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Automation in construction, 2021-07, Vol.127, p.103557, Article 103557
2021
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Details

Autor(en) / Beteiligte
Titel
Human centric accessibility graph for environment analysis
Ist Teil von
  • Automation in construction, 2021-07, Vol.127, p.103557, Article 103557
Ort / Verlag
Amsterdam: Elsevier B.V
Erscheinungsjahr
2021
Quelle
Alma/SFX Local Collection
Beschreibungen/Notizen
  • Understanding design decisions in relation to the future occupants of a building is a crucial part of good design. However, limitations in tools and expertise hinder meaningful human-centric decisions during the design process. In this paper, a novel Spatial Human Accessibility graph for Planning and Environment Analysis (SHAPE) is introduced that brings together the technical challenges of discrete representations of digital models, with human-based metrics for evaluating the environment. SHAPE: does not need labeled geometry as input, works with multi-level buildings, captures surface variations (e.g., slopes in a terrain), and can be used with existing graph theory (e.g., gravity, centrality) techniques. SHAPE uses ray-casting to perform a search, generating a dense graph of all accessible locations within the environment and storing the type of travel required in a graph (e.g., up a slope, down a step). The ability to simultaneously evaluate and plan paths from multiple human factors is shown to work on digital models across room, building, and topography scales. The results enable designers and planners to evaluate options of the built environment in new ways, and at higher fidelity, that will lead to more human-friendly and accessible environments. •Human movement and accessibility in the built environment is strongly linked to the geometry.•A ray-cast method for creating a grid-based weighted directed accessibility graph is proposed.•Path-planning is automatically evaluated and produced by human-centric measures.•Method is shown on rooms, building, large uneven terrain, steps, slope, cross-slope.•Early-stage high-fidelity design feedback based on human factors is possible.
Sprache
Englisch
Identifikatoren
ISSN: 0926-5805
eISSN: 1872-7891
DOI: 10.1016/j.autcon.2021.103557
Titel-ID: cdi_proquest_journals_2552120757

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