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A knowledge graph construction method based on co-occurrence for traffic entity prediction

delete2025-07-07
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PRE
AI
Z
Zhangcai Yin
Y
Yiran Chen *
S
Shen Ying
郭圆 封面图
郭圆 (Yuan Guo) *
DOI:10.1016/j.jag.2025.104717delete
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摘要

摘要

En 中文
• 单纯的实时感知无法满足防御性驾驶的安全响应要求。 • 实时感知中的共现关系提升了危险实体的预测性认知。 • 风险实体的预测提供关键的早期预警信息,并允许宝贵的响应窗口。 • 共现知识图谱及其概率矩阵推进了前瞻性感知技术的发展。
Keyword:
Co-occurrence relationship
Knowledge graph
Traffic entity prediction
Automated driving
Digital twins
High-definition maps
AI总结

AI总结

对已上传原文的论文进行重点信息的提取,主要内容包括:简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。

期刊

International Journal of Applied Earth Observation and Geoinformation 封面图
International Journal of Applied Earth Observation and Geoinformation
IF:
8.6
论文数:
5.3K
被引数:
2.4W

机构

W
Wuhan University of Technology
学者数:
3.4W
论文数: 2.4W
被引数: 4.4W
W
wuhan university
学者数:
8.1W
论文数: 5.8W
被引数: 70
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