CALCULATING LEAST RISK PATHS IN 3D INDOOR SPACE
Over the last couple of years, research on indoor environments has gained a fresh impetus; more specifically applications that support navigation and wayfinding have become one of the booming industries. Indoor navigation research currently covers the technological aspect of indoor positioning and t...
Main Authors: | , , , |
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Format: | Article |
Language: | English |
Published: |
Copernicus Publications
2013-08-01
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Series: | The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
Online Access: | http://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XL-2-W2/113/2013/isprsarchives-XL-2-W2-113-2013.pdf |
Summary: | Over the last couple of years, research on indoor environments has gained a fresh impetus; more specifically applications that
support navigation and wayfinding have become one of the booming industries. Indoor navigation research currently covers the
technological aspect of indoor positioning and the modelling of indoor space. The algorithmic development to support navigation
has so far been left mostly untouched, as most applications mainly rely on adapting Dijkstra's shortest path algorithm to an indoor
network. However, alternative algorithms for outdoor navigation have been proposed adding a more cognitive notion to the
calculated paths and as such adhering to the natural wayfinding behaviour (e.g. simplest paths, least risk paths). These algorithms are
currently restricted to outdoor applications. The need for indoor cognitive algorithms is highlighted by a more challenged navigation
and orientation due to the specific indoor structure (e.g. fragmentation, less visibility, confined areas…). As such, the clarity and
easiness of route instructions is of paramount importance when distributing indoor routes. A shortest or fastest path indoors not
necessarily aligns with the cognitive mapping of the building. Therefore, the aim of this research is to extend those richer cognitive
algorithms to three-dimensional indoor environments. More specifically for this paper, we will focus on the application of the least
risk path algorithm of Grum (2005) to an indoor space. The algorithm as proposed by Grum (2005) is duplicated and tested in a
complex multi-storey building. The results of several least risk path calculations are compared to the shortest paths in indoor
environments in terms of total length, improvement in route description complexity and number of turns. Several scenarios are tested
in this comparison: paths covering a single floor, paths crossing several building wings and/or floors. Adjustments to the algorithm
are proposed to be more aligned to the specific structure of indoor environments (e.g. no turn restrictions, restricted usage of rooms,
vertical movement) and common wayfinding strategies indoors. In a later stage, other cognitive algorithms will be implemented and
tested in both an indoor and combined indoor-outdoor setting, in an effort to improve the overall user experience during navigation
in indoor environments. |
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ISSN: | 1682-1750 2194-9034 |