The Flatland Framework is a multi-purpose simulation framework to tackle problems around resilient resource allocation under uncertainty with a focus on railway networks. The framework provides a flexible, method-agnostic simulation environment to support research into novel approaches from operations research and machine learning, particularly for solving real-time vehicle rescheduling and dispatching challenges.

In this presentation, we will dive into Flatland's development as an open research framework, from its origins in addressing practical railway challenges to its current role in the transportation research community. The talk will demonstrate the framework's key capabilities and explore how the open source approach sparked a rich community and ecosystem around open transport research.