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Vehicle-to-Everything (V2X) Communication for Intelligent Transportation: 2nd Edition
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Vehicle-to-Everything (V2X) Communication for Intelligent Transportation: 2nd Edition

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Communications".

Deadline for manuscript submissions: 30 September 2024 | Viewed by 1480

Special Issue Editors

Prof. Dr. Chen Chen

E-Mail Website
Guest Editor
School of Telecommunication Engineering, Xidian University, Xi’an 710071, China
Interests: Internet of Things; intelligent transportation systems; satellite communications; space-air-ground cooperation
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Kai Liu

E-Mail Website
Guest Editor
College of Computer Science, Chongqing University, Chongqing 400044, China
Interests: internet of vehicles; big data; pervasive computing
Special Issues, Collections and Topics in MDPI journals
Dr. Lei Liu

E-Mail Website
Guest Editor
State Key Laboratory of Integrated Services Networks, Xidian University, Xi’an 710071, China
Interests: intelligent transportation systems; internet of vehicles; distributed computing
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Qingqi Pei

E-Mail Website
Guest Editor
School of Communication Engineering, Xidian University, Xi’an 710071, China
Interests: trusted computing network; internet of things and edge computing security; wireless network physical layer security; blockchain technology; distributed collaborative attack and defense technology; data security and privacy protection
Special Issues, Collections and Topics in MDPI journals
Dr. Dapeng Lan

E-Mail Website
Guest Editor
Department of Informatics, University of Oslo, 0316 Oslo, Norway
Interests: mobile edge computing; artificial intelligence
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Over the last few years, as a result of advanced communication technologies, V2X (vehicle-to-everything) communication has been applied to intelligent transportation systems (ITS), such as road safety, cooperative autonomous driving, entertainment services, and many other use cases. A V2X-enabled ITS guarantees more efficient and reliable travel. Increasingly, the substantial development of wireless communication technology for V2X communication and networking enables the development of novel ITS services and applications:

  • New wireless communications and networking architecture for V2X and ITS;
  • Novel theory, technology, methodology, tools, and applications for V2X and ITS;
  • Modelling, simulation, and field evaluation for V2X and ITS;
  • Big data and data analytics for V2X and ITS;
  • Machine learning techniques for V2X and ITS;
  • Edge architecture, service, and applications for V2X and ITS;
  • New paradigms and management for smart mobility;
  • Vehicular networking, vehicular cloud, and internet of vehicles (IoV);
  • Cooperative perception strategies within V2X;
  • Cooperative decision-making processes enhanced by V2X;
  • Collaborative planning mechanisms through V2X.

This Special Issue of the Sensors aims to discuss a novel design of V2X architecture, techniques, networks, services, and applications for ITS and the search for innovative solutions for meeting the expectation of V2X communication and ITS.

Prof. Dr. Chen Chen
Prof. Dr. Kai Liu
Dr. Lei Liu
Prof. Dr. Qingqi Pei
Dr. Dapeng Lan
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sensors is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • V2X (Vehicle-to-Everything)
  • intelligent transportation systems (ITS)
  • wireless communication

Related Special Issue

Published Papers (2 papers)

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Research

21 pages, 1038 KiB  
Article
Extended Kalman Filter-Based Vehicle Tracking Using Uniform Planar Array for Vehicle Platoon Systems
by Jiho Song and Seong-Hwan Hyun
Sensors 2024, 24(7), 2351; https://doi.org/10.3390/s24072351 - 07 Apr 2024
Viewed by 574
Abstract
We develop an extended Kalman filter-based vehicle tracking algorithm, specifically designed for uniform planar array layouts and vehicle platoon scenarios. We first propose an antenna placement strategy to design the optimal antenna array configuration for precise vehicle tracking in vehicle-to-infrastructure networks. Furthermore, a [...] Read more.
We develop an extended Kalman filter-based vehicle tracking algorithm, specifically designed for uniform planar array layouts and vehicle platoon scenarios. We first propose an antenna placement strategy to design the optimal antenna array configuration for precise vehicle tracking in vehicle-to-infrastructure networks. Furthermore, a vehicle tracking algorithm is proposed to improve the position estimation performance by specifically considering the characteristics of the state evolution model for vehicles in the platoon. The proposed algorithm enables the sharing of corrected error transition vectors among platoon vehicles, for the purpose of enhancing the tracking performance for vehicles in unfavorable positions. Lastly, we propose an array partitioning algorithm that effectively divides the entire antenna array into sub-arrays for vehicles in the platoon, aiming to maximize the average tracking performance. Numerical studies verify that the proposed tracking and array partitioning algorithms improve the position estimation performance. Full article
(This article belongs to the Special Issue Vehicle-to-Everything (V2X) Communication for Intelligent Transportation: 2nd Edition)
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17 pages, 1263 KiB  
Article
Reinforcement Learning-Based Joint Beamwidth and Beam Alignment Interval Optimization in V2I Communications
by Jihun Lee, Hun Kim and Jaewoo So
Sensors 2024, 24(3), 837; https://doi.org/10.3390/s24030837 - 27 Jan 2024
Viewed by 680
Abstract
The directional antenna combined with beamforming is one of the attractive solutions to accommodate high data rate applications in 5G vehicle communications. However, the directional nature of beamforming requires beam alignment between the transmitter and the receiver, which incurs significant signaling overhead. Hence, [...] Read more.
The directional antenna combined with beamforming is one of the attractive solutions to accommodate high data rate applications in 5G vehicle communications. However, the directional nature of beamforming requires beam alignment between the transmitter and the receiver, which incurs significant signaling overhead. Hence, we need to find the optimal parameters for directional beamforming, i.e., the antenna beamwidth and beam alignment interval, that maximize the throughput, taking the beam alignment overhead into consideration. In this paper, we propose a reinforcement learning (RL)-based beamforming scheme in a vehicle-to-infrastructure system, where we jointly determine the antenna beamwidth and the beam alignment interval, taking into account the past and future rewards. The simulation results show that the proposed RL-based joint beamforming scheme outperforms conventional beamforming schemes in terms of the average throughput and the average link stability ratio. Full article
(This article belongs to the Special Issue Vehicle-to-Everything (V2X) Communication for Intelligent Transportation: 2nd Edition)
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