Vanderbilt engineers to train neural networks and enhance Chattanooga transit system

Vanderbilt engineers to train neural networks and enhance Chattanooga transit system

Chattanooga is the test city for new Department of Energy-funded project that leverages expertise of Vanderbilt engineers and widespread availability of 1-gigabyte Internet connection to revolutionize energy efficiency of transit providers.


Advancements in data sensors, data collection and machine learning will fuel the project, which aims to optimize schedules of bus routes, decrease stop-and-go bus driving and reduce energy consumption at a system-wide level.


Creating reusable tools that can benefit other mid-size cities is a key goal of the two-year project with the Chattanooga Area Regional Transportation Authority. Chattanooga’s existing Internet capabilities and multi-modal public transit options made the metropolitan area attractive for the research, the DOE said.


Vanderbilt Assistant Professor of Computer Science Abhishek Dubey and Research Assistant Professor of Civil and Environmental Engineering Yuche Chen, with Aron Laszka, an assistant professor at the University of Houston and former Vanderbilt research assistant professor, will provide context-specific, high definition energy consumption maps for the transit agency. The maps will be trained using rich data sets collected directly from CARTA vehicles that capture everything from the route to the terrain to when and how bus drivers brake and accelerate, Dubey said.