Floating Car Data as Data Source for Modelling of Air and Noise Pollution in Regions with High Traffic Density

Abstract

As air and noise pollution models depend on real-time traffic data, the integration of traffic information (air and noise emissions) has been recognised as an important step in urban areas. As the equipment of fixed measurement stations for traffic, air pollution and noise detection is limited by financial constraints information from cars equipped with sensors (Floating Cars) supplements information from these sources. The position and the speed of cars are acquired by satellite navigation in combination with mobile communication, cellular phone tracking systems and long wave positioning. Further knowledge of the relation among traffic-related parameters is used to estimate traffic flow in the road network. Based on the estimations available models for traffic-related air and noise emissions can be applied to calculate emission inventories with an improved spatial and temporal resolution. So the development of methods for the detection, storage and interpretation of Floating Car data has the potential of improving the information basis for modelling of the traffic situation, air and noise pollution in regions with high traffic density.