A Multiscale Symbolic Dynamic Entropy Analysis of Traffic Flow

Abstract

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 difficult 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 traffic system is proposed here. To verify the effectiveness of the proposed method, traffic data collected from stations in different cities are preprocessed by the proposed method. Both results of two cases show that the weekend patterns and weekday patterns are effectively distinguished using the proposed method, respectively. Specifically, compared with the traditional methods including multiscale SamEn and the multiscale modified SamEn, the complexity of the corresponding traffic system can be better evaluated without considering the selection of r, which demonstrates the effectiveness of the proposed method.