How Does a Digital Twin Network Work Well for Connected and Automated Vehicles: Joint Perception, Planning, and Control
Author:
Affiliation:
1. Chongqing University of Posts and Telecommunications, Chongqing, China
2. School of Information Science and Engineering, Shenyang University of Technology, Shenyang, China
3. University of Sydney, Sydney, Australia
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Automotive Engineering
Link
http://xplorestaging.ieee.org/ielx7/10209/10375848/10317090.pdf?arnumber=10317090
Reference14 articles.
1. Cellular Localization for Autonomous Driving: A Function Pull Approach to Safety-Critical Wireless Localization
2. Towards Compact Autonomous Driving Perception With Balanced Learning and Multi-Sensor Fusion
3. Cooperation Method of Connected and Automated Vehicles at Unsignalized Intersections: Lane Changing and Arrival Scheduling
4. Joint Optimization of Sensing, Decision-Making and Motion-Controlling for Autonomous Vehicles: A Deep Reinforcement Learning Approach
5. Digital Twin in Industry: State-of-the-Art
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