Study of the applicability of cognitive path algorithms for 3D indoor navigation

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On the way of integrating evacuation approaches

With the growing pressure on available urban space and the construction of more and more complex building infrastructures, the navigational task for building users is getting increasingly difficult. As people react more impulsive under stressful situations, emergencies can exacerbate way finding problems. Additionally, leadership and familiarity with the (topological structure of a) building can influence the ease of finding appropriate evacuation routes. In research, two separate and distinctive techniques for modelling evacuation paths have been developed: evacuation simulation modelling through complex computer simulations and 3D network modelling based on graph theory. Taking into account a global user perspective, the 3D network modelling approach has the advantage to preserve a close connection with the semantic building structure. Following this approach, existing three dimensional evacuation routing algorithms tend to use Dijkstra's shortest path algorithm. However, as more factors, compared to path length, influence evacuation situations, literature acknowledges a void in representing more realistic, complete and accurate emergency situations. This paper presents a first step in creating such integral algorithm by implementing capacity constraints based on user flow control on a 3D geometric network model. In the future additional topics such as zonal partitioning can be added to the algorithm, moving to an integration of both evacuation approaches

An automated 3D modeling of topological indoor navigation network

© 2015, Springer Science+Business Media Dordrecht. Indoor navigation is important for various applications such as disaster management, building modeling, safety analysis etc. In the last decade, indoor environment has been a focus of wide research that includes development of indoor data acquisition techniques, 3D data modeling and indoor navigation. In this research, an automated method for 3D modeling of indoor navigation network has been presented. 3D indoor navigation modeling requires a valid 3D model that can be represented as a cell complex: a model without any gap or intersection such that two cells (e.g. room, corridor) perfectly touch each other. This research investigates an automated method for 3D modeling of indoor navigation network using a geometrical model of indoor building environment. In order to reduce time and cost of surveying process, Trimble LaserAce 1000 laser rangefinder was used to acquire indoor building data which led to the acquisition of an inaccurate geometry of building. The connection between surveying benchmarks was established using Delaunay triangulation. Dijkstra algorithm was used to find shortest path in between building floors. The modeling results were evaluated against an accurate geometry of indoor building environment which was acquired using highly-accurate Trimble M3 total station. This research intends to investigate and propose a novel method of topological navigation network modeling with a less accurate geometrical model to overcome the need of required an accurate geometrical model. To control the uncertainty of the calibration and of the reconstruction of the building from the measurements, interval analysis and homotopy continuation will be investigated in the near future