Multidimensional State Estimation Rules in Urban Traffic System Based on Rough Set Theory

Traffic flow is a complex, changeful, nonlinear, unstructured, space time-varying and random system. With the foundation and operating of the Intelligent Traffic System, it is imperative to search for a traffic state estimation model, which is suitable for mixed-traffic in China. On the basic of analysis of the multidimensional state characteristics of mixed-traffic, using the Rough Set Theory, the four-dimensional state estimation model is founded. By data discretization and attribute reduction, the two-dimensional decision table is gained, and the rules of multidimensional state estimation in urban traffic system are presented. A case is given and it indicates that this method can eliminate the redundancy information of the system effectively and improve the precision of rule mining.