Innovative GTFS Data Application for Transit Network Analysis Using a Graph-Oriented Method

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.