Detecting road network errors from trajectory data with partial map matching and bidirectional recurrent neural network model

IF 4.3 1区地球科学 Q1 COMPUTER SCIENCE, INFORMATION SYSTEMS

International Journal of Geographical Information Science Pub Date : 2024-01-24 DOI:10.1080/13658816.2024.2306158

Can Yang, Peng Yue, Jianya Gong, Jian Li, Kai Yan

引用次数: 0

Abstract

Ensuring the correctness of road network data is critical for navigation, traffic control and urban planning. Errors like missing roads and absent connections can hinder its quality. Trajectory dat...

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利用部分地图匹配和双向递归神经网络模型从轨迹数据中检测路网误差

确保路网数据的正确性对于导航、交通控制和城市规划至关重要。道路缺失和连接缺失等错误会影响数据质量。轨迹数据的准确性和可靠性对导航、交通控制和城市规划至关重要。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

International Journal of Geographical Information Science 地学-计算机：信息系统

CiteScore

11.00

自引率

7.00%

发文量

审稿时长

9 months

期刊介绍： International Journal of Geographical Information Science provides a forum for the exchange of original ideas, approaches, methods and experiences in the rapidly growing field of geographical information science (GIScience). It is intended to interest those who research fundamental and computational issues of geographic information, as well as issues related to the design, implementation and use of geographical information for monitoring, prediction and decision making. Published research covers innovations in GIScience and novel applications of GIScience in natural resources, social systems and the built environment, as well as relevant developments in computer science, cartography, surveying, geography and engineering in both developed and developing countries.