Probabilistic routing for agent-based simulations
OPEN ACCESS
Author / Producer
Date
2024-08
Publication Type
Working Paper
ETH Bibliography
yes
Citations
Altmetric
OPEN ACCESS
Data
Rights / License
Abstract
Traditional route assignment approaches in agent-based models often rely on least-cost path algorithms, which may not accurately reflect the complex decision-making processes of cyclists. This research addresses these limitations by incorporating probabilistic elements into the routing model, thus accommodating the variability in route choices observed in real-world scenarios. The proposed model integrates a Recursive Logit framework to account for the influence of various factors such as gradient, surface quality, traffic conditions, and dedicated cycling infrastructure on cyclists’ route selection. A case study using a detailed Zurich scenario demonstrates the model’s application and effectiveness. Results show that the probabilistic routing model not only aligns more closely with observed cyclist behavior but also offers a robust tool for urban planning and policy evaluation aimed at promoting sustainable and active transportation modes.
Permanent link
Publication status
published
External links
Editor
Book title
Journal / series
Volume
1889
Pages / Article No.
Publisher
IVT, CSFM, ETH Zurich; HKUST Hong Kong
Event
Edition / version
Methods
Software
Geographic location
Date collected
Date created
Subject
Cycling; Route-choice; Agent-based; MATSim
Organisational unit
03521 - Axhausen, Kay W. (emeritus) / Axhausen, Kay W. (emeritus)
02261 - Center for Sustainable Future Mobility / Center for Sustainable Future Mobility
02655 - Netzwerk Stadt u. Landschaft ARCH u BAUG / Network City and Landscape ARCH and BAUG
Notes
Funding
Related publications and datasets
Is previous version of: