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

Abstract

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.