Geoscience Reference
In-Depth Information
Calculating Least Risk Paths
in 3D Indoor Space
Ann Vanclooster, Philippe De Maeyer, Veerle Fack
and Nico Van de Weghe
Abstract
Over the last couple of years, applications that support navigation and
wayfinding in indoor spaces have become one of the booming industries. However,
the algorithmic development to support indoor navigation has so far been left
mostly untouched, as most applications mainly rely on adapting Dijkstra's shortest
path algorithm to an indoor network. In outdoor space, several alternative algo-
rithms 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). 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…). Therefore, the aim of this research
is to extend those richer cognitive algorithms to three-dimensional indoor environ-
ments. More specifically for this chapter, we will focus on the application of the
least risk path algorithm of Grum (
2005
) to an indoor space. The algorithm as pro-
posed by Grum (
2005
) is duplicated and tested in a complex multi-storey building.
The results of several least risk path calculations are compared to their equivalent
shortest paths in terms of path length, improvement in route description complex-
ity and riskiness of the selected edges. The tests lead to the conclusion that the
original least risk path algorithm has to be adjusted to be more compatible with the
