Institute of Transportation, MOTC

Ruei-Feng Wu, 2006.07

Department of Transportation Technology and Management National Chiao Tung University 　　

Advanced Traveler Information System (ATIS) is one of the key elements of Intelligent Transportation System (ITS). Traveler information could be obtained via various sources such as VD and probe vehicles. Therefore, various information must be merged into a distinct and reliable information. The purpose of this research is developing a date fusion methodology for merging various traffic data source. The optimal weighting approach is proposed for fusing various traffic data. It minimizes total system uncertainty while fusing data. We use Shannon entropy to represent uncertainty. Besides, a weighted distance approach is used to reduce the impact of data classification.
　　We use simulation data to evaluate the performance of our model. The results show that our proposed approach could reduce influence of data classification and reduce the bias of centralized and separated data.