Metaverse-Enabled Intelligence for Open-Terrain Field Vehicle Fleets: Leveraging Parallel Intelligence and Edge Computing-Reference-Cited by-同舟云学术

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Metaverse-Enabled Intelligence for Open-Terrain Field Vehicle Fleets: Leveraging Parallel Intelligence and Edge Computing

Published:2024-02 Issue:2 Volume:9 Page:3111-3116
ISSN:2379-8904
Container-title:IEEE Transactions on Intelligent Vehicles
language:
Short-container-title:IEEE Trans. Intell. Veh.

Author:

Shuai Zhibin¹^ORCID,Hu Zheng¹^ORCID,Gai Jiangtao¹^ORCID,Chen Yijie¹,Chen Jicheng²^ORCID,Zhang Hui³^ORCID,Wang Fei-Yue⁴^ORCID

Affiliation:

1. China North Vehicle Research Institute, Beijing, China

2. Department of Electronic and Computer Engineering, Hong Kong University of Science and Technology, Hong Kong SAR, China

3. School of Transportation Science and Engineering, Beihang University, Beijing, China

4. State Key Laboratory for Management and Control of Complex Systems, Chinese Academy of Sciences, Beijing, China

Funder

National Natural Science Foundation of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/7274857/10510053/10468631.pdf?arnumber=10468631

Reference28 articles.

1. Hierarchical Control of Connected Vehicle Platoon by Simultaneously Considering the Vehicle Kinematics and Dynamics

2. Data-Driven Modeling and Distributed Predictive Control of Mixed Vehicle Platoons

3. A review of vehicle group intelligence in a connected environment

4. Distributed Dynamic Event-Triggered Secure Model Predictive Control of Vehicle Platoon Against DoS Attacks

5. Parallel Intelligence for Smart Mobility in Cyberphysical Social System-Defined Metaverses: A Report on the International Parallel Driving Alliance

Cited by 3 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. LLM-Based Operating Systems for Automated Vehicles: A New Perspective;IEEE Transactions on Intelligent Vehicles;2024-04

2. Perception and Planning of Intelligent Vehicles Based on BEV in Extreme Off-Road Scenarios;IEEE Transactions on Intelligent Vehicles;2024-04

3. Cognitive Reinforcement Learning: An Interpretable Decision-Making for Virtual Driver;IEEE Journal of Radio Frequency Identification;2024

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