Control Systems Design for Connected and Autonomous Vehicles

A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Electrical and Autonomous Vehicles".

Deadline for manuscript submissions: 15 November 2024 | Viewed by 1761

Special Issue Editors

Faculty of Information Technology, Beijing University of Technology, Beijing 100124, China
Interests: networking AI; networked control system; intelligent optimization
Special Issues, Collections and Topics in MDPI journals
School of Communication and Information Engineering, Chongqing University of Posts and Telecommunications, Chongqing 400065, China
Interests: vehicular edge computing; internet of vehicle
Special Issues, Collections and Topics in MDPI journals
Faculty of Traffic Information and Control Research Institute, Beijing University of Technology, Beijing 100124, China
Interests: intelligent transportation; digital twin; joint optimization of V2X and transportation networks
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

As the heart of connected and autonomous vehicles are various control systems responsible for information sensing, communication, processing, and real-time decision making. The question of how to design an efficient control system for connected and autonomous vehicles has attracted wide attention from both academia and industry. To ensure real-time decision making, the control system should be able to sense new environmental information. Furthermore, the sensed information is of a large volume and requires ultra-reliable and low-delay transmissions, which requires the control system to be able to access to the V2X network through cooperating with the other vehicles. Moreover, in order to ensure the safety of autonomous driving, the information should be processed according to differentiate QoS and accuracy requirements. Finally, autonomous driving decision making, including vehicle cruise, vehicular cooperation, etc., based on the information processing results is also necessary.

This Special Issue aims to publish original research and review articles discussing control theories, communications, applications, and implementations relevant to control systems design for connected and autonomous vehicles. Topics of interest include, but are not limited to:

  • System architecture, simulation, and test beds for control systems of connected and autonomous vehicles.
  • Communication mechanisms in control systems for connected and autonomous vehicles, including resource allocation, access policy, satellite-assisted communications, etc.
  • Edge computing and edge–cloud collaboration schemes in control systems for connected and autonomous vehicles.
  • Driving environment monitoring and real-time risk detection algorithms in control systems for connected and autonomous vehicles.
  • Vehicle cruise and vehicular cooperation mechanism in control systems for connected and autonomous vehicles.
  • Quality of service guarantee for connected and autonomous vehicle service, including information freshness, information processing delay, information transmission channel modeling, etc.
  • Muti-agent enforcement learning and distributed machine learning schemes in control systems for connected and autonomous vehicles.
  • Integrated sensing, communications, and computing schemes in control systems for connected and autonomous vehicles.
  • Privacy security protection for connected and autonomous vehicles.
  • Digital twin-empowered intelligent transportation systems.

Dr. Zhuwei Wang
Dr. Zhidu Li
Dr. Bo Fan
Guest Editors

Manuscript Submission Information

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Keywords

  • connected and autonomous vehicles
  • control system
  • wireless communication
  • edge computing
  • vehicle cruise
  • quality of service
  • artificial intelligence
  • privacy security protection

Published Papers (2 papers)

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Research

17 pages, 1240 KiB  
Article
Intelligent Security Authentication for Connected and Autonomous Vehicles: Attacks and Defenses
by Xiaoying Qiu, Jinwei Yu, Wenbao Jiang and Xuan Sun
Electronics 2024, 13(8), 1577; https://doi.org/10.3390/electronics13081577 - 20 Apr 2024
Viewed by 380
Abstract
The emergence of integrated positioning, communication, and sensing technologies has paved the way for a surge in connected and autonomous vehicles. The control system has been successful in reliable and fast transmission. However, practical applications face security risks, especially data tampering and spoofing [...] Read more.
The emergence of integrated positioning, communication, and sensing technologies has paved the way for a surge in connected and autonomous vehicles. The control system has been successful in reliable and fast transmission. However, practical applications face security risks, especially data tampering and spoofing attacks. To improve the resilience of the system against potential attacks, we attempt to leverage a generative adversarial network learning-assisted authentication framework (GAF). In addition to proposing a new method for validating vehicles, we also introduce a new architectural innovation in the generator–discriminator pair to achieve improved results. The generator sub-network is constructed using an advanced convolutional neural network, whereas the discriminator is designed to leverage global and local information to determine whether a signal is real or fake. On this basis, we propose a signal enhancement-based authentication method, a deep convolutional generative adversarial network (DCGAN). Experimental results using the National Institute of Standards and Technology (NIST) dataset show that the proposed method is effective in denoising and improving the detection performance. Full article
(This article belongs to the Special Issue Control Systems Design for Connected and Autonomous Vehicles)
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20 pages, 4393 KiB  
Article
Design of a Collaborative Vehicle Formation Control Simulation Test System
by Zhijing Xu, Yuqiong Zhang, Pengren Ding and Fangze Tu
Electronics 2023, 12(21), 4385; https://doi.org/10.3390/electronics12214385 - 24 Oct 2023
Viewed by 1018
Abstract
The purpose of this research is to tackle one of the most difficult issues in the realm of self-driving cars, which is the testing of advanced self-driving application scenarios. Thus, this study proposes a simulation testing system based on hardware-in-the-loop simulation technology. This [...] Read more.
The purpose of this research is to tackle one of the most difficult issues in the realm of self-driving cars, which is the testing of advanced self-driving application scenarios. Thus, this study proposes a simulation testing system based on hardware-in-the-loop simulation technology. This system can enable data exchange between hardware systems as well as replicate and evaluate the algorithmic operations of the equipment under laboratory conditions. The system can integrate scenario simulation software with MATLAB to evaluate algorithm performance. The vehicle formation control system is tailored for collaborative vehicle formation management scenarios and tested in the simulation test system. The findings display the functional integrity of the vehicle formation control system, the reliability of lane changing and the stability and safety of cruising. It additionally demonstrates that the simulation testing system has the ability to recreate cooperative vehicle arrangement management situations and assess their functionality and performance. In forthcoming research, comprehensive functional and performance assessments will be executed on various typical scenarios for advanced autonomous driving applications in order to authenticate the simulation test system’s applicability. Full article
(This article belongs to the Special Issue Control Systems Design for Connected and Autonomous Vehicles)
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