Community reactions to noise from freely flowing traffic,motorway traffic and congested traffic flow

Responses to a social survey were collected from residents of 27 different sites in the Greater Manchester area. The sites were exposed to noise emanating from (a) freely flowing traffic on urban roads, or (b) motorway traffic, or (c) congested or disturbed traffic flow on urban roads. Existing noise indices were tested on this general sample of traffic flow situations to determine their efficacy in the prediction of community dissatisfaction to traffic noise. No existing index could handle adequately all the traffic flow conditions. When the indices were combined with measures of traffic volume flow between midnight and 6 a.m. a marked improvement in their predictive capability was noted. In particular, extended indices based on L₁₀ (18 hour) and L_eq appeared to be useful predictors of community response to all of the traffic flow situations studied in this project.     

The differing annoyance levels of rail and road traffic noise

The results of a study on the relative annoyance by rail or road traffic noise in urban and rural areas are reported. Fourteen areas with rail and road traffic noise with differing levels of loudness (L_eq) were investigated. The annoyance was assessed by means of a questionnaire. The analysis of the relationship between annoyance and L_eq—performed separately for rail and road traffic noise—shows that the same amount of annoyance is reached for railway traffic noise at L_eq levels 4–5 dB(A) higher than for road traffic noise (railway/traffic noise “bonus”). The estimation for the difference values vary for the different variables of annoyance. Furthermore, the difference levels tend to be higher in urban than in rural areas.     

Evaluation and analysis of the environmental noise of Messina, Italy

In this paper, the results of a study on the environmental noise pollution of the city of Messina (Italy) are presented. The investigation has included a preliminary classification of the territory in six acoustically homogeneous areas according to Italian noise regulations. On the basis of the resultant acoustic zoning 35 sites were selected for an experimental survey. This last has been carried out by extensive measurements of the main indexes for noise pollution (L_eq, L₁, L₁₀, L₅₀, L₉₀, L₉₉) and of the traffic flow and composition. Results indicate that: (a) main roads of Messina are overloaded by traffic flow during day-time period and that in all the examined sites daily average sound levels due to road traffic exceed environmental standards by about 10 dBA; (b) environmental noise exhibits a certain degree of spatial variance resulting primarily from the peculiar geo-morphological structure of the town and from the transport infrastructure and (c) more than 25% of residents should be highly disturbed by road traffic noise.     

Detection of extraneous abnormal sounds affecting road traffic noise by use of a necessary condition method

When measuring and/or recording road traffic sound levels during a long time interval, extraneous abnormal sounds will inevitably affect the road traffic sound levels of interest. Such sounds include those produced by horns, sirens, animals, construction sites, and the like. The detection and elimination of such extraneous sound requires much time and effort, but are necessary if noise indices such as L_eq, L_max, and L₁₀ are to be properly estimated. This paper proposes a practical detection method of these extraneous interfering sounds by deriving a necessary condition that road traffic sound levels must satisfy. The necessary condition provides an easy method of identifying sound levels not satisfying the condition, and distinguishes them as extraneous abnormal sounds, even in a large volume of observed data. The validity and usefulness of this method are confirmed by application to actually observed data.     

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.     

A computer model to assess and predict road transport noise in built-up areas

A computer model is presented for predicting road transport noise in urban and suburban areas under non-free flowing traffic conditions. The model utilises empirical expressions developed from field studies made at 204 sites (2448 30-min samples) in Bath. Traffic flow, speed and composition, percentage of heavy and medium vehicles, distance from surrounding building façades, and distance from various junctions are taken into account in the model. Other parameters such as classification of land use, kind of junctions and characteristics of traffic are also considered. The input variables were deliberately selected to facilitate the eventual use of the model for design and land-use planning purposes. A good level of agreement has been achieved between measured and predicted values. L₁₀, L₅₀, L₉₀ and L_eq dB(A) were employed.     

The prediction of traffic noise using a scale model

This paper describes the development of means of using a scale model of a road and its surrounding urban environment to predict L_eq, L₁₀ and other measures of traffic noise. The model described is that of the Centre Scientifique et Technique du Batiment, Grenoble, France. The problems involved in the development include allowance for relative sound absorption between real life and the model situation, the constraints on the accuracy of the results due to noise source variations on the model and the effects of the finite size of the model.     

Predicting community response to road traffic noise

Several problems related to identifying the potential future impacts of road traffic noise on residential areas require for their solution the ability to predict subjective response to road traffic noise. The main difficulty in using existing regression equations relating subjective response and traffic noise for such predictions is that there has been no reported test of whether or not the data used meet the assumptions of the regression model. If the assumptions are not met, the replicability of the results and hence the reliability of the predictions, as measured by confidence limits or standard errors, cannot be established, because such inference rests on the statistical assumptions. Investigation of the data collected in a traffic noise impact study in southern Ontario indicates that such data meet the assumptions necessary for inference from regression analysis. Consequently, valid estimates of the reliability of predictive equations derived from regression analysis can be made using the standard errors of the regression parameters. This stronger inferential base also permits comparisons among different noise measures oramong different response measures. It appears that several noise measures (L_eq, L₁₀, L_dn) are all equally good predictors of subjective response. It also appears that different indicators of subjective response yield significantly different regression parameters.     

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.     

Prediction of the attenuation of road traffic noise with distance

A method is described of calculating the sound pressure level received from single, representative light and heavy vehicles after propagation over terrain composed of various combinations of hard ground and grass-land. These results are then used to derive correction contours for the attenuation with distance of the L_eq level received from streams of each class of vehicle. The results apply to conditions where the boundary between the soft and hard areas is parallel to the traffic stream and the soft ground is on the receiver side. Various positions of the boundary are considered. A simple prediction method for L_eq is developed, incorporating the distance corrections. Similar calculations are carried out for the attenuation with distance of the L₁₀ noise index for a representative stream of vehicles. Based on these results simple prediction equations for the excess attenuation are proposed in terms of the receiver position and the proportion of soft ground below the propagation path.     

Techniques for the investigation of road traffic noise in regions of restricted flow by the use of digital computer simulation methods

Computer methods of calculating and predicting the noise from road traffic operating in restricted flow conditions are discussed. A method of calculating the noise from road traffic as a function of the manoeuvring parameters by means of a Monte Carlo digital computer simulation model is briefly described. The model is used in deriving correction contours for single streams of traffic which enable free flow L₁₀ levels to be modified to allow for a flow restriction. Flow restrictions of the type encountered at traffic signals, priority intersections and pelican crossings are considered. The contours cover a stretch of road 600 m long and a distance of 60 m from the kerb line and in general show a reduction in L₁₀ level in transferring from the free to the restricted flow situation. A method of applying the contours as a modification of the United Kingdom Department of the Environment prediction method for L₁₀ is proposed and compared with experimental results. Computer simulation models of complete road intersections are discussed. Two types of intersection controls are considered, the traffic signal control and the roundabout. The results of the two types of simulation are compared and the L₁₀ level adjacent to the accelerating traffic streams is generally found to be greater than that adjacent to decelerating streams. Experimental results for both types of intersection are compared with simulation runs in which the observed traffic parameters are used.     

A study of noise in CNG driven modes of transport in Delhi

Measurements of noise and its spectral characteristics were made inside various types of transport running on Compressed Natural Gas (CNG) fuel in Delhi. Noise indices L₁₀, L₅₀, L₉₀ and L_eq were estimated from the measured noise levels for vehicles in neutral gear, slow speed (speed ?20 km/h) and under free flow (speed ?30 km/h) conditions. It is found that background levels, when averaged over all speeds, are maximum in Rural Transport Vehicles (RTV) followed by Buses, Auto-rickshaws and Taxis. With increase in the speed, noise levels are appreciably enhanced except in the case of auto-rickshaws where the increase is moderate. The spectral distributions of noise inside vehicles obtained at 1-octave band frequencies, show a rather similar nature. The study reveals significantly lower noise levels inside CNG driven public modes of transport compared to those found in an earlier survey inside diesel and petrol driven vehicles.     

Long term sleep disturbance due to traffic noise

This contribution to the evaluation of the effects of traffic noise on sleep disturbance is focused on the responses of people living near a main road. Experiments were carried out in the homes of subjects who had habitually been exposed to noise for periods of more than four years. The chronic changes in overall sleep patterns and the temporary sleep responses to particular noise events caused by traffic are demonstrated. Young people show mainly stage 3 and 4 deficits whilst older people show REM sleep deficits. The cardiac response to noise during sleep was also examined. These results highlight that both long term average and peak levels are important in assessing sleep disturbance. The threshold levels, measured inside the bedroom and above which sleep quality starts to become impaired, are 37 L_eq(A) and 45 dB (A)L_{p max}, respectively. For the type of traffic studied these two levels are coherent and it is therefore possible that a single noise index, L_eq(A), is sufficient to scale sleep disturbance.     

A multiple regression model for urban traffic noise in Hong Kong

This article describes the roadside traffic noise surveys conducted in heavily built-up urban areas in Hong Kong. Noise measurements were carried out along 18 major roads in 1999. The measurement data included L10, L50, L90, Leq, Lmax, the number of light vehicles, the number of heavy vehicles, the total traffic flow, and the average speed of vehicles. Statistical analysis using the analysis of variance (ANOVA) and Tukey test (p<0.05) reveals that the total traffic flow and the number of heavy vehicles are the most significant factors of urban traffic noise. Multiple regression was used to derive a set of empirical formulas for predicting L10 noise level due to road traffic. The accuracy of these empirical formulas is quantified and compared to that of another widely used prediction model in Hong Kong--the Calculation of Road Traffic Noise. The applicability of the selected multiple regression model is validated by the noise measurements performed in the winter of 2000.     

Road traffic sound level distributions

A microprocessor-controlled instrument has been used to form a traffic noise level histogram with a resolution better than 0·1 dB per channel. The instrument calculates the mean, standard deviation, skewness and kurtosis of the distribution, along with L_N and L_eq values. The results of over 200 measurements, of 400 s duration, are shown to be in disagreement with predictions based on the commonly assumed Gaussian distribution. Skewness values ranging from +1 to ?1 have been observed, while kurtosis can exceed 4. Measurements taken near freely flowing, pulsed and banked traffic have been used to describe the “typical” distribution shape, it being observed that banked traffic noise has markedly different characteristics from other types of traffic. Simultaneous measurements taken on each side of the road have been related to the position of the traffic on the road and these data have led to a simple model for estimating the distribution shape and statistical parameters.     

Investigation of the dose-response relationship for road traffic noise in Assiut, Egypt

A field study has been carried out in urban Assiut city, Egypt. The goals of this study are: (1) to carry out measurements to evaluate road traffic noise levels, (2) to determine if these levels exceeds permissible levels, (3) to examine people’s attitudes towards road traffic noise, (4) to ascertain the relationship between road traffic noise levels and degree of annoyance. The measurements indicate that traffic noise noise levels are higher than those set by Egyptian noise standards and policy to protect public health and welfare in residential areas: equivalent continuous A - weighted sound pressure levels (L_A eq) = 80 dB and higher were recorded, while maximum permissible level is 65 dB. There is a strong relationship between road traffic noise levels and percentage of highly annoyed respondents. Higher road traffic noise levels mean that the percentage of respondents who feel highly annoyed is also increased.     

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.     

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 prediction for urban traffic conditions—related to measurements in the Sydney Metropolitan Area

A method for the prediction of the noise levels from road traffic, developed at the National Physical Laboratory (NPL), has been used for comparison with measured values of road traffic noise in the Sydney Metropolitan Area. As the comparison was not good, multiple regression analysis, using the basic format of the NPL formula, was performed. A better comparison was obtained from a formula in which the term relating to the average road speed of the vehicles was excluded. This new formula permits a simple graphical representation for the determination of $\text{L}{}_{\mathrm{<mtext>10</mtext>}}$ for urban traffic. A similar formula and graph for the determination of $\text{L}{}_{\mathrm{<mtext>eq</mtext>}}$ is also provided.     

A method of traffic noise prognosis

This paper describes a simple method for the calculation of changes in noise levels generated by the vehicle population of a country as a whole in future time related to present population. The changes of the total number of vehicles, the introduction of quieter vehicles and the condition of wear of the running stock are taken into account in the model and the change in L_eq level is used as the output parameter. The calculated changes in L_eq values are about the same as those of L₁₀. The application examples of the model show that this simple method seems to be helpful for decision makers. The examples also allow conclusions for noise control strategy to be developed.