摘要
本文以北京城市交通为例,选取北京城市路网数据,计算城市路网介数中心性,以反映城市各道路路段的通达情况;并利用北京出租车GPS定点数据,计算实际的交通轨迹。传统的路网介数中心性主要依据各路段最短路径的比重评价理论上的道路通达性,而本文以网络介数中心性为基础,提出动态介数的方法,从城市各路段交通量比重的角度评价各道路实际拥堵情况。利用两个介数的对比能够全面客观地反映交通拥堵状况,提高交通拥堵指数的参考价值,并为城市建设规划决策及道路改建等方案提供依据,有利于缓解城市道路交通拥堵现状。
Traditional betweenness centrality of road network mainly evaluates the theoretical road accessibility based on the proportion of the shortest paths in each section. Based on the traditional network betweenness centrality, this study proposes dynamic betweenness, as a new urban traffic congestion index, to evaluate the actual congestion of each section in the city from the perspective of the proportion of traffic volume. This paper calculates the betweenness of urban road network to reflect the accessibility of urban road sections, and calculates the dynamic betweenness and traffic trajectory with taxi GPS fixed-point data. The comparison of the two betweennesses can objectively and comprehensively reflect the traffic congestion, improves the reference value of the traffic congestion index, and provides a basis for decision-making for urban construction planning and road reconstruction, which contributes to alleviating the situation of urban road traffic congestion.
作者
叶烨星
杨飞
YE Yexing;YANG Fei(Institute of Geographic Sciences and Natural Resources Research,Chinese Academy of Sciences,Beijing 100101,China)
出处
《测绘通报》
CSCD
北大核心
2021年第5期86-90,共5页
Bulletin of Surveying and Mapping
关键词
介数中心性
动态介数
交通拥堵指数
机器学习
地图匹配
betweenness centrality
dynamic betweenness
traffic congestion index
machine learning
map matching