Plane intersection noise monitoring point distribution method

Abstract

The invention provides a plane intersection noise monitoring point distribution method, comprising the following steps: defining a plane intersection range according to inlet and outlet lane speed distribution consistency; establishing a traffic simulation model for the intersection; running simulation in combination with a single-vehicle noise emission model; densely distributing monitoring points in an intersection range to collect traffic noise data, then calculating a plurality of noise indexes for each monitoring point, carrying out principal component analysis after index values are standardized, carrying out clustering analysis on point locations by taking principal components as new indexes, and screening a plurality of point locations according to a clustering result to form a monitoring point distribution scheme. According to the plane intersection noise monitoring point distribution method, change characteristics of intersection noise are fully considered, and point locations are screened by classifying monitoring points, and the number of the monitoring points is reduced while data effectiveness is guaranteed. The plane intersection noise monitoring point distribution method can be applied to research in the fields of plane intersection traffic noise modeling, traffic noise characteristic analysis and the like.

Description

technical field [0001] The invention relates to the technical field of traffic noise monitoring, and more particularly, to a method for arranging points for noise monitoring at level intersections. Background technique [0002] Urban traffic noise pollution is still an urgent problem to be solved. In recent years, the development of urban traffic noise maps has provided new means for noise pollution control. In 2017, the Ministry of Environmental Protection listed noise map technology as one of the national advanced pollution prevention and control technologies for promotion . The basis and core of the noise map is the traffic noise prediction model, and the intersection noise emission statistical model is a necessary part of it. However, in the current field of research on noise emission models at intersections, there is almost no research on statistical models, mainly because of the lack of noise monitoring data at intersections. There are two reasons for this phenomenon...

AI Technical Summary

Problems solved by technology

[0003] At present, domestic and foreign studies on this content are still relatively rare, and no standard specification on the layout of noise monitoring points at level intersections has been found. Some studies only involve specific layout schemes without discussing the rationality of the scheme; The number of bits is also large, and the implementation of the scheme requires a large cost

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