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id caadria2018_188
authors Yu, K. Daniel, Haeusler, M. Hank, Fabbri, Alessandra and Simons, Katrina
year 2018
title BiCycle Pathway Generation Through a Weighted Digital Slime Mold Algorithm via Topographical Analysis
source T. Fukuda, W. Huang, P. Janssen, K. Crolla, S. Alhadidi (eds.), Learning, Adapting and Prototyping - Proceedings of the 23rd CAADRIA Conference - Volume 2, Tsinghua University, Beijing, China, 17-19 May 2018, pp. 381-390
summary Cities are growing into larger suburbias which increasingly become dependent on cars as the primary mode of transport. Cycling is an alternative transport mode, but topography can often turn daily transport into cardiovascular exercise - not always a desirable outcome. Addressing this, planners can design cycle pathways that coincide with the landscape by planning the shortest path between two points, whilst considering the need to minimise effort (muscle power) to reach the destination. Using a Slime Mold algorithm the paper discusses possibilities of cycle pathway generation which utilises topographic gradients as the initial framework for the growth. The cycle path optimises the amount of effort required to travel between specified points, and adhere to a set of rules predefined by the user (e.g avoid occupied cadastral). A vector analysis determines the gradient sizes that define areas of the topography which are too steep for the algorithm to grow. The algorithm can be observed to generate cycling infrastructure that is both reflective of the environment and the amenities of humans. This investigation, its proposed hypothesis, methodology, implications, significance, and evaluation are presented in the paper.
keywords cycle pathway; slime mold; infrastructure generation; topography analysis; route choice
series CAADRIA
email m.haeusler@unsw.edu.au
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