Time-of-day breakpoints for traffic signal control using dynamic recurrence order clustering
LI Wen-jing1, SUN Feng2, LI Xi-yao3, MA Dong-fang1
1. Ocean College, Zhejiang University, Hangzhou 310058, China;
2. College of Transportation and Automotive Engineering, Shandong University of Technology, Zibo 255000, China;
3. College of Communication and Transportation Engineering, Dalian University of Technology, Dalian 116024, China
An intelligent partition method for the traffic flow time series data was proposed based on order clustering to compensate for the technical defects of traditional methods which neglect time characteristic of traffic flow for traffic time-of-day (TOD) breakpoints optimization. The parameter of diameter was selected with fixed number of each cluster to measure the difference between any two samples within one cluster. The sum of the diameters was the loss value for this cluster. A fast solution method for seeking the optimal plan among all possible scenarios with known number of cluster was advanced based on dynamic recurrence algorithm in order to reduce the time complexity of the original method. The optimal number of clusters and the TOD plan was determined by identifying the elbow point in the change pattern of the minimum loss values with different numbers of clusters. The optimal partition used in the actual traffic planning can significantly improve the efficiency of traffic operation.
LI Wen-jing, SUN Feng, LI Xi-yao, MA Dong-fang. Time-of-day breakpoints for traffic signal control using dynamic recurrence order clustering. JOURNAL OF ZHEJIANG UNIVERSITY (ENGINEERING SCIENCE), 2018, 52(6): 1150-1156.
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