International Journal of Engineering and Manufacturing (IJEM)
IJEM Vol. 2, No. 3, 29 Jun. 2012
Cover page and Table of Contents: PDF (size: 696KB)
Road Network Pattern Classification Using GEV Distribution Parameters
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Index Terms
Road network pattern, network topology, classification, GEV distribution
Abstract
Network pattern mentioned in this paper is referred to the geographical layout and structure of a network, which is related to the connection, direction, and combination features of roads in a road network. A quantitative method is proposed in this paper to classify patterns of networks, through which a network could be identified quantitatively to be one of the three standard patterns, i.e., grid network, circle+radial network and tree-patterned network. Metric distances of shortest paths are taken as the main features of the networks and are described by parameters through Generalized Extreme Value (GEV) fitting. The criteria for pattern classification were established according to the cluster analysis of the parameters calculated from a set of trial networks. Six real networks were calculated using the method and their patterns are identified according to the proposed criteria. It turned out that the method could capture the features of the network patterns well. This method may set a threshold of the more general and deep studies of network pattern classification, which may offer help to road network planning and assessment.
Cite This Paper
Chao Yang,Qi Liu,"Road Network Pattern Classification Using GEV Distribution Parameters", IJEM, vol.2, no.3, pp.21-29, 2012. DOI: 10.5815/ijem.2012.03.04
Reference
[1] M.Southworth, E. Ben-Joseph, "Streets and the shaping of towns and cities,".McGraw-Hill, 1996.
[2] ITE, "Recommended Practice for Context Sensitive Solutions in Designing Major Urban Thoroughfares for Walkable Communities," Washington D.C., 2006.
[3] ITE， "Smart Growth Task Force. Smart Growth Transportation Guidelines: An ITE Proposed Recommended Practice," Institute of Transportation Engineers, Washington D.C., 2003.
[4] J. Sun, G. R. Lovegrove, "Using Community-Based Macro-Level Collision Prediction Models to Evaluate the Safety Level of Neighborhood Road Network Patterns," Transportation Research Board Annual Meeting 2010, 10-0535.
[5] Z. Sun, "The Study of Fractal Approach to Measure Urban rail Transit Network Morphology," Journal of Transportation Systems Engineering and Information Technology, vol. 7, pp. 29-38, 2007.
[6] C. Yang, Y. Wang, "Morphological and Functional Analysis of Urban Rail Transit Networks," Transportation Research Board Annual Meeting 2010, 10-3018.