Evaluate traffic noise level based on traffic microsimulation combined with a refined classic noise prediction method

In this paper, a refined classic noise prediction method based on the VISSIM and FHWA noise prediction model is formulated to analyze the sound level contributed by traffic on the Nanjing Lukou airport connecting freeway before and after widening. The aim of this research is to (i) assess the traffic noise impact on the Nanjing University of Aeronautics and Astronautics (NUAA) campus before and after freeway widening, (ii) compare the prediction results with field data to test the accuracy of this method, (iii) analyze the relationship between traffic characteristics and sound level. The results indicate that the mean difference between model predictions and field measurements is acceptable. The traffic composition impact study indicates that buses (including mid-sized trucks) and heavy goods vehicles contribute a significant proportion of total noise power despite their low traffic volume. In addition, speed analysis offers an explanation for the minor differences in noise level across time periods. Future work will aim at reducing model error, by focusing on noise barrier analysis using the FEM/BEM method and modifying the vehicle noise emission equation by conducting field experimentation.

Investigation into the noise map based on traffic flow prediction in the citywide road network

As one of the measures for decreasing road traffic noise in a city, the control of the traffic flow and the physical distribution is considered. To conduct the measure effectively, the model for predicting the traffic flow in the citywide road network is necessary. In this study, the existing model named AVENUE was used as a traffic flow prediction model. The traffic flow model was integrated with the road vehicles' sound power model and the sound propagation model, and the new road traffic noise prediction model was established. As a case study, the prediction model was applied to the road network of Tsukuba city in Japan and the noise map of the city was made. To examine the calculation accuracy of the noise map, the calculated values of the noise at the main roads were compared with the measured values. As a result, it was found that there was a possibility that the high accuracy noise map of the city could be made by using the noise prediction model developed in this study.

Evaluation of valuation of noise amelioration treatments within and outside the road reserve

In urban environments road traffic volumes are increasing and the density of living is becoming higher. As a consequence the urban community is being exposed to increasing levels of road traffic noise. It is also evident that the noise reduction potential of within-the-road-reserve treatments such as noise barriers, mounding and pavement surfacing has been exhausted. This paper presents a strategy that involves the comparison of noise ameliorative treatments both within and outside the road reserve. The noise reduction resulting from the within-the-road-reserve component of treatments has been evaluated using a leading application of the CoRTN Model, developed by the UK Department of Transport 1988 [1], and the outside road reserve treatment has been evaluated in accordance with the Australian Standard 3671, Acoustics – Road traffic noise intrusion – Building sitting and construction [5]. The evaluation of noise treatments has been undertaken using a decision support tool (DST) currently being developed under the research program conducted at RMIT University and Department of Main Roads, Queensland. The case study has been based on data from a real project in Queensland, Australia. The research described here was carried out by the Australian Cooperative Research Centre for Construction Innovation [9], in collaboration with Department of Main Roads, Queensland, Department of Public Works, Queensland, Arup Pty. Ltd., Queensland University of technology and RMIT University.

Large area noise evaluation

A software tool (DRONE) has been developed to evaluate road traffic noise in a large area with the consideration of network dynamic traffic flow and the buildings. For more precise estimation of noise in urban network where vehicles are mainly in stop and go running conditions, vehicle sound power level (for acceleration/deceleration cruising and ideal vehicle) is incorporated in DRONE. The calculation performance of DRONE is increased by evaluating the noise in two steps of first estimating the unit noise database and then integrating it with traffic simulation. Details of the process from traffic simulation to contour maps are discussed in the paper and the implementation of DRONE on Tsukuba city is presented

Increased traffic exposure and negative birth outcomes : a prospective cohort in Australia

Background: Pregnant women exposed to traffic pollution have an increased risk of negative birth outcomes. We aimed to investigate the size of this risk using a prospective cohort of 970 mothers and newborns in Logan, Queensland. ----- ----- Methods: We examined two measures of traffic: distance to nearest road and number of roads around the home. To examine the effect of distance we used the number of roads around the home in radii from 50 to 500 metres. We examined three road types: freeways, highways and main roads.----- ----- Results: There were no associations with distance to road. A greater number of freeways and main roads around the home were associated with a shorter gestation time. There were no negative impacts on birth weight, birth length or head circumference after adjusting for gestation. The negative effects on gestation were largely due to main roads within 400 metres of the home. For every 10 extra main roads within 400 metres of the home, gestation time was reduced by 1.1% (95% CI: -1.7, -0.5; p-value = 0.001).----- ----- Conclusions: Our results add weight to the association between exposure to traffic and reduced gestation time. This effect may be due to the chemical toxins in traffic pollutants, or because of disturbed sleep due to traffic noise.

Large area noise evaluation

A software tool (DRONE) has been developed to evaluate road traffic noise in a large area with the consideration of network dynamic traffic flow and the buildings. For more precise estimation of noise in urban network where vehicles are mainly in stop and go running conditions, vehicle sound power level (for acceleration/deceleration cruising and ideal vehicle) is incorporated in DRONE. The calculation performance of DRONE is increased by evaluating the noise in two steps of first estimating the unit noise database and then integrating it with traffic simulation. Details of the process from traffic simulation to contour maps are discussed in the paper and the implementation of DRONE on Tsukuba city is presented.

Investigations on road noise level spatial variability within a specially designed acoustic balcony

An investigation into the spatial distribution of road traffic noise levels on a balcony is conducted. A balcony constructed to a special acoustic design due to its elevation above an 8 lane motorway is selected for detailed measurements. The as-constructed balcony design includes solid parapets, side walls, ceiling shields and highly absorptive material placed on the ceiling. Road traffic noise measurements are conducted spatially using a five channel acoustic analyzer, where four microphones are located at various positions within the balcony space and one microphone placed outside the parapet at a reference position. Spatial distributions in both vertical and horizontal planes are measured. A theoretical model and prediction configuration is presented that assesses the acoustic performance of the balcony under existing traffic flow conditions. The prediction model implements a combined direct path, specular reflection path and diffuse reflection path utilizing image source and radiosity techniques. Results obtained from the prediction model are presented and compared to the measurement results. The predictions are found to correlate well with measurements with some minor differences that are explained. It is determined that the prediction methodology is acceptable to assess a wider range of street and balcony configuration scenarios.

Decision - Support Software Tool Handbook

The road and transport industry in Australia and overseas has come a long way to understanding the impact of road traffic noise on the urban environment. Most road authorities now have guidelines to help assess and manage the impact of road traffic noise on noise-sensitive areas and development. While several economic studies across Australia and overseas have tried to value the impact of noise on property prices, decision-makers investing in road traffic noise management strategies have relatively limited historic data and case studies to go on. The perceived success of a noise management strategy currently relies largely on community expectations at a given time, and is not necessarily based on the analysis of the costs and benefits, or the long-term viability and value to the community of the proposed treatment options. With changing trends in urban design, it is essential that the 'whole-of-life' costs and benefits of noise ameliorative treatment options and strategies be identified and made available for decisionmakers in future investment considerations. For this reason, CRC for Construction Innovation Australia funded a research project, Noise Management in Urban Environments to help decision-makers with future road traffic noise management investment decisions. RMIT University and the Queensland Department of Main Roads (QDMR) have conducted the research work, in collaboration with the Queensland Department of Public Works, ARUP Pty Ltd, and the Queensland University of Technology. The research has formed the basis for the development of a decision-support software tool, and helped collate technical and costing data for known noise amelioration treatment options. We intend that the decision support software tool (DST) should help an investment decision-maker to be better informed of suitable noise ameliorative treatment options on a project-by-project basis and identify likely costs and benefits associated with each of those options. This handbook has been prepared as a procedural guide for conducting a comparative assessment of noise ameliorative options. The handbook outlines the methodology and assumptions adopted in the decision-support framework for the investment decision-maker and user of the DST. The DST has been developed to provide an integrated user-friendly interface between road traffic noise modelling software, the relevant assessment criteria and the options analysis process. A user guide for the DST is incorporated in this handbook.

Development of a practical design guide for balcony acoustic treatments

Balcony acoustic treatments can be demonstrated to provide important benefits in reducing road traffic noise within the balcony space and consequently internally for any adjacent room. The actual effect on road traffic noise is derived from a multitude of variables that can be broadly categorized into (a) acoustical and (b) geometrical for two distinct propagation volumes being (i) the street space, and (ii) the balcony space. A series of recent research activities in this area has incorporated the use of a combined image and diffuse source model, which can be used to predict the effect of balconies on road traffic noise for large number of scenarios. This paper investigates and presents a method and capability to summarize predictive data into user friendly guidelines aimed for use by acoustical professionals and architects and possible implementation in building design policies for environmental noise. The paper concludes with a presentation of the likely format of a potential design guide.

Transport and health in China : recent collaborative research relating to vehicle factors and pollution

The nature of the transport system contributes to public health outcomes in a range of ways. The clearest contribution to public health is in the area of traffic crashes, because of their direct impact on individual death and disability and their direct costs to the health system. Other papers in this conference address these issues. This paper outlines some collaborative research between the Centre for Accident Research and Road Safety - Queensland (CARRS-Q) at QUT and Chinese researchers in areas that have indirect health impacts. Heavy vehicle dynamics: The integrity of the road surface influences crash risk, with ruts, pot-holes and other forms of road damage contributing to increased crash risks. The great majority of damage to the road surface from vehicles is caused by heavy trucks and buses, rather than cars or smaller vehicles. In some cases this damage is due to deliberate overloading, but in other cases it is due to vehicle suspension characteristics that lead to occasional high loads on particular wheels. Together with a visiting researcher and his colleagues, we have used both Queensland and Chinese data to model vehicle suspension systems that reduce the level of load, and hence the level of road damage and resulting crash risk(1-5). Toll worker exposure to vehicle emissions: The increasing construction of highways in China has also involved construction of a large number of toll roads. Tollbooth workers are potentially exposed to high levels of pollutants from vehicles, however the extent of this exposure and how it relates to standards for exposure are not well known. In a study led by a visiting researcher, we conducted a study to model these levels of exposure for a tollbooth in China(6). Noise pollution: The increasing presence of high speed roads in China has contributed to an increase in noise levels. In this collaborative study we modelled noise levels associated with a freeway widening near a university campus, and measures to reduce the noise(7). Along with these areas of research, there are many other areas of transport with health implications that are worthy of exploration. Traffic, noise and pollution contribute to a difficult environment for pedestrians, especially in an ageing society where there are health benefits to increasing physical activity. By building on collaborations such as those outlined, there is potential for a contribution to improved public health by addressing transport issues such as vehicle factors and pollution, and extending the research to other areas of travel activity. 1. Chen, Y., He, J., King, M., Chen, W. and Zhang, W. (2014). Stiffness-damping matching method of an ECAS system based on LQG control. Journal of Central South University, 21:439-446. DOI: 10.1007/s1177101419579 2. Chen, Y., He, J., King, M., Feng, Z. and Chang, W. (2013). Comparison of two suspension control strategies for multi-axle heavy truck. Journal of Central South University, 20(2): 550-562. 3. Chen, Y., He, J., King, M., Chen, W. and Zhang, W. (2013). Effect of driving conditions and suspension parameters on dynamic load-sharing of longitudinal-connected air suspensions. Science China Technological Sciences, 56(3): 666-676. DOI: 10.1007/s11431-012-5091-3 4. Chen, Y., He., J., King, M., Chen, W. and Zhang, W. (2013). Model development and dynamic load-sharing analysis of longitudinal-connected air suspensions. Strojniški Vestnik - Journal of Mechanical Engineering, 59(1):14-24. 5. Chen, Y., He, J., King, M., Liu, H. and Zhang, W. (2013). Dynamic load-sharing of longitudinal-connected air suspensions of a tri-axle semi-trailer. Proceedings of Transportation Research Board Annual Conference, Washington DC, 13-17 January 2013, paper no. 13-1117. 6. He, J., Qi, Z., Hang, W., King, M., and Zhao, C. (2011). Numerical evaluation of pollutant dispersion at a toll plaza based on system dynamics and Computational Fluid Dynamics models. Transportation Research Part C, 19(2011):510-520. 7. Zhang, C., He, J., Wang, Z., Yin, R. and King, M. (2013). Assessment of traffic noise level before and after freeway widening using traffic microsimulation and a refined classic noise prediction method. Proceedings of Transportation Research Board Annual Conference, Washington DC, 13-17 January 2013, paper no. 13-2016.

Noisy Bluetooth traffic data?

Traffic state estimation in an urban road network remains a challenge for traffic models and the question of how such a network performs remains a difficult one to answer for traffic operators. Lack of detailed traffic information has long restricted research in this area. The introduction of Bluetooth into the automotive world presented an alternative that has now developed to a stage where large-scale test-beds are becoming available, for traffic monitoring and model validation purposes. But how much confidence should we have in such data? This paper aims to give an overview of the usage of Bluetooth, primarily for the city-scale management of urban transport networks, and to encourage researchers and practitioners to take a more cautious look at what is currently understood as a mature technology for monitoring travellers in urban environments. We argue that the full value of this technology is yet to be realised, for the analytical accuracies peculiar to the data have still to be adequately resolved.

Air pollution levels measured at traffic hot spots : Brisbane urban corridor study

Air pollution levels were monitored continuously over a period of 4 weeks at four sampling sites along a busy urban corridor in Brisbane. The selected sites were representative of industrial and residential types of urban environment affected by vehicular traffic emissions. The concentration levels of submicrometer particle number, PM2.5, PM10, CO, and NOx were measured 5-10 meters from the road. Meteorological parameters and traffic flow rates were also monitored. The data were analysed in terms of the relationship between monitored pollutants and existing ambient air quality standards. The results indicate that the concentration levels of all pollutants exceeded the ambient air background levels, in certain cases by up to an order of magnitude. While the 24-hr average concentration levels did not exceed the standard, estimates for the annual averages were close to, or even higher than the annual standard levels.