Modeling travel demand for dorm and non-dorm university students

Abstract

This study presents a modeling approach for estimating travel demand at Hasselt University (Flanders, Belgium), where student residence patterns and sociodemographic characteristics play a crucial role. Travel mode choice models based on the Flemish household travel survey are combined with 2023 and 2025 GTFS datasets in order to assess how different public transport services influence student mobility patterns. Results show a slight difference in the mode shares which can have been caused by the use of stochastic processes. On the other hand, model results show clear behavioral differences between dorm and non-dorm students. Residential proximity significantly shifts preferences toward active modes, especially cycling and walking.