Reconstruction of an auto-rickshaw frontal crash using FE simulation with validation using captured crash video from India

The three wheeled “Auto-Rickshaws” [Auto] plays a significant role in road transportation, especially in India. The crash safety and reconstruction studies have been widely used in four wheelers, whereas the availability of such data for Auto was found to be limited. In recent times, accident data processing from available videos is being utilised to observe the crash scenario, from which the crash parameters can be given as inputs to the crash analysis. This paper focusses on process the real-world accident data and study crash characteristics. With limitation in availability of detailed injuries post-crash, the study was restricted to reconstruction of crash kinematics and estimations of indicative injuries to driver. The source of video data is videos of crash available in public domains like YouTube. PYTHON video processing tool has been used to process the set of real-world accident video data. The object detection, Pixel per meter computation and object tracking are the major steps carried out to process the accident data, from which the collision speed is obtained. The auto-rickshaw CAE model and driver dummy (Adult male 50 percentile) were used in LS DYNA to conduct crash analysis at obtained collision speed. The reconstructed crash with matching kinematics, showed that the driver experienced a noticeable amount of impact forces near neck joint and knees. This methodology is proposed as a step in the direction of understanding occupant safety in auto rickshaws.