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.     

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.     

Noise emission assessment of a hybrid electric mid-size truck

In the attempt to improve urban environmental conditions, city or national incentives encourage the use of cleaner vehicles, including hybrid electric vehicles. This paper explores the actual noise impact of this alternative drivetrain technology on the noise emission of a mid-size delivery truck powered by a parallel hybrid powertrain, compared with an equivalent internal combustion engine truck on the basis of pass-by noise measurements. It investigates jointly the overall emission, the main noise sources and the vertical directivity of the vehicle. The essential benefit results from the existence of a full-electric mode below 50 km/h, with a significant noise reduction which may exceed 8 dB(A) at low constant speed. Even if smaller, this noise advantage is still valuable when the vehicle is accelerating or braking. Due to weaker noise emitted upwards, the benefit should be even greater for residents living on upper building floors. The rolling noise associated with the drive wheel/road contact is the main noise source in all driving situations in electric mode, and beyond 50 km/h in the configurations with engine.     

A road traffic noise pattern simulation model that includes distributions of vehicle sound power levels

Annoyance, sleep disturbance and other health effects of road traffic noise exposure may be related to both level and number of noise events caused by traffic, not just to energy equivalent measures of exposure. Dynamic traffic noise prediction models that include instantaneous vehicle noise emissions can be used to estimate either of these measures. However, current state-of-the-art vehicle noise emission models typically consider a single emission law for each vehicle category, whereas measurements show that the variation in noise emission between vehicles within the same category can be considerable. It is essential that the influence of vehicles that are producing significantly more (or less) noise than the average vehicle are taken into account in modeling in order to correctly predict the levels and frequency of occurrence of road traffic noise events, and in particular to calculate indicators that characterize these noise events. Here, an approach for predicting instantaneous sound levels caused by road traffic is presented, which takes into account measured distributions of sound power levels produced by individual vehicles. For the setting of a receiver adjacent to a dual-lane road carrying free flow traffic, the effect of this approach on estimated percentile levels and sound event indicators is investigated.     

Prediction and Limitations of Noise Maps Developed for Heterogeneous Urban Road Traffic Condition: A Case Study of Surat City,India

Road traffic noise pollution has been recognized as a serious issue which affects human health as well as affects urban regions. Noise maps are very beneficial to identify the impact of noise pollution. A noise mapping study performed to study the propagation of noise in tier-II city along with field measurements. The noise maps are developed using a computer simulation model (SoundPLAN essential 4.0 software). The noise prediction models like U.K’s CoRTN, Germany’s RLS-90, and their modified versions, which can be used for homogenous road traffic conditions, cannot be successfully applied in heterogeneous road traffic conditions of India. In developing country like India, road traffic noise pollution depends on the composition of heterogeneous traffic volume, variance in road geometrical, honking conditions, un-authorized parking, and varying density of the building on either side of the road. These traffic compositions contain vehicles, which have different sizes, speeds variations, a different dimension of vehicles. Because of fluctuating speeds, lack of lane disciplines, and un-authorized parking on main road lanes, honking events becomes inevitable, which changes and affects the urban soundscape of nations like India. Analysis of noise maps showed that horn honking due to un-authorized parked vehicles contributed an additional increase up to 11 dB (A) noise, which is quite significant.     

Road traffic noise—The influence of the road surface and its characterization

Unacceptable errors in the prediction of traffic noise occur in some cases when the road surface is largely different from that on which the prediction model is based. The reason is that tyre/road noise has appeared to be the dominating component of the noise from free-flowing traffic and that this noise is to a substantial extent dependent on the road surface.The mechanisms for tyre/road noise generation and its relation to road characteristics are described. Relevant road surface characterization methods are suggested. The major method is the measurement of the road texture profile and subsequent spectral analysis of the profile curve. Supplementary methods concern the measurement of acoustical and mechanical impedances. It is concluded that the road surface effect on traffic noise is extremely complicated and that it is very difficult to generalize any simple relations.For free-flowing traffic it is shown that the tested road surface types and conditions may influence the traffic noise by up to 11 dB(A). This calls for a correction term for the road surface in the prediction models. Despite the complicated relations, it appears feasible—within stringent limitations—to use a table where the correction term is a variable of vehicle type, vehicle speed as well as road surface type and condition.     

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.     

多通道FxAP算法的电动汽车路噪控制

汽车噪声控制是主动噪声控制领域中经典的问题.伴随着电动化的普及,路噪控制将取代内燃机噪声控制,逐渐成为汽车噪声控制的主要领域.针对传统车内路噪控制系统适应性差、算法收敛速度慢、降噪量不足的问题,该文使用了多通道滤波-x仿射投影(FxAP)算法加快收敛速度,从而实现对噪声的快速追踪并控制.通过搭建了车内多通道头靠噪声控制...     

纵坡道路噪声分布规律研究*

为了摸清纵坡道路单车噪声排放规律和两侧声场分布状况,借鉴国内外单车噪声排放模型研究方法,对水平路面单车和坡度路面单车噪声源强测试数据进行分析,提出水平路面单车噪声排放模型和坡度路面单车噪声排放修正模型。实测某纵坡道路两侧噪声分布情况验证模型的适用性,并应用模型仿真研究纵坡道路噪声分布规律,得出与道路较近的观测点处,上坡一侧噪声比下坡一侧和水平道路两侧偏高;与道路较远的观测点处,坡度产生的影响可以忽略不计。论文研究成果对道路环境影响评价和噪声地图绘制及其误差分析具有很好的参考作用。     

Identification of winter tires using vibration signals generated on the road surface

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.     

Dynamic noise modeling at roundabouts

Modeling spatial and temporal noise variations at roundabouts is a tedious task. Indeed, noise levels are strongly influenced by the complex vehicle interactions taking place at the entries. An accurate modeling of the merging process and its impact on vehicle kinematics, waiting time at the yield signs and queue length dynamics is therefore required. Analytical noise prediction models disregard those impacts since they are based on average flow demand patterns and pre-defined kinematic profiles. The only way to capture all traffic dynamics impacts on noise levels is to combine a traffic simulation tool with noise emission laws and a sound propagation model. Yet, such existing dynamic noise prediction packages fail in representing vehicle interactions when the roundabout is congested and are difficult to calibrate due to their numerous parameters. A new traffic simulation tool, specifically developed for roundabouts, is therefore proposed in this paper. It has few easy-to-calibrate parameters and can be readily combined with noise emission and propagation laws. The obtained noise package is able to produce relevant dynamic noise contour maps which can support noise emission assessment of local traffic management policies. Results are validated against empirical data collected on a French suburban roundabout on two different peak periods.     

Statistical classification of road pavements using near field vehicle rolling noise measurements

Low noise surfaces have been increasingly considered as a viable and cost-effective alternative to acoustical barriers. However, road planners and administrators frequently lack information on the correlation between the type of road surface and the resulting noise emission profile. To address this problem, a method to identify and classify different types of road pavements was developed, whereby near field road noise is analyzed using statistical learning methods. The vehicle rolling sound signal near the tires and close to the road surface was acquired by two microphones in a special arrangement which implements the Close-Proximity method. A set of features, characterizing the properties of the road pavement, was extracted from the corresponding sound profiles. A feature selection method was used to automatically select those that are most relevant in predicting the type of pavement, while reducing the computational cost. A set of different types of road pavement segments were tested and the performance of the classifier was evaluated. Results of pavement classification performed during a road journey are presented on a map, together with geographical data. This procedure leads to a considerable improvement in the quality of road pavement noise data, thereby increasing the accuracy of road traffic noise prediction models.     

Commercial road vehicle noise

A survey of the characteristics of the noise emitted by commercial vehicles has been made. The most important single parameter determining the noise of a modern diesel-engined vehicle is the engine speed. All of the other parameters such as load, road speed, etc., have only a secondary effect.The sources of noise on the vehicle are reviewed and it is shown how the characteristics of these sources determine the overall noise characteristics of the vehicle. It has been found that a simple model of the vehicle as a number of coincident point sources predicts the overall noise characteristics of the vehicle to ±2 dB(A). It is shown that there are two extremes of behaviour, the rolling noise controlled vehicle and the power unit noise controlled vehicle; the engine is currently the controlling noise source.Tyre noise has been investigated in some detail as comparatively little has been published previously on this source. Empirical relationships between the tyre noise and speed, tyre size and road surface roughness are given. It is concluded that tyre noise is generated by impacting between elements of the tyre tread and elements of the road surface.Modifications have been made to the engine, exhaust, intake and cooling fan of a 9 ton, 6 litre diesel engined truck which have reduced its ISO test noise level from 88 dB(A) to 80 dB(A). However, it is concluded that 80 dB(A) commercial vehicles are not yet feasible for production. In particular insufficient is known about cooling fan design.Finally cab noise has been investigated and it has been found to originate from the same source as the exterior noise, power unit airborne noise. Therefore any modifications to the power unit to reduce exterior noise will have a similar effect on interior noise. This is confirmed by the vehicle modifications mentioned above which reduced the maximum cab noise from 87 dB(A) to 79 dB(A).     

基于道路限速策略的规划路网噪声控制*

为缓解交通噪声污染,研究限速方案对噪声的影响,考虑道路限速策略下的阻抗函数,建立基于道路限速的随机用户均衡模型并实现路网交通分配,对规划路网在不同限速策略下的噪声控制规律进行研究。案例结果表明：道路限速控制对象应选取噪声影响道路;道路限速策略控制噪声的主要因素在于降低影响道路上出行车辆的出行速度,控制区域噪声值与路网总出行时间呈线性关系,道路限速80%的情况下,控制区域噪声和路网总出行时间分别降低2.94dB和增加0.66%;路网总噪声排放存在两种不同变化趋势,且与道路等级,绕行系数相关。研究可为从道路规划角度实现交通噪声控制提供有效参考。     

Characterisation of tram noise emission and contribution of the noise sources

The recent expansion of French tram networks and the related local residential complaints mean that a better knowledge of the situations leading to negative reactions from the local inhabitants is required. Hence a research project has been conducted to evaluate and describe noise and vibration emission of trams as well as the perception by the local residents. This paper investigates tram noise emission on common straight track sections, involving two vehicle scales. First the acoustic power and the mean vertical directivity of the total tramset is assessed using an arc of microphones. Then the localisation and the analysis of the main noise sources are performed by means of a cross array during the tram pass-by. Two tram types representing two generations of French rolling stock, both running on two sites with distinct track characteristics, have been investigated considering the effect of speed, tram type, and track type on the noise source contributions and spectral features. Most sources are located in the lower part of the trams, mainly related to rolling noise, with a strong dependence on speed and track type. The tram type dependency, although globally of second importance, influences greatly the noise spectral distribution and behaviour. The HVAC was the only roof-mounted source which could be detected; its contribution towards building storeys becomes significant in configurations of low rolling noise. A tram noise emission model based on the various noise sources has been developed.     

Influence of the automotive Start/Stop system on noise emission: Experimental study

One of the most common environmental impacts of road transportation is the traffic noise. Linked to this, Start/Stop is a technology which has demonstrated to save fuel by powering off the engine when the vehicle is stopped, such as in front of a traffic light, and restarting the engine instantly when the driver pushes back the pedal brake to proceed. The technology helps also to reduce the CO₂ emission, playing a key role in a way to accomplish stringent emission norms for vehicle manufacturer. However, we are not sure whether it reduces the noise emission and how much? Thus, the main aim of this work is to assess the engine noise emissions of a vehicle incorporating a Start/Stop system in urban traffic, and compare it with those radiated by the mean traffic stream. Experimental results demonstrate that there are no contributions of the Start/Stop system to reduce meaningfully the engine noise in urban traffic.     

Study to analyze the effects of vehicles and pavement surface types on noise

The effects of vehicles and pavement surface types on noise have been investigated at the Korea Highway Corporation’s Test Road along the southbound side of the Jungbu Inland Expressway, South Korea. The study was conducted in 2005 and 2006 through field measurements at nine surface sections of asphalt concrete and Portland cement concrete pavements using eleven vehicles. For the road noise analysis, the sound power levels (PWLs) of combined noise (e.g., tire/pavement interaction noise and power-train noise together) and tire/pavement interaction noise using various vehicles were calculated based on the novel close proximity (NCPX) and pass-by methods. Then, the characteristics of the PWLs were evaluated according to surface type, vehicle type, and vehicle speed. The results show that the PWLs of vehicles are diversely affected by vehicle speed and the condition of the road surface.     

A new methodology to assess sound power level of tyre/road noise under laboratory controlled conditions in drum test facilities

Tyre/road interaction is the main source of noise emission caused by road traffic when cruising at speeds over 30 km/h. Several methods such as the Coast-By, the Close-Proximity, the Statistical Pass-By or the Controlled Pass-By have been used over recent decades to measure noise emission. However, since Regulation (EC) No. 1222/2009 on the labelling of tyres was published, only the method described in UNECE Regulation 117 concerning the approval of tyres with regard to rolling sound emissions, can be used in order to obtain tyre/road noise emission approved values. All these conventional methods have several disadvantages such as the lack of repeatibility, the influence of environmental factors or the different results that can be obtained depending on the test track or the vehicle upon which the tests are carried out. A new methodology based on drum tests and the ISO 3744:1994 has been developed in order to avoid these limitations. This paper describes the new method including the positioning of microphones, calculating correction factors, characterising the background noise caused by the drum and obtaining the sound power level of a tyre when rolling against a drum.     

Influence of vehicle noise emission directivity on sound level distribution in a canyon street. Part I: Simulation program test

Simulation programs may be useful tools for controlling an environmental noise. The computer simulation program PROP11 that enables predictions of the time-average sound level within an urban system is used here. A roadway as a noise source is represented by a sum of the sound exposures due to individual vehicle pass-bys. Different representations of equivalent point sources for various classes of vehicles are allowed including directivity characteristics other than omnidirectional. Propagation throughout an urban system contains multi-reflections from the walls and single and double diffraction at their edges. In this paper, the PROP11 program is used to predict the sound level between opposing façades of buildings in a canyon street. A multi-lane road is assumed to contain two classes of vehicles (light and heavy) ones. The equivalent source representing vehicles is defined by the source power spectrum, its position above the ground and directivity characteristics. The consequences of introducing equivalent source directivity are analyzed.