{"title":"基于容量的城市道路网络关键节点识别","authors":"Guimin Gong, Wen-hong Lv, Ge Gao, Qi Wang","doi":"10.1109/ICCECE58074.2023.10135287","DOIUrl":null,"url":null,"abstract":"Based on the urban road traffic capacity, the identification of key nodes of urban road network is studied. Firstly, the urban road network model of undirected rights is constructed: the bearing capacity of nodes is measured by the number of lanes and the corresponding road traffic capacity of each lane, and the node importance function is established through three factors: node degree value, road section traffic capacity (edge weight) and distance between nodes. The global efficiency of the network and the maximum network connectivity subgraph were selected as the evaluation indicators to measure the network performance. The simulation analysis of the road network within Xin'an Street, Huangdao District, Qingdao City shows that compared with the degree centrality algorithm and mapping entropy algorithm, the proposed algorithm can identify the key nodes of the road network more accurately.","PeriodicalId":120030,"journal":{"name":"2023 3rd International Conference on Consumer Electronics and Computer Engineering (ICCECE)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2023-01-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Capacity-based identification of key nodes in urban road networks\",\"authors\":\"Guimin Gong, Wen-hong Lv, Ge Gao, Qi Wang\",\"doi\":\"10.1109/ICCECE58074.2023.10135287\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Based on the urban road traffic capacity, the identification of key nodes of urban road network is studied. Firstly, the urban road network model of undirected rights is constructed: the bearing capacity of nodes is measured by the number of lanes and the corresponding road traffic capacity of each lane, and the node importance function is established through three factors: node degree value, road section traffic capacity (edge weight) and distance between nodes. The global efficiency of the network and the maximum network connectivity subgraph were selected as the evaluation indicators to measure the network performance. The simulation analysis of the road network within Xin'an Street, Huangdao District, Qingdao City shows that compared with the degree centrality algorithm and mapping entropy algorithm, the proposed algorithm can identify the key nodes of the road network more accurately.\",\"PeriodicalId\":120030,\"journal\":{\"name\":\"2023 3rd International Conference on Consumer Electronics and Computer Engineering (ICCECE)\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-01-06\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2023 3rd International Conference on Consumer Electronics and Computer Engineering (ICCECE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCECE58074.2023.10135287\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2023 3rd International Conference on Consumer Electronics and Computer Engineering (ICCECE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCECE58074.2023.10135287","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Capacity-based identification of key nodes in urban road networks
Based on the urban road traffic capacity, the identification of key nodes of urban road network is studied. Firstly, the urban road network model of undirected rights is constructed: the bearing capacity of nodes is measured by the number of lanes and the corresponding road traffic capacity of each lane, and the node importance function is established through three factors: node degree value, road section traffic capacity (edge weight) and distance between nodes. The global efficiency of the network and the maximum network connectivity subgraph were selected as the evaluation indicators to measure the network performance. The simulation analysis of the road network within Xin'an Street, Huangdao District, Qingdao City shows that compared with the degree centrality algorithm and mapping entropy algorithm, the proposed algorithm can identify the key nodes of the road network more accurately.