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Agent-based simulation of human movement shaped by the underlying street structure

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Relying on random and purposive moving agents, we simulated human movement in large street networks. We found that aggregate flow, assigned to individual streets, is mainly shaped by the underlying street structure, and that human moving behavior (either random or purposive) has little effect on the aggregate flow. This finding implies that given a street network, the movement patterns generated by purposive walkers (mostly human beings) and by random walkers are the same. Based on the simulation and correlation analysis, we further found that the closeness centrality is not a good indicator for human movement, in contrast to a long-standing view held by space syntax researchers. Instead we suggest that Google's PageRank and its modified version (weighted PageRank), betweenness and degree centralities are all better indicators for predicting aggregate flow.
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Keywords: collective behavior; human movement; random walks; space syntax; street networks; topological analysis

Document Type: Research Article

Affiliations: 1: Department of Technology and Built Environment, Division of Geomatics, University of Gavle, Gavle, Sweden 2: Future Position X, Gavle, Sweden

Publication date: February 1, 2011

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