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METHODOLOGY

  • tab2tab1RASSI Methodology
  • tab5over-imgSample Data Set
Methodology

The data entered in the RASSI database is a result of accident investigations conducted by researchers trained by experienced international experts. This analytical database is based on international databases such as the National Automotive Sampling System - Crashworthiness Data System (NASS-CDS) of the USA, German In-Depth Accident Study (GIDAS) of Germany and Co-Operative Crash Injury Study (CCIS) from the UK and is tailor made to suit Indian conditions. To ensure correct coding and interpretation, a coding manual has been developed which ensures that researchers and other RASSI database users have a common understanding of the data coded.

No personal or proprietary information is stored in RASSI. The data is anonymized and, as part of the quality check processes, steps are taken to ensure that no personal data involving any names, addresses of victims, vehicle numbers, etc. are collected in the database. RASSI's Data Privacy and Protection protocol lays down measures to remove all details from the accident data collection system that can lead back to the identification of an accident vehicle or a victim of an accident, and the data thus collected is used for research purposes only.

Every case undergoes stringent quality control procedures, technical quality checks and system validations before it is released to the RASSI consortium members. This way, the consistency and quality of data is ensured, which forms the essential characteristic of RASSI data.

Dataset as of 31st December 2022

Total accidents in RASSI database: 6937

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