Simulation of track infrastructure and train traffic

To enable reinforcement learning, a realistic rail simulation was created based on infrastructure data and timetables.
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Realistic simulation

Python package for parsing the infrastructure description

Python package for parsing the RailML timetable

Challenge

  • 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

Solution

  • 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

Result

  • 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?