Big data simulation of Chicago's public transportation to improve transit planning and reduce bus crowding.
This project is a part of the 2013 Data Science for Social Good fellowship, in partnership with the Chicago Transit Authority.
For a quick and gentle overview of the project, check out our blog post.
The Chicago Transit Authority (CTA) has made a concerted effort to decrease the crowding on public transportation that has been a cause for concern over the last few years. The CTA has been collecting information such as: the number of people riding a specific bus, the times at which more people board buses at a specific stop, and the delay times on different routes, among other things. This data, after some processing, is used to understand and modify schedules and routes for the following quarter.
Read more about bus overcrowding on our blog
While current best practices are data-focused, they are retrospective in nature. We propose to turn scheduling into a more prospective exercise through statistical modeling and simulation. This will allow the planning analytics department to be more proactive and to better understand the impact of certain scheduling decisions on bus crowding before implementation. Given the richness of the data available, we believe that even a simple statistical model and simulation approach will provide useful insight into bus de-crowding.
Our tool displays historical data with the metrics the CTA uses today and incorporates new metrics along with simulated data. The new data will help the CTA have a deeper understanding of the results that arise from schedule changes. This new understanding will help the CTA in the effort to reduce crowding on buses.
Read more about our methodology in the wiki
Coming soon!
Most of the information regarding the project idea can be found in the wiki section of the github repository at https://github.com/dssg/dssg-cta-project/wiki
Mentor
Brandon Willard
Research Consultant at Chicago Booth
Fellows
 |
 |
 |
 |
|---|---|---|---|
| Andrés Akle | Jordan Bates | Walter Dempsey | David Sekora |
| Applied Mathematics and Telecommunications | Applied Math for Life and Social Science | Statistics | Mathematics and Computer Science |
| Instituto Tecnológico Autónomo de México | Arizona State University | University of Chicago (Hyde Park, baby!) | University of Chicago |
To get involved, please check the issue tracker.
To get in touch, email Walter Dempsey at [email protected].
Copyright (C) 2013 Data Science for Social Good Fellowship at the University of Chicago
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