Evaluation of French motorway network in relation to slime mould transport networks

Andrew Adamatzky, Olivier Allard, Jeff Jones and Rachel Armstrong

Environment and Planning B, 2017, vol. 44, issue 2, 364-383

Abstract: France has developed a high quality motorway system that has been rapidly rationalised and matured in the late 20th century yet has been founded on ancient, Roman infrastructures. The development of the motorway system is thus an iterative method associated with hierarchical ‘top-down’ processes taking into consideration factors such as population density, network demand, location of natural resources, civil engineering challenges and population growth. At the opposite extreme to this approach is the development of transport networks within simple biological systems which are typically decentralised, dynamic and emerge from simple, local and ‘bottom-up’ interactions. We examine the notion, and to what extent, that the structure of a complex motorway network could be predicted by the transport network of the single-celled slime mould Physarum polycephalum . This comparison is explored through its ability to ‘deduce’ the French motorway network in a series of analogue and digital experiments. We compare Physarum network and motorway network topology in relation to proximity graphs and assess the trade-off between connectivity and minimal network length with a bottom-up model of a virtual plasmodium. We demonstrate that despite the apparent complexity of the challenge, Physarum can successfully apply its embodied intelligence to rationalise the motorway topology. We also demonstrate that such calculations prove challenging in the face of significant obstacles such as, mountainous terrain and may account for the missing route between Nice, Grenoble, Avignon and Lyon. Finally, we discuss the topological findings with respect to circle and spoke city planning infrastructures and certain species of web-building spiders.

Keywords: Agent-based modelling (ABM); planning theory; self-organisation (search for similar items in EconPapers)
Date: 2017
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Persistent link: https://EconPapers.repec.org/RePEc:sae:envirb:v:44:y:2017:i:2:p:364-383

DOI: 10.1177/0265813515626924

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