WIT Press

Multi-sensor Data Fusion For Traffic Planning And Control


Free (open access)





Page Range

179 - 189




4,720 kb

Paper DOI



WIT Press


N. Corsi & A. Capitanelli


Traffic and mobility are essential ingredients of modern society, as they are important prerequisites for economic and social prosperity. Due to opportunities provided by modern technologies, traffic management has become an important component in improving quality and safety, especially in road traffic. The objective of this paper is to present a novel approach to performing data correlation and to extend the developed techniques and processing strategies to satellite COSMO-SkyMed data (CSKĀ®) in the framework of terrestrial Strategic Picture-based applications. By using an integrated system based on satellite, acoustic and GPS data, wide-area images of the entire road network can complement the selectively acquired data. The integration would take benefit of the enhanced imaging capabilities of COSMO-SkyMed and its high revisit rate given by the future constellation configuration, thus leading to fully exploitable in situ/EO integrated products. The preliminary test activity was performed in November 2010: there were promising results from the innovative system based on the heterogeneous data fusion, from Synthetic Aperture Radar to GPS and Acoustic Sensors. Keywords: traffic management, vehicles detection, synthetic aperture radar. 1 Introduction In the last years, a number of techniques have been tried to improve the management of traffic in city centres and on major roads but they have typically obtained limited success. A common concern is that the existing road network, by reason of being unmanaged, is inefficiently utilised and could better accommodate the traffic load placed on it. This would reduce the environmental impact by reducing the need for new roads and would reduce the time that road


traffic management, vehicles detection, synthetic aperture radar