Simulating better bus service

Fellows: Andres Akle, Jordan Bates, Walter Dempsey, David Sekora
Data Science Mentor(s): Brandon Willard
Project Partner: Chicago Transit Authority (CTA)
[Github Repository]

The Chicago Transit Authority (CTA) runs the nation’s second largest transit system. Its buses and trains agency move a ton of people – around 1.6 million trips are taken each day. CTA also gather lots of data: they know where buses and trains are in real-time and how many people get on and off at each bus stop.

Our 2013 DSSG team built transit planning tools that help the CTA better predict the impact of a service change on a route – and all connecting routes – before deploying a single vehicle.

We used CTA’s bus GPS and passenger count data to simulate future demand at every stop in Chicago, and predicted how well transit service is likely to perform under a particular schedule change. We also mapped how different schedules affect Chicagoans’ ability to get around. Using cutting-edge simulation, the CTA can now plan bus and rail service with greater efficiency.