PhD candidate Shivam Agarwal developed a visualization tool to analyze train schedules in the Flatland competition, organized as part of the NeurIPS 2020 conference, held virtually in December. The developed visualization received the first prize in the community category for tools to support the participants of the competition.

Flatland is an open source project which promotes research on finding alternate techniques to schedule trains on virtual rail networks. In the NeurIPS 2020 competition, special emphasis was on exploring reinforcement learning. The Flatland project is supported by the national railway companies of Germany, France, and Switzerland.

Our tool visualizes the trains’ behavior on a timeline and shows connections between important regions of the network. The visualization tool was developed in collaboration with the Flatland community and with Günter Wallner, Assistant Professor at the Eindhoven University of Technology and Senior Scientist at the University of Applied Arts Vienna.

Check out the tool here and learn more about the Flatland award winners.