Prediction and control of road traffic noise exposure and annoyance associated with non-free flowing vehicular traffic in urban areas.

Previous attempts to establish evaluation measures for noise under non-free flowing traffic conditions in urban contexts have not been entirely successful, due to the complexity of related influences. This paper describes the development of reliable prediction models for noise exposure and annoyance emanating from urban traffic where the flow is typically non-free flowing. The elements of the models are deliberately selected to facilitate the consideration of noise and people's attitudes during various transport planning and design process. The models are based on a wide ranging program of subjective and objective surveys. The level of traffic noise under various conditions, such as priority junctions, traffic conditions, such as priority junctions, traffic lights and roundabouts control, is appraised in an integrated way by considering the role of land use, building, road and traffic variables, as well as human responses. Three kinds of models are presented. The first kind predicts L10 and Leq dB(A) noise levels in terms of three classes of vehicles, building facades, various junctions and road configurations where the speed is below 50 km/h for traditional highly populated urban centres. The second model kind considers noise in terms of traffic flow, percentage of medium and heavy vehicles and other variables where the speed is up to 80 km/h under traditional outer urban conditions. The third kind evaluates people's attitudes to their surrounding environment in terms of various components, it relates the Overall Attitudes Index (created index) to noise indices and independent variables. A new relationship between L10, L50, L90 and Leq is also presented, together with a relationship between L10 and Leq. The traditional elements of noise control, advantages of the availability of prediction tools and the limitations of previous practice are summarised. In their application to practical situations the prediction models of this study are shown to provide an effective methodology for the execution of traffic noise control policy during the process of transportation planning, land use planning, traffic management, road building and building construction (A).