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Low-Cost Road-Surface Classification System Based on Self-Organizing Maps


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Título :
Low-Cost Road-Surface Classification System Based on Self-Organizing Maps
Autor :
Sánchez Andrades, Ignacio  
CASTILLO AGUILAR, JUAN JESUS  
Velasco Garcia, Juan Maria  
Cabrera Carrillo, Juan Antonio  
Sánchez-Lozano, Miguel  
Editor :
MDPI
Departamento:
Departamentos de la UMH::Ingeniería Mecánica y Energía
Fecha de publicación:
2020-10-23
URI :
https://hdl.handle.net/11000/33434
Resumen :
Expanding the performance and autonomous-decision capability of driver-assistance systems is critical in today’s automotive engineering industry to help drivers and reduce accident incidence. It is essential to provide vehicles with the necessary perception systems, but without creating a prohibitively expensive product. In this area, the continuous and precise estimation of a road surface on which a vehicle moves is vital for many systems. This paper proposes a low-cost approach to solve this issue. The developed algorithm resorts to analysis of vibrations generated by the tyre-rolling movement to classify road surfaces, which allows for optimizing vehicular-safety-system performance. The signal is analyzed by means of machine-learning techniques, and the classification and estimation of the surface are carried out with the use of a self-organizing-map (SOM) algorithm. Real recordings of the vibration produced by tyre rolling on six different types of surface were used to generate the model. The efficiency of the proposed model (88.54%) and its speed of execution were compared with those of other classifiers in order to evaluate its performance.
Palabras clave/Materias:
data acquisition
vibrations
surface estimation
machine learning
automobile systems
Área de conocimiento :
CDU: Ciencias aplicadas: Ingeniería. Tecnología
Tipo documento :
application/pdf
Derechos de acceso:
info:eu-repo/semantics/openAccess
Attribution-NonCommercial-NoDerivatives 4.0 Internacional
DOI :
https://doi.org/10.3390/s20216009
Aparece en las colecciones:
Artículos Ingeniería Mecánica y Energía



Creative Commons La licencia se describe como: Atribución-NonComercial-NoDerivada 4.0 Internacional.