A Clustering-Based Framework for Individual Travel Behaviour Change Detection

In our recently published 2021 GIScience paper “A Clustering-Based Framework for Individual Travel Behaviour Change Detection“, we propose a clustering-based pipeline to delineate travel behaviours and detect possible change periods/points from raw GPS recordings. In particular, considering trip mode, trip distance, and trip duration as travel behaviour dimensions, we measure the similarities of trips and group them into clusters using hierarchical clustering. Two different methods are then proposed to detect changes in an individual’s observed usage proportion of trip clusters. Through testing the framework on a large-scale longitudinal GPS tracking dataset, we demonstrate its effectiveness in detecting change periods/points by jointly considering multiple travel behaviour dimensions.

The code is openly available on GitHub, with the possibility to reproduce the framework on the Geolife dataset. The study is to be presented at GIScience 2021 and the pdf version is available here.

New Project V2G4CarSharing Is Funded by the SFOE

Our new project “V2G4CarSharing” in collaboration with Hive Power and Mobility is funded by the Swiss Federal Office of Energy (SFOE) mobility research program. The project aims to develop and evaluate optimal strategies to integrate car-sharing and Vehicle-to-Grid (V2G). By integrating car-sharing and V2G, our research will tackle core issues related to the stability of the Swiss power grid and the electrification of the transportation system, thus supporting the fulfillment of the Swiss Energy Strategy 2050.