Modeling Urban Mode Choice Behavior During the COVID-19 Pandemic in Switzerland Using Mixed Multiple Discrete-Continuous Extreme Value Models
Document Type
Journal Article
Publication Date
2024
Subject Area
place - europe, place - urban, ridership - behaviour, ridership - mode choice, ridership - modelling
Keywords
planning and analysis, choice models, mode choice, models/modeling, behavior analysis, mode choices
Abstract
This paper describes and models the behavioral response to the COVID-19 pandemic in Switzerland. The MOBIS-COVID GPS tracking dataset, which includes a pre-pandemic reference base, is used. Trip-level data are transformed in weekly distance proportions per mode per week, and the data are modeled using a mixed multiple discrete-continuous extreme value (MMDCEV) model. Four distinct segments are derived, from September 2019 until the end of 2020, and used to uncover natural and forced behavioral adaptations. The descriptive and model estimation results confirm the trends partly observed around the globe, that is, a large decrease in public transport usage, recovered car usage, and a cycling boom. Behavioral insights are further provided as well as policy recommendations.
Rights
Permission to publish the abstract has been given by SAGE, copyright remains with them.
Recommended Citation
Meister, A., Mondal, A., Asmussen, K. E., Bhat, C., & Axhausen, K. W. (2024). Modeling urban mode choice behavior during the COVID-19 pandemic in switzerland using mixed multiple discrete-continuous extreme value models. Transportation Research Record, 2678(12), 84-95.
