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Road Network Impedance Factor Modelling Based on Slope and Curvature of the Road


 
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1. Title Title of document Road Network Impedance Factor Modelling Based on Slope and Curvature of the Road
 
2. Creator Author's name, affiliation, country Prabhakar Alok Verma; Geoinformatics Department, Indian Institute of Remote Sensing-ISRO, Dehradun, Uttrakhand, India
 
2. Creator Author's name, affiliation, country Kislay Kumar; Department of Information Technology, Institute of Engineering & Management, Kolkata, Bengal, India
 
2. Creator Author's name, affiliation, country sameer Saran; Geoinformatics Department, Indian Institute of Remote Sensing-ISRO, Dehradun, Uttrakhand, India
 
2. Creator Author's name, affiliation, country (doi: 10.23953/cloud.ijarsg.289)
 
3. Subject Discipline(s)
 
3. Subject Keyword(s) Curvature; GIS; Impedance; Python
 
4. Description 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.
 
5. Publisher Organizing agency, location
 
6. Contributor Sponsor(s)
 
7. Date (YYYY-MM-DD) 2017-09-05
 
8. Type Status & genre Peer-reviewed Article
 
8. Type Type
 
9. Format File format PDF
 
10. Identifier Uniform Resource Identifier http://technical.cloud-journals.com/index.php/IJARSG/article/view/761
11. Source Journal/conference title; vol., no. (year) International Journal of Advanced Remote Sensing and GIS; Volume 6 (Year 2017)
 
12. Language English=en en
 
14. Coverage Geo-spatial location, chronological period, research sample (gender, age, etc.)
 
15. Rights Copyright and permissions

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