Transport Mode Detection

Advanced Environmental Statistics

1 Task Description

Understanding human mobility is a key challenge in many fields, including transportation planning, epidemiology, and environmental science. Movement data can (and is) collected in various ways, including GPS data from smartphones, GPS trackers, or other devices. Usually, we are interested in understanding the transportation mode of a user, as this can provide valuable insights into the user’s behavior and preferences. However, this information is usually not available, and it can be challenging to infer the transportation mode from the GPS data alone.

In this project, we will use anotated movement data from the project by Zheng et al. (2011). The goal is to enrich the data with additional features and build a model that can predict the transportation mode of a user based on the GPS data.

Zheng, Yu, Hao Fu, Xing Xie, Wei-Ying Ma, and Quannan Li. 2011. Geolife GPS Trajectory Dataset - User Guide. Geolife GPS trajectories 1.1. https://www.microsoft.com/en-us/research/publication/geolife-gps-trajectory-dataset-user-guide/.