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Stochastic multimodal transport planner based on Swiss data from the SBB.
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Final Project.ipynb

Stochastic multimodal transport planner


Have you ever missed a train because your previous train was late? Stochastic planners give an overview of how feasible a certain trip is. This gives the user the possibility to take alternative routes when the "fastest route" is not very likely.


Final project delivered as part of the EE-490 Lab in Data Science course. The historical data comes from the Swiss network and is made available by SBB.

  • Final Project.ipynb: Jupyter notebook containing the report along with complete codebase

  • BFKOORD_GEO: Location data of public transport stops leveraged in the project

  • graph_saved: Saved data and graphs created during code execution. These are read when re-running the code in order to reduce run time.

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