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Modern vehicles are using control and safety driving algorithms fed by various evaluations such as wheel speeds or road environmental conditions. Wheel load evaluation could be useful for such algorithms, particularly for extreme vehicle loading or uneven loads. For now, smart tires are only equipped by tire pressure monitoring systems (TPMS) and temperature sensors. Manufacturers are still working on in-tire sensors, such as load sensors, to create the next generation of smart tires. The present work aims at demonstrating that a static tire instrumented with an internal optical fiber allows the wheel load estimation for every wheel angular position. Experiments have been carried out with a static tire loaded with a hydraulic press and instrumented with both an internal optical fiber and an embedded laser. Load estimation is performed both from tire deflection and contact patch length evaluations. For several applied loads from 2800 to 4800 N, optical fiber load estimation is realized with a relative error of 1% to 3%, almost as precisely as that with the embedded laser, but with the advantage of the load estimation regardless of the wheel angular position. In perspective, the developed methodology based on an in-tire optical fiber could be used for continuous wheel load estimation for moving vehicles, benefiting control and on-board safety systems.

Publication in the conference proceedings of EUSIPCO, Kos island, Greece, 2017

EGU - European Geosciences Union General Assembly 2016 , Vienna, AUTRICHE, 17-/04/2016 - 22/04/2016; Sense-City facility is a modeled urban test-bed of 250 m2 (25m×10m) located at University Paris-Est (France) that is dedicated to the validation of measurement technologies in the field of urban sustainability [1]. The novel Ground-Penetrating Radar (GPR) test site falls within the purview of Sense-City smart road topic, as networks usually lie below road structures. This site lies within the actual concern of mapping the underground with a non-destructive technique to retrieve the location of underground pipelines, in order to update urban cadastral databases, to contribute to space saving and to a wise use of land resources when planning for new networks. Thus, the test site designed provides several sources of measurement interest expressed by the presence of a multilayered soil with significant dielectric contrasts, and two distinct areas dedicated to the validation of utility mapping tools, one with buried pipes, and the other with buried blades with various dielectric properties; the objects having a relative small lateral dimension (less than 15 cm) have been buried at several depths (ranging from 14.5 to 64.5 cm ) in trenches filled with a backfill soil different from the natural soil. This paper is focused on the buried pipe area: experimental radargrams have been acquired using several GPR systems (GSSI SIR 3000, UtilityScan DF and a SFCW made of a pair of bowtie slot antennas conceived in our laboratory) operating at frequencies ranging from 300 MHz to 1.5 GHz. At first, the comparison and the interpretation of a few raw Bscans have allowed to characterize the dielectric properties of the soil layers. Afterwards, during the experiments made with the different GPR systems, we have studied the hyperbola signatures of the buried pipes according to several parameters such as central frequency, dielectric contrast of the objects (air filled or water filled), and polarization. The results of this study will help to further evaluate and develop different types of algorithms in signal and image processing (wavelet transform, Hilbert transform, matched filter, mode decomposition, super resolution algorithm, template matching, migration...) in radargrams to finally extract quantitative information. Experimental results highlight that 800 and 900 MHz are the most suited frequencies to obtain radargrams with enough resolution and penetration to characterize the buried objects with relatively small lateral dimension. First measurements have been made in the blade zone and they are currently under interpretation.

International audience; Le relevé automatique des dégradations de surface à partir d’images de la chaussée est devenu un enjeu important dans de nombreux pays. Parmi les différentes méthodes proposées dans la littérature, cet article propose d’utiliser un algorithme de recherche de chemin minimal pour détecter les fissures. La méthode proposée prend simultanément en compte les caractéristiques photométriques et géométriques des fissures et contrairement à [1] n'impose pas des contraintes sur la forme de la fissure. L’article présente le principe de l'algorithme, puis le résultat des premiers tests sur des images collectées par un système opérationnel. Dans son état d'avancement actuel, l'algorithme fournit le squelette des fissures dans les images, qui est ensuite comparé à la pseudo-vérité terrain associée aux images.

National audience; Abstract – Automatic detection of road cracks from pavement images has become an important challenge in many countries. Among the different methods proposed in the literature, this paper proposes to combine shortest-paths previously estimated in the image. The proposed method takes account of both photometric and geometric characteristics of cracks simultaneously and requires a few informations a priori. It has been tested on image data sets collected by a dynamic imaging system.

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