On-board wet road surface identification using tyre/road noise and Support Vector Machines

Alonso, J.; López, J. Mendieta; Pavón, Ignacio; Recuero, M.; Asensio, C.; Arcas, Guillermo de; Bravo, A.

doi:10.1016/j.apacoust.2013.09.011

Cited by 106 publications

(70 citation statements)

References 11 publications

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“…Alonso et al [49] also detected wet road surface conditions by analysing tyre-road noise in real-time. Field trials were conducted with an instrumented passenger vehicle, on the chassis of which an electret microphone was installed, at the rear right wheel.…”

Section: High Frequency Vibrationsmentioning

confidence: 99%

“…Besides the methods that focus on the low-frequency range, there are a number of contributions that estimate the tyre-road friction coefficient based on high-frequency vibration information [46,47,49,66,131,132]. The assumption behind these methods is that the macro and micro texture of the road surface is influencing heavily the maximum tyre-road friction coefficient.…”

Section: High Frequency Vibrationsmentioning

confidence: 99%

“…The limitations exhibited by slip-based approaches (mainly the necessity of generating large slip values) have encouraged researchers to explore low frequency [46][47][48][49] and high frequency [4,5,50,51] vibration-based approaches. The main objective of these solutions is to achieve an accurate grip potential identification during regular driving conditions.…”

Section: Introductionmentioning

confidence: 99%

“…Then, a suitable feature vector is designed and a classifier is trained to estimate the grip potential when new samples are available. Classifiers to distinguish roads of different roughness [46] as well as wetness [49] are present in the literature.…”

Section: Introductionmentioning

confidence: 99%

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Road Friction Virtual Sensing: A Review of Estimation Techniques with Emphasis on Low Excitation Approaches

2017

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Abstract:In this paper, a review on road friction virtual sensing approaches is provided. In particular, this work attempts to address whether the road grip potential can be estimated accurately under regular driving conditions in which the vehicle responses remain within low longitudinal and lateral excitation levels. This review covers in detail the most relevant effect-based estimation methods; these are methods in which the road friction characteristics are inferred from the tyre responses: tyre slip, tyre vibration, and tyre noise. Slip-based approaches (longitudinal dynamics, lateral dynamics, and tyre self-alignment moment) are covered in the first part of the review, while low frequency and high frequency vibration-based works are presented in the following sections. Finally, a brief summary containing the main advantages and drawbacks derived from each estimation method and the future envisaged research lines are presented in the last sections of the paper.

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Section: High Frequency Vibrationsmentioning

confidence: 99%

Section: High Frequency Vibrationsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Road Friction Virtual Sensing: A Review of Estimation Techniques with Emphasis on Low Excitation Approaches

2017

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“…based on the tire noise. In some of the studies, the acoustic sensors were attached to the vehicle's chassis [31]. Figure 4 demonstrates the algorithm, which uses support vector machine (SVM) to classify different surfaces based on tire noise.…”

Section: Acoustic Sensormentioning

confidence: 99%

A technical survey on tire-road friction estimation

2017

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Lack of driver's knowledge about the abrupt changes in pavement's friction and poor performance of the vehicle's stability, traction, and ABS controllers on the low friction surfaces are the most important factors affecting car crashes. Due to its direct relation to vehicle stability, accurate estimation of tire-road friction is of interest to all vehicle and tire companies. Many studies have been conducted in this field and researchers have used different tools and have proposed different algorithms. This literature survey introduces different approaches, which have been widely used to estimate the friction or other related parameters, and covers the recent literature that contains these methodologies. The emphasize of this review paper is on the algorithms and studies, which are more popular and have been repeated several times. The focus has been divided into two main groups: experiment-based and model-based approaches. Each of these main groups has several sub-categories, which are explained in the next few sections. Several summary tables are provided in which the overall feature of each approach is reviewed that gives the reader the general picture of different algorithms, which are widely used in friction estimation studies.

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Comparison of Dimensionality Reduction Methods for Road Surface Identification System

Safont

Salazar

Rodríguez-Martínez

et al. 2020

Advances in Intelligent Systems and Computing

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On-board wet road surface identification using tyre/road noise and Support Vector Machines

Cited by 106 publications

References 11 publications

Road Friction Virtual Sensing: A Review of Estimation Techniques with Emphasis on Low Excitation Approaches

Road Friction Virtual Sensing: A Review of Estimation Techniques with Emphasis on Low Excitation Approaches

A technical survey on tire-road friction estimation

Comparison of Dimensionality Reduction Methods for Road Surface Identification System

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