Data-Fusion Approach Based on Evidence Theory Combining with Fuzzy Rough Sets for Urban Traffic Flow

The traffic detecting result is always short of accuracy by different kinds of individual sensors in urban China. A new data fusion approach is raised in this paper to solve the issue, based on fuzzy rough set theory combining with evidence theory. The method is improved to concise attribute rules and to measure fuzzy likelihood. Furthermore, a new combination rule is given to dissolve the confliction among the traffic evidence data collected by different individual sensors. Finally, the experiment to fuse the traffic data from an intersection in Hangzhou City showed that the proposed approach could obtain a high accuracy.