A New Traffic Data-Fusion Approach Based on Evidence Theory Coupled with Fuzzy Rough Sets

The traffic detecting result is always short of accuracy by different kinds of individual sensors in urban China. To solve the issue, a new data fusion approach is raised. The algorithm combines fuzzy and rough set theory based on 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 urban Hangzhou showed that the proposed approach could obtain a high accuracy.