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5G Vehicle-to-Everything (V2X): Latest Advances and Prospects
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5G Vehicle-to-Everything (V2X): Latest Advances and Prospects

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Transportation and Future Mobility".

Deadline for manuscript submissions: closed (30 June 2023) | Viewed by 10943

Special Issue Editors

Prof. Dr. Abderrezak Rachedi

E-Mail Website
Guest Editor
Gaspard Monge Computer Science laboratory, University Paris-Est Marne-la-Vallée (UPEM), 77420 Champs-sur-Marne, France
Interests: internet of things (IoT); wireless sensor networks (WSN); vehicular-to-everything communication (V2X); 5G; device-to-device (D2D) communication; machine-type communication (MTC); multi-hop cellular networks (MCN)
Special Issues, Collections and Topics in MDPI journals
Dr. Omar Sami Oubbati

E-Mail Website
Guest Editor
Laboratoire d'Informatique Gaspard Monge, Université Paris-Est Marne-la-Vallée, 77454 Marne-la-Vallée, France
Interests: UAV; mobile edge computing; reinforcement learning; IoT; computer network
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

This Special Issue of aims at publishing a collection of research contributions illustrating the recent achievements in all aspects of the development, study and understanding of Vehicle-to-Everything (V2X). We hope to establish a collection of papers that will be of interest to scholars in the field. Contributions in the form of full papers, reviews, and communications about the related topics are very welcome.

Prof. Dr. Abderrezak Rachedi
Dr. Omar Sami Oubbati
Guest Editors

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Published Papers (3 papers)

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Research

26 pages, 5272 KiB  
Article
Benchmarking 4G and 5G-Based Cellular-V2X for Vehicle-to-Infrastructure Communication and Urban Scenarios in Cooperative Intelligent Transportation Systems
by Tibor Petrov, Peter Pocta and Tatiana Kovacikova
Appl. Sci. 2022, 12(19), 9677; https://doi.org/10.3390/app12199677 - 26 Sep 2022
Cited by 17 | Viewed by 4005
Abstract
Vehicle-to-Infrastructure (V2I) communication is expected to bring tremendous benefits in terms of increased road safety, improved traffic efficiency and decreased environmental impact. In 2017, The 3rd Generation Partnership Project (3GPP) released 3GPP Release 14, which introduced Cellular Vehicle-to-Everything communication (C-V2X), bringing Vehicle-to-Everything (V2X) [...] Read more.
Vehicle-to-Infrastructure (V2I) communication is expected to bring tremendous benefits in terms of increased road safety, improved traffic efficiency and decreased environmental impact. In 2017, The 3rd Generation Partnership Project (3GPP) released 3GPP Release 14, which introduced Cellular Vehicle-to-Everything communication (C-V2X), bringing Vehicle-to-Everything (V2X) communication capabilities to cellular networks, hence creating an alternative to Dedicated Short-Range Communications (DSRC) technology. Since then, every new 3GPP Release including Release 15, a first full set of 5G standards, offered V2X capabilities. In this paper, we present a complex simulation study, which benchmarks the performance of LTE-based and 5G-based C-V2X technologies deployed for V2I communication in an urban setting. The study compares LTE and 5G deployed both in the Device-to-Device in mode 3 and in infrastructural mode. Target performance indicators used for comparison are average end-to-end (E2E) latency and Packet Delivery Ratio (PDR). The performance of those technologies is studied under varying communication conditions realized by a variation of vehicle traffic intensity, communication perimeter and message generation frequency. Furthermore, the effects of infrastructure deployment density on the performance of selected C-V2X communication technologies are explored by comparing the performance of the investigated technologies for three infrastructure density scenarios, i.e., involving two, four and eight base stations (BSs). The performance results are put into a context of the connectivity requirements of the most popular V2I communication services. The results indicate that both C-V2X technologies can support all the considered V2I services without any limitations in terms of the communication perimeter, traffic intensity and message generation frequency. When it comes to the infrastructure density deployment, the results show that increasing the density of the infrastructure deployment from two BSs to four BSs offers a remarkable performance improvement for all the considered V2I services as well as investigated technologies and their modes. Further infrastructure density increase (from four BSs to eight BSs) does not yield any practical benefits in the investigated urban scenario. Full article
(This article belongs to the Special Issue 5G Vehicle-to-Everything (V2X): Latest Advances and Prospects)
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17 pages, 1798 KiB  
Article
Chebyshev Polynomial-Based Scheme for Resisting Side-Channel Attacks in 5G-Enabled Vehicular Networks
by Mahmood A. Al-Shareeda, Selvakumar Manickam, Badiea Abdulkarem Mohammed, Zeyad Ghaleb Al-Mekhlafi, Amjad Qtaish, Abdullah J. Alzahrani, Gharbi Alshammari, Amer A. Sallam and Khalil Almekhlafi
Appl. Sci. 2022, 12(12), 5939; https://doi.org/10.3390/app12125939 - 10 Jun 2022
Cited by 32 | Viewed by 2343
Abstract
The privacy and security vulnerabilities in fifth-generation (5G)-enabled vehicular networks are often required to cope with schemes based on either bilinear pair cryptography (BPC) or elliptic curve cryptography (ECC). Nevertheless, these schemes suffer from massively inefficient performance related to signing and verifying messages [...] Read more.
The privacy and security vulnerabilities in fifth-generation (5G)-enabled vehicular networks are often required to cope with schemes based on either bilinear pair cryptography (BPC) or elliptic curve cryptography (ECC). Nevertheless, these schemes suffer from massively inefficient performance related to signing and verifying messages in areas of the high-density traffic stream. Meanwhile, adversaries could launch side-channel attacks to obtain sensitive data protected in a tamper-proof device (TPD) to destroy the system. This paper proposes a Chebyshev polynomial-based scheme for resisting side-channel attacks in 5G-enabled vehicular networks. Our work could achieve both important properties of the Chebyshev polynomial in terms of chaotic and semi-group. Our work consists of five phases: system initialization, enrollment, signing, verification, and pseudonym renew. Moreover, to resist side-channel attacks, our work renews periodically and frequently the vehicle’s information in the TPD. Security analysis shows that our work archives the privacy (pseudonym identity and unlikability) and security (authentication, integrity, and traceability) in 5G-enabled vehicular networks. Finally, our work does not employ the BPC or the ECC; its efficiency performance outperforms other existing recent works, making it suitable for use in vehicular networks. Full article
(This article belongs to the Special Issue 5G Vehicle-to-Everything (V2X): Latest Advances and Prospects)
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20 pages, 21637 KiB  
Article
A New Vehicle Dataset in the City of Los Angeles for V2X and Machine Learning Applications
by Ibtihal Ahmed Alablani and Mohammed Amer Arafah
Appl. Sci. 2022, 12(8), 3751; https://doi.org/10.3390/app12083751 - 8 Apr 2022
Cited by 2 | Viewed by 3270
Abstract
The fifth-generation (5G) network is the current emerging technology that meets the increasing need for higher throughputs and greater system capacities. It is expected that 5G technology will enable many new applications and services. Vehicle-to-everything (V2X) communication is an example of an application [...] Read more.
The fifth-generation (5G) network is the current emerging technology that meets the increasing need for higher throughputs and greater system capacities. It is expected that 5G technology will enable many new applications and services. Vehicle-to-everything (V2X) communication is an example of an application that is supported by 5G technology and beyond. A V2X communication system allows a vehicle to be connected to an entity, such as a pedestrian, another vehicle, infrastructure, and a network, to provide a robust transportation solution. It uses many models and strategies that are usually based on machine learning (ML) techniques, which require the use of a vehicle dataset. In this paper, a real vehicle dataset is proposed that was generated in the city of Los Angeles (LA). It is called the Vehicle dataset in the city of LA (VehDS-LA). It has 74,170 samples that are located on 15 LA streets and each sample has 4 features. The LA dataset has been opened to allow researchers in V2X and ML fields to use it for academic purposes. The main uses of the VehDS-LA dataset are studies related to 5G networks, vehicle automation, or ML-Based vehicle mobility applications. The proposed dataset overcomes limitations experienced by previous related works. Full article
(This article belongs to the Special Issue 5G Vehicle-to-Everything (V2X): Latest Advances and Prospects)
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