Towards the assessment of the noise level time-history for ground based transportation

Abstract

Existing noise prediction tools for ground based transportation calculate time-averaged noise levels and predict daily noise impact on humans. A typical approach is to predict the time-averaged road noise emission and propagate it to preselected observers at rest. The resulting noise level represents the energy equivalent noise impact for a specified time period. However, effects like wake-up reactions strongly depend on single noise events, which are characterized by the maximum sound level and their steepest slope in level time-history. To simulate these time and space dependent sound events for urban areas and to develop noise reducing traffic scenarios, more detailed simulations predicting time dependent noise emission are needed. This paper suggests a method for calculating time-histories of single noise events of road vehicles. It is based on the microscopic traffic simulation software SUMO, which computes the movement profile of any prescribed vehicle in a modelled transportation network, obeying all necessary constraints like speed limitations and time schedules for traffic lights. SUMO is extended by implementing models to predict the noise emission, propagation of the time-dependent noise and the wake-up probability of observers. The vehicle emission model is induced by the engine speed for acceleration, deceleration and shift of gear phases by utilizing the available driving conditions of each simulated vehicle. Finally the procedure is applied to a traffic scenario, modeling the pass-by of a truck. The level-time history of observers at rest close to the road is analyzed in terms of steepest slope of rise and maximum sound pressure level. Based on the latter an increase of wake-up probability due to the single noise event is predicted.