PROCEEDINGS of the
23rd International Congress on Acoustics
9 to 13 September 2019 in Aachen, Germany

Experimental Modelling of Tyre/Road Noise from Road Texture Spectra on Rubberized Road Surfaces

Alessandro DEL PIZZO1; Gonzalo DE LEÓN1; Luca TETI2; Francesco BIANCO2, Antonino MORO3,
Luca FREDIANELLI1, Gaetano LICITRA1
1

Università di Pisa, Dipartimento di Fisica, Italy
2
3

iPOOL srl, Italy

IPCF-CNR, Italy

ABSTRACTRoad traffic noise is one of the most common sources of acoustic pollution in urbanized environments and,
therefore, its mitigation is fundamental for urban planning. Since tyre/road interaction represents the main
contribution to overall road traffic noise, the use of low noise road surfaces represents a useful way for
reducing the acoustic impact of road traffic, acting on the main generation mechanism of noise. In thiswork, both acoustic performances and road texture of several low noise rubberized surfaces andconventional road surfaces were measured and compared. In particular, acoustic performances weremonitored using the CPX method, while road texture measurements were performed using a laser
triangulation sensor. Road profiles were processed with a tyre envelopment algorithm called indenter
method and the spectra of the resulting signal was compared with the CPX spectra on each road surface.
Findings show that surfaces with crumb rubber within the mixture behave differently compared toconventional surfaces at high frequency, while noise at frequencies lower than 1 kHz seems unaffected by
the presence of crumb rubber.
Keywords: Rubberized Surfaces, Road Texture, CPX Measurements

1.1 INTRODUCTION
Road traffic noise in urban areas represents the most common sourc of noisee, as reported in several
works, such as the 2002 European Environmental Noise Directive (END) and its revision (1) and,
therefore, the study of its generation mechanisms is of paramount importance for the proposal of
suitable mitigation actions.
Road traffic noise is caused by three different generation mechanisms: noise produced by thepower unit, aerodynamic noise induced by the car motion at high speed and, finally, tyre/roadinteraction. For light vehicles, engine noise is dominant at speeds lower than 35 km/h and profile
aerodynamics becomes relevant only at speeds higher than the typical motorway speed (i.e. 130 km/h), tyre/road noise is the dominant source from 35 to 130 km/h (2).
Tyre/road noise itself is due to both airborne and structure-borne contributions (4). The former
causes high frequency noise produced by the compression and subsequent expansion of the air
trapped within the tyre/road interface, while the latter is caused by tyre vibrations and is dominant at
frequencies below 1 kHz. In particular, the fundamental properties of road surfaces that play a rolein sound generation mechanisms are the surface macro and megatexture, defined by ISO 13473-2,
porosity and layer thickness (5).
In this paper, the relationship between road texture and tyre/road noise was analysed from anexperimental point of view, monitoring the acoustic performances of the surfaces using the CPX
method defined by ISO 11819-2:2017 and road texture on conventional and rubberized surfaces andevaluating the correlation coefficient and linear regression coefficients between one-third octave
bands of CPX noise and road texture. A test based on t-statistics, performed on the slopes found forconventional and rubberized pavements, was then used to distinguish regions where the surfaces
showed a different relation between tyre/road noise and road texture.

1 alessandro.delpizzo@df.unipi.it

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An algorithm based on the works of Goubert and Sandberg (6) was also used, in order to take
into account only the part of road texture actually into contact with the tyre.

2.1 STATE OF ART
Noise reduction at the source is a very cost effective treatment (7) and, therefore, many European
studies have focused their attention on low noise surfaces, such as porous asphalts, SMA, thin, verythin and ultra-thin surfacing and surfaces that include rubber in their mix. In particular, more andmore attention is paid to pavements which include crumb rubber deriving from end-of-life tyres. In
this way, noise reduction goes hand-in-hand with the concepts of green and circular economy.
The main kinds of surfaces which include rubber are poro elastic road surfaces (PERS) andrubberized surfaces. While the former uses rubber as a main component of the mix (7), rubberizedroad surfaces are built using hot asphalt mixes containing crumb rubber which acts as a modifier, inorder to improve the acoustical properties of the binder (8). Rubberized surfaces are subdivided in
two categories, according to their production means: wet road surfaces are created by blending
crumb rubber with liquid asphalt cement (AC) before mixing AC with the aggregate, while in thedry process, crumb rubber is added to the hot aggregate (8).
The acoustical properties of these surfaces have been monitored by several studies (9, 10), withspecific projects launched to evaluate their effectiveness (10), showing that rubberized surfaces
produce lower noise emissions compared to DAC of the same age.
Since, as already stated, the main source of road traffic noise is represented by tyre/road noise,
the study of road and tyre properties is fundamental.
Among several road surface properties, road texture covers an important role in noise generation(2, 3, 11). It is defined as the deviation of a pavement surface from a true planar surface, caused by
the random disposition of the surface elements and their superficial roughness (12). The study ofroad texture is usually performed using spectral analysis in constant-percentage bandwidth, bymeans of octave or one-third octave bands. It is also customary to report texture spectra using
texture levels, as defined by ISO 13473-4.
Based on the different wavelengths of the road profile signal, road texture is divided in three
regions: microtexture includes wavelengths shorter than 0.5 mm, wavelengths that range from 0.5
mm to 50 mm are addressed as macrotexture while longer wavelengths, up to 500 mm, are called
megatexture. Longer wavelenghts are addressed as unnevenness.
While microtexture is caused by roughness of the visible surface elements and, therefore, it
depends on the nature of the stones and chippings used, macrotexture is due to the shape, dimension
and positioning of the aggregates. Bumps and ripples present on road surfaces cause the presence ofmegatexture.
Previous studies (12, 13) underline the positive influence of high texture levels at wavelengths
shorter than 10 mm on the mitigation of tyre/road noise, since it reduces air compression due to thetyre tread, while texture levels around 63 mm play a key role in the generation of structure-borne
noise, since it induces tyre vibrations. Positive texture, produced by a surface characterised by highpeaks, results more aggressive than a surface crossed by deep valleys and grooves from an acoustic
point of view, since the peaks induce vibrations of the tyre walls (13). However, an abrupt spectral
analysis of the profile signal cannot distinguish between positive and negative texture and,
therefore, tyre envelopment algorithms have been developed, in order to calculate the road texture
actually into contact with the tyre. In this work, the indenter algorithm developed by Goubert andSandberg (6) was used. This study showed that the tyre envelopment follows the road profile until acertain depth dependent on the kind of tyre and the speed of the vehicle.

3.1 Methods and Sites Analysed
Noise and road texture measurements were carried out during Novemeber 2017 on 17 sites on the
highway that connects Merano to Bolzano, in the region of Trentino-Alto Adige/ Südtirol in Northern
Italy. Since the maximum distance between sites is about 20 km and the difference in height at thestarting and ending point of the highway is about 100 m, it is safe to assume that the sites are
exposed to the same weather and traffic condition, minimising acoustic ageing influence on
measurements (14).
Among the road surfaces, 7 were conventional dense surfaces, while the other 10 were rubberized3728

surfaces, equally subdivided in dry and wet, according to their means of production.
The mean grading curves of the dry, wet and reference surfaces are reported in Figure 1.

Figure 1 – Mean grading curves for the three kinds of road surfaces used
CPX and road texture measurements were compared, performing a linear regression between
each couple of CPX and texture one-third octave bands, separately for rubberized and conventionalroad surfaces. After evaluating goodness-of-fit, a parallelism test based on the t-statistics was used.
The results of of this test allow to discern regions where the slope that relates road texture to CPX
noise does not change between the two kinds of surfaces from regions where statistically significant
differences were found.
The flowchart and experimental plan of the work is presented in Figure 2.

Figure 2 – Flowchart and experimental plan of the paper.

3.1 The CPX method
The CPX method (15) aims to evaluate tyre/road noise close to the source. The protocol adopted
is based on a modified procedure (16) with changes regarding post-processing.
In order to comply with the last version of ISO 11819-2 (15), the Standard Reference Test Tyre
(SRTT) was used and normalisations for temperature and tyre hardness were performed at 22 °C and
66 Shore A. Moreover, due to the logarithmic dependence between vehicle speed and tyre/road3729

noise, a reference speed is required: the nature of the roads under investigation led to the choice of areference speed equal to 100 km/h.
The correction for temperature and hardness has been applied to the one-third band levels,
despite it is strictly valid for broadband levels, due to the current lack of studies on this topic.
During the measurement sessions, several acquisitions on the same surface were performed at
different speeds. In the post-processing phase, the site is subdivided in segments and a minimum χ 2
iterative algorithm was used in each segment for fitting sound levels with speed, in order to computethe one-third octave bands spectrum at the reference speed. Finally, the mean value of the soundpressure level within each band is used to characterise the whole site.
The main modification to the official protocol regards data analysis, since the test sites weredivided in segments 6.18 m long, i.e. three times a tyre circumference, instead of using the standard
section length of 20 m, in order to increase the spatial resolution of the analysis.
For each surface, the mean CPX spectrum and related uncertainty were then calculated.
3.2 Road texture measurements
All texture measurements were carried out simultaneously with CPX measurements. The
experimental setup is based on a triangulation sensor, a piezoelectric accelerometer and a rotary
encoder (12, 17), whose outputs are combined in order to yield the road profile, with a horizontal
sampling length equal to 0.5 mm.
The road profile was then processed using the indenter algorithm developed by Goubert andSandberg, in order to simulate tyre deformation caused by the profile itself. The algorithm is basedon experimental measures of SRTT deformation on known profiles and therefore represents the ideal
solution for this study, since it is based on the same tyre adopted for the measurements.
The profile obtained after the tyre envelopment was then divided in segments and fitted with anautoregressive model based on the Yule-Walker method, in order to reduce signal noise. Then, theone-third octave spectra were derived following the prescriptions of the fourth method reported in
ISO/TS 13473-4:2008.
3.3 Measurement uncertainties
The three sources of uncertainty related to mean CPX values are due to the fitting process in eachsegment, data dispersion around the mean value and:several factors and processes, whose cause and nature of disturbance are either known, but
randomly distributed in an uncontrollable way, or are of a systematic nature, but affect theresult in an unpredictable way (15).
The first source is assumed to be equal to the uncertainty of the measurement process within eachsegment, while the second source is taken into account by evaluating the standard deviation of data
and describes the spatial homogeneity of the installation. The last factor, instead, was neglected inthis analysis since the conditions of measurements do not vary greatly within the different sessions.
An estimate of measurement uncertainties for texture spectra within a segment is derived using
the same procedure adopted in (17), with the quadratic sum of two components. The first component
takes into account data dispersion around the mean value and is equal to the standard deviation ofeach band for each site, while the second contribution is inversely proportional to the root of the
bandwidth of each band times the length of each section and is assumed to be the uncertainty of the
texture measurement process.

4.1 ANALYSIS AND RESULTS
4.1 Correlation and linear regression
In order to perform a qualitative evaluation, the correlation coefficient between each couple ofenveloped road texture and CPX noise bands was calculated.
The correlation curves, shown in Figure 3 (left) and (right) separately for rubberized andconventional road surfaces, are in accordance with previous studies, which highlight a positively
correlated low frequency noise and a high frequency zone negatively correlated.

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However, road surfaces with crumb rubber added in their mix are present a larger region in which
negative correlation occurs. Conversely, the positively correlated zone occupies a smaller frequency
region for rubberized surfaces, compared to the conventional ones.
This difference could represent a first acoustical benefit of using rubberized surfaces, since theregion that contributes positively to noise emission is significantly reduced.

Figure 3 – correlation coefficient for the conventional reference surfaces (left). Correlation coefficient for
rubberized surfaces (right).
Linear regressions were performed for each couple of bands of enveloped road texture and CPX
noise and the parallelism test based on t-statistics took into account only regressions that showed a
r 2 adj value greater than 0.7, chosen as a threshold to identify high goodness-of-fit.
The values of the r 2adj calculated for each regression are reported in Figure 4 and 5. As expected,
high r 2 adj values were found where strong correlation is present.

Figure 4 – r2adj for the conventional reference surfaces. Values of r2adj higher than 0.7 are highlighted in red.

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Figure 5 – r2adj for the rubberized surfaces. Values of r2adj higher than 0.7 are highlighted in red.

4.2 Parallelism test
The parallelism test performed was based on a t-test on the regression coefficients, using thefollowing equation:t score =b1 −b 2
S E (b − b )
1

(1)

2

where b1 is the slope of the regression for the rubberized surfaces and b2 is the slope of theregression for the reference surfaces and S E( b1− b2) is the standard error of the difference of the twoangular coefficients. The values provided by Equation (1) were then used to test the hypothesis:

H 0 :b1=b2
H 1 :b 1 ≠ b2

(2)

comparing each t score with the critical value tcrit (0.975) = 2.16 for (n1 -2+n2 -2) = 13 degrees of
freedom, where n 1=10 is the number of rubberized surfaces and n 2 = 7 is the reference surface
sample size.
Results identify two different regions, at 500 Hz and at 2.5 kHz, with opposite behaviour: at 500
Hz the slope coefficients of the two samples show no difference, while at 2.5 kHz statisticallysignificant differences arise. A reduced matrix of the t-scores obtained is reported in Figure 6.
It is useful to remind that rolling noise at frequencies lower than 1 kHz is related to tyre vibration
mechanisms, while noise at higher frequencies is due to airborne processes, not directly related totyre perturbations. Bearing this in mind, it appears therefore that crumb rubber in the pavement mix
does not influence tyre vibrations due to the impact of the tyre tread against the road asperities,
while airborne noise, caused by the compression of air trapped between the tyre/road interface, issignificantly influence by its presence.
In particular, the negative slope at 2.5 kHz results significantly increased on rubberized surfaces,
as it can be inferred by observing Figure 7 (left) and (right).
Interestingly, no differences were found between the wet and dry processes.

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Figure 6 – tscore matrix resulting from the parallelism test. Blue cells highlight differences, while red
identifies cells where no statistical difference was found.

Figure 7 – Low frequency (500 Hz) as a function of enveloped texture levels (left). High frequency (2.5kHz) as a function of enveloped texture levels at 10 mm (right).

5.1 CONCLUSIONS
Rubberized asphalts represent one of the most common mitigation actions for roads with highand continuous traffic flow, managing to blend the modern concept of green and circular economy
with the necessity of improving the acoustical properties of road surfaces.
This work studied the variation of the interaction between road texture and tyre/road noise due tothe presence of crumb rubber from end-of-life tyres in the road pavement mix. A novel tyreenvelopment algorithm was also used, in order to take into account only the part of road texture incontact with the tyre.
The study was carried out by analysing the correlation between road texture and CPX noiselevels in one-third octave bands and by performing linear regressions between each couple of CPX
and road texture bands.
Results indicate that rubberized pavements show a greater frequency region negatively correlatedwith road texture compared to conventional surfaces.
A statistical test based on t-statistics was used to infer eventual differences between the linear
regressions that showed a r 2adj higher than 0.7 for both kinds of surfaces, with the identification of3733

two different regions, centred at 500 Hz and at 2.5 kHz. The 500 Hz band does not show statisticaldifferences between conventional and rubberized surfaces, while the 2.5 kHz band shows a higher
negative slope, highlighting a greater noise reduction potential of rubberized pavements compared tothe conventional road surfaces.
This work, therefore, sheds new light on the effects of the use of crumb rubber in the road mix
from an acoustic point of view. Further developments could include a physical model in oder todescribe the role of crumb rubber in road traffic noise generation. An increase of the sample size
would represent a significant improvement to the study, in order to confirm the relations found.

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