Forecast and control of traffic noise based on improved UE model during road network design

Considering the factor of traffic noise during design period could mitigate the noise emission of urban road networks. In this paper, noise prediction and control of typical points among design networks are presented, with the establishment of a univariate noise prediction model and the improvement of UE (user equilibrium) traffic assignment model. First, a univariate traffic noise prediction model is built with flow as variate merely, which is based on the line source model and introduce of the Van Aeder model. Furthermore, the accuracy of the prediction model is verified in comparison with measured traffic noise data. Secondly, the univariate traffic noise prediction model and travel time model are combined to form the impedance function with different traffic noise weight coefficients after normalization, and upon which the UE model is rebuilt with the road level of service as a constraint. Finally, the improved UE model is used to study the noise control law of the control points, which are divided in two types according to the location. The results show that the improved UE model can effectively reduce the traffic noise of control points by adjusting the traffic noise weight, and among them, the traffic noise of the control point beside the single road and the control point at the road crossing are reduced by at most 0.54 dB, 1.1 dB respectively. Meanwhile, the noise control of points in road network will cause uncertainty to the overall traffic noise emission of the road network, which confirms the noise paradox. Besides, while the traffic noise of the road where the control point is located is reduced, the noise emission and the travel delay of roads in parallel with objective road increases by 0.19 dB, 0.932 s at most. The correlation coefficient between the traffic noise difference of the control point and the VC ratio difference of the road beside the control point is as high as 0.9811 under the improved UE model with different traffic noise, and there is a linear relationship between them. The study can provide a reference for traffic noise control during urban road network design.