A Kalman Filter based information fusion method for traffic speed estimation

In order to improve the traffic data´s completeness and comprehensiveness, this paper presents a traffic information fusion method to solve the problem of road sections without GPS sampling signals. A Kalman filter method is used to fuse the information of associated road sections with traffic information to acquire the speed information of those road sections without GPS sampling signals. The fusion method is verified with the real GPS traffic data of Hangzhou city of China, and compared with the traditional method, which uses the historical speed data to replace the current speed of the road sections without GPS sampling signals. Experimental results show that the proposed method is effective and can provide more precise and comprehensive traffic information for traffic managers.