Experimental evaluation of a computer-vision based method to assess the aerodynamic drag of cyclists
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).
© Copyright 2019 Journal of Science and Cycling. Cycling Research Center. All rights reserved.
| Subjects: | |
|---|---|
| Notations: | endurance sports technical and natural sciences |
| Tagging: | Computational Fluid Dynamics |
| Published in: | Journal of Science and Cycling |
| Language: | English |
| Published: |
2019
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| Online Access: | http://www.jsc-journal.com/ojs/index.php?journal=JSC&page=article&op=view&path%5B%5D=500 |
| Volume: | 8 |
| Issue: | 2 |
| Pages: | 61-63 |
| Document types: | article |
| Level: | advanced |