A Model Framework for Analyzing Public Transit Connectivity and Its Application in a Large-scale Multi-modal Transit Network

Public transportation is essential for mobility of users especially in urban areas where transit connectivity plays a crucial role in achieving acceptable travel experience. Improvement of transit connectivity is also a critical component of transit-operations planning. The objective of this research is to develop a unique approach to measure transit connectivity that does not require transit ridership data and transit assignment models. The methodology incorporates a graph theory approach to determine the performance of large-scale multimodal transit networks by quantifying measures of connectivity at multiple levels such as transit stops, links and lines. A connectivity index is developed considering unique qualities of each transit line and stop such as location of nodes in terms of activity density, frequency at which each node is served, capacity of the transit line serving a node and speed of bus or rail serving the line when developing the connectivity index. The methodology is applied (as a case study) in two urban areas to determine public transit connectivity of large multimodal transit system using General Transit Feed Specification (GTFS) data along with some demographic and socio-economic data. The new connectivity index significantly extends the set of performance analysis tools that decision- makers can use to assess the efficiency of the transit system.

[1]  Phillip Bonacich,et al.  Eigenvector-like measures of centrality for asymmetric relations , 2001, Soc. Networks.

[2]  Sabyasachee Mishra,et al.  Land use and transit ridership connections: Implications for state-level planning agencies , 2013 .

[3]  Johan Bollen,et al.  Co-authorship networks in the digital library research community , 2005, Inf. Process. Manag..

[4]  M. Newman.  Analysis of weighted networks. , 2004, Physical review. E, Statistical, nonlinear, and soft matter physics.

[5]  David C. Bell,et al.  Centrality measures for disease transmission networks , 1999, Soc. Networks.

[6]  P. Torrens.  A Toolkit for Measuring Sprawl , 2008 .

[7]  Phillip Bonacich,et al.  Some unique properties of eigenvector centrality , 2007, Soc. Networks.

[8]  Loet Leydesdorff,et al.  Betweenness Centrality" as an Indicator of the , 2006 .

[9]  Edward A Beimborn,et al.  Transit Accessibility and Connectivity Impacts on Transit Choice and Captivity , 2003 .

[10]  Avishai Ceder,et al.  Measuring Public Transport Connectivity Performance Applied in Auckland, New Zealand , 2009 .

[11]  Ronald Rousseau,et al.  Social network analysis: a powerful strategy, also for the information sciences , 2002, J. Inf. Sci..

[12]  L. Freeman.  Centrality in social networks conceptual clarification , 1978 .

[13]  Avishai Ceder,et al.  Using connectivity for measuring equity in transit provision , 2014 .

[14]  Britta Ruhnau,et al.  Eigenvector-centrality - a node-centrality? , 2000, Soc. Networks.

[15]  C. Prell.  Social Network Analysis: History, Theory and Methodology , 2011 .

[16]  Avishai Ceder,et al.  Comparing Public Transport Connectivity Measures of Major New Zealand Cities , 2010 .

[17]  Timothy F Welch,et al.  Locating the Most Connected Transit Stop, Route, and Transfer Center: Tool for Users and Decision Makers , 2014 .

[18]  Ali Modarres,et al.  Polycentricity and transit service , 2003 .

[19]  P. Torrens.  Moving Agent Pedestrians Through Space and Time , 2012 .

[20]  Jeff Bowman,et al.  Applications of graph theory to landscape genetics , 2008, Evolutionary applications.

[21]  Seong-Cheol Kang,et al.  A Model for Evaluating the Connectivity of Multimodal Transit Networks , 2010 .

[22]  S. Moore,et al.  International NGOs and the role of network centrality in humanitarian aid operations: a case study of coordination during the 2000 Mozambique floods. , 2003, Disasters.

[23]  J. A. Rodríguez-Velázquez,et al.  Subgraph centrality in complex networks. , 2005, Physical review. E, Statistical, nonlinear, and soft matter physics.

[24]  Avishai Ceder,et al.  Public Transit Planning and Operation , 2007 .

[25]  Alejandra Martínez-Monés,et al.  Combining qualitative evaluation and social network analysis for the study of classroom social interactions , 2003, Comput. Educ..

[26]  V. Latora,et al.  Centrality in networks of urban streets. , 2006, Chaos.

[27]  Falk Schreiber,et al.  Exploration of biological network centralities with CentiBiN , 2006, BMC Bioinformatics.

[28]  Sabyasachee Mishra,et al.  A functional integrated land use-transportation model for analyzing transportation impacts in the Maryland-Washington, DC Region , 2011 .

[29]  Timothy F Welch,et al.  Performance indicators for public transit connectivity in multi-modal transportation networks , 2012 .

[30]  Tim Dwyer,et al.  GEOMI: GEOmetry for Maximum Insight , 2005, GD.

[31]  Yuval Hadas,et al.  Assessing public transport systems connectivity based on Google Transit data , 2013 .

[32]  Tenny N Lam,et al.  CONNECTIVITY INDEX FOR SYSTEMWIDE TRANSIT ROUTE AND SCHEDULE PERFORMANCE , 1982 .

[33]  S. Wasserman,et al.  Models and Methods in Social Network Analysis: Structural Analysis in the Social Sciences , 2005 .

[34]  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.