通过深度反强化学习和多意图建模实现低采样率轨迹的地图匹配

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

International Journal of Geographical Information Science Pub Date : 2024-08-19 DOI:10.1080/13658816.2024.2391411

Reza Safarzadeh, Xin Wang

引用次数: 0

摘要

由于环境条件和硬件限制会影响数据的准确性，因此使用 GPS 轨迹数据分析货运车辆的移动情况是一项挑战。地图匹配是一个将数据与地图相匹配的过程。

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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Map matching on low sampling rate trajectories through deep inverse reinforcement learning and multi-intention modeling

Analyzing freight vehicle movements using GPS trajectory data presents challenges due to environmental conditions and hardware limitations impacting data accuracy. Map matching, the process of alig...

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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.