Experimental evaluation of a computer-vision based method to assess the aerodynamic drag of cyclists

Cedric Lemaitre, Matthieu Voiry, Cyrille André, Antoine Lavault


We have previously introduced in Science Cycling 2017 an inexpensive method to assess the aerodynamic drag of a cyclist [1]. Last year we presented in the same conference a first evaluation of the method [2] where the regression method [3] was used as ground truth. In this work, the few data available had been obtained on a open road, which could increase the source of noise (wind-direction) and imprecision. In this paper we propose a consistent comparison of our method with a larger dataset. This new ground truth is still obtained with the regression method but the data were grabbed on a 200m indoor track (Bourges, France). The dataset contains records for 4 cyclists for 3 positions (top bar position, brakes hood position, bottom bar positions) at 4 different speeds (25, 30, 35, 40 km/h). All variables needed to compute aerodynamic forces are directly measured by sensors (temperature and pressure : Bosch BME280; power : Rotor inPower Powermeter; speed : Garmin 010-12103-00 speed sensor).

[1] Voiry, M., Lemaitre, C., & Andre, C. (2017). Toward a robust and inexpensive method to assess the aerodynamic drag of cyclists. Journal of Science and Cycling, 6(3)

[2] Lemaître, C., Voiry, M., & André, C. (2018). First evaluation of an automated system for cyclist’s aerodynamic drag assessment. Journal of Science and Cycling, 7(2), 9.

[3]Grappe, F., Candau, R., Belli, A., & Rouillon, J. D. (1997). Aerodynamic drag in field cycling with special reference to the Obree's position. Ergonomics, 40(12), 1299-1311.


Aerodynamics, 3D scanning, CFD, Cycling

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DOI: https://doi.org/10.28985/jsc.v8i2.500


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