Peloton tracking and analysis from the 2016 Tour de France


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.



Document Type




File Format


Viewing Instructions

MatLab or open source program required to open .mat files.

Publication Date



Office of Naval Research


Utah State University

Award Number

Office of Naval Research N00014-19-1-2059


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



Code Lists

See attached README file


data supports forthcoming article and will be released upon article publication.


Mechanical Engineering


Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.

Additional Files

README.txt (4 kB)
MD5: 93d37a3622396b1b7c22b0e0074c0f56

analysis.zip (3147 kB)
MD5: 56bff06c6fed15162997045e8ff9457d

TdF_Clips_Flat_Head_2.zip (475243 kB)
MD5: de1597b21a436012e8080d99a058da88

TdF_Clips_Flat_Head_4_Catching.zip (107720 kB)
MD5: f858438ea7d1df60fb8c4d35b02e89a2

TdF_Clips_Greater_than_10km_greater_than_60s_Arrow.zip (228494 kB)
MD5: 2d4245ac0cdd426b341ae4ede2c2cf42

TdF_Clips_Greater_than_10km_greater_than_60s_Echelon_2.zip (342369 kB)
MD5: 6549653ef8f61646c95f25f6a59d51aa

TdF_Clips_Greater_than_10km_greater_than_60s_Echelon.zip (177165 kB)
MD5: 8fabcf80afad453e494bc6561fca1024

TdF_Clips_Greater_than_10km_greater_than_60s_Echelon.zip (177165 kB)
MD5: 8fabcf80afad453e494bc6561fca1024

TdF_Clips_Greater_than_10km_greater_than_60s_Flat.zip (243521 kB)
MD5: dadf4df9961663615f50b750996fcd76

TdF_Clips_Greater_than_10km_less_than_60s_Arrow.zip (224754 kB)
MD5: 0443bd6db7c756b86703c0e05698d5f8

TdF_Clips_Greater_than_10km_Less_than_60s_Flat.zip (425524 kB)
MD5: d9a3f9b8e9f05d301929985afddf0f7a

TdF_Clips_Less_than_10_Less_than_60_2_Arrow.zip (299491 kB)
MD5: 6ddb726f1eed9ba04b820fe41874b4c3

TdF_Clips_Less_than_10km_greater_than_60s_Arrow.zip (229301 kB)
MD5: 745f047bfbd2c7f108271bfd46e2d93a

TdF_Clips_Less_than_10km_greater_than_60s_Echelon.zip (112884 kB)
MD5: 2fd6c37723fe63e94d8eacbfee5fb695

TdF_Clips_Less_than_10km_greater_than_60s_Flat.zip (268187 kB)
MD5: 0ba548a0d045d436e861a3f16afd472f

TdF_Clips_Less_than_10km_greater_than_60s_Line.zip (175849 kB)
MD5: 097544d87ab2976325a68014b4e2fdd0

TdF_Clips_Less_than_10km_Less_than_60s_Echelon_2.zip (140526 kB)
MD5: faf9a3330c74145d6920b0bfb8d77af3

TdF_Clips_Less_than_10km_Less_than_60s_Echelon_3.zip (84379 kB)
MD5: 8ff353e747c8b80cf1d6226fac523c7e

TdF_Clips_Less_than_10km_Less_than_60s_Echelon.zip (227095 kB)
MD5: e8dc83cde424d3df145d5dfeaac5e697

TdF_Clips_Less_than_10km_Less_than_60s_Flat_1.zip (201883 kB)
MD5: d03965f16e24f3abcd48929d4f2b9e9f

TdF_Clips_Less_than_10km_Less_than_60s_Line_1.zip (191951 kB)
MD5: bf2bcddd8f77ba9bc2b8b34bb1461745

TdF_Clips_Stage_1_1_Double_razor_into_razor.zip (114488 kB)
MD5: a02f2bd95034b2af3433a0a2a6998225

TdF_Clips_Stage_1_3.zip (1095479 kB)
MD5: cb3e39269043709abb48d0f132271017

TdF_Clips_Stage_4_three.zip (183876 kB)
MD5: a5e181cce1334ffaf4a97aa9ca7628af

TdF_Clips_Stage_6_two.zip (659967 kB)
MD5: af85833c58dfefffbf50c9f6b1babb7a

TdF_Clips_Stage_16.zip (238800 kB)
MD5: d2de4de9d56626e358e99d70cdc0d979