Computational Model Library

Bicycle model (version 2.0.0)

The purpose of the model is to generate the spatio-temporal distribution of bicycle traffic flows at a regional scale level. Disaggregated results are computed for each network segment with the minute time step. The human decision-making is governed by probabilistic rules derived from the mobility survey.

Release Notes

Download the GAMA-platform (GAMA1.8 with JDK version) from The platform requires a minimum of 4 GB of RAM.

After installation set up the maximum memory allocated to the GAMA to at least 4 GB. It is possible through the GAMA menu in Help -> Preferences -> Interface. Make sure the platform uses the same coordinate reference system as the input shapefiles (EPSG:32633) in Help -> Preferences -> Data and Operators.

The download zip has the “code” folder with the GAMA project files. Import these files into the GAMA by right-clicking on the “User-models” in the “Models” tab of the GAMA interface. Select the “GAMA project”. In the new window browse to the “code” folder as a root directory. Make sure to check the boxes “Search for nested projects” and “Copy project into workspace”. Click Finish.

Alternatively, you can download the model from the GitHub repository

Running experiment

The input data of the project is in the “includes” folder and the model code in the “models” folder under “bicycle_model.gaml” name.

Before running the model code there is an option to parameterize the routing algorithm by selecting either the “shortest path” or “safest path” (default). The rest of the parameters is used to set the weights for bikability index calculation.

Associated publications
Kaziyeva, D.; Loidl, M.; Wallentin, G. Simulating Spatio-Temporal Patterns of Bicycle Flows with an Agent-Based Model. ISPRS Int. J. Geo-Inf. 2021, 10, 88.

Version Submitter First published Last modified Status
2.0.0 Dana Kaziyeva Mon Feb 22 14:32:32 2021 Mon Feb 22 14:32:32 2021 Published
1.0.0 Dana Kaziyeva Tue Jan 15 09:39:40 2019 Tue Jan 15 09:39:40 2019 Published

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