Many Vulnerable Road Users (VRUs) experience injuries and fatalities every year, making road safety a challenge in the World. According to the Ministry of Road Transport and Highway (MoRTH) during the year 2021, a total number of 4,12,432 road accidents have been reported in India, claiming 1,53,972 lives and causing injuries to 3,84,448 persons. In terms of road-user categories, the total fatality of the Pedestrian road-users was 18.9 per cent of persons killed in road accidents.
One of the ways to handle the situation is to protect pedestrians utilizing active safety measures in the vehicle. In addition, active safety research heavily relies on perceptions of pre-crash scenarios. The objective of the study is to examine passenger car-to-pedestrian scenarios and model active safety system in a car to prevent or mitigate collisions.
Road Accident Sampling System – India (RASSI) database is used for this research, which provided a comprehensive set of accident data describing the interaction between the vehicle, the environment and the pedestrian. RASSI has collected in depth information of more than 6000 cases from the year 2011 in India. From RASSI database, query was performed for car-to-pedestrian accident from the year 2019 to 2022. After querying, 48 cases were considered for the study. The study solely considers cars, thus pertinent information on the location of the pedestrian in relation to the vehicle and the time before impact is gathered using the accident reconstructions available in RASSI.
The study is conducted in two parts. Firstly, the study focuses on identifying the optimum Field-Of-View (FOV) for a stereo camera sensor for Pedestrian detection. The second part of the study uses the data from the FOV study to model active safety system and evaluate its effectiveness on the queried scenarios collected from RASSI in PC-Crash. Proposed active safety system shows the promise for future work related to developing active safety system for car-to-pedestrian scenarios in India.