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Article

EXPLAINING TRAFFIC FLOW PATTERNS USING CENTRALITY MEASURES

DOI: 10.7708/ijtte.2015.5(2).05


5 / 2 / 134-149 Pages

Author(s)

Amila Jayasinghe - Urban Transport Engineering and Planning Lab, Department of Civil and Environmental Engineering, Environment Systems Engineering, Graduate School of Engineering - Doctoral Program, Nagaoka University of Technology, Nagaoka, 940-2137, Japan -

Kazushi Sano - Urban Transport Engineering and Planning Lab, Department of Civil and Environmental Engineering, Environment Systems Engineering, Graduate School of Engineering - Doctoral Program, Nagaoka University of Technology, Nagaoka, 940-2137, Japan -

Hiroaki Nishiuchi - Urban Transport Engineering and Planning Lab, Department of Civil and Environmental Engineering, Environment Systems Engineering, Graduate School of Engineering - Doctoral Program, Nagaoka University of Technology, Nagaoka, 940-2137, Japan -


Abstract

This study examines the capability of centrality parameters of the road network to explain and predict traffic flow by types of vehicles. The case study was conducted in Colombo Metropolitan Area, Sri Lanka. Study used four centrality parameters i.e. connectivity, global integration, local integration and choice; and three analysis methods i.e. topological, metric and angular which introduced by space syntax analysis method to compute network centrality of the road network. Findings of this study stress that, (1) human beings perceive the space mostly from geometrical distance (topological and angular distance) in comparison to metric distance. Further to this, it was found that angular distance is more powerful in global level whereas topological distance is more powerful in local level; (2) it is more appropriate to consider the multiple influences from multiple centrality parameters rather being confined to a single best parameter and influence of each parameter varies based on type of vehicles.


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References:

Altshuler, Y.; Puzis, R.; Elovici, Y.; Bekhor, S.; Pentland, A. 2011. Augmented Betweenness Centrality for Mobility Prediction in Transportation Networks. Athens. In Proceedings of the International Workshop on Finding Patterns of Human Behaviors in Network and Mobility Data (NEMO), 1-12.

 

Chiaradia, A. 2007. Emergent Route Choice Behaviour, Motorway and Trunk Road Network: the Nantes conurbation. In Proceedings of the 6th International Space Syntax Symposium, ITU Faculty of Architecture, Ä°stanbul, 078.1-078-17.

 

Crucittia, P.; Latorab, V.; Marchioric, M. 2004. Topological analysis of the Italian electric power grid, Physica A: Statistical Mechanics and its Applications. DOI: http://dx.doi.org/10.1016/j.physa.2004.02.029, 338(1-2): 92-97.

 

Cutini, V. 2001. Configuration and Centrality: Some evidence from two Italian case studies. In Proceedings of the 3rd International Space Syntax Symposium, Atlanta, 32.1-32.11.

 

Department of Census & Statistics, Sri Lanka. 2012. Census of Population & Housing-2011, Department of Census & Statistics, Sri Lanka.

 

Galafassi, C.; Bazzan, L.C. 2014. Analysis of Traffic Behavior in Regular Grid and Real World Networks, Porto Alegre, Brazil. Available from Internet: http://www.inf.ufrgs.br/maslab/pergamus/pubs/GalafassiBazzan2013-wein.pdf.

 

Gao, S.; Wang, Y.; Gao, Y.; Liu, Y. 2013. Understanding urban traffic flow characteristics: a rethinking of betweenness centrality, Environment and Planning B: Planning and Design. DOI: http://dx.doi.org/10.1068/b38141, 40(1): 135-153.

 

Hillier, B. 1999. Space is the Machine: A Configurational Theory of Architecture. Cambridge: Cambridge University Press. UK.

 

Hillier, B.; Hanson, J. 1984. The Social Logic of Space. Cambridge: Cambridge University Press. UK.

 

Hillier, B.; Iida, S. 2005. Network and psychological effects in urban movement. Berlin. In Proceedings of Spatial Information Theory: International Conference, 475-490.

 

Holme, P. 2003. Congestion and centrality in traffic flow on complex networks, Advances in Complex Systems: A Multidisciplinary Journal. DOI: http://dx.doi.org/10.1142/S0219525903000803, 6(2): 163-176.

 

Japan International Cooperation Agency - JICA. 2014. Final Report - CoMTrans Urban Transport Master Plan. Japan International Copperation Agency. Japan.

 

Jiang, B.; Jia, T. 2011. Agent-based simulation of human movement shaped by the underlying street structure, Journal of Geographical Information Science. DOI: http://dx.doi.org/10.1080/13658811003712864, 25(1): 51-64.

 

Jiang, B.; Liu, C. 2009. Street-based topological representations andanalyses for predicting traffic flow in GIS, International Journal of Geographical Information Science. DOI: http://dx.doi.org/10.1080/13658810701690448, 23(9): 1119-1137.

 

Jiang, B.; Yin, J.; Zhao, S. 2014. Characterizing the Human Mobility Pattern in a Large Street Network. Available from Internet: http://arxiv.org/ftp/arxiv/papers/0809/0809.5001.pdf.

 

Jun, C.; Kwon, J.H.; Choi, Y.; Lee, I. 2007. An Alternative Measure of Public Transport Accessibility Based on Space Syntax, Advances in Hybrid Information Technology Lecture Notes in Computer Science. DOI: http://dx.doi.org/10.1007/978-3-540-77368-9_28, 4413: 281-291.

 

Kazerani, A.; Stephanr, W. 2009. Modified Betweenness Centrality for Predicting Traffic Flow. In Proceedings of the 12th AGILE International Conference, Hannover, 13-21.

 

Noulas, A.; Scellato, S.; Lambiotte, R.; Pontil, M.; Mascolo, C. 2012. A tale of many cities: universal patterns in human urban mobility. In PloS one, Public Library of Science, 7.

 

Porta, S.; Crucitti, P.; Latora, V. 2006. The network analysis of urban streets: A dual approach, Physica A. DOI: http://dx.doi.org/10.1016/j.physa.2005.12.063, 369(2): 853-866.

 

Puzis, R.; Altshuler, Y.; Elovici, Y.; Bekhor, S.; Shiftan, Y.; Pentland, A. 2013. Augmented Betweenness Centrality for Environmentally Aware Traffic Monitoring in Transportation Networks, Journal of Intelligent Transportation Systems. DOI: http://dx.doi.org/10.1080/15472450.2012.716663, 17(1): 91-105.

 

Scheurer, J.; Curtis, C.; Porta, S. 2007. Spatial Network Analysis of Public Transport Systems: Developing a Strategic Planning Tool to Assess the Congruence of Movement and Urban Structure in Australian Cities. Available from Internet: http://abp.unimelb.edu.au/files/miabp/3spatial-network-analysis.pdf.

 

Turner, A. 2001. Angular analysis. In Proceedings of the 3rd international symposium on space syntax, Atlanta.


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