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Using the PCM philosophy and including 5 seconds before the accident in the crash analysis combined with the driving behaviours of the vehicles out of PC-Crash, it is possible to analyse, whether or not a sensor system would have been able to recognise the dangerous situation in time to avoid or mitigate the accident.

Each accident in this sample is modeled numerically by the simulation tool PC-Crash. In parallel, a model representing the function of an AEB system has been established.

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.

Furthermore, 183car-to-pedestrian cases, with detailed information regarding accident vehicles, pedestrians and environment, were reconstructed using PC-Crash. A hypothetical autonomous braking system would activate when the pedestrian successfully detected by the sensing system and then new impact speeds will be calculated.

Development of crash avoidance systems and active safety systems must not be only based on experimental knowledge. The goal is to provide an efficient answer to still unsolved severe real-world car crashes which occur despite enhanced passive safety devices. This requires to know precisely the pre-crash conditions during about 3 to 10 seconds before impact. The paper describes the multidisciplinary systemic approach leading to the comprehensive methodology used in accident reconstruction in order to determine the best scenario, and to assess initial car speeds, paths and events in the different phases of the accident. This has already been carried out for about 400 car crashes with car occupant injuries (including 6% fatal and 10% severely injured). The necessity of collecting data on the spot of the crash scene is highlighted. Three well-trained investigators are involved.