Agent-based Simulation of Human Movement Shaped by the Underlying Street Structure
Abstract
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.
Cite
@article{arxiv.0910.3055,
title = {Agent-based Simulation of Human Movement Shaped by the Underlying Street Structure},
author = {Bin Jiang and Tao Jia},
journal= {arXiv preprint arXiv:0910.3055},
year = {2013}
}
Comments
some figures taken away, and Appendix B added Accepted by International Journal of Geographical Information Science, minor changes Keywords: Random walks, human movement, street networks, topological analysis, collective behavior, and space syntax