Travel demand generation using Bayesian networks
Open access
Date
2023Type
- Conference Paper
ETH Bibliography
yes
Altmetrics
Abstract
Thanks to their ability to simulate the travel behavior at the individual scale, agent-based models have gained popularity over the last years. These models are data-intensive, with regards to transport supply and demand. In particular, a detailed description of the population and its travel behavior is required. Bayesian Networks (BNs) are directed acyclic graphs representing joint probability distributions. They have recently been employed for population synthesis and daily activity patterns generation in studies showing that BNs effectively capture the causality links existing between variables and are easily interpretable. Moreover, given their flexible structure, BNs can be adapted for situations in which data from various sources is combined. In this paper, our goal is to estimate a BN for both population and activity pattern synthesis in Switzerland. We evaluate the performance of this approach compared to the statistical matching algorithm using aggregated and disaggregated metrics. In particular, we show that understanding the dependency structure linking the population characteristics and its mobility behavior is key to generate representative synthetic agents and daily activity patterns. This study is a contribution towards the development of interpretable, flexible and behaviorally rich travel demand generation models. Show more
Permanent link
https://doi.org/10.3929/ethz-b-000617405Publication status
publishedExternal links
Editor
Book title
The 14th International Conference on Ambient Systems, Networks and Technologies Networks (ANT 2022) and The 6th International Conference on Emerging Data and Industry 4.0 (EDI40)Journal / series
Procedia Computer ScienceVolume
Pages / Article No.
Publisher
ElsevierEvent
Subject
Travel demand generation; Activity-based models; Bayesian networks; Synthetic populationOrganisational unit
03521 - Axhausen, Kay W. (emeritus) / Axhausen, Kay W. (emeritus)
02655 - Netzwerk Stadt u. Landschaft ARCH u BAUG / Network City and Landscape ARCH and BAUG
Funding
18613 - Weiterführung des MOBIS/COVID19 Panels - Verkehrsverhaltenspanel für die Schweiz (SNF)
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Is new version of: http://hdl.handle.net/20.500.11850/548635
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ETH Bibliography
yes
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