Microaccessibility with OpenTripPlanner

Analysis of accessibility is generally undertaken in large regions, such as metropolitan areas or entire countries. Frequently it also uses macro temporal scales, as in before-and-after analysis. This analysis instead looks at micro scales, both spatial and temporal. The study area is the University of California, Santa Barbara campus and the adjoining student community of Isla Vista.

I analyzed accessibility at every hour of a typical week, so that accessibility can be compared at different times of day and on different days. This has been done before, looking at accessibility at different times of day (page 8) in the Los Angeles area. I used tighter temporal scales (one hour instead of four chunks) and also analyzed accessibility over the entire week to allow the discernment of weekly cycles.

Only accessibility to eateries was analyzed. Data were obtained from OpenStreetMap for network data and from the UCSB Interactive Campus Map for data on eatery locations. Animations of accessibility over a typical week follow; in the darker blue areas more eateries are accessibile within five minutes’ travel time. Five minutes was chosen as the cutoff because it is half of the walking time between the intersection of Pardall and Embarcadero Del Norte and the front of the University Center, two areas where many eateries are concentrated. A more systematic study would need to estimate this from travel data. Acessibility was analyzed for both walking and cycling.

Accessibility to eateries at different times of day by walking.
Accessibility to eateries at different times of day by bicycling

The two animated maps show the accessibility to eateries at different times of day by different modes. The bicycle map shows much more accessibility because with a bicycle one can reach many more opportunities in 5 minutes’ time. A daily cycle can easily be determined, with most (but not all) businesses closing in the late evening and opening again in the morning, creating a pulsing accessibility. The eateries on campus (the eastern portion of the maps) do not have the same span of service as the eateries in Isla Vista. On the weekends, most of the campus eateries are not open at all.

There are a few limitations. OpenTripPlanner’s cycling mode currently does not support bicycle parking; at UCSB, there are many bicycle parking areas where one must park before going to one’s building. At a micro scale of analysis, correctness of the network is also very important because small absolute errors can be large relative to the total length of the trip; OpenStreetMap data was improved for this project but is still not perfect, especially given construction on campus.

Further research would use behavioral data to better estimate parameters for the accessibility measure, as well as to interpret the results. Sara Matthews analyzed mode choice in trips to Humboldt State University in the context of residential location. Accessibility could be used as a independent variable in a similar analysis of mode choice.

Even in the context of comprehensive transportation models such as SimAGENT ( Southern California Association of Governments) and SF-CHAMP ( San Francisco County Transportation Authority), accessibility measures rendered as maps such as these are valuable. They are understandable and thus can easily be presented to non-technical decisionmakers and to the public. They also generally have more of a descriptive rather than projective role; that is, they describe current situations rather than predicting future ones. Finally, they can play a role in individual decision support; Jarrett Walker has noted the usefulness of isochrones for decision support, and these accessibility measures can play the same role. Walk Score® has recently announced understandable accessibility maps; this makes these types of measures much more available.

For a more in-depth treatment, see the full report.

Special thanks to Dr. Konstadinos Goulias and Jae Lee in the GeoTrans lab at UCSB, and to Bryan Karaffa in the UCSB Department of Geography.

Map data © OpenStreetMap contributors. Eatery data © UCSB Interactive Campus Map.

These maps and analyses are the result of a research project and should not be used for decision support without additional consultation.

Matthew Wigginton Conway
Matthew Wigginton Conway
PhD Candidate in the School of Geographical Sciences and Urban Planning, Arizona State University

I am PhD Candidate in Geography at Arizona State University, where I research how zoning codes influence transport outcomes.