基于拓扑强度的核心慢行道路识别和网络分级

邬岚 ,  杨奇缘 ,  陈茜 ,  陆文瑄 ,  张小奕

科学技术与工程 ›› 2024, Vol. 24 ›› Issue (34) :14854-14862

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科学技术与工程 ›› 2024, Vol. 24 ›› Issue (34) :14854-14862 DOI: 10.12404/j.issn.1671-1815.2401504
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基于拓扑强度的核心慢行道路识别和网络分级

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Core Non-motorized Road Identification and Network Classification Based on Topological Intensity

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摘要

核心慢行道路承担着慢行路网中最大的步行流量和非机动车流量,并以其补充衔接公共交通和服务周边等多种功能,构成慢行路网的骨架。在进行网络分级的同时,合理准确地识别核心慢行道路并针对其加强建设有助于进一步提升慢行出行吸引力,对居民慢行出行及活力城市的建设具有重要意义。以扬州老城区慢行路网为例,在构建P空间慢行网络的基础上,通过拓扑强度识别核心慢行道路,与模糊聚类分析得到的慢行路网层次划分方案进行对比。实验表明,在两种方法的层次划分方案中,拓扑强度的实验结果能对核心慢行道路进一步补充完善。

Abstract

The core non-motorized road is responsible for the largest pedestrian and non-motorized traffic in the non-motorized road network. It forms the skeleton of the non-motorized road network with its various functions such as connecting public transportation and service surroundings. While carrying out network classification, reasonably and accurately identifying the core non-motorized road and strengthening its construction can help further improve the attractiveness of non-motorized travel, which is of great significance to non-motorized travel and the construction of dynamic cities. Taking the non-motorized road network in the old town of Yangzhou as an example, based on constructing the non-motorized network in P-space, the core non-motorized road was identified by topological intensity, and the hierarchical division scheme of non-motorized road network obtained by fuzzy cluster analysis was compared. Experiments show that the experimental results of topological strength can further supplement and improve the core non-motorized road in the hierarchical division scheme of the two methods.

关键词

慢行交通 / 核心慢行道路 / 网络分级 / 拓扑强度 / P空间法

Key words

non-motorized traffic / core non-motorized roads / network classification / topological intensity / P-space method

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邬岚, 杨奇缘, 陈茜, 陆文瑄, 张小奕. 基于拓扑强度的核心慢行道路识别和网络分级[J]. 科学技术与工程, 2024, 24(34): 14854-14862 DOI:10.12404/j.issn.1671-1815.2401504
WU Lan, YANG Qi-yuan, CHEN Qian, LU Wen-xuan, ZHANG Xiao-yi. Core Non-motorized Road Identification and Network Classification Based on Topological Intensity[J]. Science Technology and Engineering, 2024, 24(34): 14854-14862 DOI:10.12404/j.issn.1671-1815.2401504

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国家重点研发计划(2020YFB1600500)

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