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。     

A GIS based road traffic noise prediction model

A road traffic noise prediction model has been developed suitable for use in China. This model is based on local environmental standards, vehicle types and traffic conditions. The model was accurate to 0.8 dBA at locations near the road carriage way and 2.1 dBA within the housing estate, which is comparable to the FHWA model. An integrated noise-GIS system was developed to provide general functions for noise modeling and an additional tool for noise design, where a new interaction mode in “WHAT IF Question/Explanation” format was used. Application of this system offered improvements in the efficiency and accuracy of traffic noise assessment and noise design.     

Computer simulation model for the prediction of traffic noise levels

This paper describes a computer simulation model capable of predicting the noise levels generated by traffic passing through road intersections controlled by roundabouts where departures from free-flow traffic conditions occur. The model depends for its operation on the acoustical and flow characteristics of single vehicles travelling on a road from which the overall noise generated by traffic streams can be deduced using a sampling/integration technique. Distance effects, ground cover, vehicle type, velocity and headway characteristics, etc. are taken into account in the model and the simplest possible input parameters are used deliberately to facilitate the eventual use of the model by highway and planning authorities. Good agreement has been achieved between measured and predicted L₁₀ values for freely flowing traffic negotiating roundabouts. Further applications of the model involving road intersections controlled by traffic lights and the effect of traffic queues are nearing completion.     

Development of a highway traffic noise prediction model that considers various road surface types

A highway traffic noise prediction model has been developed for environmental assessment in South Korea. The model is based on an outdoor sound propagation method and is fully compliant with ISO 9613 and the sound power level (PWL) estimation for a road segment, as suggested in the ASJ Model-1998 that is based on PWLs. Due to that model’s selection of two pavement types, such as asphalt or concrete pavement, an unacceptable traffic noise prediction is made in cases where the road surface is different from that on which the model is based. In order to address this problem, several road surface types are categorized, and the PWL of each surface type is determined and modeled by measuring the noise levels obtained from newly developed methods. An evaluation of the traffic noise prediction model using field measurements finds good agreement between predicted and measured noise levels.     

An optical scale model of traffic noise propagation in an urban environment

This paper describes principles of modelling traffic noise using an optical scale model. The main difference between this model and the widely used ‘acoustical’ scale model is that it makes use of light instead of sound. There were four phases to the study. The first of these involved the propagation of single vehicle noise over ground and its dependence upon distance and vehicle velocity. The second phase was concerned with light emitted by a small lamp, which imitated a single vehicle. The third part of the work dealt with the principles of the optical model, its construction and use in predicting the equivalent level, $\text{L}{}_{\mathrm{<mtext>eq</mtext>}}$, of traffic noise. Finally, a model of a part of a residential area of Poznań, Poland, was built and values of $\text{L}{}_{\mathrm{<mtext>eq</mtext>}}$ computed. These results were compared with field measurements.     

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.     

Small-time scale network traffic prediction based on a local support vector machine regression model

In this paper we apply the nonlinear time series analysis method to small-time scale traffic measurement data. The prediction-based method is used to determine the embedding dimension of the traffic data. Based on the reconstructed phase space, the local support vector machine prediction method is used to predict the traffic measurement data, and the BIC-based neighbouring point selection method is used to choose the number of the nearest neighbouring points for the local support vector machine regression model. The experimental results show that the local support vector machine prediction method whose neighbouring points are optimized can effectively predict the small-time scale traffic measurement data and can reproduce the statistical features of real traffic measurements.     

A traffic noise prediction method based on vehicle composition using genetic algorithms

The effect of traffic composition on the noise pollution has been investigated in a small city Erzurum, located in eastern Turkey, where the population is about 400,000. Manual noise measurements and vehicle counts were performed at the four heaviest traffic points in the city for a period of 12 h. Using the information on vehicle composition and the maximum legal noise emissions of each type of vehicles, two prediction models based on genetic algorithms have been developed that can be used as tools for in-city traffic flow redesign. The models have been validated against some of the noise data. Measured traffic noise levels have been compared with predictions using the new models and some existing ones and a relatively good agreement has been obtained between them.     

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.     

The prediction of noise from urban traffic under interrupted flow conditions

A computer model is described for predicting noise levels generated by urban road traffic under interrupted flow conditions. The model is composed of two subsections. The first predicts the propagation characteristics of sound in typical street configurations and the second simulates the flow of road traffic in urban areas. The two subsections are combined to yield a model capable of predicting traffic noise levels in urban conditions.Predictions obtained from application of this model are compared with those given from application of predictive models based upon field measurements. The agreement between the predictions is good. It is shown that the model described in this paper can predict noise levels for situations which existing field-based models cannot handle.     

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.     

Network traffic prediction by a wavelet-based combined model

Network traffic prediction models can be grouped into two types, single models and combined ones. Combined models integrate several single models and thus can improve prediction accuracy. Based on wavelet transform, grey theory, and chaos theory, this paper proposes a novel combined model, wavelet--grey--chaos (WGC), for network traffic prediction. In the WGC model, we develop a time series decomposition method without the boundary problem by modifying the standard \grave\rm a trous algorithm, decompose the network traffic into two parts, the residual part and the burst part to alleviate the accumulated error problem, and employ the grey model GM(1,1) and chaos model to predict the residual part and the burst part respectively. Simulation results on real network traffic show that the WGC model does improve prediction accuracy.     

基于局域相关向量机回归模型的小尺度网络流量的非线性预测

基于非线性时间序列局域预测法与相关向量机回归模型, 本文提出了局域相关向量机预测方法, 并应用于预测实际的小尺度网路流量序列. 应用基于信息准则的局域预测法邻近点的选取方法来选取局域相关向量机回归模型的邻近点个数. 对比分析了局域相关向量机预测法、前馈神经网络模型与局域线性预测法对网络流量序列的预测性能, 其中前馈神经网络模型的参数采用粒子群优化算法来优化. 实验结果表明: 邻近点优化后的局域相关向量机回归模型能够有效地预测小尺度网络流量序列, 归一化均方误差很小; 局域相关向量机回归模型生成的时间序列具有与原网络流量时间序列相一致的概率分布; 局域相关向量机回归模型的预测精度好于前馈神经网络模型的与局域线性预测法的. 关键词： 小尺度网络流量 非线性时间序列预测方法 局域预测法 相关向量机回归模型     

Highway traffic noise prediction using method fully compliant with ISO 9613: comparison with measurements

In this study, we introduce outdoor sound simulation that is fully compliant with ISO 9613 yet with some complementary methods that enhance its applicability; for example, calculation of sound attenuation due to undulating terrain in octave bands, geometric divergence in the near-field of the source, and short-term wind effects. Using the method, we have carried out highway traffic noise prediction and measurement for 12 sites with representative road shapes and structures. In the prediction, the sound power level for a road segment was estimated by the method suggested in ASJ Model-1998 with experimental corrections to the overall noise level and spectrum. Comparing results between predicted and measured noise levels show good correspondence at direct, diffracted and reflected sound fields within 30m from the center of the near side lane.     

The return wall as a traffic noise barrier

The attenuation of road traffic noise by a number of finite barrier configurations is investigated using scale modelling and computer simulation. It is found that the accepted UK prediction technique gives a consistently conservative estimate of barrier performance. It is shown that the use of a return wall as a noise barrier can be advantageous in certain circumstances.     

公路交通噪声等效车道距离的确定方法探讨

在公路交通噪声计算中,目前常用的确定等效车道距离的方法是计算接受点至近车道和远车道的距离的几何平均值,但使用该方法得到的接受点处的交通噪声与使用两个车道分别计算后再叠加的方法所得到结果相比,存在一定偏差。本文提出用调和平均值确定等效车道距离,即用接受点至近车道和远车道的距离的几何平均值的平方除以算术平均值来确定等效车道距离。通过比较,证明调和平均法比几何平均法具有更高的精确性。     

An exploratory study into the prediction of low frequency traffic noise

An exploratory study whose main aim was to develop equations for the prediction of low frequency traffic noise scales (from traffic parameters) is described. Summaries of noise and traffic measurement procedures are documented and the results of data analysis presented.The equations developed are shown to be accurate, but will require development to cater for more variable site conditions. The equations also indicate the large contribution made to low frequency noise levels by heavy vehicles. The implication of this for ‘lorry nuisance’ is discussed. Broad-band scales are shown to be reasonable surrogates for most, but not all, narrow-band low frequency effects. A method for determining low frequency scales using simple instrumentation is described.This paper is the first of three based on work carried out with the assistance of the Greater London Council (Scientific Branch) and which deal with the prediction of low frequency traffic noise scales and their relevance to vibration disturbance, lorry nuisance and building vibration.