In-tire load estimation for autonomous vehicle safe driving strategies
Résumé
In order to ensure safe driving without human supervision the autonomous vehicles are using a wide range of sensors as cameras, lasers, lidar to evaluate the road scene and to measure the vehicle trajectory. The vehicle weight is of critical importance since it affects both braking dynamics and stability in curves. This total weight depends on the number of occupants and goods or luggage, so it has to be dynamically estimated, at least at each traveling start. The literature review indicates that some infrastructure-based sensors exist but tire related systems are preferable if the vehicles can start routes at indefinite points. In this work an experimental system is developed to estimated the load applied to a non rolling tire with several concurrent sensors. First the elongation of the tire to road contact patch is estimated by the means of an internal optical fiber sensor based on Rayleigh scattering interferometry, since this elongation is related to the applied load according to literature results. A laser sensor situated inside the tire is giving the tire sidewalls deflection which is related to applied load too. At last tire to road contact patch length and width are estimated by using Fuji pressure sensible paper. As a results for loads of 2.8 to 4.8 kN the optical sensor and the laser sensor are leading to
load estimation error lower than 3%. Moreover the estimated tire contact patch is confirming the tire belt elongation estimated by the optical fiber sensor. In perspective the two measurements from optical fiber and laser could be used by autonomous vehicles in order to have a redundant load estimation for one or several wheel, under vehicle symmetry hypothesis.
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