Analysis of Impact Factors for Traffic Noise in urban Areas

Abstract

Road traffic noise contributes significantly to outdoor environmental noise, especially in urban areas. The pressure of traffic noise is influenced by many factors such as types of engines, exhaust systems and tires interacting with the road, weather and road conditions. The tire/pavement interaction noise has been proven to be the major source of the traffic noise, especially for cruising driving conditions, which is highly influenced by surface characteristics of road pavement. Traffic flow is also a factor – apart from vehicles, tires and road surface characteristics – in affecting traffic noise pressures. The noise level can increase by about 3 dBA when traffic flow doubles, if the traffic composition, speed and driving patterns are constant. Consequently, it is required to investigate the effects of road pavement conditions and traffic flow on traffic noise emission, and further explore the interactive effect of operation time of pavement and traffic flow for traffic noise control and mitigation. In this research, a series of field experiments are conducted on highways of new and old pavements. The variations of traffic flow and traffic noise pressure levels together with the functional relationships between them are analyzed based on the noise data collected from the highways in an urban area. With the collected data, the maximum traffic flow and traffic noise pressure levels are determined in a specified time manner. Logarithmic functional relationships are found between traffic noise pressure level and traffic flow for both old and new pavements. It is also found that the improvement in pavement material of highway may promote the absorption of traffic noise. A single value index is developed for quantitatively and conveniently evaluating the acoustic quality of highways. The findings in this research may give some inspiration for construction and management of low noise highways. The field experiment is expanded to the year of 2014, with the road near the measurement sites repaved in 2013. The results indicate that the re-pavement of road surface can effectively reduce the traffic noise. However, as the road surface ages, such reduction effect would also decrease. Additionally, an entropy-copula method is proposed for modelling dependence between traffic flow and traffic noise on the Trans-Canada Highway (#1 highway of Canada) in the City of Regina based on the field experiment measurements. The proposed entropy-copula method combines the maximum entropy and copula methods into a general framework, in which the marginal distributions of traffic flow and traffic noise are estimated through the principle of maximum entropy (POME) theory, and the joint probabilities are derived through the Gaussian and Student t copulas. The proposed method is applied at two field experiment sites on the Trans-Canada Highway. Based on the K-S and A-D tests and RMSE value, the entropy method shows well performance in quantifying the probability distributions of traffic flow and traffic noise. Meanwhile, both Gaussian and Student t copulas can well model the joint probability distributions for traffic flow and traffic noise at both experiment sites, which are demonstrated by the Cramér von Mises statistics and the RMSE values. Furthermore, the conditional CDFs of the traffic noise at two experiment sites are derived based on the established Gaussian and Student t copulas under different traffic flow scenarios. The obtained conditional CDFs indicate positive structures between traffic flow and traffic noise at both experiment sites. II