Dataset for "Lane nucleation in complex active flows"
Experimental data from human crowd experiments on lane nucleation, including processed videos, extracted trajectories, as well as data processing code.
Code and high-level processed results of agent-based simulations of active binary flows, including hard sphere model, and data-driven model.
Cite this dataset as:
Bacik, K.,
Bacik, B.,
Rogers, T.,
2023.
Dataset for "Lane nucleation in complex active flows".
Bath: University of Bath Research Data Archive.
Available from: https://doi.org/10.15125/BATH-01242.
Export
Data
Experiment_Trajectories.zip
application/zip (6MB)
Creative Commons: Attribution 4.0
Pedestrian trajectories extracted from the experiment
Code
Experimental … Processing.zip
application/zip (14kB)
Creative Commons: Attribution 4.0
Data processing for pedestrian experiments. Includes collisional operator extraction, density analysis, and chiral symmetry assessment.
Simulation … and_Results.zip
application/zip (260MB)
Creative Commons: Attribution 4.0
Code and metadata from agent-based simulations of complex flows.
Mixed access regime: Experiment_Videos.zip will be made available on request to bona fide researchers.
Creators
Karol Bacik
University of Bath
Bogdan Bacik
Academy of Physical Education in Katowice
Tim Rogers
University of Bath
Contributors
University of Bath
Rights Holder
Academy of Physical Education in Katowice
Rights Holder, Data Collector
Documentation
Data collection method:
All methodology information can be found in the main article, and accompanying Supplemental Materials.
Funders
Engineering and Physical Sciences Research Council
https://doi.org/10.13039/501100000266
Discrete noise in stochastic active flows
EP/V048228/1
Publication details
Publication date: 2 March 2023
by: University of Bath
Version: 1
DOI: https://doi.org/10.15125/BATH-01242
URL for this record: https://researchdata.bath.ac.uk/id/eprint/1242
Related papers and books
Bacik, K. A., Bacik, B. S., and Rogers, T., 2023. Lane nucleation in complex active flows. Science, 379(6635), 923-928. Available from: https://doi.org/10.1126/science.add8091.
Contact information
Please contact the Research Data Service in the first instance for all matters concerning this item.
Contact person: Karol Bacik
Faculty of Science
Mathematical Sciences
Research Centres & Institutes
Centre for Networks and Collective Behaviour
