太阳成8722(中国)有限公司-GREEN NO.1

标题: Graphic Simplification and Intelligent Adjustment Methods of Road Networks for Navigation with Reduced Precision

作者: Guo, QS (Guo, Qingsheng); Wang, HH (Wang, Huihui); He, J (He, Jie); Zhou, CQ (Zhou, Chuanqi); Liu, Y (Liu, Yang); Xing, B (Xing, Bin); Jia, ZJ (Jia, Zhijie); Li, M (Li, Meng)

来源出版物: ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION 卷: 9 期: 8 文献号: 490 DOI: 10.3390/ijgi9080490 出版年: AUG 2020

摘要: With the rapid development of high-precision road network maps, low-precision road network maps (basic data unrelated to hardware) will need to be directly produced for traditional navigation software from high-precision maps. To do so, large amounts of vector data representing road networks must be simplified and spatial directional similarity in road networks must be maintained while reducing precision. In this study, an elite strategy genetic algorithm based on the grid model is applied to spatial directional adjustment in road networks for producing road network maps for traditional navigation. Firstly, semantic features and critical vertices are extracted from the road network with high precision. Secondly, some high-precision vertices are eliminated under constraints of the digital navigation map. During this process, the local shape maintenance of the road is considered, and the destruction of the spatial topological relationships is avoided. Thirdly, a genetic algorithm for minimizing the total changes in road azimuths at nodes of road networks is developed to maintain spatial directional relationships while reducing precision. Experimental results and visualization effects on the test data of different cities show that this method is suitable for generating road network maps for traditional navigation software from high-precision ones.

入藏号: WOS:000565072500001

语言: English

文献类型: Article

作者关键词: road network; simplification; improved Opheim algorithm; precision reduction; spatial directional relationship; genetic algorithm

KeyWords Plus: LINE SIMPLIFICATION; SPATIAL SIMILARITY; ALGORITHMS; MULTISCALE; POLYLINES

地址: [Guo, Qingsheng; Wang, Huihui; He, Jie; Zhou, Chuanqi; Liu, Yang] Wuhan Univ, Sch Resource & Environm Sci, Wuhan 430079, Peoples R China.

[Xing, Bin; Jia, Zhijie; Li, Meng] Beijing NavInfo Polytron Technol Inc, Beijing 100094, Peoples R China.

通讯作者地址: Guo, QS (corresponding author)，Wuhan Univ, Sch Resource & Environm Sci, Wuhan 430079, Peoples R China.

电子邮件地址: guoqingsheng@whu.edu.cn; wanghh@whu.edu.cn; hejie.chn@whu.edu.cn; Legend21@whu.edu.cn; 2015202050050@whu.edu.cn; xingbin@navinfo.com; jiazhijie@navinfo.com; limeng2978@navinfo.com

影响因子：2.239