Control Subarea Partitioning Method Based On Dynamic Clustering

The regional coordinated traffic signal control method is an effective approach to decrease road congestion level.Before using a regional coordinated traffic signal control scheme,the traffic network needs to be partitioned into homogeneous subareas.So,traffic network partitioning has been of great importance in regional coordinated traffic signal control.Traffic flow characteristic parameters representing the traffic flow situation largely affects the results of traffic control subarea division.Most partitioning algorithms only use a single traffic parameter to represent dynamic traffic information,which will lead to inaccurate results.Moreover,traditional clustering and heuristic partitioning algorithms are not practical in applications.Therefore,this thesis first proposes a new combinatorial characteristic parameter for clustering-based partitioning algorithm by using the Pearson correlation coefficient and data normalization.Then,referring to the idea of existing clustering algorithm,this thesis also implements two kinds of traffic control subarea partitioning methods.Based on the real traffic data of a Chinese city,the experiments verify the effectiveness of the proposed methods.The main work of this thesis is as follows:1.A new combinatorial characteristic parameter for clustering-based partitioning algorithm by using Pearson correlation coefficient and data normalization is proposed.2.Referring to the new combinatorial characteristic parameter and the idea of “snake” algorithm,two kind of traffic network partitioning methods are proposed.3.A real case was studying,and the result of comparative experiments verify the effectiveness of the new parameter.