Leveraging road accident database to enhance ADAS features and testing protocols in context of Indian driving conditions

Advanced Driver Assistance Systems (ADAS) are pivotal in enhancing road safety by reducing human error and assisting drivers in critical situations. Since, major ADAS technologies are developed and validated using data and test scenarios that are predominantly based on driving conditions and road environments of developed countries. But for country like India where driving behaviour, traffic dynamics, road infrastructure and the accident characteristics differ significantly, the ADAS technologies and test scenarios validated by different forums create a critical gap in deploying such systems on vehicles to work on Indian roads. The objective of this research is to identify and generate India specific ADAS test scenarios from the Road Accident Sampling system India (RASSI) database, available MoRTH reports, data available from previously executed ADAS test cases, etc. Through this research we propose a methodology to identify, extract and analyse accident scenarios pertaining to Indian driving environment and their usefulness in developing the ADAS technologies to result best when deployed on vehicles in India. The RASSI database provides exposure to various different data factors related to accidents from the accident reconstructions like velocities at different time stamps, position of vehicles with respect to time, pre-crash manoeuvres etc. Also, the data from MoRTH reports regarding different category of vehicle collisions will be analysed extensively for scenario identification and generation for evaluation of different ADAS features such as automatic emergency braking, lane departure warning, pedestrian detection, and blind spot monitoring. Furthermore, the data generated from available ADAS Test validations will also be examined to verify the different parameters related to specific ADAS features. For validation of the identified Test scenarios, the scenarios will be simulated in the available simulation software to check the functioning of ADAS technology if present in the identified scenario. The work aims to bridge the localization gap in ADAS validation by offering a standardized and data-driven approach for generating test scenarios specific to Indian conditions. This will not only facilitate the development of safer and more effective ADAS solutions for India but also support regulatory bodies in formulating context-aware safety benchmarks.