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Evidence-Based Parametric Design: Computationally Generated Spatial Morphologies Satisfying Behavioural-Based Design Constraints
Human-Centred Cognitive Assistance Research Group, University of Bremen, Bremen, Germany. (The DesignSpace Group, Germany)ORCID iD: 0000-0003-0392-026x
University of Münster, Münster, Germany. (The DesignSpace Group, Germany)
Human-Centred Cognitive Assistance Research Group, University of Bremen, Bremen, Germany. (AASS; The DesignSpace Group, Germany)ORCID iD: 0000-0002-6290-5492
2017 (English)In: 13th International Conference on Spatial Information Theory (COSIT 2017), Springer International Publishing AG , 2017, Vol. 86, p. 11:1-11:14Conference paper, Published paper (Refereed)
Abstract [en]

Parametric design is an established method in engineering and architecture facilitating the rapid generation and evaluation of a large number of configurations and shapes of complex physical structures according to constraints specified by the designer. However, the emphasis of parametric design systems, particularly in the context of architectural design of large-scale spaces, is on numerical aspects (e.g., maximising areas, specifying dimensions of walls) and does not address human-centred design criteria, for example, as developed from behavioural evidence-based studies. This paper aims at providing an evidence-based human-centred approach for defining design constraints for parametric modelling systems. We determine design rules that address wayfinding issues through behavioural multi-modal data analysis of a wayfinding case study in two healthcare environments of the Parkland hospital (Dallas). Our rules are related to the environmental factors of visibility and positioning of manifest cues along the navigation route. We implement our rules in FreeCAD, an open-source parametric system.

Place, publisher, year, edition, pages
Springer International Publishing AG , 2017. Vol. 86, p. 11:1-11:14
Series
Leibniz International Proceedings in Informatics, LIPIcs, E-ISSN 1868-8969 ; 86
Keywords [en]
parametric modelling, behavioural studies, Evidence-Based Design, design computing, wayfinding, spatial cognition
National Category
Computer Sciences
Identifiers
URN: urn:nbn:se:oru:diva-63587DOI: 10.4230/LIPIcs.COSIT.2017.11Scopus ID: 2-s2.0-85026824906ISBN: 9783959770439 (electronic)OAI: oai:DiVA.org:oru-63587DiVA, id: diva2:1168923
Conference
13th International Conference on Spatial Information Theory (COSIT 2017), L'Aquila, Italy, September 4-8, 2017
Available from: 2017-12-21 Created: 2017-12-21 Last updated: 2018-11-06Bibliographically approved

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Kondyli, VasilikiBhatt, Mehul

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Citation style
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