On-board Sound Intensity Research Articles

Experimental Analysis of Noise Characteristics on Different Types of Pavements inside and outside Highway Tunnels

Aiming to reduce noise pollution and optimize the acoustic quality in highway tunnels, the noise characteristics on different types of pavements were analyzed and compared in this research, based on the on-site noise measurement in two tunnels with the free fields as a control group. Specifically, the noise characteristics include two aspects: various noise and noise time attenuation performance. Various noise includes on-board sound intensity (OBSI) noise and cabin noise. The noise time attenuation performance uses the indicator of reverberation time. Three types of pavements were measured, including dense-graded asphalt concrete (DAC) and single-layered and double-layered porous asphalt (PA) pavement. The results showed that, for the same type of pavement, compared with the free fields, the difference in OBSI noise in tunnels was within a range of less than 1 dBA; the cabin noise increased by 3.4 dBA~6.6 dBA. The noise level in tunnels was greater than that outside tunnels, and the longer tunnel exhibited higher traffic noise and worse noise time attenuation performances. For the same tunnel, PA pavement could reduce the cabin noise by 3.8 dBA~6.7 dBA. PA pavement also exhibited shorter reverberation time. The application of PA pavement could effectively improve the acoustic quality in the tunnel. This research contributes to noise pollution abatement and the improvement of the comfort and safety of drivers in tunnels.

Road-pavement classification by artificial neural network model based on tire-pavement noise and road-surface image

This study focuses on an artificial neural network (ANN) model for classifying pavement types using acoustic and image data. While conventional studies often use road-surface images for pavement classification, they face challenges with image quality degradation owing to external factors, such as sunlight angle, shadows, and lighting. Therefore, in this study, tire-pavement noise, which has different noise characteristics depending on the material and surface treatment, is used independently and in conjunction with image data for ANN training. To construct the training dataset, tire-pavement noise, and road-surface images are collected from 11 highway sampling sites in South Korea. Two simultaneous measurements are used: the tire-pavement noise is collected using the On-board sound intensity (OBSI) method, and the camera captures the road-surface images. 1/3 octave SIL, spectrum, MFCC, GLCM, and HOG are extracted from the raw data, and the ANN models are trained by these features. Using the spectrum as an input feature for the ANN yields a classification accuracy of 95.18%. However, the total number of parameters in the ANN is double that of the other models. To reduce the ANN size, 1/3 octave band SIL is used for training, and the model size is halved. However, the accuracy decreases by 13.47 percentage points. To overcome this significant decrease, the 1/3 octave bands SIL and image features were used to train ANN, simultaneously. This approach increases the accuracy by 93.85%. By training the ANN using MFCC, which is commonly used as an acoustic feature in other machine learning studies, the highest classification accuracy of 96.84% is achieved. Additionally, MFCC models are affected by the number of coefficients and the signal length. To include the dominant frequency of tire-pavement noise, more than 13 coefficients are used, a number generally known to be suitable for speech recognition. Increasing the number of coefficients from 13 to 40 improves accuracy by 1.17 percentage points. The interval for slicing raw WAV files is reduced to increase the training data and classify the pavement using shorter signals without statistically significant accuracy loss. Although accuracy does not decrease until the signal lengths reach 0.5 seconds, it rapidly decreases when the signal lengths become shorter than 0.4 seconds.

Development of a recommended practice for evaluating rumble strip noise and vibration performance

As part of the NCHRP 15-68 project "Effective Low-Noise Rumble Strips" project, a recommended measurement program was developed for evaluating the noise and vibration performance of rumble strip designs. Two rumble strip designs located in Northern California, which included cylindrical indentations ground into the pavement at regular intervals and a continuous sinusoidal profile, were used to assess the input to a vehicle operator and the resultant exterior noise when the vehicle departed from the travel lane. Measurements were conducted on and off shoulder rumble strips at 60 and 45 mph with eight light vehicles ranging from small compact passenger cars to large sport utility vehicles. Six triaxial vibration measurements and six microphone locations were evaluated on the interior of the vehicle, and from these measurements, one primary and one (optional) secondary location for noise and vibration were selected for the recommended procedure. Vehicle pass-by measurements were also made following the procedures of AASHTO TP 98 Statistical Isolated Pass-By Method. While not required, on-board sound intensity (OBSI) testing is recommended to establish the off-strips pavement level. The recommended procedure is intended to be used by transportation agencies and other practitioners to assure comparable results when evaluating existing and alternative rumble strip designs.

Investigation of Medium-Term Performance of Porous Asphalt and Its Impacts on Tire/Pavement Noise

To assess the medium-term performance of porous asphalt pavement during service and its influence on tire/pavement noise level, a seven-year continuous observation and data analysis study was conducted. Key performance indicators were measured and calculated by using automated pavement technology testing equipment. The noise levels were tested by using the on-board sound intensity (OBSI) method on three types of porous asphalt pavements (PUC-10, PAC-13, and PUC-10 + PAC-13) and one dense thin layer course (DTC) for comparison. The findings indicated that the Damage Rate (DR) and Surface Friction Coefficient (SFC) of porous asphalt pavements diminished greatly over time, while the International Roughness Index (IRI) and Rut Depth (RD) remained relatively stable. The two-layer porous asphalt pavement showed the largest noise reduction over the medium-term. Compared to DTC, the OBSI noise levels of these structures were lower by 2.09 dB, 1.53 dB, and 2.88 dB, respectively. The OBSI was found to be closely correlated with the SFC, IRI, test speed, lane, and pavement type. The RD had a notable effect on the OBSI in PUC-10 pavements. In PUC-10 + PAC-13 pavements, a significant linear relationship was observed between the OBSI and SFC. This is mainly because of the polishing of the coarse aggregates, which leads to micro-texture reduction, high frequency noise increase, and SFC decrease. This study makes a valuable contribution to understanding the laws of porous asphalt pavement performance changes and the relationship between tire/pavement noise and pavement characteristics.

Noise Performance of Chip Seal Pavements

Increasing numbers of local and state highway agencies are using chip seals for highway pavement maintenance owing to their relatively low cost and simplicity of application. These surfaces can significantly increase both exterior traffic noise levels and interior noise for vehicle occupants. Recent studies included as part of the NCHRP 15-68 Effect Low Noise Rumble Strips Project have quantified these effects using pass-by and interior noise and on-board sound intensity (OBSI) measurements in several states. To minimize the tire–pavement noise generated by chip seals, the California Department of Transportation (Caltrans) has conducted research on different chip seal pavement designs near the City of Bishop, California. Previous measurements of chip seal pavement have indicated an average OBSI level of 106.2 dBA with a range of ±2 dB. The five quietest test sections at Bishop produced an average level of 101.8 dB with a range of ±0.6 dB. In this paper, previous pass-by and interior noise and OBSI measurements are provided along with the comparison of OBSI data to that measured at the Bishop sites. The performance and design information on the Bishop sites are also provided.

An application of Next Generation Concrete Surface texture to an existing concrete pavement

Between 2011 and 2013, the California Department of Transportation (Caltrans) installed New Generation Concrete Surface (NGCS) along a stretch of State Route 113 (SR 113). In the fall of 2013, this pavement was evaluated using the on-board sound intensity (OBSI) testing method. NGCS is a flush ground and grooved surface developed at Purdue University's Herrick Laboratory in 2004. This innovative, low noise grinding texture has minimal positive texture with good microtexture, which was intended to reduce noise levels at low frequencies, and has great macrotexture, which was intended to reduce noise levels at high frequencies. To evaluate the acoustic longevity of the pavement, OBSI testing was again completed in early 2023, and the long-term results are discussed in this paper. Additionally, the acoustic longevity of the NGCS pavement is compared to the long-term OBSI results collected between 2003 and 2010 on a ground concrete surface installed along Mojave SR 58. In 2022, NGCS was applied on a section of the U.S. 101 Freeway in Carpinteria in Southern California. The results of these measurements and the noise reductions achieved are also presented.

Noise and Pavement Rehabilitation Using Chip Seal Surfaces

In the United States, increasing number of local and state highway agencies are using chip seals for highway pavement rehabilitation due to their relatively low cost and simplicity of application. These surfaces can significantly increase both exterior traffic noise levels and interior noise for vehicle occupants. Recent studies have quantified these effects using pass-by and interior noise and on-board sound intensity (OBSI) measurements. In order to minimize these effects, the California Department of Transportation (Caltrans) has conducted research on different chip seal pavement designs near the City of Bishop, California. Previous measurements of chip seal pavement have indicated an average OBSI level of 106.2 dBA with a range of ±2 dB. The five quietest test sections at Bishop produced an average level of 101.8 dB with a range of ±0.6 dB. In this presentation, the previous pass-by and interior noise and OBSI measurements are provided along with the comparison of OBSI data to that measured at the Bishop sites. The performance and design information on the Bishop sites are also provided.

Study the Effect of Parameters on Tire-Pavement Interaction Noise (TPIN)

The present study was prepared to determine the effect of different parameters on tire-pavement Interaction noise (TPIN). TPIN was calculated utilizing the Onboard Sound Intensity Method (OBSI) using apparatus Lutron 801 sound level meter single probe 1 kHz of one microphone is placed at the right back test tire with a specific distance. A total of 30 sections were selected for the main roads in Baghdad city, with 134 meters for each test section in length. TPIN data was calculated for various parameters such as different pavement types, various test vehicles, different speeds (40, 56, and 72) km/h, various types of tires, different pavement aging, and different mean texture depth (MTD) values Which is measured by a sand patch test. The sound intensity dBA increases when MTD value and vehicle speed increase in both types of pavements. On the other hand, the sound intensity dBA increases when age increases for asphalt pavement type while it decreases in asphalt concrete pavement type. In addition, the sound intensity dBA in the asphalt pavement type is lower than in the asphalt concrete pavement when compared to the condition of the new pavement. The opposite is in the case of old pavement surfaces. As well as, the sound intensity dBA in Bus is greater than in the passenger car, and the silver stone tire is lower than the Dunlop tire in the passenger car. Finally, it is concluded that TPIN may be reduced or increased due to the effect of different parameters.

Influence of temperature on tire-pavement noise in hot climates: Qatar case

The ambient air temperature greatly influences tire-pavement noise measurements. Therefore, various international standards recommended a temperature correction factor to compensate for noise measurements at varying temperatures. This temperature correction factor is developed based on the local environment (temperature varying from 5 °C to 35 °C) and generally varies with different pavements. Pavements in the Gulf region experienced harsh weather conditions, with temperatures often crossing 40 °C during summer. This study investigates the effect of air temperature on noise measurements in hot climatic conditions of Gulf regions. The On-Board Sound Intensity (OBSI) noise measurements technique was used to collect the noise data at different temperatures ranging from 25 °C to 43 °C. A linear regression analysis was performed to verify the relationship between noise and temperature. Three statistical criteria were selected to avoid parasitic phenomena and contamination of noise data during measurement. Statistical analysis demonstrated a strong relationship between noise intensity and temperature, especially at a frequency above 1250 Hz. Spectra analysis of the noise measurements also showed that the temperature coefficient is frequency-dependent, and generally, a frequency above 1250 Hz has a higher temperature coefficient. OBSI test results at various pavements with different mean texture depths of dense-graded pavement showed that the temperature coefficient varied from 0.052 dB/°C to 0.142 dB/°C. There is an apparent trend of decreasing temperature coefficient with increasing mean texture depth of dense graded asphalt pavements. However, no clear dependence on the temperature coefficient on the vehicle’s speed is observed in this study.

Artificial Neural Network Model for Road Pavement Classification using Features of Tire-Pavement Noise and Road Surface Images

Artificial neural network models were developed to classify road pavement types into the transverse-tined, the longitudinal-tined, NGCS(Next Generation Concrete Surface), Diamond Grinding, and Stone Mastic Asphalt by utilizing tire-pavement noise and road surface images. Tire-pavement noise data were collected by OBSI(On-Board Sound Intensity) method, and analyzed to obtain sound intensity level, sound pressure level, and sound quality indices. Road surface image data was analyzed through image feature extraction algorithms of Hough transformation and HOG(Histogram of gradient). The important features among the acoustic and image characteristics were selected by a random forest model. The acoustic features selected by the random forest algorithm are the overall sound intensity level of 400~5kHz 1/3-octave bands, the sound intensities (W/m2) of 800~2kHz 1/3-octave bands, loudness, fluctuation strength and tonality. The image features selected are the number of longitudinal lines extracted from Hough transform algorithm and HOG of the central cell. The two groups of the selected features were applied separately or together to an artificial neural network model to find classification performance. The classification accuracy rates of the models using acoustic features only, image features only and both acoustic and image features combined were 90.8%, 88.8%, and 97.3%, respectively.

Acoustic Performance Evaluation of Dense-Graded Asphalt Pavements in Qatar

There is pressing and growing demand from the public to design and construct roads with a low noise level. This paper investigated the acoustic performance of asphalt pavements in the State of Qatar to assist transport authorities in designing and constructing quieter pavements. In this study, a field-testing setup was assembled to measure the tire-pavement noise of dense-graded asphalt (DGA) pavements at the source using the on-board sound intensity (OBSI) method. The repeatability and reproducibility of test results demonstrated that the assembled OBSI test setup could measure the sound intensity with excellent repeatability and reproducibility. The measured noise level of existing pavements varied from 101.8 dBA to 106.2 dBA depending on the age of pavement sections. Measured noise levels of pavements in Qatar were higher than typical DGA pavements in Europe and the US. Test results also demonstrated that the acoustic performance of pavements in Qatar deteriorates faster compared to those in the US and Europe. The findings of this study demonstrate that there is a need to consider alternative asphalt mixture designs in Qatar and the Arabian Gulf. The results also showed a good correlation between the mean texture depth of studied pavement sections and noise level, especially at the low-frequency range.

Investigation of ambient noise, surface quality improvements, and friction characteristics of different asphalt surfaces in Alberta, Canada

To determine how pavement noise and grip may be affected by pavement treatment type, a test section was constructed on a major arterial roadway in St. Albert, Alberta. This test section was used to compare the noise and friction differences of a microsurfacing layer, stone mastic asphalt (SMA), and high traffic asphalt (HT) utilizing an onboard sound intensity (OBSI) device, roadside noise meters, and a grip tester. The results of the grip tests revealed that SMA and HT had little effect on improving friction in the corridor, while microsurfacing improved the corridor grip by 15%. From noise testing, it was found that HT provided the best immediate noise attenuation compared to SMA and microsurfacing.

Low-Noise pavement technologies and evaluation techniques: a literature review

ABSTRACT Traffic noise is the perpetual form of environmental pollution adversely affecting human health in urban environments. This literature review, intended for pavement researchers and professionals, looks at the continuously evolving low-noise asphalt pavement technologies and the techniques which can be used to evaluate them. Test methods for determining the acoustical properties of asphalt pavements are reviewed, in both the laboratory and field environments. The Close-Proximity (CPX) method is the most commonly used field test for pavement acoustics, followed by the Statistical Pass-By (SPB) and On-Board Sound Intensity (OBSI) methods. SPB seems is the most comprehensive methods, while the CPX is more practical. Methods for measuring the acoustical properties in the laboratory include the impedance tube for sound absorption and laboratory pavement noise simulators; with only the larger drum methods being able to produce conditions similar to in-situ. Methods for noise-relevant non-acoustical characteristics like surface texture, porosity and airflow resistivity were also reviewed. Optimizing surface texture at the macro-scale was found to be important in reducing tire/road noise. For pavement types, porous asphalt concrete (PAC) and its variants result in low-noise properties the most reliably, while having some drawbacks in durability and maintenance. Finally, various acoustical performance prediction models were discussed.

Modeling Vibration-Induced Tire-Pavement Interaction Noise in the Mid-frequency Range

ABSTRACT Tire-pavement interaction noise (TPIN) is one of the main sources of exterior noise produced by vehicles traveling at greater than 50 kph. The dominant frequency content is typically within 500–1500 Hz. Structural tire vibrations are among the principal TPIN mechanisms. In this work, the structure of the tire is modeled and a new wave propagation solution to find its response is proposed. Multiple physical effects are accounted for in the formulation. In an effort to analyze the effects of curvature, a flat plate and a cylindrical shell model are presented. Orthotropic and nonuniform structural properties along the tire's transversal direction are included to account for differences between its sidewalls and belt. Finally, the effects of rotation and inflation pressure are also included in the formulation. Modeled frequency response functions are analyzed and validated. In addition, a new frequency-domain formulation is presented for the computation of input tread pattern contact forces. Finally, the rolling tire's normal surface velocity response is coupled with a boundary element model to demonstrate the radiated noise at the leading and trailing edge locations. These results are then compared with experimental data measured with an on-board sound intensity system.

AASHTO specifications for noise evaluations of pavement surfaces

Three specifications for the noise evaluation of pavement surfaces have been developed for the American Association of State Highway Transportation Officials (AASHTO). These include (1) the On-Board Sound Intensity (OBSI) method (AASHTO T-360-16) of directly measuring noise generated at the tire-pavement interface in isolation of other noise sources, (2) the Statistical Isolated Pass-By (SIP) method (AASHTO TP 98-13) of measuring noise from isolated vehicles in existing traffic, and (3) the Continuous-Flow Traffic Time Integrate (CTIM) method (AASHTO TP 99-18) of capturing the sound from existing traffic for all vehicles on all roadway lanes. This presentation will describe and compare the procedures of the three AASHTO measurement methods used for the noise evaluation of pavements.

In-door laboratory high-speed testing of tire-pavement noise

ABSTRACT The ability to measure traffic-speed tire-pavement noise in the laboratory is useful for predicting the tire-pavement noise performance of a design mix without conducting expensive and time-consuming field trials. This research developed an in-door high-speed test facility HTP2 for tire-pavement noise measurements. Housed in a semi-anechoic room, HTP2 has a circular test track of vertical wall, and a horizontal rotating arm system mounted with full-scale test tires. The test track can accommodate 12 specimens in each test run. The highest test speed achievable is currently 70 km/h, eventually 100 km/h when fully developed. The On-Board Sound Intensity Method was adopted for tire-pavement noise measurement. Tests were conducted to assess the reliability and repeatability of the test facility. Additional tests involving eight different pavement surface types were performed to illustrate that HTP2 was able to (i) measure sound intensity-frequency characteristics of tire-pavement noise matching those of actual vehicles and pavements, (ii) differentiate sound intensity of tire-pavement noise generated by different pavement types, (iii) identify increase in tire-pavement noise caused by texturing of concrete pavement, (iv) detect differences between tire-pavement noise generated by longitudinally and transversely tined concrete pavements, and (v) measure effects of surface macrotexture on tire-pavement noise.

Prediction models for distress noise generated due to tire-pavement surface interaction

The major objective of this research is to assess the distress noise generated due to tire-pavement surface interaction for different modes and to evolve a noise prediction model for any manner taking into consideration the different factors impacting the distress noise generation. Seven flexible and four rigid pavement roads were chosen for the calculation of the noise in Baghdad city. Tire-pavement interaction noise was calculated using Onboard Sound Intensity (OBSI) Method by restricting the noise generated from the vehicle exhaust and the engine systems. Prediction models were developed for assessing tire pavement noise from vehicle speed, pavement age, wheel load, mean texture depth (MTD) and pavement distresses. Four statistical models were obtained from this research to assess the distress noise generated due to tire-pavement surface interaction using linear regression stepwise method. These models showed the effect of different types of distresses in addition to the factors that have been taken into consideration on tire pavement noise. Vehicle speed was the greatest considerable variable influencing the noise generated due to tire-pavement surface interaction. Some distresses and factors have been excluded from the models due to their poor relationship with tire-pavement noise. These models have been categorized based on the type of pavement surface (flexible or rigid) and the presence or absence of pavement distresses. The predicted statistical models were verified with calculation, by comparing the data estimated by the models and data form field tests. Therefore, it can be used as a method of detecting distresses rather than visual inspection.

Analysis of Skid Resistance and Noise Characteristics for Varieties of Concrete Pavement

To establish evaluation criteria for the pavement skid resistance and noise level in tunnels pavements, the zoning and control standards for skid resistance and concrete pavement noise were examined. Transverse friction coefficient (TFC) test equipment and the on‐board sound intensity (OBSI) method were used to evaluate the antisliding characteristics and noise levels of several tunnel pavements. The results indicated poor antisliding characteristics and noise levels in ordinary grooved cement concrete pavement, whereas new types of cement concrete pavements, such as exposed concrete pavements and polymer‐modified cement concrete pavements, had good antisliding characteristics and achieved low noise levels. Combined with the cluster analysis method, a zoning method for the antisliding and noise level in concrete pavement is proposed. The antisliding characteristics and noise levels of the pavement are divided into three zones. To ensure safety and comfort during driving, the antisliding value (SFC) of the tunnel pavement should be more than 50, and the noise level should not exceed 105 dB. Finally, the correlation between the antisliding and noise levels for pavement was analyzed. The results indicated that the antiskiding value of pavement has a strong correlation to the noise level.

Effect of Rubber Hardness and Tire Size on Tire-Pavement Interaction Noise

ABSTRACT Tire-pavement interaction noise (TPIN) is a dominant noise source for passenger cars and trucks above 25 mph (40 km/h) and above 43 mph (70 km/h), respectively. TPIN is generated due to excitations of the tread pattern and pavement texture. For the same tread pattern and pavement texture at the same speed, TPIN might also be influenced by the tire structure (e.g., the tread rubber hardness and tire size). In the present study, 42 tires with different rubber hardnesses and/or tire sizes were tested at five different speeds (45–65 mph, i.e., 72–105 km/h) on a nonporous asphalt pavement (a section of U.S. Route 460, both eastbound and westbound). An on-board sound intensity system was instrumented on the test vehicle to collect the tire noise data at both the leading edge and the trailing edge of the contact patch. An optical sensor recording the once-per-revolution signal was also installed to monitor the vehicle speed and, more importantly, to provide the data needed to perform the order-tracking analysis to break down the tire noise into two components. These two components are the tread pattern noise and the non–tread pattern noise. It is concluded that for the nonporous asphalt pavement tested, the non–tread pattern noise increases with rubber hardness by ∼0.23 dBA/Shore A. The tire carcass width (section width plus two times section height) influences the central frequencies of the non–tread pattern noise spectrum; the central frequencies decrease as the tire carcass width increases.

Evaluation of Noise Performance of Multi-Lane Highways in the State of Qatar

In recent years, a growing number of people are complaining to transportation authorities for the traffic noise as a result of increased traffic volume on the highways. Therefore, transportation authorities are actively pursuing ways to reduce the traffic noise. In recent years, quieter pavement has become one of the cost-effective ways of sustainable highway noise reduction. However, for design and construction of quieter pavements, proper and accurate noise measurement is of paramount importance for evaluating the noise level of existing pavement as well as evaluating noise level of newly constructed pavements. In this study, the variation of noise level among different lanes of existing multi-lane highways in the State of Qatar was examined. Tire-pavement noise was measured by using onboard sound intensity (OBSI) technique. OBSI test results showed that highest noise level was observed at outer lane of multi­lane highways. This is probably due to the pavement distress caused by the heavy vehicle travelling at the outer lane of multi-lane highways.