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Three-dimensional Urban Traffic Noise Prediction Model And Its Application Research

Posted on:2014-06-09Degree:MasterType:Thesis
Country:ChinaCandidate:M ZhuangFull Text:PDF
GTID:2252330401484399Subject:Cartography and Geographic Information System
Abstract/Summary:PDF Full Text Request
Along with the accelerating speed of urban construction and the land can bedeveloped and utilized increasingly scarce, the concept of urban sustainabledevelopment has been constantly promoted, and make the urban form gradually intothe air three-dimensional development. At the same time, with the expansion of theurban traffic road network, environmental noise pollution, as well as atmosphericpollution, water pollution and solid waste pollution were treated as fourenvironmental nuisance. Environmental noise pollution, as one of the four majorenvironmental hazards, has gradually got the attention of the all levels’ governmentdepartments and urban residents, become one of the major problems hinder the urbanliving environment quality improvement. Compared with the rapid trend of China’surban development, environmental noise pollution prediction and preventiontechnology has not been a corresponding rapid development. Therefore, how to do theoverall planning of the city, scientific prediction of urban traffic noise level as well asvisual analysis system for our country’s sustainable and comprehensive developmenthas an irreplaceable function.Comprehensive comparison and analysis presented in this paper is commonlyused traffic noise prediction model at domestic and international, high-rise buildings,which are surrounded east-west expressway in Qingdao city, was treated as researchobject to established the suitable three-dimensional traffic noise prediction model, andthe research results and three-dimensional simulation software I4City were integratedto achieve a visual representation of the traffic noise prediction results. The mainthesis work and research achievements are as follows:1. The relationship between the ground and the connection of high-rise’s trafficnoise peak point and the road centerline: A-weighted network was used formonitoring of high-rise building that along the trunk road in Qingdao city. Grapher software was used to analyze the peak point of buildings. It was used to drawcontinuous line graph firstly, Leq values were looked as the reference value.According to the distance between the building and the road centerline, the angle,which displayed the relationship between the ground and the connection of high-rise’straffic noise peak point and the road centerline, was worked out about30°.2. The three-dimensional predictive models of urban traffic noise: After acomparative analysis of several more commonly used traffic noise prediction model athome and abroad, we can obtained traffic forecasting model as the basis of Qingdaocity road traffic conditions. Noise data and other relevant distance informationobtained through field monitoring, using the vehicle conversion coefficientscalculation of the total traffic, using regression analysis to do numerical analysis andsimulation, using the by-difference correction method to correct the model parameters,and ultimately got the high-rise buildings’ three-dimensional prediction model ofurban traffic noise.3. Urban traffic noise visualization: The visualization system is the seamlessintegration of three-dimensional prediction model of urban traffic noise and regionalfeature three-dimensional simulation model. The studies looked I4City platform as thebasis of the visual system platform, combining with corrected three-dimensionaltraffic noise prediction model, I4City was used to manage spatial and attributedatabase. According to the need of the model calculation, visual analysis extractrelevant data from the database to obtain accurate and reliable analysis, and in thebasis of the visualization results, the evaluation of the traffic noise was made tosee if it is within the State Level prescribed.
Keywords/Search Tags:Urban traffic noise, High-rise buildings, Peak point, three-dimensionalforecast model, visualization
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