The strategy of traffic congestion management based on case-based reasoning

Abstract

This paper proposes a case-based reasoning (CBR) method for traffic congestion management in view of the rapid development of urban motorization and the increasingly prominent problem of traffic congestion. The reasoning model based on CBR congestion management is established, and the characteristic attributes of traffic congestion cases are analyzed. The calculation methods combining local and global similarity are adopted for different types of attributes. Meanwhile, it proposes the update and preservation mode for traffic congestion case database. The cases indicate that traffic congestion management can quickly find a solution to traffic congestion problem by calculating the similarity between congestion cases through CBR. The cases prove that this method can improve the accuracy of CBR results and have certain guiding significance for traffic management.