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 based on their risk appetite 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.