Resumen de Case study: Establishment of a vehicle noise emission model for gradient roads
Weijun Yang, Ziqin Lan, Haibo Wang, Ming Cai
Traffic noise prediction is an important consideration for sound environmental planning in cities, and an accurate noise emission model is the key to the prediction of traffic noise. Since gradient road sections are common in urban road networks, a noise emission model for gradient roads is necessary. This study considers the relationship between the longitudinal slope of a road section and the driving state of the vehicle, which is a different approach from most of the existing noise emission models. The longitudinal gradient of the road section can be converted to additional acceleration and the extra output power of the vehicle. Thus, the noise emitted by a vehicle can be directly connected to its driving state, including the speed, acceleration, and the output power of the engine of the vehicle. To establish such a noise emission model, an experiment is conducted, and hundreds of data points for the vehicle's speed, acceleration, and noise emissions values are collected. The least-squares method is applied, and the accuracy of the model is verified by a comparison with the measured data and the canonical values. The results show that the average error between the established model and the measured values is less than 2 dB(A). A traffic simulation is conducted, and the results indicate that the noise value predicted by the model established in this article is closer to the measured value. Thus, the presented model can facilitate relatively accurate results in predicting the noise emission of vehicles on gradient road sections. © 2019 Institute of Noise Control Engineering
