平行车联网:基于ACP的智能车辆网联管理与控制

王晓; 要婷婷; 韩双双; 曹东璞; 王飞跃

doi:10.16383/j.aas.2018.c170463

平行车联网:基于ACP的智能车辆网联管理与控制

doi: 10.16383/j.aas.2018.c170463

王晓^1,2,,
要婷婷^1,3,,
韩双双^1,2,3,,
曹东璞^2,4,,
王飞跃^1,5, ,

1.
中国科学院自动化研究所复杂系统管理与控制国家重点实验室北京 100190 中国
2.
青岛智能产业技术研究院青岛 266000 中国
3.
青岛慧拓智能机器有限公司青岛 266000 中国
4.
滑铁卢大学机械和机电工程学院滑铁卢 N2L 3G1 加拿大
5.
国防科技大学军事计算实验与平行系统技术中心长沙 410073 中国

基金项目:

国家自然科学基金 61533019

国家自然科学基金 61702519

国家自然科学基金 91720000

国家自然科学基金 61501461

详细信息

作者简介:
王晓中国科学院自动化研究所复杂系统管理与控制国家重点实验室助理研究员.2016年获得中国科学院大学社会计算博士学位.研究方向为社会交通, 动态网群组织, 人工智能和社交网络分析.E-mail:x.wang@ia.ac.cn

要婷婷中国科学院自动化研究所复杂系统管理与控制国家重点实验室工程师.2015年、2016年分别获得英国伯明翰大学、北京交通大学硕士学位.主要研究方向为平行驾驶与数据挖掘.E-mail:tingting.yao@ia.ac.cn

韩双双中国科学院自动化研究所复杂系统管理与控制国家重点实验室助理研究员.2013年获得加拿大阿尔伯塔大学博士学位.主要研究方向为平行网络、物联网、智能交通、无线通信关键技术.E-mail:shuangshuang.han@ia.ac.cn

曹东璞加拿大滑铁卢大学副教授, 驾驶员认知与自动驾驶实验室主任.中国科学院自动化研究所客座研究员.主要研究方向为自动驾驶, 人车协同与平行驾驶.E-mail:dongpu@uwaterloo.ca

通讯作者:
王飞跃中国科学院自动化研究所复杂系统管理与控制国家重点实验室主任, 国防科技大学军事计算实验与平行系统技术研究中心主任, 中国科学院大学中国经济与社会安全研究中心主任, 青岛智能产业技术研究院院长.主要研究方向为平行系统的方法与应用, 社会计算, 平行智能以及知识自动化.本文通信作者.E-mail:feiyue.wang@ia.ac.cn

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出版历程
- 收稿日期: 2017-08-28
- 录用日期: 2017-10-30
- 刊出日期: 2018-08-20

Parallel Internet of Vehicles:The ACP-based Networked Management and Control for Intelligent Vehicles

WANG Xiao^{1,2
,},
YAO Ting-Ting^{1,3
,},
HAN Shuang-Shuang^{1,2,3
,},
CAO Dong-Pu^{2,4
,},
WANG Fei-Yue^{1,5
, ,}

1.
The State Key Laboratory for Management and Control of Complex Systems, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China
2.
Qingdao Academy of Intelligent Industries, Qingdao 266000, China
3.
Vehicle Intelligence Pioneers Inc., Qingdao 266000, China
4.
School of Mechanical and Mechatronics Engineering, University of Waterloo, Waterloo N2L 3 1, Canada
5.
Research Center of Military Computational Experiments and Parallel Systems, National University of Defense Technology, Changsha 410073, China

Funds:

National Natural Science Foundation of China 61533019

National Natural Science Foundation of China 61702519

National Natural Science Foundation of China 91720000

National Natural Science Foundation of China 61501461

More Information

Author Bio:
Assistant professor at the State Key Laboratory for Management and Control of Complex Systems, Institute of Automation, Chinese Academy of Sciences.She received her Ph.D.degree in social computing from University of Chinese Academy of Sciences, in 2016.Her research interest covers social transportation, cyber movement organizations, artificial intelligence, and social network analysis

Engineer at the State Key Laboratory for Management and Control of Complex Systems, Institute of Automation, Chinese Academy of Sciences.She received her master degree from University of Birmingham and Beijing Jiaotong University in 2015 and 2016, respectively.Her research interest covers parallel driving and data mining

Assistant professor at the State Key Laboratory for Management and Control of Complex Systems, Institute of Automation, Chinese Academy of Sciences.She received her Ph.D.degree from University of Alberta, Canada, in 2013.Her research interest covers parallel networks, internet of things, intelligent transportation system and wireless communications

Associate professor, director of Driver Cognition and Automated Driving Laboratory, University of Waterloo, Canada.Visiting professor at Institute of Automation, Chinese Academy of Sciences.His research interest covers automated driving, driver-automation collaboration and parallel driving.

Corresponding author: WANG Fei-Yue State specially appointed expert and director of the State Key Laboratory for Management and Control of Complex Systems, Institute of Automation, Chinese Academy of Sciences.Professor of the Research Center for Computational Experiments and Parallel Systems Technology, National University of Defense Technology.Director of China Economic and Social Security Research Center in University of Chinese Academy of Sciences.Dean of Qingdao Academy of Intelligent Industries.His research interest covers methods and applications for parallel systems, social computing, parallel intelligence, and knowledge automation.Corresponding author of this paper

摘要

摘要: 本文将平行智能方法引入智能车辆的网联化管理与控制, 提出平行车联网的概念、框架、功能与流程.平行车联网致力于通过人工车联网与物理车联网的虚实互动、协同演化与闭环反馈, 为人-车-路-智能交通信息网一体化的智能交通系统增加计算实验与平行引导的功能, 实现描述、预测与引导相结合的车联网智能, 有效解决异构、移动、融合的交通网络环境下智能车辆的管理与控制问题.
- 平行智能 /
- 平行车联网 /
- 智能交通系统 /
- 计算实验
Abstract: This paper applies the ACP-based parallel intelligence methods into the networked management and control for intelligent vehicles, and proposes the concepts, frameworks, capabilities and processes of Parallel Internet of Vehicles (PIoV).Via the construction of artificial IoV systems that perform interaction, co-evolution, and closed-loop feedback with IoV systems, PIoV aims to offer the human-vehicle-road-traffic information integrated IoV systems with key capabilities including computational experiments, parallel planning and decision-making, thus realizing the effective management and control of intelligent vehicles in the time-varying, heterogeneous, complex traffic environment with descriptive intelligence, predictive intelligence and prescriptive intelligence.
- Parallel intelligence /
- parallel internet of vehicles /
- intelligent transportation systems /
- computational experiments
注释:

1) 本文责任编委张俊

HTML全文

图 1 基于ACP的平行智能架构体系

Fig. 1 Framework of the ACP-based parallel intelligence approach

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图 2 复杂系统的建模鸿沟

Fig. 2 Modeling gap from Newton$'$s world to Merton$'$s world

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图 3 面向CPSS的平行智能体系架构

Fig. 3 CPSS-oriented parallel intelligent architecture

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图 4 平行交通系统PtMS组成

Fig. 4 Composition of PtMS

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图 5 车联网基本架构体系

Fig. 5 General infrastructure of IoV systems

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图 6 平行车联网基本框架

Fig. 6 Framework of PIoV

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图 7 人工车联网子系统组成

Fig. 7 Composition of artificial IoV (AIoV) subsystem

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图 8 基于多智能体建模的人-车-路互动示意图

Fig. 8 Illustration of the human-vehicle-road interaction in AIoV based on multi-agent modeling

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图 9 "计算实验室"中实验设计示意

Fig. 9 Experiment design in computational experiment laboratory

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图 10 基于复杂自适应系统的动态网络分配方法的计算实验

Fig. 10 Framework of dynamic network assignment based on complex adaptive systems

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图 11 平行车联网架构

Fig. 11 Architecture of PIoV

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图 12 平行车辆的虚实互动、平行执行

Fig. 12 Virtual interaction and parallel execution between parallel vehicles

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