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Topological Analysis of the Evolution of Public Transport Networks KTH  TSCMT  TSCMT

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Topological Analysis of the Evolution of Public Transport Networks KTH  TSCMT  TSCMT , 2014 Topological Analysis of the Evolution of Public Transport Networks Transport Public of Evolution the of Analysis Topological Topological Analysis of the Evolution of Public Transport Networks JACOB ROMMEL TSCMT KTH ­ www.kth.se Topological Analysis of the Evolution of Public Transport Networks Jacob Rommel 5/29/2014 Supervisor: Oded Cats Master Thesis M.Sc. Transport and Geoinformation Technology Programme DEPARTMENT OF TRANSPORT AND LOCATION ANALYSIS Abstract Many studies have been conducted regarding network theory and how it can be applied to public transport network. This has led to knowledge on how network indicators relate to the performance of a network and also to insights of how networks can best be extended. Little is known however on how rail bound public transport networks and their network indicators have evolved over time. This would be interesting to know since many metro and other rail bound public transport networks have evolved over a long period of time with extensions being made at different times by different policy makers and stakeholders. This means that there has not been a unified planning process for many of the networks. It would hence be beneficial to get a better picture of how the networks have evolved, when extending the networks or when creating new ones. By creating networks for every year in the development of a rail bound public transport network and then calculate the different network indicators, the evolutionary trends could be found. The networks were created in L-space which means that stations were represented as nodes and the rail connection between stations as edges. To every link in the networks, travel time was attached as weights. This was done in order to make the network indicators more realistic. By assigning geographical coordinates to nodes, indicators such as directness and closeness centrality with respect to geographical distance could be derived. A case study was conducted by applying the methodology to the Stockholm rail bound public transport network. The study period was chosen to be from 1950 up until 2025. 1950 was the year when the Stockholm Metro opened, and the extensions to the network that are decided upon are planned to be completed in 2025. By including the future extensions it was hoped that it could be seen if the future trends are following the trends from the 20th century. Trends regarding the evolution of the network in Stockholm were found. In general it can be said that indicators were relatively high in the first 15-20 years of the study. This was due to the inner city tram network that existed in these years. The tram network was relatively intra-connected with a relatively high average degree, clustering coefficient and connectivity. When the tram network closed down the indicators drastically decreased, after 1971 many of the indicators started to slowly increase due to the additions of new lines and also extensions of already existing ones. Between the year 2000 and 2025, many of the indicators increased substantially, this was partly due to Tvärbanan that connected many older lines creating nodes with a high degree. The fact that the future extensions will lead to an increase in many network indicators (and a decrease in average connectivity) was seen as an indication that the future extensions will accentuate trends that have taken place since the early 1970’s. It was also seen that many of the extensions included in this study will help to develop the network in a way that is in line with the overarching planning principles set by the Stockholm council. The structure of the network consisted of a dense core with branches reaching out to the suburbs in the 1950’s and early 1960’s. In the late 1960’s the network got a radial shape with branches going to the suburbs, no denser core existed in these years. This structure remained relatively unchanged up until the year 2000. After 2000 and up until 2025 a structure emerged in the network with a dense core and also a ring line going around half of the city. This type of structure had been seen in many other rail bound networks around the world. 2 Acknowledgement I have always been interested in transportation in general, the interest has been particularly focused on public transport. Whenever I have traveled to a new city, one of the first things I have done has always been to look at public transport maps for the city. Due to my public transport interest it has always been my intent to base my master thesis on public transport. After having discussions with Oded Cats, the subject for this thesis emerged. I will like to thank Oded, who became my supervisor, for his help throughout the process of writing this thesis. His inputs and guidance have been very helpful. 3 TABLE OF CONTENT 1 INTRODUCTION ......................................................................................................................... 7 1.1 Background ......................................................................................................................................... 7 1.2 Problem Statement ............................................................................................................................. 8 1.3 Objective ............................................................................................................................................. 8 2 LITERATURE STUDY ................................................................................................................ 9 2.1 Network Theory ................................................................................................................................... 9 2.2 Temporal evolution of networks ....................................................................................................... 10 2.3 Public Transport Network .................................................................................................................. 11 2.4 Contribution to the literature ............................................................................................................ 12 3 METHODOLOGY ...................................................................................................................... 13 3.1 Network Representation ................................................................................................................... 13 3.2 Creating the Networks ....................................................................................................................... 14 3.3 Network Indicators ............................................................................................................................ 14 3.3.1 Number of Nodes and Edges ............................................................................................................... 15 3.3.2 Connectivity ......................................................................................................................................... 15 3.3.3 Clustering Coefficient .......................................................................................................................... 15 3.3.4 Degree Centrality ................................................................................................................................. 16 3.3.5 Betweeness Centrality ......................................................................................................................... 16 3.3.6 Closeness Centrality ............................................................................................................................ 17 3.3.7 Network Diameter ............................................................................................................................... 17 3.3.8 Directness ............................................................................................................................................ 17 3.3.9 Assortative ........................................................................................................................................... 18 3.3.9.1 Average Node Degree ................................................................................................................. 18 3.3.9.2 Pearson Coefficient ..................................................................................................................... 18 3.3.10 Summary .............................................................................................................................................. 19 3.4 Implementation Details ..................................................................................................................... 19 4 CASE STUDY ............................................................................................................................. 21 4.1 Data ................................................................................................................................................... 22 4.1.1 Topological Data .................................................................................................................................. 22 4.1.1.1 Metro .......................................................................................................................................... 22 4.1.1.2 The old tram network ................................................................................................................. 24 4 4.1.1.3 Spårväg City ...............................................................................................................................
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