Description
The work associated with this project is described in a manuscript entitled "How vision governs the collective behavior of cycling pelotons" by Belden et al., along with an electronic supplementary material document. We investigate properties of densely packed groups of bicycle racers, which are known as cycling pelotons. These pelotons exhibit features of collective animal behavior, including emergent behavior from inter-individual interactions. In this data set, we classify global shapes of the peloton, and identify and track individual cyclists to determine the details of network structure. We also investigate motion waves that propagate through the pelotons.
Author ORCID Identifier
Tadd T. Truscott https://orcid.org/0000-0003-1613-6052
Jesse Belden https://orcid.org/0000-0003-3754-6528
OCLC
1117775103
Document Type
Dataset
DCMI Type
Dataset
File Format
.MAT, .M, .FIG, .XLSX, .TIFF, .EPS, .TXT, .PNG
Viewing Instructions
MatLab or open source program required to open .mat files.
Publication Date
3-26-2019
Funder
Office of Naval Research
Publisher
Utah State University
Award Number
Office of Naval Research N00014-19-1-2059
Methodology
The raw data come from video footage of the 2016 Tour de France professional bicycle stage race, which is filmed from a helicopter to provide an overhead view of the pelotons. Video clips of interested are extracted and associated with certain metadata about the details of the race at the instant of the clip. Video clips are parsed into individual images at the time spacing corresponding to the frame rate of capture. A set of image processing algorithms is used to extract rider locations, network structure, and wave propagation behavior in a metric reference frame; these algorithms are described in "How vision governs the collective behavior of cycling pelotons" by Belden et al., and in the supplementary material document supplied with the paper.
Referenced by
Belden, J., Mansoor, M. M., Hellum, A., Rahman, S. R., Meyer, A., Pease, C., Pacheco, J., Koziol, S., & Truscott, T. T. (2019). How vision governs the collective behaviour of dense cycling pelotons. Journal of The Royal Society Interface, 16(156), 20190197. https://doi.org/10.1098/rsif.2019.0197
Language
eng
Code Lists
See attached README file
Disciplines
Mechanical Engineering
License
This work is licensed under a Creative Commons Attribution 4.0 License.
Recommended Citation
Truscott, T. T., & Belden, J. (2019). Peloton racking and analysis from the 2016 Tour de France. Utah State University. https://doi.org/10.26078/SBQ2-1C60
Checksum
743eb12c4d5b2d80d53269b306b381ab
Additional Files
README.txt (4 kB)MD5: 93d37a3622396b1b7c22b0e0074c0f56
analysis.zip (3147 kB)
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TdF_Clips_Flat_Head_2.zip (475243 kB)
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TdF_Clips_Flat_Head_4_Catching.zip (107720 kB)
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TdF_Clips_Greater_than_10km_greater_than_60s_Arrow.zip (228494 kB)
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TdF_Clips_Greater_than_10km_greater_than_60s_Echelon_2.zip (342369 kB)
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TdF_Clips_Greater_than_10km_greater_than_60s_Echelon.zip (177165 kB)
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TdF_Clips_Greater_than_10km_greater_than_60s_Echelon.zip (177165 kB)
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TdF_Clips_Greater_than_10km_less_than_60s_Arrow.zip (224754 kB)
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TdF_Clips_Less_than_10_Less_than_60_2_Arrow.zip (299491 kB)
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TdF_Clips_Less_than_10km_greater_than_60s_Arrow.zip (229301 kB)
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TdF_Clips_Less_than_10km_greater_than_60s_Line.zip (175849 kB)
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TdF_Clips_Less_than_10km_Less_than_60s_Echelon_2.zip (140526 kB)
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TdF_Clips_Less_than_10km_Less_than_60s_Echelon_3.zip (84379 kB)
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TdF_Clips_Less_than_10km_Less_than_60s_Echelon.zip (227095 kB)
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TdF_Clips_Less_than_10km_Less_than_60s_Flat_1.zip (201883 kB)
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TdF_Clips_Less_than_10km_Less_than_60s_Line_1.zip (191951 kB)
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TdF_Clips_Stage_1_1_Double_razor_into_razor.zip (114488 kB)
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TdF_Clips_Stage_1_3.zip (1095479 kB)
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TdF_Clips_Stage_4_three.zip (183876 kB)
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TdF_Clips_Stage_6_two.zip (659967 kB)
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TdF_Clips_Stage_16.zip (238800 kB)
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Comments
data supports forthcoming article and will be released upon article publication.