An identification model of urban critical links with macroscopic fundamental diagram theory

详细信息    查看全文

• 作者：Wanli Dong ; Yunpeng Wang ; Haiyang Yu
• 关键词：urban road network ; critical links ; intelligent transportation system ; macroscopic fundamental diagram
• 刊名：Frontiers of Computer Science
• 出版年：2017
• 出版时间：February 2017
• 年：2017
• 卷：11
• 期：1
• 页码：27-37
• 全文大小：
• 刊物类别：Computer Science
• 刊物主题：Computer Science, general;
• 出版者：Higher Education Press
• ISSN：2095-2236
• 卷排序：11

文摘

How to identify the critical links of the urban road network for actual traffic management and intelligent transportation control is an urgent problem, especially in the congestion environment. Most previous methods focus on traffic static characteristics for traffic planning and design. However, actual traffic management and intelligent control need to identify relevant sections by dynamic traffic information for solving the problems of variable transportation system. Therefore, a city-wide traffic model that consists of three relational algorithms, is proposed to identify significant links of the road network by using macroscopic fundamental diagram (MFD) as traffic dynamic characteristics. Firstly, weightedtraffic flow and density extraction algorithm is provided with simulation modeling and regression analysis methods, based on MFD theory. Secondly, critical links identification algorithm is designed on the first algorithm, under specified principles. Finally, threshold algorithm is developed by cluster analysis. In addition, the algorithms are analyzed and applied in the simulation experiment of the road network of the central district in Hefei city, China. The results show that the model has good maneuverability and improves the shortcomings of the threshold judged by human. It provides an approach to identify critical links for actual traffic management and intelligent control, and also gives a new method for evaluating the planning and design effect of the urban road network.