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Network design, Transit planning, Graph theory, Accessibility, Connectivity, Directness,

This paper demonstrates that network topologies play a key role in attracting people to use public transit; ridership is not solely determined by cultural characteristics (North American versus European versus Asian) or city design (transit oriented versus automobile oriented). The analysis considers 19 subway systems worldwide: those in Toronto, Ontario, Canada; Montreal, Quebec, Canada; Chicago, Illinois; New York City; Washington, D.C.; San Francisco, California; Mexico City, Mexico; London; Paris; Lyon, France; Madrid, Spain; Berlin; Athens, Greece; Stockholm, Sweden; Moscow; Tokyo; Osaka, Japan; Seoul, South Korea; and Singapore. The relationship between ridership and network design was studied by using updated graph theory concepts. Ridership was computed as the annual number of boardings per capita. Network design was measured according to three major indicators. The first is a measure of transit coverage and is based on the total number of stations and land area. The second relates to the maximum number of transfers necessary to go from one station to another and is called directness. The third attempts to get an overall view of transfer possibilities to travel in the network to appreciate a sense of mobility; it is termed connectivity. Multiple-regression analysis showed a strong relationship between these three indicators and ridership, achieving a goodness of fit (adjusted R2 value) of .725. The importance of network design is significant and should be considered in future public transportation projects.

Whilst being hailed as the remedy to the world’s ills, cities will need to adapt in the 21st century. In particular, the role of public transport is likely to increase significantly, and new methods and technics to better plan transit systems are in dire need. This paper examines one fundamental aspect of transit: network centrality. By applying the notion of betweenness centrality to 28 worldwide metro systems, the main goal of this paper is to study the emergence of global trends in the evolution of centrality with network size and examine several individual systems in more detail. Betweenness was notably found to consistently become more evenly distributed with size (i.e. no “winner takes all”) unlike other complex network properties. Two distinct regimes were also observed that are representative of their structure. Moreover, the share of betweenness was found to decrease in a power law with size (with exponent 1 for the average node), but the share of most central nodes decreases much slower than least central nodes (0.87 vs. 2.48). Finally the betweenness of individual stations in several systems were examined, which can be useful to locate stations where passengers can be redistributed to relieve pressure from overcrowded stations. Overall, this study offers significant insights that can help planners in their task to design the systems of tomorrow, and similar undertakings can easily be imagined to other urban infrastructure systems (e.g., electricity grid, water/wastewater system, etc.) to develop more sustainable cities.

The study of geographical systems as graphs, and networks has gained significant momentum in the academic literature as these systems possess measurable and relevant network properties. Crowd-based sources of data such as OpenStreetMaps (OSM) have created a wealth of worldwide geographic information including on transportation systems (e.g., road networks). In this work, we offer a Geographic Information Systems (GIS) protocol to transfer polyline data into a workable network format in the form of; a node layer, an edge layer, and a list of nodes/edges with relevant geographic information (e.g., length). Moreover, we have developed an ArcGIS tool to perform this protocol on OSM data, which we have applied to 80 urban areas in the world and made the results freely available. The tool accounts for crossover roads such as ramps and bridges. A separate tool is also made available for planar data and can be applied to any line features in ArcGIS.

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