Home // GEOProcessing 2017, The Ninth International Conference on Advanced Geographic Information Systems, Applications, and Services // View article
Authors:
Lucas José Machado
Diogo Bortolini
Fabiano Baldo
Keywords: Graphs Theory; Centrality; Connectivity; Bicycle Paths; Decision Support System.
Abstract:
Bicycle paths are increasingly becoming part of road infrastructure of cities. However, the expansion of bicycle paths network demands planning to prioritize investment in order to attend the population needs properly. The connectivity between bicycle paths is considered the most important issue pointed out by cyclists. In this work, it is assumed that the problem of planning bicycle path networks can be solved by using graph theory. Therefore, this work proposes a decision support to help planning bicycle path network, prioritizing the connectivity between the existing bicycle paths by using concepts of clustering, centrality and shortest path. In experiments performed in Joinville -- Brazil, it could be seen that the proposed method can help specialists by promoting discussions about the bicycle path network connectivity. Also, it was observed that the usage of graph database increased considerably the solution performance.
Pages: 51 to 56
Copyright: Copyright (c) IARIA, 2017
Publication date: March 19, 2017
Published in: conference
ISSN: 2308-393X
ISBN: 978-1-61208-539-5
Location: Nice, France
Dates: from March 19, 2017 to March 23, 2017