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Future Internet
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Future Intelligent Vehicular Networks toward 6G
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Future Intelligent Vehicular Networks toward 6G

A special issue of Future Internet (ISSN 1999-5903). This special issue belongs to the section "Internet of Things".

Deadline for manuscript submissions: closed (25 August 2023) | Viewed by 9601

Special Issue Editors

Dr. Paulo Mendes

E-Mail Website
Guest Editor
Airbus Central Research and Technology, Willy-Messerschmitt-Str 1, Taufkirchen, 82024 Munich, Germany
Interests: FANET; ICN; SDN; service function chains; fog computing
Prof. Dr. Eduardo Cerqueira

E-Mail Website
Guest Editor
Computer Science Faculty, Federal University of Pará, Belém 66075-110, Brazil
Interests: SDN; vehicular cloud; VANET
Special Issues, Collections and Topics in MDPI journals
Prof. Denis Rosário

E-Mail Website
Guest Editor
Computer Science Faculty, Federal University of Pará, Belém 66075-110, Brazil
Interests: edge computing; FANET; SDN; VANETs
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear colleagues,

Vehicular networks have been built to connect human communication and transportation around the world for many years to come, but this reality is rapidly changing for a future autonomous vehicle era. With the rapid growth in the number of connected vehicles, vehicular networks become heterogeneous, dynamic, with a large diameter, where orchestrating vehicular ecosystems to meet the requirements of novel services is still a challenging task, such as services requiring ultralow latency, ultrahigh bitirate, high reliability, high security, and massive connections. Emerging services in autonomous vehicles will range from 3D displays to holographic systems and improved in-car infotainment. In this context, the grand vision is that vehicular networks, supported by the sixth generation (6G) of wireless systems and advanced Internet protocols, will be an instrumental element of future connected autonomous vehicles. This Special Issue is focused on the most recent scientific research on the evolution of communication architectures and protocols needed to support the efficient development of intelligent vehicular networks.

This Special Issue is aligned with the scope of the MDPI Future Internet journal by tackling the evolution of wireless and Internet technologies to leverage the development of smart transportation systems.

Dr. Paulo Mendes
Prof. Eduardo Cerqueira
Prof. Denis Rosário
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. Future Internet is an international peer-reviewed open access monthly 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 1600 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

  • autonomous communication
  • connected autonomous vehicles
  • vehicular networks
  • 6G
  • internet protocols
  • emerging services
  • service centric networking
  • fog and edge computing
  • vehicular cloud computing
  • edge intelligence
  • orchestration of network functions
  • artificial intelligence
  • self-organized networks
  • V2X communication
  • software-defined network functions
  • network virtualization

Published Papers (3 papers)

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Research

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17 pages, 5922 KiB  
Article
Redundancy Mitigation Mechanism for Collective Perception in Connected and Autonomous Vehicles
by Wellington Lobato, Paulo Mendes, Denis Rosário, Eduardo Cerqueira and Leandro A. Villas
Future Internet 2023, 15(2), 41; https://doi.org/10.3390/fi15020041 - 22 Jan 2023
Cited by 3 | Viewed by 1513
Abstract
Due to poor local range of the perception and object recognition mechanisms used by autonomous vehicles, incorrect decisions can be made, which can jeopardize a fully autonomous operation. A connected and autonomous vehicle should be able to combine its local perception with the [...] Read more.
Due to poor local range of the perception and object recognition mechanisms used by autonomous vehicles, incorrect decisions can be made, which can jeopardize a fully autonomous operation. A connected and autonomous vehicle should be able to combine its local perception with the perceptions of other vehicles to improve its capability to detect and predict obstacles. Such a collective perception system aims to expand the field of view of autonomous vehicles, augmenting their decision-making process, and as a consequence, increasing driving safety. Regardless of the benefits of a collective perception system, autonomous vehicles must intelligently select which data should be shared with who and when in order to conserve network resources and maintain the overall perception accuracy and time usefulness. In this context, the operational impact and benefits of a redundancy reduction mechanism for collective perception among connected autonomous vehicles are analyzed in this article. Therefore, we propose a reliable redundancy mitigation mechanism for collective perception services to reduce the transmission of inefficient messages, which is called VILE. Knowledge, selection, and perception are the three phases of the cooperative perception process developed in VILE. The results have shown that VILE is able to reduce it the absolute number of redundant objects of 75% and generated packets by up to 55%. Finally, we discuss possible research challenges and trends. Full article
(This article belongs to the Special Issue Future Intelligent Vehicular Networks toward 6G)
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42 pages, 5579 KiB  
Article
Handover Management in 5G Vehicular Networks
by Ioannis Kosmopoulos, Emmanouil Skondras, Angelos Michalas, Emmanouel T. Michailidis and Dimitrios D. Vergados
Future Internet 2022, 14(3), 87; https://doi.org/10.3390/fi14030087 - 13 Mar 2022
Cited by 7 | Viewed by 3128
Abstract
Fifth-Generation (5G) vehicular networks support novel services with increased Quality of Service (QoS) requirements. Vehicular users need to be continuously connected to networks that fulfil the constraints of their services. Thus, the implementation of optimal Handover (HO) mechanisms for 5G vehicular architectures is [...] Read more.
Fifth-Generation (5G) vehicular networks support novel services with increased Quality of Service (QoS) requirements. Vehicular users need to be continuously connected to networks that fulfil the constraints of their services. Thus, the implementation of optimal Handover (HO) mechanisms for 5G vehicular architectures is deemed necessary. This work describes a scheme for performing HOs in 5G vehicular networks using the functionalities of the Media-Independent Handover (MIH) and Fast Proxy Mobile IPv6 (FPMIP) standards. The scheme supports both predictive and reactive HO scenarios. A velocity and alternative network monitoring process prepares each vehicle for both HO cases. In the case of predictive HO, each time the satisfaction grade of the vehicular user drops below a predefined threshold, the HO is initiated. On the other hand, in the case of reactive HO, the vehicle loses the connectivity with its serving network and connects to the available network that has obtained the higher ranking from the network selection process. Furthermore, the HO implementation is based on an improved version of the FPMIPv6 protocol. For the evaluation of the described methodology, a 5G vehicular network architecture was simulated. In this architecture, multiple network access technologies coexist, while the experimental results showed that the proposed scheme outperformed existing HO methods. Full article
(This article belongs to the Special Issue Future Intelligent Vehicular Networks toward 6G)
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Review

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34 pages, 904 KiB  
Review
The Car-Following Model and Its Applications in the V2X Environment: A Historical Review
by Junyan Han, Huili Shi, Longfei Chen, Hao Li and Xiaoyuan Wang
Future Internet 2022, 14(1), 14; https://doi.org/10.3390/fi14010014 - 27 Dec 2021
Cited by 17 | Viewed by 3746
Abstract
The application of vehicle-to-everything (V2X) technology has resulted in the traffic environment being different from how it was in the past. In the V2X environment, the information perception ability of the driver–vehicle unit is greatly enhanced. With V2X technology, the driver–vehicle unit can [...] Read more.
The application of vehicle-to-everything (V2X) technology has resulted in the traffic environment being different from how it was in the past. In the V2X environment, the information perception ability of the driver–vehicle unit is greatly enhanced. With V2X technology, the driver–vehicle unit can obtain a massive amount of traffic information and is able to form a connection and interaction relationship between multiple vehicles and themselves. In the traditional car-following models, only the dual-vehicle interaction relationship between the object vehicle and its preceding vehicle was considered, making these models unable to be employed to describe the car-following behavior in the V2X environment. As one of the core components of traffic flow theory, research on car-following behavior needs to be further developed. First, the development process of the traditional car-following models is briefly reviewed. Second, previous research on the impacts of V2X technology, car-following models in the V2X environment, and the applications of these models, such as the calibration of the model parameters, the analysis of traffic flow characteristics, and the methods that are used to estimate a vehicle’s energy consumption and emissions, are comprehensively reviewed. Finally, the achievements and shortcomings of these studies along with trends that require further exploration are discussed. The results that were determined here can provide a reference for the further development of traffic flow theory, personalized advanced driving assistance systems, and anthropopathic autonomous-driving vehicles. Full article
(This article belongs to the Special Issue Future Intelligent Vehicular Networks toward 6G)
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