Estimating traffic noise for inclined roads with freely flowing traffic

Traffic noise measurements on the kerbs of 19 independent inclined trunk roads with freely flowing traffic within the residential areas of Hong Kong are carried out in the present investigation. The performance of the existing noise prediction models in predicting traffic noise from inclined roads is evaluated. By regression analysis and simple physical consideration of the traffic noise production mechanisms, formulae for the prediction of the L_A10, L_A50, L_A90 and L_Aeq are developed or re-calibrated. Results suggest tyre noise has the major contribution to the overall noise environment when the source is an inclined trunk road. Also, the road gradient is found to have a higher contribution to the traffic noise than assumed in the existing models, but becomes unimportant when the background noise level L_A90 is concerned.     

New vehicle noise emission for French traffic noise prediction

Traffic noise prediction models in France are based on vehicle noise emission values defined by the French Guide du Bruit des Transports Terrestres (Noise Guide for Ground Transport - Noise levels prediction). These emission values are suited for models addressing the noise assessments of road infrastructures and the dimensioning of acoustic protections, needing traffic noise estimations in terms of ?_Aeq over a long period of time (an hour or more).The values, obtained from measurements collected in the 70s, are updated in the publication of a new guide (Methodological Guide, Vehicle noise emissions, to be published), which addresses the road surface influence on tyre/road noise. The emission values are now expressed through the contributions of a power unit component, function of traffic speed, traffic flow type and road declivity, and of a rolling noise component, function of traffic speed and road pavement.The paper outlines the procedures followed to determine the components, gives their numerical values, and illustrates some vehicle noise emissions.     

Honking noise corrections for traffic noise prediction models in heterogeneous traffic conditions like India

In developing countries like India, the nature of the composition of traffic is heterogeneous. A heterogeneous traffic flow consists of vehicles that have different sizes, speeds, vehicle spacing and operating characteristics. As a result of the widely varying speeds, vehicular dimensions, lack of lane disciplines, honking becomes inevitable. In addition, it changes the urban soundscape of developing countries. In heterogeneous traffic conditions, horn events increase noise level (L_den) by 0.5–13 dB(A) as compared to homogenous traffic conditions. Therefore, the traffic prediction models that are used for homogenous traffic conditions are not applicable in heterogeneous traffic conditions. To increase the accuracy of noise prediction models, in depth understanding of heterogeneous traffic noise is required. Understanding the real traffic noise characteristics requires quantification of some of the basic traffic flow characteristics such as speed, flow, Level Of Service (LOS) and density. In a given roadway, the noise level changes with density and LOS on the road. In this paper, a new factor for horn correction is introduced with respect of Level Of Service (LOS). The horn correction values can be incorporated in traffic noise models such as CRTN, FHWA, and RLS 90, while evaluating heterogeneous traffic conditions.     

Motorway noise modelling based on perpendicular propagation analysis of traffic noise

A model for motorway traffic noise has been obtained from measurements along the the Bangkok-Chonburi motorway. The model’s parameters include traffic volume and combination, the average spot speed of each type of vehicle and the physical conditions of the motorway in terms of right-of-way width, number of lanes, lane width, shoulder width, and median width for both of the main carriageways and frontage roads. The noise level that is generated by each type of vehicle has been analyzed according to the propagation in the direction perpendicular to the center line of motorway’s carriageway. The total traffic noise is then analyzed from traffic volume of all vehicle types on both sides of carriageways and frontage roads. The basic noise levels used in the motorway traffic noise model are modified according to the effective ground effect along the propagation path. The final result of this study is that a motorway traffic noise model based on the perpendicular propagation analysis technique performs well in a statistical goodness-of-fit test against the field data, and therefore, can be used effectively in traffic noise prediction for related or similar motorway projects.     

Influence of expanding ring roads on traffic noise in Beijing City

The road network in Beijing is expanding in the form of loop-lines. Following the 2nd and 3rd ring roads, the 4th has been completed and come into operation in 2002. Traffic noise surveying and analysis was performed along four main roads in the Beijing urban area—the 2nd, 3rd and 4th ring roads circling the central downtown area and Chang-An Avenue, a major east-west corridor through the heart of the city. Measured noise data along the 2nd, 3rd and Chang-An Avenue were compared with the data surveyed before the completion of the 4th ring road for determining influence of expanding ring roads on traffic noise pattern in Beijing City. The results indicate that these main roads remain overloaded by traffic flow during daytime, and noise levels due to road traffic along these roads exceeds relavent environmental standards by 5 dBA. Reduced traffic noise level was observed along the northern half of the 2nd and 3rd ring roads, and along the central section of Chang-An Avenue. Increased traffic noise level was observed along the southern half of the 2nd and 3rd ring roads, and along the non-central section of Chang-An Avenue. Expanding ring roads mitigate heavy traffic flow in the central part of Beijing City, but spread high traffic noise outwards at the same time.     

公路交通噪声预测模型探讨

对公路交通噪声预测模型进行了分析推导,指出美国联邦公路局FHWA模型为近似表达式,并给出了精确表达式。对FHWA模型与精确表达式在硬地面、软地面、混合地面几种条件下的值进行了比较分析。结果表明,两者在硬地面条件下的形式和计算结果相同;在混合地面,即公路的实际情况下,两者存在差异,差值等于10lg(r1/r0)α。在用于高速公路交通噪声预测计算时,当r0取15m,该差值较小,当r0取7.5m,该差值增大;在一般情况下,r0取15m时的差值为±0.3dB(A),r0取7.5m时的差值为1.2—1.8dB(A),后者约占交通噪声预测值的1.5-4%,是不应忽视的。说明我国在引用FHWA模型时,对参考点距离的更改,会造成用于高速公路交通噪声预测的误差增大。建议我国使用本文推导给出的修订模型。     

考虑加速度的交通噪声源强研究

本文为研究机动车噪声源强与速度、加速度的关系,对车辆在不同速度和加速度下的A计权声压级进行测试,运用统计学方法对测试数据进行分析,得到机动车单车噪声源强与车辆速度、加速度的关系模型,并与《公路建设项目环境影响评价规范(JTG B03-2006)》中的交通噪声源强预测模型进行比较,实测验证结果表明,利用本研究建立的机动车单车噪声源强模型所得预测结果更符合实际。     

Variability in road traffic noise levels

Environmental noise levels can vary over a wide range as a result of the diversity of site conditions and activities occurring during field measurements. This variability, extremely important for a correct measurement interpretation, is often a source of disagreement when applying standards and regulations, as there is no consensus about how to estimate and present it. The paper contributes to this technical debate by investigating the statistical variability associated with a large measurement database acquired under field conditions. The database consists of 2 week’s noise recordings at each of 50 separate locations in residential areas affected mainly by road traffic noise. The results show increased variability (standard deviations) at the lower values of either logarithmic or arithmetic mean L_Aeq over the time periods investigated. It is anticipated that the observed relationships may be of assistance when estimating the noise level variability and the uncertainty associated with a noise measurement affected by road traffic or other environmental noise sources.     

Effects of urban morphology on the traffic noise distribution through noise mapping: A comparative study between UK and China

Due to the rapid urban development and massive population increase in many eastern cities, the difference in urban density and morphology between typical western and eastern cities is becoming significant. This consequently makes the noise distribution in the eastern cities rather different from typical low density European cities. In this research, two representative cities with different urban densities, Greater Manchester in the UK and Wuhan in China, were selected, which have low and high average urban density respectively, and also have considerable differences in building form and traffic pattern. In the mean time, these two cities have similar urban scale and traffic amount. In each city, based on the urban morphological analyses considering urban land-use, building and road density, and noise source distribution, a number of typical urban areas, 500 * 500 m² each, were sampled. A noise-mapping software package was then used to generate generic noise maps, based on existing digital vector maps for terrain and building, and traffic data obtained by on-site measurements. The comparison results show that the average and minimum noise level in Greater Manchester samples is generally higher than that in Wuhan samples, while the maximum noise level in Wuhan samples is mostly higher. By developing a Matlab program, correlations have been analysed between noise distributions and the urban characteristics relating to urban density, such as the road and building coverage ratio. Overall, comparisons between these two typical cities have shown significant effects of urban morphology on the traffic noise distribution.     

A simple formula for evaluating the acoustic effect of balconies in protecting dwellings against road traffic noise

This study explores the noise reducing effect of a balcony and describes the development of a simple theory pertaining to the propagation of traffic noise from a road into a balcony. A new methodology is proposed that is based on the well-known prediction scheme—“Calculation of Road Traffic Noise” (CRTN)—developed in the UK. A geometrical ray theory is developed for the prediction of noise levels inside a balcony due to road traffic. The source level of road traffic noise is obtained as per the standard CRTN methodology. However, road sub-segmentations and new approaches for the prediction of noise levels at illuminated and shadow zones inside a balcony are proposed. Field measurements have been conducted on four different types of balcony to validate the proposed methodology. The insertion loss, defined as the difference in the noise levels with and without the presence of a balcony, has been used to assess the shielding effectiveness of a balcony against road traffic noise. The simple theory is validated by outdoor field measurements. It is also found that a properly designed balcony can provide considerable screening effects in protecting dwellings against road traffic noise.     

考虑行驶状态的水泥路机动车噪声排放模型

本文旨在建立机动车单车辆的基础噪声排放模型,通过对大中小车辆在加速、减速、匀速及怠速状态下A计权声压级进行测量,运用回归分析方法拟合实验数据,得到考虑车型和行驶状态的水泥路面机动车单车辆噪声排放模型,并利用另一部分实测数据进行对比验证。误差分析显示:比较《公路建设项目环境影响评价规范(JTG B03-2006)》中的噪声模型,本研究建立的单车辆噪声排放模型预测精度更高。     

Blind separation to improve classification of traffic noise

In order to apply noise mapping to traffic noise prediction, a knowledge of several information about traffic characteristics is required to predict the noise levels emitted by the roads involved. In the European case, the CNOSSOS-EU calculation method for traffic-noise level prediction is now under discussion, to be agreed in response to the European Directive relating to the Assessment and Management of Environmental Noise (2002/49/EC). In this application context, standard ISO 1996-2:2007 Determination of Environmental Noise Levels, in its Section 6.2, specifically mentions that during L_eq measurements of road traffic noise the number of vehicle pass-bys shall be counted during the measurement time interval. This information is often not available in many roads, so it is typically registered by means of casual counts, often through manual procedures. Besides, if the measurement result is converted to other traffic conditions, a categorization of the vehicles involved is also required. Some additional information, such as the traffic density and the average speed, should be registered if a calculation method is used to build a noise map.In this paper a new automatic classification system of traffic noise covering these requirements is presented. The portable system processes a two channel audio recording to provide information of the average speed and the number of vehicles, which are classified in six categories during the measurement period. After several evaluations of the possibilities to get a good classification of the noise emission of a road from audio recordings, it is shown that increasing the within-class separation, as well as introducing a novel BSS–PCA-based classifier, the precision achieved in the final results is substantially improved.     

Property prices in urban areas affected by road traffic noise

This paper reports a revealed preference study into the different effects of road traffic noise on property values in residential areas with similarly high road traffic sound levels but with what appear to be important differences in the market for different types of residential property in each area. The results show significant differences in the revealed effects of noise on property prices between the three areas with in one case an increasing (and possibly misleading) relationship between higher monetary values and higher sound levels. A number of possible explanations for the findings are discussed in the paper.     

Road traffic noise prediction based on speed-flow diagram

The method enables calculation of the annual average sound level of the road traffic noise, when the characteristics of the speed-flow diagram are available: the average speed of freely cruising vehicles, capacity of the traffic flow, traffic speed at the traffic flow capacity, and the slope of the decreasing traffic speed versus traffic flow. Under any conditions, traffic congestion reduces the annual average sound level. The final conclusion is that strong traffic congestion cannot be ignored in noise prediction.     

Practical guidance for risk assessment of traffic noise effects on sleep

Environmental noise disturbs sleep and may impair well-being, performance and health. The European Union Directive 2002/49/EC (END) requires member states to generate noise maps and action plans to mitigate traffic noise effects on the population. However, practical guidance for the generation of action plans, i.e. for assessing the effects of traffic noise on sleep, is missing. Based on the current literature, we provide guidance on hazard identification, exposure assessment, exposure-response relationships and risk estimation: there is currently no consensus on both exposure and outcome variables that describe traffic noise effects on sleep most adequately. END suggests the equivalent noise level L_night as the primary exposure variable, and our own simulations of single nights with up to 200 noise events based on a field study on the effects of aircraft noise on sleep support using expert consensus L_night ranges (<30, 30-40, 40-55, >55 dB) for risk assessment. However, the precision of risk assessment may be considerably improved by adding information on the number of noise events contributing to L_night. The calculation of L_night should be extended to the shoulder hours of the day if traffic is busy during these periods. More data are needed on the combined effects of different traffic modes.     

Analysis of the prediction capacity of a categorization method for urban noise assessment

A street categorization method to study urban noise was tested by comparing its results and predictive capacity with those of a reference method – the standard grid method (mentioned in the ISO 1996 standard). To this end, two independent noise surveys were carried out simultaneously in the city of Cáceres (Spain), each using one of these two methods. In a first step, the overall values of each procedure were obtained and the differences analyzed. Then, to analyze the predictive capacity of the categorization method, the two noise maps were constructed, and their predicted values (the noise levels of the squares of the grid for the grid method, and of the categories for the categorization method) were compared with the data of the other procedure used as control.It was found that the categorization method yielded similar results for the overall analysis of the city to those obtained with the value of the points of the grid method with considerably fewer sampling points.The categorization method also seems to be a more suitable predictor for new measurements, particularly for levels in the noisiest streets of the town.     

Exposure-effect relationships between road traffic noise annoyance and noise cost valuations in Valladolid, Spain

Environmental noise can produce negative effects on people’s health since it interferes with basic activities such as sleeping, resting, studying and communicating. These effects depend not only on the physical characteristics of the noise itself, but also on parameters associated to each person and each environment. It is thus important to study noise pollution from a quantitative point of view as well as a from the point of view of the annoyance that it produces in the population.We have conducted a social survey aiming to identify the main sound sources, evaluate the annoyance and analyse the main effects of noise on people. The survey was distributed to a sample of people living approximately in the corners of an imaginary 250 m grid placed over the map of the city of Valladolid (Spain). The same corners were used to perform in situ measurements for a noise city map.There are two main purposes for this research work: (1) we want to compare the objective noise measurements to the annoyance reported by the people in order to find some kind of dose-effect relationship, and (2) we want to analyse how the population of Valladolid evaluates noise reduction from an economical and social point of view.