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Public Transit Travel Time Estimation
11: Urban Studies and Planning
September 7, 2020
Hui Kong: email@example.com
Estimating passengers’ door-to-door travel time by public transit can be complex for large networks with many path alternatives available. Additional complications arise in tap-on only transit systems, where passenger alighting data are not recorded. This project is designed to compare the three methods that estimate the travel time by public transit: assuming optimal path choice given scheduled service, as represented in the General Transit Feed Specification (GTFS); assuming optimal path choice given actually operated bus service, as recorded by Automatic Vehicle Location (AVL) systems; and using inferred path choices based on Automated Fare Collection (AFC) records, as processed with an Origin-Destination-Interchange inference algorithm (ODX). The case study will be conducted in Chicago, with the support of the Chicago Transit Authority (CTA). Methods 1 and 2, hereinafter GTFS and AVL respectively, use a common open-source shortest path algorithm to calculate travel times. The third method uses an implementation of ODX customized for the CTA.
Prior experience with querying and analyzing large data sets is required; experience with python is recommended.