城市场景中车联网时空数据分析及其通达性方法
Spatio-temporal data analysis and accessibility method for IoV in an urban scene
- 通信学报 2021年42卷第6期 页码：52-61
- 作者机构：
1. 同济大学嵌入式系统与服务计算教育部重点实验室，上海 200092
2. 安徽大学计算机科学与技术学院，安徽 合肥 230601
3. 同济大学机械与能源工程学院，上海 200092
4. 上海师范大学天华学院，上海 201815
5. 同济大学电子与信息工程学院，上海 200092
- 作者简介：
[ "程久军（1974− ），男，安徽怀宁人，博士，同济大学教授、博士生导师，主要研究方向为车联网、无人驾驶等" ]
[ "原桂远（1993− ），男，山东烟台人，同济大学博士生，主要研究方向为车联网、无人驾驶等" ]
[ "崔杰（1980− ），男，河南淮阳人，博士，安徽大学教授、博士生导师，主要研究方向为车联网安全、物联网安全等" ]
[ "周爱国（1973− ），男，湖南株洲人，博士，同济大学副教授、博士生导师，主要研究方向为机器人控制、无人驾驶等" ]
[ "吕博（1977− ），女，辽宁抚顺人，博士，上海师范大学副教授，主要研究方向为计算机视觉、机器学习等" ]
[ "李光耀（1965− ），男，安徽安庆人，博士，同济大学教授、博士生导师，主要研究方向为图形图像、数据挖掘及人工智能等" ]
- 基金信息：国家自然科学基金资助项目(61872271);中央高校基本科研业务费重点领域学科交叉重大基金资助项目(22120190208);网络与交换技术国家重点实验室（北京邮电大学）开放课题基金资助项目(SKLNST-2020-1-20)
DOI：10.11959/j.issn.1000-436x.2021110
中图分类号： TP391.9-
网络首发：2021-06，
纸质出版：2021-06-25
- 稿件说明：
移动端阅览
程久军, 原桂远, 崔杰, 等. 城市场景中车联网时空数据分析及其通达性方法[J]. 通信学报, 2021,42(6):52-61.
Jiujun CHENG, Guiyuan YUAN, Jie CUI, et al. Spatio-temporal data analysis and accessibility method for IoV in an urban scene[J]. Journal on Communications, 2021, 42(6): 52-61.
程久军, 原桂远, 崔杰, 等. 城市场景中车联网时空数据分析及其通达性方法[J]. 通信学报, 2021,42(6):52-61. DOI： 10.11959/j.issn.1000-436x.2021110.
Jiujun CHENG, Guiyuan YUAN, Jie CUI, et al. Spatio-temporal data analysis and accessibility method for IoV in an urban scene[J]. Journal on Communications, 2021, 42(6): 52-61. DOI： 10.11959/j.issn.1000-436x.2021110.
摘要
为了解决城市场景中车联网时空数据异构以及单个基础设施范围内存在连通效率低下的问题，提出一种车联网时空数据分析及其通达性方法。首先，给出基于噪声去除和数据填充的时空数据分析方法，构建基于张量因子聚合的神经网络预测车辆之间的连通强度；然后，基于车联网连通强度给出有基础设施车联网的通达性方法。仿真实验结果表明，基于张量因子聚合的神经网络可以有效预测车辆之间的连通强度，所提方法可以有效减少连通冗余和路边基础设施负载。
Abstract
In order to solve the problems of diversity spatio-temporal data and low connectivity efficiency in a single road side unit for Internet of vehicles (IoV) in an urban scene
a spatio-temporal data analysis and accessibility method was presented.First
a spatio-temporal data analysis method based on de-noising and data filling was introduced
and a tensor factor aggregation-based neural network was constructed to predict connectivity intensity among vehicles.Then
a connectivity intensity prediction-based accessibility method was proposed.The simulation results demonstrate that the proposed connectivity intensity prediction method can accurately predict connectivity intensity among vehicles
and the proposed accessibility method can effectively reduce connectivity redundancy and loads of road side units.
关键词
Keywords
references
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