Street-based Topological Representations and Analyses for Predicting Traffic Flow in GIS

Details Street-based Topological Representations and Analyses for Predicting Traffic Flow in GIS Street-based Topological Representations and Analyses for Predicting Traffic Flow in GIS

2007-09-13

arxiv.org/abs/0709.1981v1

International Journal of Geographical Information Science, 23(9), 2009, 1119-1137.

Physics

Data Analysis, Statistics and Probability

14 pages, 9 figures, 6 tables, submitted to International Journal of Geographic Information Science

Scientific paper

10.1080/13658810701690448

It is well received in the space syntax community that traffic flow is significantly correlated to a morphological property of streets, which are represented by axial lines, forming a so called axial map. The correlation co-efficient (R square value) approaches 0.8 and even a higher value according to the space syntax literature. In this paper, we study the same issue using the Hong Kong street network and the Hong Kong Annual Average Daily Traffic (AADT) datasets, and find surprisingly that street-based topological representations (or street-street topologies) tend to be better representations than the axial map. In other words, vehicle flow is correlated to a morphological property of streets better than that of axial lines. Based on the finding, we suggest the street-based topological representations as an alternative GIS representation, and the topological analyses as a new analytical means for geographic knowledge discovery.

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