Connecting people to places: spatiotemporal analysis of transit supply using travel-time cubes

Steven Farber, University of Utah


Transit planning traditionally emphasizes the spatial dimension of accessibility; networks are built to bridge locations in the city with the assumption that the provision of spatial connectivity is equivalent to providing people with access to their destinations. However, often underrepresented in transit analyses, is that travel time, not network proximity, is the fundamental unit of influence over people's travel behavior. It is the time lost in travel that drives whether or not people will make trips. Moreover, it is the time lost in travel that provides the clearest indicator of the burdens and benefits associated with spatial and temporal dimensions of transit provision to the public. Thus, understanding the supply of transit through an analysis of end-to-end travel times can help transit planners better explain patterns of ridership and implement changes to the network that will better serve its ridership. At the same time, by advancing the science of measuring transit accessibility, planners will be able to more accurately assess the equality with which their system provides opportunities to different locations and demographic sectors within their service area.

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 multi-modal 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 aims to assess spatiotemporal dynamics in transit supply in the Wasatch Front and the Portland Area through an investigation of scheduled travel time variability.

Project Details

Project Type:
Project Status:
End Date:
June 30,2016
UTC Grant Cycle:
Tier 1 Round 2
UTC Funding:

Other Products

  • Fransen, K., Farber, S., Deruyter, G., & De Maeyer, P. (2018). A spatio-temporal accessibility measure for modelling activity participation in discretionary activities. Travel Behaviour and Society, 10, 10-20 (PUBLICATION)
  • Fransen, K., Neutens, T., Farber, S., De Maeyer, P., Deruyter, G. & F. Witlox. “Identifying public transport gaps using time-dependent accessibility levels.” Journal of Transport Geography. (PUBLICATION)
  • Building a Multi-modal Network to Perform Accessibility Equity Analyses. (PRESENTATION)
  • Dynamic public transit accessibility: Comparing the effects of infrastructure (dis)investments over time. (PRESENTATION)
  • Public Transport Gaps in Flanders (Belgium). (PRESENTATION)
  • Spatiotemporal accessibility to supermarkets using public transit: an interaction potential approach in Cincinnati, Ohio. (PRESENTATION)
  • Widener, M.J., Farber, S., Neutens, T., & M.W. Horner (2015). Spatiotemporal accessibility to supermarkets using public transit: an interaction potential approach in Cincinnati, Ohio. Journal of Transport Geography (Accepted) (PUBLICATION)
  • Farber, S., Marin, M. R. and Páez, A. (2015), Testing for Spatial Independence Using Similarity Relations. Geogr Anal, 47: 97–120. doi:10.1111/gean.12044 (PUBLICATION)
  • Farber, S., Morang, M. Z., & Widener, M. J. (2014). Temporal variability in transit-based accessibility to supermarkets. Applied Geography, 53, 149-159. (PUBLICATION)
  • Temporal variability in transit-based accessibility: A case study of Cincinnati (PRESENTATION)
  • Farber, S., Ritter, B. & L. Fu. “Space-Time Mismatch between Transit Supply and Travel Demand in the Wasatch Front, Utah.” Travel Behaviour and Society. (PUBLICATION)