Exploring Railway Network Dynamics in China from 2008 to 2017

China’s high speed rail (HSR) network has been rapidly constructed and developed during the past 10 years. However, few studies have reported the spatiotemporal changes of railway network structures and how those structures have been affected by the operation of high speed rail systems in different periods. This paper analyzes the evolving network characteristics of China’s railway network during each of the four main stages of HSR development over a 10-year period. These four stages include Stage 1, when no HSR was in place prior to August 2008; Stage 2, when several HSR lines were put into operation between August 2008, and July 2011; Stage 3, when the network skeleton of most main HSR lines was put into place. This covered the period until January 2013. Finally, Stage 4 covers the deep intensification of several new HSR lines and the rapid development of intercity-HSR railway lines between January 2013, and July 2017. This paper presents a detailed analysis of the timetable-based statistical properties of China’s railway network, as well as the spatiotemporal patterns of the more than 2700 stations that have been affected by the opening of HSR lines and the corresponding policy changes. Generally, we find that the distribution of both degrees and strengths are characterized by scale-free patterns. In addition, the decreasing average path length and increasing network clustering coefficient indicate that the small world characteristic is more significant in the evolution of China’s railway network. Correlations between different network indices are explored, in order to further investigate the dynamics of China’s railway system. Overall, our study offers a new approach for assessing the growth and evolution of a real railway network based on train timetables. Our study can also be referenced by policymakers looking to adjust HSR operations and plan future HSR routes.

[1]  Patrick Thiran,et al.  Extraction and analysis of traffic and topologies of transportation networks. , 2006, Physical review. E, Statistical, nonlinear, and soft matter physics.

[2]  Yi Yang,et al.  Urban spatial structure influenced by the introduction of high-speed railway terminal , 2011, 2011 International Conference on Remote Sensing, Environment and Transportation Engineering.

[3]  Gitakrishnan Ramadurai,et al.  Statistical Analysis of Bus Networks in India , 2015, PloS one.

[4]  Ľuboš Buzna,et al.  Controlling congestion on complex networks: fairness, efficiency and network structure , 2015, Scientific Reports.

[5]  R. Guimerà,et al.  The worldwide air transportation network: Anomalous centrality, community structure, and cities' global roles , 2003, Proceedings of the National Academy of Sciences of the United States of America.

[6]  Michael T. Gastner,et al.  The complex network of global cargo ship movements , 2010, Journal of The Royal Society Interface.

[7]  Fengjun Jin,et al.  Impacts on accessibility of China’s present and future HSR network , 2014 .

[8]  Sameer Alam,et al.  A complex network approach towards modeling and analysis of the Australian Airport Network , 2017 .

[9]  Chen Zhao,et al.  Analysis of the Chinese Airline Network as multi-layer networks , 2016 .

[10]  Hans J. Herrmann,et al.  Revealing the structure of the world airline network , 2014, Scientific Reports.

[11]  Jing Shi,et al.  How Cities Influenced by High Speed Rail Development: A Case Study in China , 2013 .

[12]  Xiaoqian Sun,et al.  Worldwide Railway Skeleton Network: Extraction Methodology and Preliminary Analysis , 2017, IEEE Transactions on Intelligent Transportation Systems.

[13]  M E J Newman,et al.  Modularity and community structure in networks. , 2006, Proceedings of the National Academy of Sciences of the United States of America.

[14]  Roger Vickerman,et al.  High-speed rail networks, economic integration and regional specialisation in China and Europe , 2015 .

[15]  Yee Leung,et al.  Statistical Tests for Spatial Nonstationarity Based on the Geographically Weighted Regression Model , 2000 .

[16]  Luis Miguel Martínez,et al.  Assessing High-Speed Rail’s impacts on land cover change in large urban areas based on spatial mixed logit methods: a case study of Madrid Atocha railway station from 1990 to 2006 , 2014 .

[17]  Selima Sultana,et al.  The impacts of high-speed rail extensions on accessibility and spatial equity changes in South Korea from 2004 to 2018 , 2015 .

[18]  Arnab Chatterjee,et al.  Small-world properties of the Indian railway network. , 2003, Physical review. E, Statistical, nonlinear, and soft matter physics.

[19]  Zhixiang Fang,et al.  Impacts of high speed rail on railroad network accessibility in China , 2014 .

[20]  D. Watts,et al.  An Experimental Study of Search in Global Social Networks , 2003, Science.

[21]  S. Havlin,et al.  Scaling theory of transport in complex biological networks , 2007, Proceedings of the National Academy of Sciences.

[22]  Jingyi Lin,et al.  Network analysis of China's aviation system, statistical and spatial structure , 2012 .

[23]  Avishek Banerjee,et al.  STATISTICAL ANALYSIS OF THE INDIAN RAILWAY NETWORK: A COMPLEX NETWORK APPROACH , 2011 .

[24]  J. Hołyst,et al.  Statistical analysis of 22 public transport networks in Poland. , 2005, Physical review. E, Statistical, nonlinear, and soft matter physics.

[25]  Adam Rose,et al.  The Impact of High-Speed Rail Investment on Economic and Environmental Change in China: A Dynamic CGE Analysis , 2015 .

[26]  T. Geisel,et al.  The scaling laws of human travel , 2006, Nature.

[27]  Jiangping Zhou,et al.  China's high-speed rail network construction and planning over time: a network analysis , 2018, Journal of Transport Geography.

[28]  Fahui Wang,et al.  Spatiotemporal evolution of China's railway network in the 20th century: An accessibility approach (vol 43, pg 765, 2009) , 2009 .

[29]  Ganesh Bagler,et al.  Analysis of the airport network of India as a complex weighted network , 2004, cond-mat/0409773.

[30]  Megan S. Ryerson,et al.  Grand challenges for high-speed rail environmental assessment in the United States , 2014 .

[31]  Mark Newman,et al.  Networks: An Introduction , 2010 .

[32]  Michael Szell,et al.  Multirelational organization of large-scale social networks in an online world , 2010, Proceedings of the National Academy of Sciences.

[33]  Jun Zhang,et al.  Evolution of domestic airport networks: a review and comparative analysis , 2019 .

[34]  Ben Derudder,et al.  The evolving structure of the Southeast Asian air transport network through the lens of complex networks, 1979–2012 , 2018, Journal of Transport Geography.

[35]  Moshe Givoni,et al.  The Accessibility Impact of a New High-Speed Rail Line in the UK - A Preliminary Analysis of Winners and Losers , 2012 .

[36]  Shauhrat S Chopra,et al.  A network-based framework for assessing infrastructure resilience: a case study of the London metro system , 2016, Journal of The Royal Society Interface.

[37]  Qingquan Li,et al.  Accessibility Impacts of China's High-Speed Rail Network , 2013 .

[38]  Fahui Wang,et al.  Exploring the network structure and nodal centrality of China , 2011 .

[39]  Chengxuan Cao,et al.  Multi-objective optimization of train routing problem combined with train scheduling on a high-speed railway network , 2014 .

[40]  Xiao Liang,et al.  Unraveling the origin of exponential law in intra-urban human mobility , 2012, Scientific Reports.

[41]  Wenjie Wu,et al.  Evaluating the Impact of China’s Rail Network Expansions on Local Accessibility: A Market Potential Approach , 2016 .

[42]  X. Cai,et al.  Empirical analysis of a scale-free railway network in China , 2007 .

[43]  Jianhua Zhang,et al.  Comparison analysis on vulnerability of metro networks based on complex network , 2018 .

[44]  Faraz Zaidi,et al.  Maritime constellations: a complex network approach to shipping and ports , 2012 .

[45]  B. H. Mayhew,,et al.  Size and the Density of Interaction in Human Aggregates , 1976, American Journal of Sociology.