北京邮电大学学报

  • EI核心期刊

北京邮电大学学报 ›› 2019, Vol. 42 ›› Issue (3): 91-97.doi: 10.13190/j.jbupt.2018-230

• 研究报告 • 上一篇    下一篇

基于出租车轨迹数据的车联网通信机会间隔模型

皇甫伟1,2, 杨心竹1, 王欢1,2, 胡晓彦3   

  1. 1. 北京科技大学 计算机与通信工程学院人工智能研究院, 北京 100083;
    2. 北京市融合网络与泛在业务工程技术研究中心, 北京 100083;
    3. 中国移动通信集团设计院有限公司, 北京 100080
  • 收稿日期:2018-09-11 出版日期:2019-06-28 发布日期:2019-06-20
  • 作者简介:皇甫伟(1975-),男,副教授,E-mail:huangfuwei@ustb.edu.cn.
  • 基金资助:
    教育部-中国移动科研基金项目(MCM20160103)

Modeling the Statistical Distribution of the Inter-Contact Times for Communication Opportunities in Vehicle Networks

HUANGFU Wei1,2, YANG Xin-zhu1, WANG Huan1,2, HU Xiao-yan3   

  1. 1. Institute of Artificial Intelligence, School of Computer and Communication Engineering, University of Science and Technology Beijing, Beijing 100083, China;
    2. Beijing Engineering and Technology Research Center for Convergence Networks and Ubiquitous Services, Beijing 100083, China;
    3. China Mobile Group Design Institute Co., Ltd., Beijing 100080, China
  • Received:2018-09-11 Online:2019-06-28 Published:2019-06-20

摘要: 针对车联网中车辆间相遇机会间隔的统计分布模型及其参数估计问题,基于北京市出租车轨迹大数据,提出了基于栅格划分和地理哈希值索引的过滤查找方法和轨迹内插方法以高效提取车辆间的相遇机会时刻,进而对机会间隔进行统计建模、参数估计和假设检验.模型呈现分段分布,在小尺度时间间隔上呈指数分布,在大尺度间隔上呈对数正态分布,并具有重尾特征.

关键词: 车联网, 机会网络, 通信机会间隔, 车辆密度, 统计模型

Abstract: As a kind of opportunistic networks, the vehicle network, in which vehicles communicate instantaneously with each other only when they meet opportunely, attracts more and more attentions. The inter-contact times of communication opportunities depend on the factors such as the vehicle moving model and the vehicle density. Based on the data of the taxi traces in Beijing city, an efficient method which combines the GeoHash-based filter and the trace interpolation is proposed to extract all the instants of the communication opportunities to model the statistical distribution. It is concluded that the inter-contact times obey an exponential distribution if the interval is small while a log-normal one if the interval is large. Such a piecewise heavy-tailed distribution will affect the design of the vehicle networks to some extent.

Key words: internet of vehicles, opportunistic networks, inter-contact times, vehicle density, statistical model

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