This document outlines the methodology used to analyze transit patterns using TriMet's internal data. The analysis focuses on understanding how passengers move through the transit network by tracking their origins, destinations, and transfer points.
The ODX data covers approximately 22% of TriMet rides taken by passengers who pay and tap via Hop:
The Hop taps represents approximately 48% of unlinked trips on TriMet bus and Max.
Of these, the ODX Model can infer a destination for 65% of those trips.
The model filters out 30% of journeys that don't meet our quality standards, resulting in 22% of total journeys being available for analysis.
Base Datasets
The Origin-Destination Transfer inference algorithm (ODX Methodology) depends on the following datasets, all sourced from TriMet's enterprise data warehouse:
HOP transaction journal: A journal of all the boarding taps made by riders using any fare payment method besides cash. Included are the date, time, stop ID, line ID, and anonymized card ID that allows different transactions to be tied to an anonymized individual rider.
Automated Vehicle Location (AVL): The observed stop times and stop IDs across all times of in-service TriMet vehicles. Covers both buses and light rail. A trip ID associates a set of stop times and IDs across a service date.
Static GTFS data: Attributes fields like the operating line ID to the AVL data.
Validation
A number of different methods were used to validate the results of the ODX inference:
Comparison with a human expert: a human expert reviewed approximately three months of journey data, achieving a success rate above 90% with strict validation of interlining events.
Evaluation of synthetic journeys: The ODX methodology was tested against 320 synthetic journeys, where 78% of the inferred alighting locations were within 1500 feet of the actual locations.
Comparison with quarterly APC (Automated Passenger Counters): When accounting for the coverage of the HOP transaction journal and the inference success rate, 90-96% of the inferred ODX counts fell within one standard deviation of the APC measurements.
The full extent of the validation is documented in the Validation Memo.
Main Methodology Assumptions
There are three main assumptions made in the ODX methodology. These are important to note.
First, the ODX methodology assumes that a rider's alighting location is close to their following boarding location. In the below figure, the dark gray circles indicate observed boarding events drawn from the HOP transaction journal. The light gray circles indicate inferred alightings, the target outcome of this process.
Second, the ODX methodology assumes that if a rider is inferred to have missed several boarding opportunities at a stop, then the location of their inferred alighting was, in fact, the end of their trip. In this case, the alighting is tagged as a destination, and the subsequent boarding is classified as an origin. All events (whether boarding or alighting) between an origin boarding or a destination alighting are tagged as mid-journey. The threshold for determining if an alighting is a destination depends on the headway observed at the next boarding stop/line pair. The threshold value follows a sigmoidal relationship bounded between one and three and centered on fifteen minutes. For low headways, riders must have above three boarding opportunities before alighting is tagged as a destination. Inversely, for high headways, a rider must take advantage of only one boarding opportunity for the alighting to be considered a destination.
Third, to select an inferred alighting location from the suite of possible candidates, a rider is assumed to minimize the time to the following boarding location. This time is composed of the ride time and the transfer time. The ride time is the time spent riding the transit vehicle to the alighting location, while the transfer time is the time taken to walk from the alighting location to the following boarding location. A walking speed of four feet per second estimates the transfer time. The below figure shows the ride times and transfer times given a candidate's alighting location.
Additional Notes on Methodology
The HOP Transaction Journal does not cover all rider events. For example, the transaction journal does not include riders who do not pay or pay through cash. The HOP transaction journal covers approximately 48% of riders.
Only journeys that exclusively use TriMet infrastructure are included, i.e., Portland Streetcar and C-TRAN are not included. The inference process successfully infers alightings for approximately 65% of boardings.
The dataset excludes certain types of journeys to ensure data quality. Specifically, we remove "loop" journeys that end within 200 feet of their starting point and journeys with duplicate boarding taps at the same location. Each journey is evaluated using two scores: a validity score (indicating the likelihood of the trip being completed via transit) and a confidence score (showing the model's certainty about the inferred itinerary).
Through Sensitivity Analysis, we established thresholds for these scores, leading to the removal of approximately 30% of inferred journeys that fell below these standards. Considering the coverage of the HOP transaction journal, the inference success rate, and the discard rate, the ODX data cover approximately 22% of TriMet’s ridership.
The unique identifier per card is rotated once a month, meaning it is impossible to follow a card’s movement patterns across months. This causes the number of successful inferences to dip around the beginning/end of each month.
Have Questions?
In-app support is the best way to get help or answer questions regarding anything in the UrbanLogiq Platform (even questions regarding methodology). First, you can click on the chat bubble icon at the bottom left corner of the sidebar. Then you can start a new conversation in the chat box pop-up.
Furthermore, this is the best way to provide product feedback. We thrive and love hearing how our platform can be better. Giving us product feedback in the in-app chat requests is gathered and prioritized. This is the best way to give feedback. We love hearing feedback from our customers and love answering questions!
You can also call us (1-833-872-2647) or email us (customersuccess@urbanlogiq.com)
Happy Exploring!