- In order to be able to generate decision recommendations for train scheduling, reinforcement learning is to be applied.
- As a basis for the training of RL models, a realistic, track-focused simulation of train traffic is to be created. SUMO is to be used as the simulation software
- Track plan data and timetable must be translated into a format that can be used for the simulation. The resulting track graph should represent the actual location and position of the operating points
- Understanding structure and documentation of the data formats used
- Evaluation of the realism of the simulation based on simulated times and distances using target data
- Modular software structure to allow the use of different data sources (e.g. timetable) or simulation tools
- Realistic simulation that can be used to generate states for reinforcement learning
- Python package for parsing the infrastructure description and generating the track graph for the simulation
- Python package for parsing the RailML timetable and generating route files for the simulation
Are you interested in your own use cases?