A traffic noise model for road intersections in the city of Cartagena de Indias,Colombia

Road traffic noise models are fundamental tools for designing and implementing appropriate prevention plans to minimize and control noise levels in urban areas. The objective of this study is to develop a traffic noise model to simulate the average equivalent sound pressure level at road intersections based on traffic flow and site characteristics, in the city of Cartagena de Indias (Cartagena), Colombia. Motorcycles are included as an additional vehicle category since they represent more than 30% of the total traffic flow and a distinctive source of noise that needs to be characterized. Noise measurements are collected using a sound level meter Type II. The data analysis leads to the development of noise maps and a general mathematical model for the city of Cartagena, Colombia, which correlates the sound levels as a function of vehicle flow within road intersections. The highest noise levels were 79.7 dB(A) for the road intersection María Auxiliadora during the week (business days) and 77.7 dB(A) for the road intersection India Catalina during weekends (non-business days). Although traffic and noise are naturally related, the intersections with higher vehicle flow did not have the highest noise levels. The roadway noise for these intersections in the city of Cartagena exceeds current limit standards. The roadway noise model is able to satisfactorily predict noise emissions for road intersections in the city of Cartagena, Colombia.     

Urban road traffic noise spatiotemporal distribution mapping using multisource data

Many residents are disturbed by road traffic noise which needs to be controlled and managed. The noise map is a helpful and important tool for noise management and acoustical planning in urban areas. However, the static noise map is not sufficient for evaluating noise annoyance at different temporal periods. It is necessary to develop the dynamic noise map or the noise spatiotemporal distribution. In this study, a method about urban road traffic noise spatiotemporal distribution mapping is proposed to obtain the representative road traffic noise maps of different periods. This method relies on the proposed noise spatiotemporal distribution model with two time-dependent variables - traffic density and traffic speed, and the spatiotemporal characteristics derived from multisource data. There are three steps in the method. First, the urban road traffic noise spatiotemporal distribution model is derived from the law of sound propagation. Then, the temporal characteristics are extracted from traffic flow detecting data and E-map road segment speed data by the outlier detection analysis. Finally, the noise distributions corresponding to different periods are calculated by an efficient algorithm which can save 90% above of the computing time. Moreover, a validation experiment was conducted to evaluate the accuracy of the proposed method. There is only 2.26-dB[A] mean absolute error that is within an acceptable range, which shows that the method is effective.     

The effect of road traffic noise on the prices of residential property – A case study of the polish city of Olsztyn

The key factors that determine the prices of real estate are location, technical standard of property as well as the local environment. In urban agglomerations, road traffic noise has a considerable impact on the purchasing decisions made by apartment buyers. This is a widespread problem in Central-Eastern Europe. The main objective of this study was to verify the working hypothesis that apartment prices are correlated with traffic noise levels in Olsztyn, the capital city of the Region of Warmia and Mazury in north-eastern Poland.The study was carried out in four principal stages. Firstly, traffic noise intensity was determined for apartments (objects of real estate transactions concluded in 2013), based on an acoustic map for the city of Olsztyn. The map was developed in line with the provisions of Directive 2002/49/EC of the European Parliament and of the Council of 25 June 2002 relating to the assessment and management of environmental noise. Secondly, the values of the Noise Depreciation Sensitivity Index (NDSI) were calculated. NDSI determines the percentage change in property prices per dB increase in noise levels. The distribution of unit prices of apartments was mapped relative to noise levels, and the relationships between the analyzed variables were assessed. Thirdly, linear correlations between the unit prices of apartments and noise levels were analyzed. The strength and direction of relationships between the analyzed parameters were determined based on Pearson’s correlation coefficient. In the last stage, the distribution of the unit prices of apartments was mapped by ordinary kriging, a geostatistical estimation method. The research hypothesis was confirmed by comparing the spatial distribution of traffic noise levels measured in stage 1 with the spatial distribution of apartment prices.     

A methodology to control urban traffic noise under the constraint of environmental capacity: A case study of a double-decision optimization model

This paper presents a novel methodology to control urban traffic noise under the constraint of environmental capacity. Considering the upper limits of noise control zones as the major bottleneck to control the maximum traffic flow is a new idea. The urban road network traffic is the mutual or joint behavior of public self-selection and management decisions, so is a typical double decision optimization problem.The proposed methodology incorporates theoretically model specifications. Traffic noise calculation model and traffic assignment model for O–D matrix are integrated based on bi-level programming method which follows an iterated process to obtain the optimal solution. The upper level resolves the question of how to sustain the maximum traffic flow with noise capacity threshold in a feasible road network. The user equilibrium method is adopted in the lower layer to resolve the O–D traffic assignment.The methodology has been applied to study area of QingDao, China. In this illustrative case, the noise pollution level values of optimal solution could satisfy the urban environmental noise capacity constraints. Moreover, the optimal solution was intelligently adjusted rather than simply reducing the value below a certain threshold. The results indicate that the proposed methodology is feasible and effective, and it can provide a reference for a sustainable development and noise control management of the urban traffic.     

Effects of a hovering unmanned aerial vehicle on urban soundscapes perception

Several industry leaders and governmental agencies are currently investigating the use of Unmanned Aerial Vehicles (UAVs), or ‘drones’ as commonly known, for an ever-growing number of applications from blue light services to parcel delivery. For the specific case of the delivery sector, drones can alleviate road space usage and also lead to reductions in CO₂ and air pollution emissions, compared to traditional diesel-powered vehicles. However, due to their unconventional acoustic characteristics and operational manoeuvres, it is uncertain how communities will respond to drone operations. Noise has been suggested as a major barrier to public acceptance of drone operations in urban areas. In this paper, a series of audio-visual scenarios were created to investigate the effects of drone noise on the reported loudness, annoyance and pleasantness of seven different types of urban soundscapes. In soundscapes highly impacted by road traffic noise, the presence of drone noise lead to small changes in the perceived loudness, annoyance and pleasantness. In soundscapes with reduced road traffic noise, the participants reported a significantly higher perceived loudness and annoyance and a lower pleasantness with the presence of the same drone noise. For instance, the reported annoyance increased from 2.3 ± 0.8 (without drone noise) to 6.8 ± 0.3 (with drone noise), in an 11-point scale (0-not at all, 10-extremely). Based on these results, the concentration of drone operations along flight paths through busy roads might aid in the mitigation of the overall community noise impact caused by drones.     

The cumulative effect of nuisances from road transportation in residential sectors on the Island of Montreal – Identification of the most exposed groups and areas

Air pollution and road traffic noise are considered to be the two most important nuisances that could negatively affect the quality of life. A prolonged exposure to high concentrations of these pollutants could conduct to various health problems. Studies in environmental equity have often considered these nuisances individually whenever it comes from the same source. The main objective of this paper is to determine if the 15 years of age, those aged 65 and over, visible minorities and low income individuals located in a portion of the Island of Montreal are overrepresented in city blocks characterized by having among the highest levels of transportation-related air pollutants (i.e., ambient concentrations of NO₂ and road traffic noise in decibels (dB(A)). The results show that low-income individuals and, to a lesser extent, visible minorities, are significantly overrepresented in city blocks characterized by the higher levels of NO₂ and road traffic noise in dB(A). Multinomial logistic regression analysis confirms these results, and also shows that young people under 15 years are under-represented in the most polluted areas. However, contrary to the previous bivariate results, people aged 65 and over are negatively and significantly associated with the likelihood of their living in a city block located in an advantaged area after controlling for the independent effects of the other explanatory variables. Moreover, visible minorities are significantly overrepresented in advantaged areas. Considering the observed results, some solutions are identified to reduce road traffic noise and air pollution in the city blocks localized near major traffic arteries.     

A new approach to evaluating on-road public transport priority projects: balancing the demand for limited road-space

Despite widespread growth in on-road public transport priority schemes, road management authorities have few tools to evaluate the impacts of these schemes on all road users. This paper describes a methodology developed in Melbourne, Australia to assist the road management authority, VicRoads, evaluate trade-offs in the use of its limited road-space for new bus and tram priority projects. The approach employs traffic micro-simulation modelling to assess road-space re-allocation impacts, travel behaviour modelling to assess changes in travel patterns and a social cost benefit framework to evaluate impacts. The evaluation considers a comprehensive range of impacts including the environmental benefits of improved public transport services. Impacts on public transport reliability improvements are also considered. Although improved bus and tram reliability is a major rationale for traffic priority its use in previous evaluations is rare. The paper critiques previous approaches, describes the proposed method and explores some of the results found in its application. A major finding is that despite a more comprehensive approach to measuring the benefits of bus and tram priority, road-space reallocation is difficult to economically justify in road networks where public transport usage is low and car usage high. Strategies involving the balanced deployment of bus and tram priority measures where the allocation of time and space to PT minimises negative traffic impacts is shown to improve the overall management of road-space. A discussion of the approach is also provided including suggestions for further methodology development.

Options for reducing noise from roads and railway lines

The fundamental noise generation mechanisms of road and rail vehicles are discussed with attention to noise abatement measures. Based on an evaluation of publicly available tire noise data and the European road traffic noise emission model CNOSSOS, it is shown that on the road side there is a significant noise reduction potential in the usage of low-noise tires. From a three months measurement campaign a noise model was derived to predict the maximal sound pressure level of heavy duty vehicles during a pass-by in 7.5 m distance with the parameters vehicle speed and number of axles. With help of recently published information about external costs caused by heavy duty vehicles and the noise prediction tool, a model was developed to derive a money equivalent that can be used as a bonus/malus in a heavy duty vehicle fee. As a measure at the infrastructure, the installation of low-noise pavements is an effective, durable and economically attractive measure. Recent experiences with different technologies from all over the world are compiled and evaluated. On the rail side, an overview of the possible noise reduction strategies is given, followed by a discussion of the current policy and legislation in the EU and on the national level of different European countries.     

公路噪声预测达标距离超出评价范围现象的探讨

文章根据公路项目环保竣工验收的交通噪声监测结果,通过理论值与实测值的比较,分析了典型路段交通噪声预测达标距离超出评价范围现象产生的原因,并提出了相应的解决措施及建议,为公路建设项目环境影响评价工作提供参考。     

Modeling traffic noise in a mountainous city using artificial neural networks and gradient correction

Different regions have established traffic noise prediction models to adapt to their particular environmental characteristics. This paper aimed to develop a traffic noise prediction model for mountainous cities. In China, the traffic noise prediction model HJ 2.4-2009, which itself is based on the sound pressure level corrected for roadway gradients (RGs), has been receiving widespread acceptance. On the basis of the model in HJ 2.4-2009, the RG correction coefficient was proposed to modify the original model and a per-vehicle noise prediction model was built using a multilayer feedforward artificial neural network (ANN) model. The data collected from a municipal road of a hilly city, Chongqing, was used to train and validate the ANN model. The predictor variables comprised the per-vehicle noise value, vehicle type, vehicle velocity, and roadway gradient. The results showed that the modified HJ 2.4-2009 model incorporating the gradient correction coefficient achieved a significantly higher R² for mountainous cities than the original model. Besides, the ANN-based noise prediction model achieved considerable accuracy improvement over the empirical predictive equations.     

A combined assessment of air and noise pollution on the High Line,New York City

The High Line is an elevated public park in New York City, transformed from an unused freight rail line. Pedestrians walking through Manhattan’s West Side can walk either on the High Line or on a footpath below. Using Manhattan as a laboratory, this paper offers a combined assessment of noise and particulate matter pollution for its pedestrians. Noise and PM_2.5 levels were recorded simultaneously for two cases (i) pedestrians walking on a footpath alongside road traffic and (ii) pedestrians walking on the elevated High Line. Testing took places over three days in autumn 2014. Results were analysed to investigate if pedestrians using the High Line would have a lower pollution exposure to those using the footpath below. Results showed statistically significant differences between the upper and lower levels in exposure to both pollution types. In order to quantify the overall impact, results are expressed through a combined air–noise pollution index. This index indicates that the average reduction in PM_2.5 and noise pollution along the High Line compared to the footpath below is approximately 37%.     

Neural based contingent valuation of road traffic noise

In this paper, we present a new approach to value the willingness to pay to reduce road noise annoyance using an artificial neural network ensemble. The model predicts, with precision and accuracy, a range for willingness to pay from subjective assessments of noise, a modelled noise exposure level, and both demographic and socio-economic conditions. The results were compared to an ordered probit econometric model in terms of the performance mean relative error and obtained 85.7% better accuracy. The results of this study show that the applied methodology allows the model to reach an adequate generalisation level, and can be applicable as a tool for determining the cost of transportation noise in order to obtain financial resources for action plans.     

Exploring the impacts of road surface texture on tyre/road noise - A case study in Hong Kong

The impacts of road surface texture on tyre/road noise are explored by analysing field data applying fast Fourier transform technique to tyre/road noise spectrum analysis. The results indicate that the tyre/road noise can be higher at lower frequency bands but lower at higher bands. Cluster analysis on surface texture in terms of wavelength identified three cluster groups that centred at 1.32 mm, 3.65 mm, and 5.11 mm have different impacts on noise. The shorter wavelength group suppressed tyre/road noise, medium group aggravated it and the high wavelength group were outliers.     

Economic-environmental analysis of traffic-calming devices

A set of indicators are proposed to determine the effect of traffic-calming devices on the environment and economy. They are based on vehicular emissions and energy consumption and are used to evaluate the viability and positioning of traffic-calming devices. First, a time window is defined on which the influence of a traffic-calming device can be determined providing a convenient frame of reference. Second, a concept of local cruising conditions is defined in order to have a basis of comparison between cases “with” and “without” traffic calming devices. The emissions considered were: HC, NOx, CO, PM₁₀, and CO₂. From the latter fuel consumption was estimated. Valuation of speed bumps on a secondary road in Mexico City was obtained as an example application of the proposed methodology.     

An equilibration scheme for the traffic assignment problem with elastic demands

This note presents an algorithm for the solution of the traffic assignment problem with elastic demands. The algorithm is based on the concept of “equilibration operator” introduced by Dafermos and Sparrow (1969) for the solution of the traffic assignment problem with fixed demands. Computational experience is provided for linear and nonlinear problems for both the algorithm proposed here and the Dafermos-Sparrow algorithm applied to the “excess-demand” reformulations of the problems.     

综合降噪技术在新泰至宁阳高速公路中的应用研究

采用低噪音路面和新型高效声屏障综合降噪技术处置交通噪声,并进行现场测试,测试数据表明,采用OGFC-13低噪音路面结构,在噪声200~1250 Hz频段,路面的平均吸声系数在0.25~0.59,吸声性能较好,可有效降低车内交通噪声约3.0 dB;在对试验段综合降噪效果的测试后发现,采用本文采用的综合降噪技术处置后,项目试验路段在距离声屏障屏体30 m处降噪效果为9.9 dB,相较普通路段降噪效果提升约4.3 dB,且监测数据表明,随着距离的增加,采用综合降噪技术处置的路段降噪效果表现的更加高效。     

Estimating origin‐destination matrices from link volume counts: a simple intercity auto travel demand model for Sri Lanka

The cost of nation wide travel surveys is high. Hence in many developing countries, planners have found it difficult to develop intercity transportation plans due to the non availability of origin‐destination trip matrices. This paper will describe a method for the intercity auto travel estimation for Sri Lanka with link traffic volume data.

The paper outlines the rationale of selecting the district capitals of Sri Lanka as its “cities,” the methodology for selecting the intercity road network, determination of link travel times from express bus schedules and the location of link volume counting positions.

Initially, the total auto travel demand model is formulated with various trip purpose sub‐models. This model is finally modified to a simple demand model with district urban population and travel times between city pairs as the exogenous variables, to overcome statistical estimation difficulties. The final demand model has statistics within the acceptable regions.

The advantages of a simple model are discussed and possible extensions are proposed.     

Exploiting the fundamental diagram of urban networks for feedback-based gating

Traffic signal control for urban road networks has been an area of intensive research efforts for several decades, and various algorithms and tools have been developed and implemented to increase the network traffic flow efficiency. Despite the continuous advances in the field of traffic control under saturated conditions, novel and promising developments of simple concepts in this area remains a significant objective, because some proposed approaches that are based on various meta-heuristic optimization algorithms can hardly be used in a real-time environment. To address this problem, the recently developed notion of network fundamental diagram for urban networks is exploited to improve mobility in saturated traffic conditions via application of gating measures, based on an appropriate simple feedback control structure. As a case study, the proposed methodology is applied to the urban network of Chania, Greece, using microscopic simulation. The results show that the total delay in the network decreases significantly and the mean speed increases accordingly.     

Modeling Capacity Reliability of Minor Roads at At-Grade Un-Signalized Intersections for Potential Performance Evaluation

Abstract

Given stochastic features of the demands on both the major road and the minor road at an at-grade un-signalized intersection, the capacity of the minor road is viewed as the vulnerable and critical part impacting on the overall capacity of the intersection. To facilitate the analysis of intersection performance reliability, the capacity reliability of the minor road is defined as the probability that the capacity of the minor road can accommodate a certain traffic demand at a certain degree of saturation. The headway distribution of traffic stream on major road is reflected by three types of distributions, namely, exponential distribution, shifted exponential distribution, and Cowan's M3 distribution. Based on field observations, the volumes on both major roads and minor roads are treated as correlated normal random variables. This paper presents the methods for modeling capacity reliability of the minor road at an at-grade un-signalized priority intersection. A method based on first-order reliability method is used to model the capacity reliability index. As important associated factors of capacity reliability analysis, the methods for modeling and analyzing capacity sensitivity of the minor road and reserve capacity of the priority intersection are also presented. A procedure for evaluating the intersection potential performance using capacity reliability, sensitivity and reserve capacity is developed and demonstrated with a numerical example. Finally, some new findings from the case studies are summarized.     

Including congestion effects in urban road traffic CO2 emissions modelling: Do Local Government Authorities have the right options?

Tailpipe emissions from vehicles on urban road networks have damaging impacts, with the problem exacerbated by the common occurrence of congestion. This article focuses on carbon dioxide because it is the largest constituent of road traffic greenhouse gas emissions. Local Government Authorities (LGAs) are typically responsible for facilitating mitigation of these emissions, and critical to this task is the ability to assess the impact of transport interventions on road traffic emissions for a whole network.This article presents a contemporary review of literature concerning road traffic data and its use by LGAs in emissions models (EMs). Emphasis on the practicalities of using data readily available to LGAs to estimate network level emissions and inform effective policy is a relatively new research area, and this article summarises achievements so far. Results of the literature review indicate that readily available data are aggregated at traffic level rather than disaggregated at individual vehicle level. Hence, a hypothesis is put forward that optimal EM complexity is one using traffic variables as inputs, allowing LGAs to capture the influence of congestion whilst avoiding the complexity of detailed EMs that estimate emissions at vehicle level.Existing methodologies for estimating network emissions based on traffic variables typically have limitations. Conclusions are that LGAs do not necessarily have the right options, and that more research in this domain is required, both to quantify accuracy and to further develop EMs that explicitly include congestion, whilst remaining within LGA resource constraints.