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Along with exhaust emissions and Fuel Consumptions (FCs), noise emission from cars is one of the main concerns of automotive industry. Hybridization is a promising method to not only make automobiles more environmentally-friendly, but also reduce their noise emissions. However, a proper control design for Hybrid Electric Vehicles (HEVs) to make noise emissions lower is still required in addition to exhaust emissions and FC reductions. In this study, we modify Equivalent Consumption Minimization Strategy (ECMS) to keep the engine noise less than tire/road noise during driving. A test bench is established for calculating the engine noise and brake specific FC. Moreover, tire/road noise is experimentally defined as a function of the vehicle speed. It is shown that by implementing the basic ECMS, the engine noise exceeds the tire/road noise in some moments of driving cycle, which is annoying to the passengers. Therefore, a modified ECMS is proposed to limit the candidate engine operating points such that the engine noise does not exceed the tire/road noise. It is shown that the engine noise level is kept below the tire/road noise level by using the modified ECMS at the expense of a very small increase (about 1%) in the vehicle's FC. [ABSTRACT FROM AUTHOR]

This paper evaluates the amount of noise reduction when using different pavement materials in two adjacent lanes, where the close-proximity (CPX) method is introduced to analyze the tire/road noise before and after pavement maintenance. We consider four types of pavement materials, including ECA-10, PUC-10, PAC-13, and double-layer porous asphalt pavement (PAC-13+PUC-10), where these materials and their combinations are paved on two adjacent lanes. We measure the tire/road noise with the CPX method using a two-wheel trailer that can install two types of tires in different tests. This study provides some guidelines on controlling traffic noise pollution by using the combination of low noise pavement materials. From the experimental and theoretical results, one can see that the highest amount of noise reduction can be obtained when both the inner and outer lanes use the double-layer porous asphalt pavement. To make a balance between the noise reduction performance and the road maintenance cost, one can have the suboptimal choice, where the inner lane uses PUC-10 and the outer lane uses the double-layer porous asphalt pavement. [ABSTRACT FROM AUTHOR]

As a common preventive maintenance technique for asphalt pavement, micro-surface (MS) has the advantages of waterproofing and crack sealing. However, issues such as the fact that the conventional MS generates large noise and the evaluation of the indexes of tire-road noise are relatively less studied. The traditional surface texture index cannot reveal the range and distribution of pavement surface texture, thus hindering research of low-noise MS. To study the mechanism of tire-road noise generated by MS, and propose the tire-road noise and surface texture indicators for MS. In this study, the mechanism of five low-noise MS was systematically analyzed and compared through surface texture and noise tests. Then, a three-dimensional digital texture model (3D-DTM) of MS surface texture was constructed using a series of digital image processing techniques, including grayscale identification, binary conversion, and noise reduction. The results show that optimizing the gradation, adding sound-absorbing materials, and improving the workability of construction can improve the noise reduction performance of MS, it is worth mentioning that the MS prepared with sound-absorbing materials and low-noise gradation has the greatest noise reduction effect, with a maximum reduction of 6.3 dB(A). In addition, it was also found that the 3D-DTM can well reflect the surface texture characteristics of MS. The probability of convex peak distribution (PCD) and the proportion of convex peak area (PCA) with peak heights greater than 0.25 mm (Kh ≥ 0.25), which are extracted from the 3D-DTM, can well reflect the surface texture, tire-road noise, respectively. The results show that the 3D-DTM is a promising tool to optimize the design of low-noise MS.

Current literature on the performance characteristics of road surfaces is primarily focused on evenness, roughness and technical durability. However, other important surface properties require analysis, including noisiness, which is an important feature of the environmental impact of vehicular traffic around roads. This can be studied using various methods by which road noise phenomena are investigated. The method used to measure the noise performance of road surfaces herein is the Statistical Pass-By (SPB) method, as described in ISO 11819-1:1997. The impedance tube method was used for sound absorption testing, as described in ISO 13472-2:2010. These tests were performed under a variety of conditions: in situ and in laboratory. The existence of relationships between them can be helpful in selecting surfaces for noise reduction. Preliminary surface noise tests can be performed in the laboratory with samples consisting of various compounds. This is less expensive and faster than doing so on purpose-built surfaces. The paper presents study results for sound absorption coefficients of various types of low-noise surfaces in in situ conditions (on an experimental section and on operated road sections) and in the laboratory setting. The results of the tests performed on the operational sections were compared to the results of the surface impact on road noise using the SPB method. The correlations between the test results help confirm the feasibility of road surface pre-testing in the laboratory and the relation to tests performed using the SPB method under typical operating conditions.

This paper evaluates the amount of noise reduction when using different pavement materials in two adjacent lanes, where the close-proximity (CPX) method is introduced to analyze the tire/road noise before and after pavement maintenance. We consider four types of pavement materials, including ECA-10, PUC-10, PAC-13, and double-layer porous asphalt pavement (PAC-13+PUC-10), where these materials and their combinations are paved on two adjacent lanes. We measure the tire/road noise with the CPX method using a two-wheel trailer that can install two types of tires in different tests. This study provides some guidelines on controlling traffic noise pollution by using the combination of low noise pavement materials. From the experimental and theoretical results, one can see that the highest amount of noise reduction can be obtained when both the inner and outer lanes use the double-layer porous asphalt pavement. To make a balance between the noise reduction performance and the road maintenance cost, one can have the suboptimal choice, where the inner lane uses PUC-10 and the outer lane uses the double-layer porous asphalt pavement.

• The bidirectional knowledge graph of the tire/road airborne sound quality is proposed. • A multitarget prediction method based on the adaptive balanced learning mechanism for ResNet is proposed. • A knowledge- and data-driven method is developed for the prediction and optimization of TRA sound quality. • The proposed method overperformed the conventional prediction and optimization methods in effectiveness and robustness. With the promotion of pure electric vehicles (PEVs), the overall interior noise level has been gradually reduced. Tire/road noise is increasingly becoming noticeable in PEVs and represents a primary concern for passengers. Vehicle acoustic packages are crucial for suppressing tire/road noise, and numerous studies have focused on improving the acoustic package performance and sound quality of tire/road noise. However, the prediction and optimization of tire/road acoustic comfort have two deficiencies: (1) The characteristics and transfer paths of tire/road noise are complex. Using knowledge-driven methods (such as simulation models) and data-driven methods (such as neural networks) for analysis has difficulty in accuracy parameter acquisition and unexplainable models. (2) The sound quality of tire/road noise is multidimensional. In the development of multitarget prediction models, when multiple targets contradict each other, prediction bias may result from wide differences among targets in the gradient value of the loss function in training. Therefore, in this paper, a knowledge- and data-driven method is proposed, which introduces the knowledge graph technique to develop a vehicle tire/road noise knowledge graph architecture and uses an improved residual network to drive reasoning in the domain knowledge graph. In addition, a multitarget prediction method based on the adaptive balanced learning mechanism for a residual network is proposed, which uses the dynamic weighted average method to adaptively adjust the loss weight of each target according to the convergence speed and learning difficulty of each target. The proposed dual-drive method is applied to predict and optimize the performance of vehicle acoustic package and to further improve the multiple sound quality metrics of tire/road noise. In the experimental validation, the proposed method outperforms the traditional prediction and optimization methods in effectiveness and robustness. [ABSTRACT FROM AUTHOR]

Tire/road noise in most driving conditions dominates other sources of traffic noise. One of the most efficient ways of reducing tire/road noise is to use the so-called “low noise pavement”. According to numerous studies, at present, poroelastic road pavement that is composed of rubber and mineral aggregate and polyurethane or bituminous binder gives the best noise reduction up to 12 dB. Unfortunately, there are many problems with making durable poroelastic pavements. This article presents the first results of a project that is executed in Poland and aims at the development of a durable, low noise poroelastic pavement based on polymer-modified asphalt binder called Safe, Eco-friendly POroelastic Road Surface (SEPOR). Two test sections were built in 2019 to test the production technology and performance of the SEPOR pavement. It is observed that some of the problems with previous poroelastic materials were mainly eliminated (especially delamination from the base layer and raveling) but noise reduction is a little less than expected (up to 9 dB). Rolling resistance for car tires is acceptable and fire properties (damping of spill fuel fires, toxic gas emission) are very good.

Traffic noise has large consequences on the appreciation of the living quality close to roads and leads to speech interference, sleep disturbances, and general annoyance. Furthermore, it impacts the economy as it increases the costs for noise abatement and decreases the value of properties, which are close to noisy road transport infrastructure. However, existing methods to measure tire/road noise lack in mobility, in the possibility of measuring comprehensively, and are expensive and sophisticated to use. We present a novel method and an exploitation model to predict different types of road surfaces based on tire cavity sound acquired under normal vehicle operation. With the information of the road surface, further parameters can be estimated, such as tire/road noise, tire/road friction or rolling resistance. Our method can be applied comprehensively and is inexpensive. In contrast to special measurement vehicles with laser profilometers, normal vehicles can be equipped with our measurement system and the data can be automatically analyzed with our method. Therefore, the road infrastructure can not only be monitored in fixed intervals of about one to four years but constantly. We tested our classifier with unseen data, which were not used for training. Our final classifier after post-processing has an average precision and recall of respectively 95.1 and 90.6% and a accuracy of 91.8%. The output of our model could be fused with other parameters such as weather data, to create a digital map to automatically identify noisy roads or dangerous spots with low tire road friction. This might be an important input for advanced driver assistance systems. Based on the detected road hazards, an optimal regulation of the vehicle speed could be achieved. For the civil engineering departments and road infrastructure operators, this tool could be used to perform a more efficient maintenance of the whole road infrastructure. [ABSTRACT FROM AUTHOR]

Performing numerous analyses of tire/road noise measurements on low-noise pavements during the last several years, the authors observed significant inhomogeneity of the wearing course in numerous cases, while similar problems were almost non-existent when dense pavements were measured. Three main causes of low-noise pavement inhomogeneity can be defined. The first one is imperfections in the technology used for asphalt mix production and/or errors made during the laying process of the wearing course. The second one is clogging that takes place during the pavement’s service life. The third reason is related to uneven and/or excessive wear of the pavement (raveling and stripping of the aggregate may appear in this case). Findings of analyses of noise data acquired from low-noise pavements (based on 10 m long segments), using the close-proximity (CPX) method, are presented and discussed herein. Significant differences in measured averaged noise levels, up to 1.7 dB, between test sections of open-graded wearing courses that were the same in principle, located on the same road but in different lanes were found when performing CPX measurements. At the same time the test sections of a dense pavement differed by max. 0.5 dB only. The calculated A-weighted sound pressure level variability index Scpx, considered to be an indication of pavement homogeneity, reached the value of 1.69 dB over a 500 m long test section of the porous pavement while the Scpx values for dense pavements were much below 0.5 dB. [ABSTRACT FROM AUTHOR]

Noise is one of the most important environmental problems related to road traffic. During the last decades, the noise emitted by the engines and powertrains of vehicles was greatly reduced and tires became a clearly dominant noise source. The article describes the concept of low noise poroelastic road surfaces that are composed of mineral and rubber aggregate bound by polyurethane resin. Those surfaces have a porous structure and are much more flexible than standard asphalt or cement concrete pavements due to high content of rubber aggregate and elastic binder. Measurements performed in several European countries indicate that such surfaces decrease tire/road noise between 7 dB and 12 dB with respect to reference surfaces such as dense asphalt concrete or stone matrix asphalt. Furthermore, poroelastic road surfaces ascertain the rolling resistance of car tires, which is comparable to classic pavements. One of the unforeseen properties of the poroelastic road surfaces is their ability to decrease the risks related to car fires with fuel spills. The article presents the road and laboratory results of noise, rolling resistance, and fire tests performed on a few types of poroelastic road surfaces. [ABSTRACT FROM AUTHOR]

Traffic noise is a particular threat to the environment in the vicinity of roads. The level of the noise is influenced by traffic density and traffic composition, as well as vehicle speed and the type of surface. The article presents the results of studies on tire/road noise from passing vehicles at a speed of 40-80 kph, carried out by using the statistical pass-by method (SPB), on seven surfaces with different characteristics. It has been shown that increasing the speed from40 kph to 50 kph contributes to the increase in the maximum A-weighted sound pressure level by about 3 dB, regardless of the type of surface. For larger differences in speed (30 kph-40 kph) increase in noise levels reaches values about 10 dB. In the case of higher speeds, this increase is slightly lower. In this article, special attention is paid to the noisiness from surfaces made of porous asphalt concrete (PAC), BBTM (thin asphalt layer), and stone mastic asphalt (SMA) with a maximum aggregate size of 8 mm and 5 mm. It has also been proved that surfaces of porous asphalt concrete, within two years after the commissioning, significantly contribute to a reduction of the maximum level of noise in the streets and roads with lower speed of passing cars. Reduction of the maximum A-weighted sound pressure level of a statistical car traveling at 60 kph reaches values of up to about 6 dB, as compared with the SMA11. Along with the exploitation of the road, air voids in the low-noise surface becomes clogged and acoustic properties of the road decrease to a level similar to standard asphalt. [ABSTRACT FROM AUTHOR]

The use of road surfaces with low noise emission characteristics is one of the actions mostly applied all over the world to decrease the number of road traffic noise annoyed people. Since many Italian roads are going to be paved with such surfaces, the LEOPOLDO project (funded by the Tuscany Region and the Italian Ministry of Transportation) was planned to check the efficacy in time of this action. Among all solutions, rubberized road surface is one of the most applied in USA, Canada, Europe and Asia. This paper describes results obtained by monitoring four rubberized surfaces one year after the laying and by evaluating the time stability of LEOPOLDO one by means of the Close Proximity method (CPX). All surfaces here analyzed are laid in real scenarios, so the actual efficacy of this action is evaluated. The results on the LEOPOLDO surface show spatial homogeneity, a good time stability and a significant noise emission reduction. Instead, analysis of the four rubberized surfaces shows variability in the results, probably due to the pavement installation quality, as supported by the data. Thus, the rubberized road surface looks to be a very efficient mitigation technology, providing the installation have been carried out with care and proficiency. [ABSTRACT FROM AUTHOR]

In almost all urban contexts and in many extra-urban conurbations, where road traffic is the main noise pollution source, the use of barriers is not allowed. In these cases, low-noise road surfaces are the most used mitigation action together with traffic flow reduction. Selecting the optimal surface is only the first problem that the public administration has to face. In the second place, it has to consider the issue of assessing the efficacy of the mitigation action. The purpose of the LEOPOLDO project was to improve the knowledge in the design and the characterization of low-noise road surfaces, producing guidelines helpful to the public administrations. Several experimental road surfaces were tested. Moreover, several measurement methods were implemented aiming to select those that are suitable for a correct assessment of the pavement performances laid as mitigation planning. In this paper, the experience gained in the LEOPOLDO project will be described, focusing on both the measurement methods adopted to assess the performance of a low-noise road surface and the criteria by which the experimental results have to be evaluated, presenting a comparison of the obtained results and their monitoring along time. [ABSTRACT FROM AUTHOR]

End-of-life tires are waste materials that pollute landscapes when they are disposed of in tire dumps. However, its life cycle is not finished when they are scrapped. The rubber of end-of-life tires could be used for new purposes as construction material in road rehabilitation. A gap-graded mix characterization was carried out in this work by means of laboratory and field performance tests. The mixture has a high content of crumb rubber (CR) by weight of bitumen. Crumb Rubber was added to the binder by a wet process. Close proximity methodology has been used in in-situ characterization of the acoustic behaviour. Moreover, absorption and dynamic stiffness tests were also conducted to determine the noise generation mechanisms involved in noise. According to the results achieved, a reduction of the noise emitted by the tire/pavement interaction could be accomplished with the construction of roads with mixture with CR added by a wet process. In addition, this would result in a decrease of the amount of waste tires in landfills. [ABSTRACT FROM AUTHOR]

Abstract: During the winter, traffic regulations state that automobile drivers must use winter tires on unsafe roads such as snowy expressways. The present report is concerned with the development of an automatic tire identification system that can discriminate winter tires from summer tires with high accuracy. The system detects the impact vibration signal that is specifically generated by winter tires when tread blocks with wide grooves strike the road surface during rolling. The signal is picked up by a commercially available vibration sensor. If the signal contains specified impact frequency components, the tire is judged to be a winter tire. Compared with the previous identification system, which used airborne tire/road noise, the proposed system has two advantages. First, it is unaffected by meteorological factors such as wind noise. Second, the proposed system performs well even when the target vehicle is traveling at low speed. We evaluate the performance of the system outdoors using a number of vehicles with various tires and demonstrate an overall improvement in identification accuracy for vehicles traveling at low or moderate speeds. [Copyright &y& Elsevier]

The basic theory on the structural transfer path analysis of noise is presented and the measurement method of excitation force is analyzed in detail. With the tire/road noise of a vehicle as example, a transfer path analysis model is built and a structural transfer path test is carried out. Meanwhile the resultant interior noises at target points are calculated with a result well agreeing with test data. By calculating coupled excitation force and sound/vibration transfer function, it is found that the top three transfer paths having greatest contributions on interior noise are those going through the connecting points of right / left rear axles and left shock absorber with vehicle body. With the modification of rear axle structure, the issue of tire/road noise of the vehicle is successfully resolved. [ABSTRACT FROM AUTHOR]

[Display omitted] • An improved interval analysis method (IIAM) for uncertain optimization is proposed. • A group paired comparison method (GPCM) is proposed. • The tire/road structure-borne (TRS) noise of PEVs is objectively and subjectively evaluated. • Contribution factors that influence the TRS noise of PEVs are analyzed. • The TRS noise of PEVs is optimized and compared through the IIAM and GA. Without the masking effect of engine noise, tire/road (TR) noise is increasingly becoming noticeable in pure electric vehicles (PEVs) and represents a primary concern for drivers and passengers. Currently, numerous works have studied PEV motor and powertrain noises, but few studies have investigated the tire/road structure-borne (TRS) noise of PEVs. Therefore, in this paper, the sound quality of TRS noise is studied through objective and subjective evaluations, and the group paired comparison method (GPCM) is proposed to evaluate a large noise sample set. The correlation between sound quality metrics and the subjective annoyance of TRS noise is analyzed, and the contribution of chassis dynamic parameters to the TRS noise of PEVs is quantified. In addition, because of the nonlinear transfer and complex characteristics of TRS noise, the expected design results will easily be affected by material, processing and manufacturing uncertainties, which are difficult to process with conventional optimization methods. Therefore, to overcome the uncertainty problem, an improved interval analysis method (IIAM) is proposed. This method is used to optimize the interior TR sound quality of PEVs while treating riding comfort as a constraint. The optimized result of the IIAM is compared with that of the advanced genetic algorithm (GA) optimization method. Through real vehicle verification, the proposed IIAM outperforms the GA method in terms of accuracy and robustness. [ABSTRACT FROM AUTHOR]

The mechanical impedance describes the ability of a structure to resist motion when subjected to a given force. It has received increasing attention as a parameter that could influence the tire/road noise in the medium frequency range (630-1600 Hz). In this study, the impedance hammer device is used for measuring the mechanical impedance on thin layer surface mixture samples in the lab. In the test, the excitation is induced by hitting the sample surface with the hammer. Values of the driving force and acceleration of the vibrating slab are recorded. The mechanical impedance can then be calculated from the ratio of the force to the velocity that is obtained by integration of the acceleration. The influence of the material properties were investigated by comparing the results on different samples. A further measurement of dynamic stiffness on the same material is also discussed and related to the hammer measurement. [ABSTRACT FROM AUTHOR]

Current literature on the performance characteristics of road surfaces is primarily focused on evenness, roughness and technical durability. However, other important surface properties require analysis, including noisiness, which is an important feature of the environmental impact of vehicular traffic around roads. This can be studied using various methods by which road noise phenomena are investigated. The method used to measure the noise performance of road surfaces herein is the Statistical Pass-By (SPB) method, as described in ISO 11819-1:1997. The impedance tube method was used for sound absorption testing, as described in ISO 13472-2:2010. These tests were performed under a variety of conditions: in situ and in laboratory. The existence of relationships between them can be helpful in selecting surfaces for noise reduction. Preliminary surface noise tests can be performed in the laboratory with samples consisting of various compounds. This is less expensive and faster than doing so on purpose-built surfaces. The paper presents study results for sound absorption coefficients of various types of low-noise surfaces in in situ conditions (on an experimental section and on operated road sections) and in the laboratory setting. The results of the tests performed on the operational sections were compared to the results of the surface impact on road noise using the SPB method. The correlations between the test results help confirm the feasibility of road surface pre-testing in the laboratory and the relation to tests performed using the SPB method under typical operating conditions. [ABSTRACT FROM AUTHOR]

Road surface friction is one of the most important parameters determining road safety and macrotexture is one of the important factors affecting it. There are two types of traditional and automated data gathering methods. One of the disadvantages of automated methods is the high cost of purchasing or manufacturing. The purpose of this study is evaluating the feasibility of a low-cost dynamic method based on tire/road noise to evaluate the macrotexture of cracked non-porous asphalt pavements. To this end, the tire/road noise gathering system has been developed inspired by the ISO 11819-2 standard. The developed system has been used for data collection alongside with the health monitoring system of the Amirkabir University of Technology. After data gathering, the relationship between macrotexture indices (laser-based) and tire/road noise features has been evaluated. Using artificial neural networks, models for relating different sound and macrotexture indices in each frequency band are presented with the best correlation result being R2 = 0.76 between MPD and power spectral density in the 500 to 1500 Hz frequency band. The results indicate that in cracked pavement surfaces, by focusing on the vibration mechanism, acceptable results can be achieved in macrotexture monitoring by using interaction noise. • Pavement macrotexture can be calculated via tire/road noise at adequate accuracy in cracked sections. • By using tire/road noise, MPD can be determined with higher accuracy than other indicators. • The tire/road noise between 0.5 and 1.5 kHz frequency band and the PSD method result in the best performance model. • The nature of the tire/road noise and the processing methods affect on evaluating the macrotexture. [ABSTRACT FROM AUTHOR]

• Modeling all predominant tire noise generation and amplification mechanisms. • A comprehensive parametric study to provide a guideline for quiet tire design. • Sensitivity analysis of tire noise to its parameters and operating conditions. • Illustrating interactions between factors to reveal unprecedented impacts. • Proposing a novel approach for optimization of tire parameters to reduce noise. Tire/road noise is a dominant source of passenger car noise, especially above 40 km/h. Given the complexity, variety, and contradiction between different mechanisms, it is a severe challenge to reduce this noise. This paper aims to pave the way to design low-noise tires and assist manufacturers based upon scientific insights. In this regard, unlike other research, all predominant mechanisms, including texture impact, tread impact, air pumping, pipe resonance, Helmholtz resonance, air cavity resonance, and horn effect, are modeled. After verification, a design of experiment method, small central composite design, is implemented for sensitivity analysis of different mechanisms. The analysis of variance results with a high adjusted determination of coefficients and low p-value are discussed to reveal noteworthy guidelines to lower noise generated by each mechanism. The outstanding feature of this parametric study is an illustration of vital interaction effects between factors that lead to different instructions for changing the parameters in each situation. Finally, a novel approach to lower tire noise is provided utilizing a multi-objective minimization method. Since the material properties only affect texture impact, they are optimized by reducing texture noise by the genetic algorithm method. On the other hand, other mechanisms are decreased together using a non-dominated sorting genetic algorithm to optimize tread pattern specifications. The outcomes of two smooth tires are verified. The 80% reduction in their normalized noise has resulted in about 2 dB(A) decrement in total noise. Moreover, the average normalized sound of a patterned tire has been 27% reduced by a 10% change in its factors. [ABSTRACT FROM AUTHOR]

Tire/road noise in most driving conditions dominates other sources of traffic noise. One of the most efficient ways of reducing tire/road noise is to use the so-called "low noise pavement". According to numerous studies, at present, poroelastic road pavement that is composed of rubber and mineral aggregate and polyurethane or bituminous binder gives the best noise reduction up to 12 dB. Unfortunately, there are many problems with making durable poroelastic pavements. This article presents the first results of a project that is executed in Poland and aims at the development of a durable, low noise poroelastic pavement based on polymer-modified asphalt binder called Safe, Eco-friendly POroelastic Road Surface (SEPOR). Two test sections were built in 2019 to test the production technology and performance of the SEPOR pavement. It is observed that some of the problems with previous poroelastic materials were mainly eliminated (especially delamination from the base layer and raveling) but noise reduction is a little less than expected (up to 9 dB). Rolling resistance for car tires is acceptable and fire properties (damping of spill fuel fires, toxic gas emission) are very good. [ABSTRACT FROM AUTHOR]

Data collection and the associated automated methods are one of the main building blocks of pavement management systems. One of the main problems associated with automated data collection methods is the high cost of the equipment involved. The aim of this research is to develop a cost-effective system for dense-graded asphalt pavement macrotexture monitoring. To this end, a system based on the tire/road noise, utilizing microphones and employing cepstral signal processing has been developed. The proposed method is compared with the current state of the art PCA based method and is shown that the precision error of the proposed method is about 7%, which outperforms the previous state of the art. To enhance the precision of the cepstral method for the vehicle speed variation amongst the collected dataset, the combination of the cepstral signal processing with Gaussian mixture models is proposed which results in the final precision error of 8%. • Narrow range macrotexture can be evaluated by targeting the vibration mechanism • Macrotexture evaluation using Cepstrum method provides a low precision error of 7% • Cepstral coefficients are appropriate features for macrotexture monitoring • Combination of GMM with cepstral coefficients has resulted in an improved model [ABSTRACT FROM AUTHOR]

Low-noise pavements are used as an effective method of traffic noise mitigation. Low-noise pavements reduce the noise that arises due to interactions between tires and road surfaces (tire/road) via the implementation of three main components: low pavement roughness, negative pavement texture, and a high pavement air-void content. The tire/road noise reduction capabilities of the wearing layer vary depending on the aggregate type, gradation, bitumen and air-void content, and density. Consequently, the demand for an accurate tire/road noise prediction model has arisen from the design of asphalt mixtures. This paper deals with how asphalt mixture components of the wearing layer influence tire/pavement noise reduction and presents a model for tire/road noise level prediction based on the asphalt mixture composition. The paper demonstrates that the noise reduction level of low-noise asphalt pavements is dependent on the composition of the asphalt mixture. Asphalt wearing layer mixture composition parameters were tested in the laboratory from cores taken from 18 road sections, where acoustic properties were measured using a close-proximity (CPX) method. The proposed linear model is based on the bitumen amount, the air-void content of the mixture and aggregate shape and involves materials that comply with the general requirements for high-quality asphalt mixtures. The model allows for the prediction of the tire/road noise level at the asphalt mixture design stage using asphalt mixture components and volumetric properties. The proposed model is the first stage in the building of a complex model with a much wider range of low-noise asphalts components, pavement profile depth and CPX-value relationships. [ABSTRACT FROM AUTHOR]