A Multiscale Symbolic Dynamic Entropy Analysis of Traffic Flow

The complexity analysis of traffic flow is important for understanding the property of traffic system. Being good at analyzing the regularity and complexity, multiscale SamEn has attracted much attention and many methods have been proposed for complexity analysis of traffic flow. However, there may exist discontinuity of the calculated entropy value which makes the regularity of the traffic system difficult to understand. The phenomenon occurs due to an inappropriate selection of the parameter r in the multiscale SamEn. Moreover, it is dicult to select an appropriate r for the accurate evaluation of the complexity, which limits the application of multiscale entropy for traffic flow analysis. To solve this problem, a new entropy-based method, multiscale symbolic dynamic entropy, for evaluating the trac system is proposed here. To verify the eectiveness of the proposed method, trac data collected from stations in dierent cities are preprocessed by the proposed method. Both results of two cases show that the weekend patterns and weekday patterns are eectively distinguished using the proposed method, respectively. Specically, compared with the traditional methods including multiscale SamEn and the multiscale modied SamEn, the complexity of the corresponding trac system can be better evaluated without considering the selection of r, which demonstrates the eectiveness of the proposed method.