Study on Traffic Flow Patterns Identification of Single Intersection Intelligent Signal Control

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• 作者：Yun Zhu ; ^{18260089839@163.com" class="auth_mail" title="E-mail the corresponding author} ; Ningbo Gao ; Jianyu Wang ; Chen Liu
• 关键词：intersection ; traffic flow patterns ; Fuzzy C-Means ; quality evaluation ; clustering algorithm.
• 刊名：Procedia Engineering
• 出版年：2016
• 出版时间：2016
• 年：2016
• 卷：137
• 期：Complete
• 页码：452-460
• 全文大小：617 K

文摘

To improve the level of intersection traffic management, we research traffic flow patterns of intersections. Based on Fuzzy C-Means clustering algorithm, this paper finished quality evaluating on cluster center value and optimizing the clustering process through combining with comprehensive evaluation method of fuzzy clustering quality. Based on above contents we proposed a process to recognize intersection traffic flow pattern based on fuzzy c-means clustering. After analyzing example like intersection of West Beijing Road and Xi Kang Road in Nanjing, we obtained this intersection traffic flow can be divided into high peak, evening peak, flat peak in morning, afternoon, and noon peak 5 modes from field data. Then we simulated and analyzed the delay to verify the effectiveness and practicality of the method.