Visuo-Locomotive Complexity as a Component of Parametric Systems for Architecture Design

EasyChair Preprint 4811

Abstract

A people-centred approach for designing large-scale built-up spaces necessitates systematic anticipation of user's embodied visuo-locomotive experience from the viewpoint of human-environment interaction factors pertaining to aspects such as navigation, wayfinding, usability. In this context, we develop a behaviour-based  visuo-locomotive complexity model that functions as a key correlate of cognitive performance vis-a-vis internal navigation in built-up spaces. We also demonstrate the model's implementation and application as a parametric tool for the identification and manipulation of the architectural morphology along a navigation path as per the parameters of the proposed visuospatial complexity model. We present examples based on an empirical study in two healthcare buildings, and showcase the manner in which a dynamic and interactive parametric (complexity) model can promote behaviour-based decision-making throughout the design process to maintain desired levels of visuospatial complexity as part of a navigation or wayfinding experience.

Keyphrases: AI and design, Cognitive Computational Modelling, architecture design, environmental psychology, parametric design, spatial cognition, visual perception

@booklet{EasyChair:4811,
  author    = {Vasiliki Kondyli and Mehul Bhatt and Evgenia Spyridonos},
  title     = {Visuo-Locomotive Complexity as a Component of Parametric Systems for Architecture Design},
  howpublished = {EasyChair Preprint 4811},
  year      = {EasyChair, 2020}}