The program includes all types of traffic accidents with injury outcomes. This paper focuses on the current investigation area of the Coimbatore district in the state of Tamil Nadu in India. The RASSI team consists of trained automotive engineers and injury coding experts who work in collaboration with the state police. To assure that the data collected will serve not only current but unforeseen future research needs, on-site crash investigations include - (1) photographing the crash site and vehicles and creating true-to-scale diagrams of the accident scene; (2) examining crash vehicles, including deformations, intrusions and human contacts; and (3) detailed injury coding of the involved victims. Critical crash information, such as driving and collision speed, (Delta-v), is determined from traces at the scene as well as from vehicle deformation patterns for the assessment of energy speed absorption. The possible ways to make calculations and accident reconstructions from the collected data are described, and the benefit of such comprehensive in-depth accident data collection is shown, along with examples correlating technical parameters with injury outcome.