Transit Trails

Visualization of bus location data before and after major transit cuts.

1. Camille Cobb [email protected]
2. Caitlin Bonnar [email protected]
3. Yi Pan [email protected]
4. Katie Kuksenok [email protected]

###Breakdown & Development Process In the early stage of our project, all four of us met to discuss ideas and storyboard the project. We then discussed how to break up the work amongst us, and came up with the following task assignments:

• Camille:
  • Designed paper prototypes
  • Created & delivered progress presentation
  • Conducted user studies, worked on interview script
  • Performed iterative enhancement on design
  • Designed poster
  • Structured and wrote majority of paper
• Yi:
  • Designed paper prototypes
  • Conducted user studies, worked on interview script
  • Performed iterative enhancement on design
  • Designed poster
  • Helped with early data cleaning
• Katie:
  • Brainstormed initial idea, found related work
  • Curated and handled data
  • Created API for accessing curated data
  • Wrote progress report, contributed to and formatted final paper
• Caitlin:
  • Gathered project data from OneBusAway servers, performed first round of cleaning
  • Created the web prototypes
  • Performed iterative enhancement on design
  • Implemented final visualization & touched up final design
  • Contributed to final paper

We were all very communicative throughout the process, and in reality, we all were involved in each stage. There were a lot of frustrations with the data, which also took a lot of time to gather and clean, but everyone remained responsive and quickly adapted the project needs to support the data.

Abstract:

We created an interactive visualization intended to depict the effect of route cuts in Puget Sound over a year’s time (specifically, March 2011- March 2012), and allow exploration of congestion data by day of week and time of day. To support this task, we designed and implemented an interactive visualization depicting historical OneBusAway data, which consist of individual bus positional check-ins every ten seconds and their deviation from schedule at that time and location. Our final visualization includes a side-by-side comparison of points on a map of Puget Sound. Points represent a location where at least one bus checked in at within a time interval specified by the user. The color of each point represents the average deviation of buses that checked in at that location. We conducted eight user studies with transit experts and regular bus riders in order to evaluate and test our design and elicit feedback about how well we supported these goals. We then performed iterative enhancement to improve interactions and layout. Although we believe that the available data were not sufficiently complete to warrant more detailed exploration, the product we created accomplishes the goals of facilitating exploration of congestion and coverage differences resulting from transit changes and serves as a useful starting point for future visualizations once data collection has been improved.

Poster, Final Paper

Running Instructions

Access our visualization at http://homes.cs.washington.edu/~cbonnar/viz/busviz.html or download this repository and run python -m SimpleHTTPServer 9000 and access this from http://localhost:9000/.