Studies Of Urban Traffic Noise Prediction And Noise Mapping Based On Canda/A

With increasing urbanization and the continuous development of the transport industry, traffic noise pollution has become a serious urban environmental problem. In order to control the noise pollution from the upstream, it is necessary to conduct comprehensive analysis of the city's existing noise levels, and to explore the possible noise impact of new options and new plan. Regional urban traffic noise prediction and noise mapping based on it are effective means to achieve these goals. However, there are only few studies about the selection of urban traffic noise prediction model and the methods of 3D noise mapping in China, which increases the uncertainty of prediction and makes decision-makers and public less informed.This paper analyzes the process of traffic noise prediction and noise mapping, and studies the various domestic and international traffic noise prediction models. After this, the appropriate traffic noise prediction models are chosen based on the current situation in China. Through field monitoring, the variation laws of road traffic flow, vehicle speed and vehicle type are analyzed, as well as the relationship between road noise and traffic condition. Also, the accuracies of the chosen traffic noise prediction models are examined. Then, the relevant information and geospatial data are collected to construct 3D geographical model, which is used by noise prediction software Cadna/A to complete the traffic noise prediction and 2D noise mapping. Finally, based on the prediction results from Cadna/A, using ArcScene as 3D display tool, ArcMap as data analysis and management platform and 3ds Max as visual modeling software, the spatial distribution of observation points, interpolation and visualization are completed, and the 3D noise mapping is successed.Based on the current situation in China, this study develops methods of urban traffic noise prediction and 3D noise mapping with good operability and feasibility. The study is well organized, focuses on practicality. The results of traffic noise prediction are accurate, and the 3D noise mapping is informative and intuitive. The results of this study have great practical significance for urban construction, transportation planning, noise assessment, public participation and decision-making.