A Generative Methodology for the Design and Implementation of Social Distancing Measures in Public Buildings
The research will consider public accessible buildings as test case for the development and implementation of automated wayfaring design for the post-pandemic recovery phase. As part of post-pandemic recovery planning, local government and retail buildings that house essential services for the public will be some of the first to be re-opened. This research aims to provide a unique methodology using Rhino and Grasshopper to automate a risk analysis of existing floor plans to identify areas of social distance non-compliance. Using generative design methods, the work will go on to automate and implement optimised wayfinding designs to ameliorate the risk of areas identified as non-compliant.
1) Can social distancing guidance be effectively automated using generative software (Grasshopper w/python) for building floor plans?
2) How does the design of signage impact the effectiveness of social distancing measures?
3) How does branding impact signage – should signage be designed at the level of government, municipal or case by case?
4) How might signage ‘fatigue’ be avoided through intelligent design?
Initially the work will be desktop based, completed from floor plans submitted with results generated through processing by computer software including Rhino, Grasshopper and Python.
The implementation phase will then propose the creation of a ‘live’ wayfinding test case located in the Lancaster City Council owned ‘The Storey’ building. This will provide data gathering for analysis and review of the success of social distancing measures. A user survey and heat mapping tracking will provide qualitative data on experience and operational success.
1) Designer team builds an outline on the basis of floor plans.
2) Grasshopper Algorithm charts the median route between obstructions, using Voronoi calculations, including aisles, places of work, places to queue, places to sit.
3) A 2m exclusion zone between two passing users is tracked onto the plans and an area (shown in Fig.1 in red above) is highlighted at risk of non-compliance for social distancing.
4) The algorithm generates an optimised layout for wayfinding and floor signage/graphics based on minimum distances between furniture and walls. This is checked and evaluated by the designer.
5) The design is tested in a Pilot Study at ‘The Storey’ in Lancaster with Heat Mapping data tracking and questionnaires for evaluation.