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.

Highlights

  • Significant modelling of any real world phenomenon requires proper representation of the object

  • Road networks are geometric networks, a geometric network is composed of nodes and edges where nodes are junction points and edges are road segments

  • For each real world road network, direction and impedance must be assigned with each edge to calculate travel cost/time (Husdal, 1999)

Read more

Summary

Introduction

Significant modelling of any real world phenomenon requires proper representation of the object. Geographic information system (GIS) provides facility to represent real world. One of the GIS tool is network analysis tool, which is having functionalities to calculate optimum path, closest facility, service area etc. According to Lupien et al, (1987) network is a line graph composed of links & nodes where links represent linear channels of flow, and nodes represent connections of links. For each real world road network, direction and impedance must be assigned with each edge to calculate travel cost/time (Husdal, 1999). Transportation planning requires network analysis in situations like finding the shortest path, service area within a specified travel cost (Husdal, 1999)

Objectives
Methods
Results
Full Text
Paper version not known

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.