Advances in Computational Design
Volume 3, Number 4, 2018, pages 339-336
DOI: 10.12989/acd.2018.3.4.339
Precedent based design foundations for parametric design: The case of navigation and wayfinding
Vasiliki Kondyli, Mehul Bhatt and Timo Hartmann
Abstract
Parametric design systems serve as powerful assistive tools in the design process by providing a
flexible approach for the generation of a vast number of design alternatives. However, contemporary parametric
design systems focus primarily on low-level engineering and structural forms, without an explicit means to
also take into account high-level, cognitively motivated people-centred design goals.
We present a precedent-based parametric design method that integrates people-centred design \"precedents\"
rooted in empirical evidence directly within state of the art parametric design systems. As a use-case, we
illustrate the general method in the context of an empirical study focusing on the multi-modal analysis of
wayfinding behaviour in two large-scale healthcare environments. With this use-case, we demonstrate the
manner in which: (1). a range of empirically established design precedents - e.g., pertaining to visibility
and navigation - may be articulated as design constraints to be embedded directly within state of the art
parametric design tools (e.g., Grasshopper); and (2). embedded design precedents lead to the (parametric)
generation of a number of morphologies that satisfy people-centred design criteria (in this case, pertaining to
wayfinding).
Our research presents an exemplar for the integration of cognitively motivated design goals with parametric
design-space exploration methods. We posit that this opens-up a range of technological challenges for the
engineering and development of next-generation computer aided architecture design systems.
Key Words
human behaviour studies; navigation; wayfinding; architecture design; spatial cognition; visual perception; parametric design; architectural computing; design computing
Address
Vasiliki Kondyli, Mehul Bhatt: DesignSpace Group. www.design-space.org
CoDesign Lab – Cognition. AI. Interaction. Design. www.codesign-lab.org
Applied Autonomous Sensor Systems (AASS), Orebro University, Sweden
Timo Hartmann: Systems Engineering, Civil Engineering Institute, TU Berlin, Germany