The Parametric Social Distance Lab

The research considers a publicly accessible building as a test case for the development and implementation of automated social distance layout redesign for the pandemic recovery phase.  Retail buildings that house essential goods and services for the public were some of the first to be re-opened; many with social distance measures still in place. This research aims to develop and test a unique methodology using Rhino3D and Grasshopper to automate the redesign of an interior layout to automatically provide compliant social distancing at optimal user/customer capacity. The process is evaluated in a live lab scenario, with results demonstrating that the methodology provides an agile, accurate, efficient and visually clear outcome for automating a compliant layout for social distancing.

Keywords: Generative, Social Distancing, Optimization, Signage, Wayfinding.

COVID-19 has had an unprecedented impact on the day-to-day use of buildings. These effects are likely to have an enduring medium­ and long- term impact on the arrangement of building layouts to comply with social distancing, posing immediate and ongoing risks to both the personal health of users through non-compliance and to the financial viability of building operation due to increased circulation and distancing requirements. The cost in person-hours to the global economy represented by the millions of concurrent and disparate exercises in building layout replanning during the pandemic has been truly significant. To ameliorate against further substantial cost to the economy through both abortive space planning and non-compliant layouts, we propose a unique automated methodology for building operators to redesign their layouts to comply with social distancing. This will reduce timescales for reopening and adaptation in the event of revised government advice, local lockdown, or further variant outbreaks [5]; benefitting user health through verification of distances, whilst improving the efficiency of building operation through optimization of capacity.

Our approach was to build a multi-criteria optimization definition using parametric software Grasshopper to generate a redesigned floor layout with minimal human design input. A review of existing research revealed that no existing study provides practical development, testing and evaluation of generative floor layout design in relation to social distancing.

To evaluate the methodology, the project tested a ‘live’ site, automating the design of the interior layout and wayfinding signage of the ground floor of a public building complex owned by Lancaster City Council (LCC) – the Storey Building in Lancaster City centre. The Generative Social Distancing Lab opened to key stakeholders for three weeks in May 2020, providing opportunity for local business owners to explore a building altered to comply with social distance restrictions, with the dual purpose of collecting evaluation data from users active in the space.  

It became apparent that considering the layout alone was insufficient without also considering the information necessary for the public using the space, and so we also considered the design and location of signage. Variable inputs to the definition were retained as customizable sliders, to afford changes in social distance length to provide for responsive alteration in the event of changing legislation. Signage typologies and layouts were developed concurrently in collaboration with the client LCC. An Open Source Signage Pack was authored as part of the research, providing fully customizable signs to compliment the variable generative outcomes of the Grasshopper definition. This comprised 65 unique signs with 1,040 possible directional iterations available for download under CC BY-NC. 

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