Road Network Impedance Factor Modelling Based on Slope and Curvature of the Road
Abstract
Travelling in hills like Himalaya is very time-consuming due to presence of high slope and curvature in the road. Travel time is also affected by condition of the road i.e. surface roughness, rut depth, pavement conditions etc. However, for this research paper only slope and curvature is considered. To plan the journey in proper way, exact time required for travelling plays key role for any person. Google is providing best route to travel and estimated time required between source and destination. This travel time estimate by Google is up to the mark in plain region but not satisfactory in hills. Because road transportation network in hills contains a lot of curvature and slope of the network in also very high and varying due to undulating terrain of the mountains. Therefore, in this research a technique is proposed to calculate better travel time estimate. Proposed technique considers natural obstacles to the travel speed in the hills like slope and curvature. In this a network model is proposed which assigns average driving speed to the road segment, and this driving speed is calculated by percentage rise in the slope & radius of curvature of the road segment. Model takes road network and raster image of slope in degrees. Open source tools and languages (Python, GDAL, and QGIS) are used to make this model. Results of proposed network model are near to the ground truth value.
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*2016 Journal Impact Factor was established by dividing the number of articles published in 2014 and 2015 with the number of times they are cited in 2016 based on Google Scholar, Google Search and the Microsoft Academic Search. If ‘A’ is the total number of articles published in 2014 and 2015, and ‘B’ is the number of times these articles were cited in indexed publications during 2016 then, journal impact factor = A/B. To know More: (http://en.wikipedia.org/wiki/Impact_factor)