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Robust Journey Planning

Guarin Fluck, Emilio Fernández, Hiroki Hayakawa, Xiangyu Tian

In this project, we developed a robust journey planner for Swiss public transport network in the city of Zurich. In other words, we tried to build our own custom "Google Maps" but also taking probability of delay into account for prioritasing the less delayed connections. The detailed task description can be found in project_description whereas final_notebook explains the structure of the project. A short video presenting the final solution can be found here.


Installation setup

conda env create -f local_environment.yml
jupyter labextension install @pyviz/jupyterlab_pyviz

If there are any issues run:

conda env create -f local_environment_export.yml
jupyter labextension install @pyviz/jupyterlab_pyviz

Journey Planner Interface

Journey Visualization

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Final Project for Data Science Lab

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