Studying (non-planar) road networks through an algorithmic lens

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Studying (non-planar) road networks through an algorithmic lens

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Geographic Information Systems archive
Proceedings of the 16th ACM SIGSPATIAL international conference on Advances in geographic information systems table of contents

Irvine, California

SESSION: Terrain and road network algorithms table of contents

Article No. 16

Year of Publication: 2008

ISBN:978-1-60558-323-5

Authors

David Eppstein	University of California, Irvine
Michael T. Goodrich	University of California, Irvine

Sponsors

: Google
: Oak Ridge National Laboratory
: ESRI
Microsoft : Microsoft

Publisher

ACM New York, NY, USA

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ABSTRACT

This paper studies real-world road networks from an algorithmic perspective, focusing on empirical studies that yield useful properties of road networks that can be exploited in the design of fast algorithms that deal with geographic data. Unlike previous approaches, our study is not based on the assumption that road networks are planar graphs. Indeed, based on the a number of experiments we have performed on the road networks of the 50 United States and District of Columbia, we provide strong empirical evidence that road networks are quite non-planar. Our approach therefore instead is directed at finding algorithmically-motivated properties of road networks as non-planar geometric graphs, focusing on alternative properties of road networks that can still lead to efficient algorithms for such problems as shortest paths and Voronoi diagrams. In particular, we study road networks as multiscale-dispersed graphs, which is a concept we formalize in terms of disk neighborhood systems. This approach allows us to develop fast algorithms for road networks without making any additional assumptions about the distribution of edge weights. In fact, our algorithms can allow for non-metric weights.

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