Road Traffic Noise Data Research Articles

Statistical evaluation of road traffic noise in complex sound environment by using fuzzy inference

In order to evaluate road traffic noise in a sound environment, it is necessary to predict the sound levels at evaluation points based on the observations at a reference point. In actual sound environment, road traffic noise shows various types of probability distribution of non-Gaussian distribution and nonstationary property. Furthermore, there potentially exist various nonlinear correlations in addition to the linear correlation between the sound levels at evaluation and reference points. Consequently, the relationship between both points cannot be represented by a simple linear model based on only the linear correlation and lower order statistics. In this study, a complex sound environment difficult to analyze by using usual structural method is considered. By introducing a nonlinear model based on conditional probability distribution with various correlations between the sound levels, and applying fuzzy inference, an evaluation method for road traffic noise is theoretically proposed in a suitable form for the complex sound environment with nonlinear, non-Gaussian and nonstationary properties. The effectiveness of the proposed method is experimentally confirmed by applying it to the observed road traffic noise data in a complex sound environment.

Assessment of Road Traffic Noise Differentials in the Land Uses of Jos, Nigeria

The relationship between land use and traffic has been likened to the chicken and egg relation because of their inter-dependability. For instance, the way land is used affects the generation and character of traffic on the streets and roads corridors. This paper investigated the road traffic noise differentials in the land uses of Jos, Nigeria. Twenty-five (25) road corridors, five (5) in each of the selected land use were purposively chosen to constitute the sample frame for the study. Road traffic noise data were collected at the sampled locations along the selected road corridors using Graiger TL-200 digital Sound Level Meter at 1.5 accuracy level and measured range of 30-130 dB. The road traffic noise data were collected three times a day during peak hour periods, 7:00 - 9:00 am, 12:00 noon - 2:00 pm, and 4:00 - 6 pm from Monday to Saturday. Noise data were measured for 15 minutes at an interval of 6 seconds in each location for six days, making a total of 18 records per location. The RTN data was analyzed using descriptive statistics and regression analyses. The findings of this study revealed that, there was a significant mean difference in RTN levels in the land uses of Jos. This paper therefore, recommends land use dispersal, markets and commodity specification within Jos as a strategy for reducing road traffic noise.

Road traffic noise in European cities: Learnings from a European-wide study on the health impacts of road traffic noise.

Road traffic noise is one of the main environmental risks to health and wellbeing. We aimed to provide an in-depth assessment of available road traffic noise data and to estimate population exposure and health impacts for cities in Europe. We analyzed 724 cities and 25 greater cities in 25 European countries. We retrieved road traffic strategic noise maps delivered under the Environmental Noise Directive (END) or available from local sources. We assessed noise exposure using the 24h day-evening-night noise level indicator (Lden) starting at exposure levels of 55 dB Lden for the adult population aged 20 and over and estimated the health impacts of compliance with the World Health Organization (WHO) recommendation of 53 dB Lden. Two primary health outcomes were assessed: high noise annoyance and Ischemic Heart Disease (IHD), using mortality from IHD causes as indicator. Almost 60 million adults were exposed to road traffic noise levels above 55 dB Lden, 11 million adults were highly annoyed and more than 3600 deaths from IHD could be prevented annually. A considerable number of adults are exposed to road traffic noise levels harmful for health. Efforts to standardize the strategic noise maps and to increase data availability at the city level are needed to provide a more accurate and comprehensive assessment of the health impacts of road traffic noise.

Evaluation of road traffic noise exposure considering differential crowd characteristics

• A road traffic noise evaluation method for heterogeneous crowds is presented. • Heterogeneous crowd distribution, age and acoustic requirements are considered. • A noise response curve (NRC) is established. • The application verified the reasonableness and practicality of the method. The primary objective of this study is to develop an urban traffic noise exposure evaluation method for differential crowd characteristics, which takes crowd distribution, ages and acoustic requirements into consideration. First, road traffic noise data are simulated using a line-source model, and crowd distribution data are obtained by the decomposition of demographic data based on the different building attraction coefficients of the heterogeneous crowd. Then, the noise response curve (NRC) of the heterogeneous crowd is established with the normalization of subjective feelings of respondents and calibrating the response level of each age group in combination. Finally, with the help of the proposed noise evaluation indicators, and considering the noise function requirements (NFR), the traffic noise evaluation of differential crowd characteristics is realized. The method is applied to a typical scenario, and the results and analysis verified the reasonability and practicability of the method in urban traffic noise exposure evaluation.

Impact of road traffic noise on annoyance and preventable mortality in European cities: A health impact assessment.

Road traffic is the main source of environmental noise in European cities and one of the main environmental risks to health and wellbeing. In this study we aimed to provide an in-depth assessment of available road traffic noise data and to estimate population exposure and health impacts for cities in Europe. We conducted the analysis for 724 cities and 25 greater cities in 25 European countries. We retrieved road traffic strategic noise maps delivered under the Environmental Noise Directive (END) or available from local sources. We assessed noise exposure using the 24hday-evening-night noise level indicator (Lden) starting at exposure levels of 55dB Lden - based on data availability - for the adult population aged 20 and over (n=123,966,346). For the adults exposed to noise levels above 55dB Lden we estimated the health impacts of compliance with the World Health Organization (WHO) recommendation of 53dB Lden. Two primary health outcomes were assessed: high noise annoyance and Ischemic Heart Disease (IHD), using mortality from IHD causes as indicator. Exposure Response Functions (ERFs) relating road traffic noise exposure to annoyance and IHD mortality were retrieved from the literature. Uncertainties in input parameters were propagated using Monte Carlo simulations to obtain point estimates and empirical 95% Confidence Intervals (CIs). Lastly, the noise maps were categorized as high, moderate and low quality following a qualitative approach. Strategic noise map data was delivered in three distinct formats (i.e. raster, polygon or polyline) and had distinct noise ranges and levels of categorization. The majority of noise maps (i.e. 83.2%) were considered of moderate or low quality. Based on the data provided, almost 60 million adults were exposed to road traffic noise levels above 55dB Lden, equating to a median of 42% (Interquartile Range (IQR): 31.8-64.8) of the adult population across the analysed cities. We estimated that approximately 11 million adults were highly annoyed by road traffic noise and that 3608 deaths from IHD (95% CI: 843-6266) could be prevented annually with compliance of the WHO recommendation. The proportion of highly annoyed adults by city had a median value of 7.6% (IQR: 5.6-11.8) across the analysed cities, while the number preventable deaths had a median of 2.2 deaths per 100,000 population (IQR: 1.4-3.1). Based on the provided strategic noise maps a considerable number of adults in European cities are exposed to road traffic noise levels harmful for health. Efforts to standardize the strategic noise maps and to increase noise and disease data availability at the city level are needed. These would allow for a more accurate and comprehensive assessment of the health impacts and further help local governments to address the adverse health effects of road traffic noise.

Modelling and Prediction of Road Transportation Noise Pollution in Some Capital Cities in Eastern Nigeria by Use of Artificial Neural Network

The study attempts to model and predict road transportation noise pollution in five capital cities in Eastern Nigeria. The capital cities are Calabar, Uyo, Umuahia, Owerri and Port Harcourt. Feed-forward neural network (FNN) with negative back-propagation algorithm was used to do this. The software used was NeuroXL. The ability of this software to handle multiple non-linear relationships makes it ideall y suited for this work. The input data used were total road traffic volume, road traffic mix, road traffic noise pollution response data, and distances from road centre-line to measurement points. The output data used was A-weighted energy mean sound level (L A eq). Models based on this negative back- propagation neural network were trained, validated and tested using data collected. The performance of the model was tested by an error measure, root mean square error (RMSE). RMSE is low as expected, ranges from 1.007 - 1.814, showing that the model is good for the prediction of road traffic noise data. The correlation between observed and predicted noise levels (LAeq) was also obtained, and ranges between +0.757 to +0.974, showing that there is no significant difference between observed and predicted noise levels, thereby, proving the model accurate and reliable. Keywords : Artificial neural network, back-propagation, road traffic noise modeling, road traffic noise prediction, NeuroXL software DOI: 10.7176/JEES/11-10-06 Publication date: October 31 st 2021

Classification of Urban Road Traffic Noise based on Sound Energy and Eventfulness Indicators

Noise energetic indicators, like Lden, show good correlations with long term annoyance, but should be supplemented by other parameters describing the sound fluctuations, which are very common in urban areas and negatively impact noise annoyance. Thus, in this paper, the hourly values of continuous equivalent level LAeqh and the intermittency ratio (IR) were both considered to describe the urban road traffic noise, monitored in 90 sites in the city of Milan and covering different types of road, from motorways to local roads. The noise data have been processed by clustering methods to detect similarities and to figure out a criterion to classify the urban sites taking into account both equivalent noise levels and road traffic noise events. Two clusters were obtained and, considering the cluster membership of each site, the decimal logarithm of the day-time (06:00–22:00) traffic flow was used to associate each new road with the clusters. In particular, roads with average day-time hourly traffic flow ≥1900 vehicles/hour were associated with the cluster with high traffic flow. The described methodology could be fruitfully applied on road traffic noise data in other cities.

Application of the Intermittency Ratio Metric for the Classification of Urban Sites Based on Road Traffic Noise Events.

Human hearing adapts to steady signals, but remains very sensitive to fluctuations as well as to prominent, salient noise events. The higher these fluctuations are, the more annoying a sound is possibly perceived. To quantify these fluctuations, descriptors have been proposed in the literature and, among these, the intermittency ratio (IR) has been formulated to quantify the eventfulness of an exposure from transportation noise. This paper deals with the application of IR to urban road traffic noise data, collected in terms of 1 s A-weighted sound pressure level (SPL), without being attended, monitored continuously for 24 h in 90 sites in the city of Milan. IR was computed on each hourly data of the 251 time series available (lasting 24 h each), including different types of roads, from motorways to local roads with low traffic flow. The obtained hourly IR values have been processed by clustering methods to extract the most significant temporal pattern features of IR in order to figure out a criterion to classify the urban sites taking into account road traffic noise events, which potentially increase annoyance. Two clusters have been obtained and a “non-acoustic” parameter x, determined by combination of the traffic flow rate in three hourly intervals, has allowed to associate each site with the cluster membership. The described methodology could be fruitfully applied on road traffic noise data in other cities. Moreover, to have a more detailed characterization of noise exposure, IR, describing SPL short-term temporal variations, has proved to be a useful supplementary metric accompanying LAeq, which is limited to measure the energy content of the noise exposure.

An Empirical Model of Road Traffic Noise on Heterogeneous Traffic Situation

The motorcycle domination on heterogeneous traffic situation in many cities in developing countries including Indonesia leads to the decreasing of environment qualities such noise pollution. Regarding the road traffic noise (RTN) pollution, this paper attempts to develop an empirical model for a RTN prediction model. The model based on a motorcycle unit as reference unit to consider flow rate of the road traffic which dominated by motorcycles. The study collected the RTN data such volume of each vehicle types, i.e., motorcycle; light vehicle; and high vehicle, and the noise level on the forty arterial roads in Makassar, Indonesia. The survey methods based on the traffic count method and the measurement noise level using a video camera and a sound level meter, respectively. We collected data during ten minutes of each one-hour period of each road. The empirical relationship models between the noise level and the traffic volume based on the motorcycle unit were developed using various types of regression models. The results showed that the polynomial model is more significant than the other models. We expected that the model provides a basic RTN prediction model in order to simulate some measures of the traffic management system in reducing the RTN level in Makassar City.

The Effect of Road Traffic Noise on Psychological Health Disorders of School Children at Cipinang Muara Elementary School, Jatinegara Sub District, East Jakarta City, DKI Jakarta Province, 2005

Normal 0 false false false EN-US X-NONE X-NONE MicrosoftInternetExplorer4 The traffic noise is the main issue of the community who live in urban area because it may cause an adverse human health and psychological effects. The purpose of this study is to describe the effect of road traffic noise to psychological health disorders on school children of Cipinang Muara elementary school at Jatinegara Sub District, and other risk factors such as distance, length of exposure, learning periode in school, and age. This research applied a case-control study with sample population of elementary school students from grade 4 to 6. Total samples were 240 children, including 80 cases and 160 controls. Data were collected through a multistage of random sampling. Data analysis used a computer program of univariate, bivariate and multivariate. Road traffic noise data measure in the classroom using noise logging dosimeter Q-400/500. Bivariate analysis (Chis-Square) and multiple logistic regression analysis are applied in the analysis. Bivariate analysis showed that there were a significantly effect of traffic noise, distance of seat, and length of exposure towards psychological health problems. On the other side, the length of school period and age of respondents did not have any significantly effect to the psychological health problems on the elementary school students. Multivariate analysis indicated that the elementary school students exposed to traffic noise more than 61.8 dBLAeq   in the school area having a risk of psychological health problem 10.9 higher than those who were exposed to traffic noise less than 61.8 dBLAeq,   a long with the distance variable and the length of noice exposure. It is required to socialize and apply the regulation on noise control and its impact in a consistently manner. Also, it is necessary to conduct health promotion and integrated monitoring both with inter-sector and inter-program. At last, to ensure the presence of inferential causal temporality, it is required to conduct further study with design of cohort or experimental study. This includes the increase of variable number and location of study in order to describe the real condition.   

A precise estimation method of probability distribution based on roughly observed data with quantized level and its application to environmental sound noise measurement.

The noise fluctuation is very often measured in a quantized level form at a discrete time interval. By paying attention to this quantization procedure of the actual noise measurement, in this paper, a precise estimation method for the probability distribution form is proposed by using the roughly observed data with quantized levels. That is, we first introduce theoretically a general statistical orthonormal expression of the probability density function for the original noise level fluctuation of continuous level type before passing through the level quantization measurement mechanism. Based on this quantization mechanism and the averaging operation of statistical information, we propose a reasonable estimation method of the distribution parameters in the above statistical expression by using the statistical information on the roughly observed data. The original probability distribution form of the continuous noise level can be precisely estimated by substituting the estimated distribution parameters into the introduced probability expression of general type. On the basis of this estimation theory, a precise evaluation method for the Lx and Leq noise evaluation indices is proposed. The effectiveness of the proposed method is confirmed experimentally too by applying it to first the simulation experiment and then the actual road traffic noise data.

A statistical study for determining the minimum sample size for [formula omitted] estimation of periodic nonstationary random noise

A statistical evaluation method for the accuracy of equivalent sound level measurement is proposed theoretically from the viewpoint of reliability. The confidence interval of Leq caused by the finiteness of the sample size is discussed, in the case when the equivalent sound level of a periodic nonstationary random noise of arbitrary probability distribution type is experimentally estimated by using the usual sound level meter and sampling method. Next, a practical method for determining the minimum sample size to obtain the Leq value with a certain confidence coefficient is given by considering several simple cases with the aid of a digital simulation technique. Finally, the theoretical evaluation method is applied to nonstationary road traffic noise data controlled by the traffic signals.

A practical method of predicting noise produced by road traffic controlled by traffic signals

A new expression of the probability density function for periodic nonstationary noise level fluctuation is first derived in a case where the road traffic flow is controlled by traffic signals. Next, a new practical procedure for estimating and/or predicting the probability distribution form of road traffic noise, on the basis of the simplified time patterns of the statistics on the noise level or number of moving vehicles, is proposed as an application of the above theory. By using the actual road traffic noise data observed in Hiroshima City, it was experimentally confirmed that the theoretical method was valid and effective as a prediction technique.

A statistical analysis for estimating the noise level probability distribution from Leq and Lx noise levels.

In this report, a statistical method for estimating generally the noise level probability distribution from the observed values of Leq and specific Lx noise levels is proposed theoretically by introducing newly a statistical orthonormal expansion expression on an intensity scale taking the lognormal distribution as the first expansion term. The effectiveness of the proposed method is experimentally confirmed by applying it to the actual road traffic noise data through the comparisons of estimation accuracy between the proposed method and the previous one based on the statistical Laguerre expansion expression.

A new estimation method of noise evaluation index, Leq, by use of the statistical information on the arbitrary type noise level fluctuation.

In this report, the equivalent expression for the mean value of arbitrary non-linear type state variable with respect to the arbitrary non-Gaussian random phenomena is first derived theoretically by use of the expectation operation based on only the standard Gaussian distribution function. Next, based on this convenient expression, an estimation method of the noise evaluation index, Le, is newly derived in a hierarchical form containing the well-known usual estimation method derived under the assumption of the standard Gaussian distribution as the first expansion term. That is, this method is generally applicable to any kind of random phenomena by grasping the statistical information on the noise level fluctuation. Finally, the validity of the proposed method is experimentally confirmed too by applying it to the actual road traffic noise data.

A prediction method for road traffic noise generated from arbitrary non-poisson type traffic flow based on an approach equivalent to that for a standard poisson type traffic flow

In order to establish a prediction method for road traffic noise generated from actual traffic flow of an arbitrary non-Poisson type, a new approach equivalent to that for an idealized Poisson type traffic flow is proposed for practical use. This prediction method is able to treat any kind of road traffic noise fluctuation generated from actual non-Poisson type traffic flow, once information has been obtained on the wave form of the level time pattern observed when one vehicle passes directly in front of an observation point. The validity of the proposed prediction method has been experimentally confirmed by applying it to actually observed road traffic noise data.

A design for a general digital filter for state estimation of an arbitrary stochastic sound system.

This article describes a new attempt at the design of a general digital filter for the state estimation of a nonstationary nonlinear stochastic sound system. A recursive algorithm for estimating the higher-order statistics of arbitrary-function type, mean, and variance is obtained by introducing a new expansion form of Bayes' theorem. Further, the state probability density function (PDF) can also be estimated in a unified form of orthogonal or nonorthogonal series expansions by using these estimates. This method is widely applicable for cases where the random-noise fluctuation is non-Gaussian. The estimation algorithm proposed in this article agrees completely with a well-known Kalman filtering theory [J. Basic Eng. 82, 35-45 (1960); Kalman and Buchy, J. Basic Eng. 83, 95-108 (1961)], as a simplified special case when the stochastic system is of linear type with Gaussian random excitation. The validity and effectiveness of the proposed theory were confirmed experimentally by applying it to actually observed room acoustic data and road-traffic noise data.

A prediction theory of random level distribution based on a generalized difference type of Fokker-Planck equation and its application to environmental noise and vibration, II: Experimental study

In a companion paper [1], a procedure for solving the short time prediction problem in terms of the transition probability distribution has been theoretically derived, for discrete time-sampled data. Explicit algorithms for estimating the non-stationary moment statistics of arbitrary order also have been derived, based on a generalized difference equation of Fokker-Planck type for the conditional probability distributed function, which is central to the theory. In this paper, evidence for the validity and effectiveness of the proposed method is presented, as obtained not only by means of digital simulation but also by using road traffic noise data obtained experimentally in Hiroshima. For several non-stationary random processes simulated by means of random numbers, the theoretical and experimental conditional probability functions are compared. For non-stationary road traffic noise data the theoretically predicted and experimentally determined confidence intervals are compared; in these comparisons several types of conditional probability function and various values of weighting parameter are used in the algorithm. All of the theoretical results show good agreement with the experimental results.

State prediction for environmental noise system by a generalized adaptive function model

This paper describes a new attempt at predicting the fluctuations of an environmental noise system by use of adaptive functions. Principally, some kinds of correlations (in some cases, in the form of simple inertia) can be actually found between the recorded past data and the future values. In this paper, the basic correlative relationship of this kind is expressed universally with the use of newly introduced adaptive functions of both the linear, and nonlinear types. In prediction algorithms, discrete or continuous adaptive functions of orthogonal and/or nonorthogonal types are employed to meet the actual observation mechanism and to get the effective data processing. Finally, the effectiveness of the proposed method has been confirmed by computer simulation and application to actually obtained road traffic noise data.

A trial of generalizing discrete and continuous type probability expressions due to Kurze for road traffic noise.

Until the present, various expressions of a probability distribution function, which play an important role in the evaluation of road traffic noise, have been presented. We firstly derive a new universal expansion expression of multivariate joint probability distribution with both discrete and continuous random variables, based on the Lebesgue's decomposition theorem. We show that our expressions, as special cases, agree with Kurze's probability expressions introduced for the road traffic noise such as “semiinfinite source line, ” “short source line” and “very light traffic.” As one example, after choosing a combination form of Gaussian and gamma distribution functions as the first term of our expansion expression, we confirm experimentally the validity and the effectiveness of our theory not only by means of a digital simulation technique but also by applying to actually observed road traffic noise data.