This past summer I worked with the Washington Metropolitan Area Transit Authority (WMATA) in their office of Transit Performance Management (PERF). The purpose of PERF is to monitor the performance of all of WMATA’s operations including the trains, busses, and internal departments. My main project was developing a tool that is able to automatically determine the estimated trip time between all pairs of rail stations. Previously, if any adjustment to the rail network was made, be it changes to headways (times between trains), station closures, or line rerouting, the PERF team would have to manually update the trip times between all the stations. The tool that I developed in R is able to represent the metro system as a graph and run shortest path algorithms to determine baseline expected travel times. Already, the tool has been used to benchmark rail trips to get a more accurate sense of train on-time performance.

This summer gave me a great sense of the ways that data science and algorithms can be applied to the field of planning. Getting to see this intersection of fields in a context outside of my normal academic work has helped reaffirm my appreciation for my major in course 11-6, and I am grateful to have gotten this opportunity.