Abstract
With the growing number of developing large-scale cities, traffic congestion has becomes a global issue. Traffic congestion could be attributed to topological structure of street network and traffic flow concentration. It is necessary to investigate these two factors simultaneously to solve traffic congestion. Therefore, this study proposed an innovative analytical procedure of ranking algorithm, the Flow-based PageRank (FBPR), for investigating the traffic flow concentration, complexity of street network structure and traffic impact areas. By overlapping these factors, street segments prone to traffic congestion are identified. A network modularity algorithm is used for delineating the traffic impact areas that will be affected by traffic congestion. Our results indicate that only relying on the topological structure of the street network, this framework could identify the Central Business Districts (CBD), and the areas proximate to the stations of the combination of MRT and train railway systems are prone to traffic congestion. Meanwhile, the delineation of traffic impact areas could be spatially targeted at priorities of traffic improvement for city planners.
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References
Añez, J., De La Barra, T., & Perez, B. (1996). Dual graph representation of transport networks. Transportation Research Part B: Methodological, 30(3), 209–216.
Bauza, R., & Gozaálvez, J. (2013). Traffic congestion detection in large-scale scenarios using vehicle-to-vehicle communications. Journal of Network and Computer Applications, 36(5), 1295–1307.
Blondel, V. D., Guillaume, J. L., Lambiotte, R., & Lefebvre, E. (2008). Fast unfolding of communities in large networks. Journal of Statistical Mechanics: Theory and Experiment, 10, P10008(12 pp).
Brin, S., & Page, L. (1998). The anatomy of a large-scale hypertextual Web search engine. Computer Networks and ISDN Systems, 30, 107–117.
Chin, W. C. B., & Wen, T. H. (2015). Geographically modified PageRank algorithm: Identifying the spatial concentration of human movement in a geospatial network. PLoS ONE, 10(10), e0139509.
Coifman, B. (2003). Identifying the onset of congestion rapidly with existing traffic detectors. Transportation Research Part A: Policy and Practice, 37(3), 277–291.
Gall, A. I., & Hall, F. L. (1989). Distinguishing between incident congestion and recurrent congestion: A proposed logic. Transportation Research Record, No. 1232.
Hu, M. B., Jiang, R., Wu, Y. H., Wang, W. X., & Wu, Q. S. (2008). Urban traffic from the perspective of dual graph. The European Physical Journal B, 63(1), 127–133.
Jassbi, J., Makv, P., Ataei, M., & Sousa, P. A. (2011). Soft system modeling in transportation planning: Modeling trip flows based on the fuzzy inference system approach. African Journal of Business Management, 5(2), 505–514.
Jenks, G. F. (1967). The data model concept in statistical mapping. International Yearbook of Cartography, 7, 186–190.
Jiang, B. (2009). Ranking spaces for predicting human movement in an urban environment. International Journal of Geographical Information Science, 23(7), 823–837.
Kerner, B. S. (1999). Congested traffic flow: Observations and theory. Transportation Research Record, No. 1678 (pp. 160–167).
Kwon, J., Mauch, M., & Varaiya, P. (2006). Components of congestion: Delay from incidents, special events, lane closures, weather, potential ramp metering gain, and excess demand. Transportation Research Record: Journal of the Transportation Research Board, 1959(1), 84–89.
Lakas, A., & Shaqfa, M. (2011). Geocache: Sharing and exchanging road traffic information using peer-to-peer vehicular communication. In 73rd Vehicular Technology Conference (VTC Spring) (pp. 1–7). New York: IEEE.
Lu, J., & Cao, L. (2003). Congestion evaluation from traffic flow information based on fuzzy logic. Intelligent Transportation Systems, 1, 50–53.
Newman, M. E. J. (2006). Modularity and community structure in networks. Proceedings of the National Academy of Sciences of the United States of America, 103(23), 8577–8696.
Pongpaibool, P., Tangamchit, P., & Noodwong, K. (2007). Evaluation of road traffic congestion using fuzzy techniques. In TENCON 2007 IEEE Region 10 Conference (pp. 1–4). New York: IEEE.
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, 17(1), 91–105.
Rodrigue, J. P. (2013). The geography of transport systems. New York: Routledge.
Vickrey, W. S. (1969). Congestion theory and transport investment. American Economic Review, 59(2), 251–260.
Xing, W., & Ghorbani, A. (2004). Weighted PageRank algorithm. In: 2nd Annual Conference on Communication Networks and Services Research, NB, Canada. New York: IEEE.
Yang, X., Liu, J., Vaidya, N. F., & Zhao, F. (2004). A vehicle-to-vehicle communication protocol for cooperative collision warning. In 1st Annual International Conference on Mobile and Ubiquitous Systems: Networking and Services, MOBIQUITOUS 2004 (pp. 114–123). New York, IEEE.
Yao, L., Guan, H., & Yan, H. (2008). Trip generation model based on destination attractiveness. Tsinghua Science and Technology, 13(5), 632–635.
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Wen, TH., Chin, WCB., Lai, PC. (2017). Link Structure Analysis of Urban Street Networks for Delineating Traffic Impact Areas. In: Nemiche, M., Essaaidi, M. (eds) Advances in Complex Societal, Environmental and Engineered Systems. Nonlinear Systems and Complexity, vol 18. Springer, Cham. https://doi.org/10.1007/978-3-319-46164-9_10
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DOI: https://doi.org/10.1007/978-3-319-46164-9_10
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