Public transit networks are constantly evolving in the face of frequent economic and social challenges. There exists a large knowledge base on travel demand; however, there is a shortage of information on travel supply and networks. To our knowledge, no analysis tool can, at this point, systematically characterize a network and observe changes over time in a structured and automated manner. This paper addresses this issue and proposes a graph-oriented method for developing an analysis tool that will characterize a single network and then provide the necessary means to compare two distinct networks. A time-expanded model was applied to import General Transit Feed Specification (GTFS) data into a graph database. With built-in algorithms, shortest paths were computed and indicators were derived from these paths. A small case study demonstrates the applicability of the method. This approach still needs to be optimized to process networks that are more complex.
Fortin, Philippe, et al.
Innovative GTFS Data Application for Transit Network Analysis Using a Graph-Oriented Method.
Journal of Public Transportation, 19 (4): 18-37.
Available at: https://digitalcommons.usf.edu/jpt/vol19/iss4/2