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 predict traffic noise in urban situations under free flow and traffic light conditions

A computer model is presented for predicting traffic noise indices in built-up situations for free flow traffic conditions and for a flow interrupted by a traffic light. The stream of vehicles is simulated by a given time headway distribution, and a transfer function obtained from a 1 : 100 scale model is used to simulate the specific built-up situation. Different time headway distributions result in only very small discrepancies; even the simple “equally spaced” distribution is adequate for predicting noise indices with high accuracy, unless L₉₀ has to be predicted. In eight built-up situations along a road with freely flowing traffic only minor mutual differences are found when L₁ ? L_eq and L₁₀ ? L_eq are compared, but L₅₀ and L₉₀, and consequently TNI and L_np, show discrepancies of the order of 10 dB(A). If a traffic light is introduced the value of L_eq rises compared with the free flow case, and the values of L₁ and L₁₀ increase, especially at higher traffic intensities, while L₅₀ and L₉₀ decrease. If the noise indices are calculated as a function of the distance along the road to the traffic light increases in L₁, L₁₀ and L_eq are found at about 50 m beyond the traffic light. The principal cause for this increase appears to be the differences between the peak levels of an accelerating car and the sound level at the ultimate speed. More in situ measurements are required to test the accuracy of the model, especially for accelerating vehicles.     

Road traffic noise attenuation by belts of trees

Measurements were made at a number of sites of road traffic noise propagating through belts of trees and bushes and above grass-covered ground, respectively. The belt widths were between 3 and 25 m. The distance from the road to the front of the belts also varied from site to site. The microphones were placed 1·5 m above the ground. A comparison between attenuations obtained, expressed as differences in equivalent constant A-weighted sound pressure levels, L_Aeq, showed no significantly higher attenuation values for propagation through belts of trees than for propagation above grass-covered ground. Only in the frequency range above 2 kHz were attenuations significantly higher through the belts of trees and bushes. The belts of trees selected consisted mainly of deciduous trees and bushes between 5 and 10 years of age. Such types and widths are representative of what could often be used in normal urban situations in an attempt to provide practical noise reduction. According to the results of this investigation, however, these do not significantly reduce L_Aeq 1·5 m above the ground. Planting of belts of trees and bushes between roads and dwellings might influence the environmental quality of residential areas due to nonacoustic factors or reduce nuisance due to spectral changes not affecting L_Aeq. This has not been investigated.     

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.     

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.     

Patterns of behaviour in dwellings exposed to road traffic noise

An inquiry involving a total of 1500 subjects residing in 15 different sites in the conurbations of Lyon and Marseilles was carried out in 1979 with a view to determining the behaviour and attitudes of people with regard to traffic noise. The main purpose of the inquiry was to identify the objective reactions to the traffic noise and to determine how such reactions varied with the noise level, with account taken of the socio-economic characteristics of the subjects (age, income, owner occupier or tenant, etc.). The 08.00–20.00 hour L_eq noise level was measured or calculated for each of the dwellings included in the inquiry. The 00.00–05.00 and 20.00–24.00 hour L_eq values were also derived for each case and a total of nearly 20 000 different noise levels were involved in the analysis of the data for this inquiry. On considering the completed questionaires it was found that the annoyance experienced during the day was more closely correlated with the noise level (r = 0·64) than had been the case with the results of previous studies. In addition to showing how traffic noise can interfere with activities and lead, for example, to the closing of windows to shut out the noise, the inquiry yielded information on the way in which activities affected by noise are transferred to quieter rooms, on the extent to which individual dwellings are sound proofed, on the extent to which occupants are likely to move to another dwelling in order to escape from the noise and finally on some aspects of the effects of noise on health and sleep. Thus it appears that a daytime L_eq value of more than 65 dB(A) gives rise to what can be regarded as forced behavioural responses to the extent that there are significant changes in the normal way of life of the people concerned and such responses give an indication of the magnitude of the social costs that can be attributed to the undesirable effects of traffic noise.     

Estimating health related costs and savings from balcony acoustic design for road traffic noise

A multi-faceted study is conducted with the objective of estimating the potential fiscal savings in annoyance and sleep disturbance related health costs due to providing improved building acoustic design standards. This study uses balcony acoustic treatments in response to road traffic noise as an example. The study area is the State of Queensland in Australia, where regional road traffic noise mapping data is used in conjunction with standard dose–response curves to estimate the population exposure levels. The background and the importance of using the selected road traffic noise indicators are discussed. In order to achieve the objective, correlations between the mapping indicator (L_{A10 (18 hour)}) and the dose response curve indicators (L_den and L_night) are established via analysis on a large database of road traffic noise measurement data. The existing noise exposure of the study area is used to estimate the fiscal reductions in health related costs through the application of simple estimations of costs per person per year per degree of annoyance or sleep disturbance. The results demonstrate that balcony acoustic treatments may provide a significant benefit towards reducing the health related costs of road traffic noise in a community.     

The relationship between traffic noise and insomnia among adult Japanese women

To clarify the relationship between traffic noise and insomnia, the authors conducted a survey and measured the actual sound level of noise in an urban area. Questionnaires were distributed to adult women who lived within 150 m from two major roads and were completed by 648 of the 1286 subjects (50.4%). The area was divided into three zones according to distance from the road (more than 50, 20-50 and 0-19.9 m). Fifty-seven subjects (8.8%) were classified as having insomnia. Average values of sound level at distances of 20, 50, and 100 m from the major road were L_eq 64.7, 57.1, and 51.8 dBA, respectively. Overall, there were no significant differences among the three zones in the prevalence of insomnia and no association between distance from the road and insomnia. However, the result from a sub-data set of the subjects who lived in the areas that showed decreasing noise level as the distance from the main road increased showed that distance from the road was associated with insomnia. This study suggests that researchers should consider the actual traffic situation and its sound level in epidemiological studies about the effects of traffic noise on insomnia.     

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.     

Assessing methodologies for calculating road traffic noise levels in Ireland - Converting CRTN indicators to the EU indicators (Lden, Lnight)

To comply with the EU Noise Directive 2002/49/EC, Member States are required to produce strategic noise maps for designated areas, including mapping road traffic noise from major roads. These maps must be presented using the EU indicators L_den and L_night. However, the most common noise indicator used in Ireland at present is the L_A10,18h indicator arising from the use of the Calculation of Road Traffic Noise (CRTN) prediction method. Therefore, a relationship needs to be established between L_A10,18h and L_den and L_night, separately. In addition to noise mapping these indicators are used for noise abatement purposes, so the proposed relationship must be accurate and robust. In 2002, the UK’s Transport Research Laboratory (TRL) published a paper describing mathematical procedures that could be used to convert values of L_A10 to L_den and L_night. These procedures were then adopted for use in Ireland. This paper examines the suitability of the TRL conversion methods 1 and 3 for use under Irish road conditions. Method 2 was not considered in this study, as it was a methodology not applicable in an Irish scenario. Studies concluded that where hourly traffic data are available, the conversion methodology outlined in TRL Method 1 is robust and reproducible. However, in the absence of hourly traffic data where daily traffic counts are used, the relevant conversion procedures produce variable results for both L_den and L_night when applied to Irish road conditions. To reduce the variability, new conversion procedures were developed, specifically for Irish road conditions.     

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.     

A cellular automata model for urban traffic with multiple roundabouts

Urban transportation with multiple roundabouts is facing significant challenges such as traffic congestion, gridlock and traffic accidents. In order to understand these behaviors, we propose a two-dimensional cellular automata (CA) model, where all streets are two-way, with one lane in each direction. To allow the turning movement, a roundabout is designed for each intersection where four roads meet. The distance between each pair of roundabouts is configured with the parameter K while the turning behavior of drivers is modeled by a parameter γ. To study the impact of these different parameters on the urban traffic, several traffic metrics are considered such as traffic flow, average velocity, accident probability and waiting time at the entrance of roundabout. Our simulation results show that the urban traffic is in free flow state when the vehicle’s density is low enough. However, when the density exceeds a critical density ρ_c, the urban traffic will be in gridlock state whenever γ is nonzero. In the case where $\gamma =0,$ the urban traffic presents a phase transition between free flow and congested state. Furthermore, detailed analysis of the traffic metrics shows that the model parameters (γ, K) have a significant effects on urban traffic dynamics.     

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.     

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.     

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.     

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.