Object Oriented Cellular Automaton for Multiple Lane Road Traffic Noise Mapping

Due to the traffic and its noise emission, road infrastructures represent a major source of illness. Noise measurement campaigns in order to produce map noises are essential for the decision-making of urban and suburban areas, yet wide measurements turn out to be expensive and unpractical. In this manner, simulation tools to help predict noise emitted from road traffic are designed. In this paper, a cellular automaton simulates traffic of a multiple-lane road, and the associated noise map of the road are calculated. The cellular automaton relies on the stochastic Nagel-Schreckenberg method. The real-world quantities are then assigned to the cellular automaton, giving each vehicle a speed in km/h. Using the common model of noise assessment CNOSSOS-EU, noise power levels are assigned to vehicles according to their kinematic parameters. The spreading of noise through the map is done through point-like source propagation respecting the time of propagation. The results highlight the effect of the number of lanes and traffic frequency on the noise maps.