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Local transit, Travel time (Traffic engineering)


Despite its importance, temporal measures of accessibility are rarely used in transit research or practice. This is primarily due to the inherent difficulty and complexity in computing time-based accessibility metrics. Estimating origin-to-destination travel times that include the “last mile” of travel between the transit network and actual start and endpoints of the trip is technically difficult. Not only do such estimations require multimodal network structures, they also require detailed knowledge of transit schedules and sophisticated algorithms for calculating shortest paths using such inputs. Recently, new standards for sharing transit schedules and geographic data, namely the General Transit Feed Specification (GTFS) have prompted innovations in the analysis of complex transit travel times using the Esri ArcGIS package with the Network Analyst extension. With continued development of the analytical capabilities of network analysis functionality, this project assesses spatiotemporal dynamics in transit supply through an investigation of scheduled travel time variability.

This report consists of a collection of three stand-alone research papers. The first defines a new data object, the public transit travel time cube, and demonstrates its use in measuring changes in transit provision over time, changes in accessibility to jobs, and the impacts of bicycling on the last mile problem. The second paper consists of a study of temporal mismatch between observed travel patterns and the spatiotemporal patterns of transit supply in the Wasatch Front. The third paper expands the food desert literature by measuring temporal fluctuations in food accessibility over the course of a typical day, and examining the trends for disparities between socioeconomic subgroups. Our findings indicate that time-based measures of transit accessibility provide more nuanced abilities for us to understand how people are impacted by temporal variability in transit provision.


This is a final report, NITC-RR-662, from the NITC program of TREC at Portland State University, and can be found online at:



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