Data Influenced Infrastructure Generation - Combining holistic urban datasets through a digital Slime Mold algorithm for cycle path generation

Abstract

Existing infrastructure in cities has become increasingly incapable of operating at its designed efficiency. This demand has been created by the growth in population generating a larger demand and strain on the existing infrastructure. This paper explores how user-generated data could be utilised to create transport infrastructure, more specifically bicycle pathways. Through a series of 'four sprints', a pathway generation system has been adapted from the behaviour of Slime Molds (Physarum Polycephalum), in particular, its ability to define shortest paths on a terrain. The first sprint outlines the design of a Slime Mold algorithm between user-specified points, the second utilises the algorithm for pathway generation in a macro and micro urban scale (acknowledging both the existing infrastructure and cadastral), the third defines weight or effort limits for the pathways in order to suite realistic user-profiles (fitness level of cyclist groups), and the last sprint creates the start and end points for the pathway generation from user-generated data, applying the Slime Mold system to a 'real world' context. Through the four sprints, a design tool has been created that can be used to not only create and analyse cycle pathways, but tweaked for various other forms of tangible transport infrastructure.