Tactile Map Tile
Landscape architecture’s discourse surrounding inclusive and accessible design is largely centered on the Universal Design Principals established at North Carolina State’s Center for Universal Design. A lack of critical engagement with these and related ideas has left significant room for improvement when it comes to equitable design.
This project presents an alternative approach to exploring the pedestrian experience. Challenging the existing primacy afforded to vision, this work takes a tactile approach. This project uses the development of tactile graphics as both a means of better understanding the pedestrian experience for people with low vision and blindness, as well as a step towards developing way nding tools that can be used by people with range of visual experiences.
Designed as tools that enhance spatial understanding for people within a large range of visual capacities, these maps consider circumstances that influence a full spectrum of experience. These tiles confront gaps in the cartographic record as it pertains to inclusive design, and considers how that is manifested in the lived experience.
Pairing a participatory, data-driven design approach together with interdisciplinary collaboration, these 3D printed, parametrically designed maps allow for user feedback, and ever changing open-data sets to be quickly incorporated.
Prototypes were printed throughout the process to test legibility with expert users and to better understand the technical and material constraints associated with 3D printing. Ultimately, the maps were printed using a Wood PLA and sandblasted to achieve a softer texture. A custom folder was bound to organize the map tiles, so they could be used at home prior to a journey, or folded and taken en route.
Topography was considered at multiple scales: macro-topography characterizing street or district level grade changes, transitional features such as stairs and ramps, and micro topography changes such as curb heights and tree well depths.
Features of the pedestrian environment were evaluated for inclusion on the maps. Surfaces were grouped according to similar traits in order to reduce the number of symbols required.