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
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Python package for parsing the infrastructure description

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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?

Challenge

An automotive company would like to visualise various market-specific data in order to create a Competitive analysis for the US market.

Solution

There will be a interactive and Flexible application, includingย of different maps with two different views implemented.

Result

Relevant markets are identifies, analyses and visualises. The dealer or the respective sales department have the possibility to compare the direct competition with their own product and to visualise the relevant data.