Data fusion seeks to combine data from a multiple number of sources (sensors, websites, voice communications, etc.) to perform inferences that may not be possible from a single sensor alone. The data fusion process takes the collective data from a series of sensors to collect, organize, and create a wholly new picture, effectively a new perception of the object that could not easily be achieved in another way. Experiments and studies of data fusion have indicated selected techniques can be successful. Data fusion is increasingly being considered as a significant technique in the development and advancement of Intelligent Transportation Systems (ITS) applications. This report summarizes some of the recent developments in ITS data fusion. A framework for analysis is presented and used to describe opportunities and challenges for advancing data fusion techniques and concepts in ITS applications.
Samenvatting