The Cognitive Internet of Vehicles for Autonomous Driving

被引:98
|
作者
Lu, Huimin [1 ,2 ,3 ]
Liu, Qiang [7 ]
Tian, Daxin [8 ]
Li, Yujie [9 ]
Kim, Hyoungseop [4 ]
Serikawa, Seiichi [5 ,6 ]
机构
[1] Kyushu Inst Technol, DC2 PD & FPD, Kitakyushu, Fukuoka, Japan
[2] Kyushu Inst Technol, Kitakyushu, Fukuoka, Japan
[3] Yangzhou Univ, Yangzhou, Jiangsu, Peoples R China
[4] Kyushu Inst Technol, Dept Control Engn, Kitakyushu, Fukuoka, Japan
[5] Kyushu Inst Technol, Ctr Sociorobot Synth, Kitakyushu, Fukuoka, Japan
[6] Kyushu Inst Technol, Dept Elect & Elect Engn, Kitakyushu, Fukuoka, Japan
[7] Beijing Jiaotong Univ, Sch Comp & Informat Technol, Beijing, Peoples R China
[8] Beihang Univ, Sch Transportat Sci & Engn, Beijing, Peoples R China
[9] Fukuoka Univ, Fukuoka, Fukuoka, Japan
来源
IEEE NETWORK | 2019年 / 33卷 / 03期
基金
中国国家自然科学基金;
关键词
CARS;
D O I
10.1109/MNET.2019.1800339
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
As it combines Al and IoT, autonomous driving has attracted a great deal of attention from both academia and industry because of its benefits to the economy and society. However, ultra-low delay and ultra-high reliability cannot be guaranteed by individual autonomous vehicles with limited intelligence and the existing architectures of the Internet of Vehicles. In this article, based on a cloud/fog-computing pattern and the IoT Al service framework, we propose a cross-domain solution for auto-driving. In contrast to existing studies, which mainly focus on communication technologies, our solution achieves intelligent and flexible autonomous driving task processing and enhances transportation performance with the help of the Cognitive Internet of Vehicles. We first present an overview of the enabling technology and the architecture of the Cognitive Internet of Vehicles for autonomous driving. Then we discuss the autonomous driving Cognitive Internet of Vehicles specifically from the perspectives of what to compute, where to compute, and how to compute. Simulations are then conducted to prove the effect of the Cognitive Internet of Vehicles for autonomous driving. Our study explores the research value and opportunities of the Cognitive Internet of Vehicles in autonomous driving.
引用
收藏
页码:65 / 73
页数:9
相关论文
共 50 条
  • [11] Overview and prospect of communication-sensing-computing integration for autonomous driving in the internet of vehicles
    Ma, Zhong-Gui
    Li, Zhuo
    Liang, Yan-Peng
    [J]. Gongcheng Kexue Xuebao/Chinese Journal of Engineering, 2023, 45 (01): : 137 - 149
  • [12] Cognitive Internet of Vehicles
    Chen, Min
    Tian, Yuanwen
    Fortino, Giancarlo
    Zhang, Jing
    Humar, Iztok
    [J]. COMPUTER COMMUNICATIONS, 2018, 120 : 58 - 70
  • [13] A COMPUTATIONAL MODEL OF DRIVING FOR AUTONOMOUS VEHICLES
    REECE, DA
    SHAFER, SA
    [J]. TRANSPORTATION RESEARCH PART A-POLICY AND PRACTICE, 1993, 27 (01) : 23 - 50
  • [14] Trust in AI in Autonomous Driving Vehicles
    Lian, Ru
    Siau, Keng
    [J]. AMCIS 2020 PROCEEDINGS, 2020,
  • [15] Assuring Responsible Driving of Autonomous Vehicles
    Schoener, Hans-Peter
    [J]. 2022 IEEE INTELLIGENT VEHICLES SYMPOSIUM (IV), 2022, : 718 - 722
  • [16] Are Autonomous Vehicles the Solution to Drowsy Driving?
    Grunstein, Daniel
    Grunstein, Ron
    [J]. INTELLIGENT HUMAN SYSTEMS INTEGRATION 2020, 2020, 1131 : 27 - 33
  • [17] Prospects for Electric Vehicles and Autonomous Driving
    Ajanovic, Amela
    [J]. 2020 9TH MEDITERRANEAN CONFERENCE ON EMBEDDED COMPUTING (MECO), 2020, : 10 - 10
  • [18] Safe Driving Capacity of Autonomous Vehicles
    Wang, Yuan-Ying
    Wei, Hung-Yu
    [J]. 2018 IEEE 88TH VEHICULAR TECHNOLOGY CONFERENCE (VTC-FALL), 2018,
  • [19] Driving Speed Profiles for Autonomous Vehicles
    Anastassov, Anton
    Jang, Dongwook
    Giurgiu, Gavril
    [J]. 2017 28TH IEEE INTELLIGENT VEHICLES SYMPOSIUM (IV 2017), 2017, : 1446 - 1451
  • [20] Autonomous Driving Simulation for Unmanned Vehicles
    Zhao, Danchen
    Liu, Yuehu
    Zhang, Chi
    Li, Yaochen
    [J]. 2015 IEEE WINTER CONFERENCE ON APPLICATIONS OF COMPUTER VISION (WACV), 2015, : 185 - 190