A Dynamic Custom Travel Survey
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Updated
Jun 4, 2025 - JavaScript
A Dynamic Custom Travel Survey
Discrete choice model for the choice of main transport mode by foreign tourists in Switzerland, estimated on the data of the Tourism Monitor Switzerland (TMS) from Switzerland Tourism
This repository provides a model‑agnostic, uncertainty‑aware framework for transportation mode‑choice prediction via Inductive Mondrian Conformal Prediction (IMCP). While XGBoost is used as the base classifier in our experiments, the conformal wrapper is compatible with any predictive model.
R-Script for EDA of Travel Diary Data and developing Mode Choice Models based on Utility Functions.
Four-step travel demand model on a real Bangkok OSM network comparing MNL and eUnit mode choice (Python, OSMnx)
In this project, we are trying to understand the travel behavior of people. Specifically, we are interested in the causal mechanism of how people choose a particular mode over other available modes. Ultimately, we learned which variables are causally related to each other by employing causal structure learning techniques.
Survey analysis of commuter mode choice in Bengaluru: metro, bus, two-wheeler, cab and barriers to public transport
Classifying Travel Mode choice in the Netherlands using KNN, XGBoost, RF and TabNet
Code and reproducible analysis for the TU Delft MSc Thesis "Mode choice behaviour of dynamic street space allocation: A stated-preference experiment in Amsterdam"
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