Marshall DAVEY

Biographical note
Marshall Davey (BSc) is a research assistant at Concordia University s Transportation Research for Integrated Planning (TRIP) lab.,working under the supervision of Zachary Patterson.

Presentation: Transit network complexity in the context of transit itinerary inference with smartphone travel survey data
Thanks to increased spatial and temporal accuracy, travel survey applications for smartphones, and GPS loggers are becoming commonplace amongst network analysts’ tools. Along with the increased usage of these technologies has come the opportunity to expand the repertoire of indices used by researchers to analyze networks. By combining GPS data and geographically faithful General Transit Feed Specification (GTFS) data, Transit Itinerary Inference algorithms have allowed researchers to almost fully describe
riders’ trips based solely on limited data. Where these algorithms fall short, however, is in correctly attributing transit route info to trips that occur in areas of high transit overlap.
The researched proposed in this paper aims to address these areas of high network complexity by introducing a new metric. The “active routes on links” count (AROL), aims to provide a more nuanced description of a network than the currently available indices. The problem of correct route inference typically occurs in areas of high transit overlap, and while the concept of transit overlap has been explored by Vuchic and Musso (2005), their “line overlapping index” only provides one measure for the entire network. Our metric expands upon this idea by allowing for the ranking of individual road links according to how many routes they each contain, furthermore, a time series can be generated for the amount of overlap occurring at any given time of the day.
The AROL index is especially handy for describing complex networks on a fine scale, a scale at which other metrics simply don’t provide information. Most importantly, the AROL metric will provide network analysts with a measure of how reliably the GPS data-points collected from their travel surveys can correctly be attributed to one specific transit route. By performing a comparative study of the transit networks of Montreal, Toronto, Calgary, and Vancouver, contrasted with validated survey data for Montreal, we create a ranking of each city’s transit networks based on how reliably a route detection algorithm will function. By using geographically faithful GTFS datasets, provided free of charge by transit agencies, as well as GIS road shapefiles, the metrics described in this paper are intended to be readily available to researchers and planners from a variety of backgrounds and industries.