Record nummer 1938353
Titel Pedestrian route planning in a hybrid data environment : calculating optimal routes based on vector and raster data
toon extra info.
J.H. Bakermans
Auteur(s) Bakermans, J.H.
Uitgever [S.l. : s.n.]
Jaar van uitgave 2010
Pagina's 45 p ill
Titel van reeks Thesis report GIRS (2010-13)
Msc Thesis Wageningen University
Online full text
Trefwoorden (cab) lopen / wandelpaden / planning / paden / geografische informatiesystemen / computer software / navigatie
Rubrieken Geografische informatiesystemen / Openluchtrecreatie
Publicatie type Studentenverslag
Taal Engels
Toelichting (Engels) Navigation is a common daily activity for human beings and people use a wide range of tools to make it easier. Following car drivers pedestrians have found their way to route planning, however a suitable dataset is not yet provided. Due to their origin in car navigation current pedestrian navigation datasets do not include free walkable space. This is open space that can be freely accessed by fit pedestrians e.g. squares, parks or parking lots. This drawback leads to the idea for this research. It presents an approach that uses a hybrid data environment with both vector and raster data to calculate an optimal path as part of pedestrian route planning. Hence, the research objective is to calculate the optimal route for pedestrians in an urban environment based on a hybrid dataset that contains vector network data to represent corridor-like paths and raster data to represent free walkable space. To reach the objective a method is provided on a conceptual level. First the free walkable space is to be derived from the topographical map. Next, the free walkable space has to be divided by a user into subspaces with equal accessibility values. The resulting weighted free walkable space together with a road dataset can then be used to calculate paths passing through the free walkable space. In this process a set of fixed paths is also created. Subsequently, the fixed paths and the internal paths are joined into one pedestrian infrastructure dataset. The latter is used to create a network dataset on which Dijkstra’s algorithm can be applied to find the shortest path (Dijkstra, 1959). Implementation of the method takes place by using ESRI’s ArcGIS Desktop software and the Python programming language. Furthermore some user actions are required for editing and adding expert knowledge. Finally this implementation was applied on a case study in the city center of ‘s-Hertogenbosch (NL) and to test resulting network dataset, three source/destination scenarios were assessed. Overall the method implemented on a case study provides satisfying results as it returns plausible pedestrian routes that are slightly better than conventional methods. Main shortcomings involve parameters to fine tune the implementation: even a minor change can have major effect on the final output. Furthermore, the method lacks an inconsistency check for fixed paths and walkable areas which causes the network to be imperfect. Additionally the raster path calculation used still fails to yield the desired paths. Future research should focus on the derivation of fixed walkable paths to match with the walkable area and on optimizing path calculation in a raster environment.
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