Abstract
The primary goal of the pavement is to provide a safe and smooth riding surface. Few research studies have explored the influence of geopathic stress in road accidents. Still, its effect on the pavement distresses and, as a result, on-road accidents are yet to be explored. This research aims to formulate regression models between the average number of accidents with geopathic stress and Pavement Condition Index (PCI) values. For Pune city, 36 accident black spots on the flexible pavement are considered, and accident data from 2016 to 2020 has been used. On each spot, the Pavement Condition Index (PCI) is determined using the traditional, precise manual method as per IRC 82:2015. Geopathic stress is measured using the innovative NAAV meter instrument. In the NAAV meter due to the influence of geopathic stress, the laser beam deviates, which can be visually observed; which is not possible with other devices such as Esmog Spion and magnetometer. Three linear regression models are developed. The first one relates the average number of road accidents (Ā) with the Pavement Condition Index (PCI). In contrast, the second one relates (Ā) with the electric field output on account of the interference of geopathic stress with a laser beam emitted from the source in the NAAV meter, (NR) in microamperes. Equation three relates the pavement condition index (PCI) with (NR) as well. It is found that the number of accidents increases on distressed spots with the increase in geopathic stress. The mathematical models developed would effectively establish a relationship between road accidents, geopathic stress, and pavement surface condition. This would further enable transportation authorities to predict the number of road accidents at specific locations on existing pavement. In addition, transport authorities can economize at the road maintenance cost by identifying critically distressed sections at black spots which are severely impacted by weak electromagnetic fields emanating from the subgrade on account of the geopathic stress.
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