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RHTP-STD:基于时空数据库的实时启发式轨迹预测模型

李任杰 乔少杰 李庆 蒋宇河 李洲 甘戈 陈浩 卓小军 韩楠

无线电通信技术2025,Vol.51Issue(3):466-477,12.
无线电通信技术2025,Vol.51Issue(3):466-477,12.DOI:10.3969/j.issn.1003-3114.2025.03.005

RHTP-STD:基于时空数据库的实时启发式轨迹预测模型

RHTP-STD:Real-time Heuristic Trajectory Prediction Based on Spatio-Temporal Databases

李任杰 1乔少杰 1李庆 1蒋宇河 1李洲 1甘戈 2陈浩 3卓小军 4韩楠5

作者信息

  • 1. 成都信息工程大学 软件工程学院,四川 成都 610225
  • 2. 成都市公安局 监所管理支队,四川 成都 611731
  • 3. 成都市公安局 科技信息化处,四川 成都 610017
  • 4. 四川九门科技股份有限公司,四川 成都 610046
  • 5. 成都信息工程大学 管理学院,四川 成都 610225
  • 折叠

摘要

Abstract

With pervasiveness of mobile devices and internet of things technologies,collection and analysis of spatio-temporal data become increasingly important.Trajectory prediction,especially real-time trajectory prediction,is crucial for various application fields,such as intelligent transportation and urban planning.However,existing trajectory prediction methods often fail to guarantee prediction accuracy as well as meet real-time requirement.Moreover,real-time data is usually incomplete or noisy,necessitating that prediction algorithms adapt to incomplete trajectory information.To address these challenges,Real-time Heuristic Trajectory Prediction Based on Spatio-Temporal Databases(RHTP-STD)is proposed.RHTP-STD utilizes MobilityDB database platform to store and manage trajectory data and employs a graph construction algorithm to transform trajectory data into spatio-temporal graphs.Subsequently,RHTP-STD em-ploys a heuristic algorithm that integrates historical and real-time data to rapidly predict future trajectories of moving objects.Experi-mental results on Argoverse dataset demonstrate that RHTP-STD outperforms existing methods in terms of prediction accuracy and real-time performance.Furthermore,applicability of RHTP-STD in different application scenarios is discussed,and potential future re-search directions are presented.

关键词

时空数据库/实时处理/轨迹预测/启发式算法

Key words

spatio-temporal databases/real-time processing/trajectory prediction/heuristic algorithm

分类

信息技术与安全科学

引用本文复制引用

李任杰,乔少杰,李庆,蒋宇河,李洲,甘戈,陈浩,卓小军,韩楠..RHTP-STD:基于时空数据库的实时启发式轨迹预测模型[J].无线电通信技术,2025,51(3):466-477,12.

基金项目

国家自然科学基金(62272066) (62272066)

四川省科技计划资助(2025ZNSFSC0044,2025YFHZ0194) (2025ZNSFSC0044,2025YFHZ0194)

成都市技术创新研发项目重点项目(2024-YF08-00029-GX) (2024-YF08-00029-GX)

成都市技术创新研发项目(2024-YF05-01217-SN) (2024-YF05-01217-SN)

成都市区域科技创新合作项目(2025-YF11-00050-HZ) (2025-YF11-00050-HZ)

网络空间安全教育部重点实验室及河南省网络空间态势感知重点实验室开放基金课题(KLCS20240106) (KLCS20240106)

网络空间大数据智能安全教育部重点实验室开放基金课题(CBDIS202404) National Natural Science Foundation of China(62272066) (CBDIS202404)

Sichuan Science and Technology Program(2025ZNSFSC0044,2025YFHZ0194) (2025ZNSFSC0044,2025YFHZ0194)

Chengdu Technological Innovation Research and Development Major Project(2024-YF08-00029-GX) (2024-YF08-00029-GX)

Chengdu Technological In-novation Research and Development Project(2024-YF05-01217-SN) (2024-YF05-01217-SN)

Chengdu Regional Science and Technology Innovation Cooperation Project(2025-YF11-00050-HZ) (2025-YF11-00050-HZ)

Open Foundation of Key Laboratory of Cyberspace Security,Ministry of Education of China and Henan Key Laboratory of Cy-berspace Situation Awareness(KLCS20240106) (KLCS20240106)

Open Research Fund of Key Laboratory of Cyberspace Big Data Intelligent Security(Chongqing Univer-sity of Posts and Telecommunications),Ministry of Education of China Under Grant(CBDIS202404) (Chongqing Univer-sity of Posts and Telecommunications)

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