大数据环境下的车路人协同控制模型VID

计算机科学 ›› 2019, Vol. 46 ›› Issue (11A): 185-188.

大数据环境下的车路人协同控制模型VID

程显毅^1,2, 施佺², 朱建新³, 陈凤妹¹, 代冉冉¹

(硅湖职业技术学院江苏昆山215300)¹;
(南通大学交通工程学院江苏南通226019)²;
(武汉理工大学信息工程学院武汉430010)³

出版日期:2019-11-10 发布日期:2019-11-20
通讯作者: 程显毅(1956-),男,博士,教授,主要研究方向为大数据应用、自然语言处理,E-mail:xycheng@ntu.edu。
基金资助:
本文受国家自然科学基金项目(61771265),江苏省现代教育技术研究课题(2017-R-54131),江苏省高等教育学会职业能力研究委员会课题(ZY2018C008),江苏省“333工程”(BRA2017475)资助。

VID Model of Vehicles-infrastructure-driver Collaborative Control in Big Data Environment

CHENG Xian-yi^1,2, SHI Quan², ZHU Jian-xin³, CHEN Feng-mei¹, DAI Ran-ran¹

(Silicon Lake College,Kunshan,Jiangsu 215300,China)¹;
(College of Traffic Engineering,Nantong University,Nantong,Jiangsu 226019,China)²;
(School of Information Engineering,Wuhan University of Technology,Wuhan 430010,China)³

Online:2019-11-10 Published:2019-11-20

摘要/Abstract

摘要： 针对车联网集中控制方式存在严重的数据冗余现象,及多源数据相互增强的实施成本高的问题,文中从大数据的角度描述了车路人协同控制模型VID(Vehicles-infrastructure-driver)。该模型是由集中控制的感知中心和分布式控制的任务执行过程组成的混合式控制系统。统一的感知中心可提供公共感知服务,整合感知资源管理、任务调度与数据收集功能。基于“去中心化的“车路协同系统”“人车协同系统”和“驾驶员行为分析”执行感知任务。VID模型打通了从感知到服务的全局循环与局部循环,针对需要协同的应用场景均有较好的适用性。

关键词: 车联网, 车路人协同, 大数据, 群智感知计算, 协同控制

Abstract: Aiming at the serious redundancy in the centralized control mode of Internet of vehicles,and the high cost implementation of mutually reinforcing inmulti-source data,this paper described the VID (Vehicles-Infrastructure-driver) model of collaborative control from the perspective of big data.The model consists of perception center and distributed task execution.The unified perception center provides public perception services and integrates perception resource management,task scheduling and data collection.Vehicles-infrastructure Cooperative System (VCS),Driver-Vehicles Cooperative System and Driver Behavior Analysis perform perceptual tasks in a decentralized way.The VID model opens up the global and local loops from perception to service,and has good applicability for scenarios requiring collaborations.

Key words: Big data, Collaborative control, Internet of vehicles, Swarm intelligence computing, Vehicles-infrastructure-driver coordination

中图分类号:

U471

程显毅, 施佺, 朱建新, 陈凤妹, 代冉冉. 大数据环境下的车路人协同控制模型VID[J]. 计算机科学, 2019, 46(11A): 185-188. https://doi.org/

CHENG Xian-yi, SHI Quan, ZHU Jian-xin, CHEN Feng-mei, DAI Ran-ran. VID Model of Vehicles-infrastructure-driver Collaborative Control in Big Data Environment[J]. Computer Science, 2019, 46(11A): 185-188. https://doi.org/

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