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Special Issue "Sensor and Communication Systems Enabling Autonomous Vehicles"

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

Deadline for manuscript submissions: 31 May 2020.

Special Issue Editors

Prof. Francisco J. Martinez
Website
Guest Editor
Department of Computer Science and System Engineering, University of Zaragoza, Zaragoza, Spain
Interests: VANET simulation; intelligent transportation systems; traffic safety; 802.11p; warning messages; traffic safety; Artificial Intelligence; vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communications
Special Issues and Collections in MDPI journals
Prof. Dr. Celimuge Wu
Website
Guest Editor
Department of Computer and Network Engineering, Graduate School of Informatics and Engineering, The University of Electro-Communications, 1-5-1, Chofugaoka, Chofu-shi, Tokyo,182-8585 Japan
Interests: ad hoc networks; sensor networks; intelligent transport systems; communication protocols; IoT; big data
Special Issues and Collections in MDPI journals
Dr. Syed Hassan Ahmed
Website
Guest Editor
Department of Computer Science, Georgia Southern University, Statesboro, GA 30460, USA
Interests: Internet of Things (IoT); connected and smart communities; sensors and ad hoc networks; vehicular communications (V2V, V2I, V2X); next-generation networks (information/content-centric and named data networking); smart and mobile health
Special Issues and Collections in MDPI journals
Prof. Johann M. Marquez-Barja
Website
Guest Editor
University of Antwerpen – IMEC, 2020 Antwerpen, Belgium
Interests: 5G advanced architectures including edge computing; flexible and programmable future end-to-end networks; IoT communications and applications; vehicular communications, mobility, and smart cities deployments
Special Issues and Collections in MDPI journals

Special Issue Information

Dear colleagues,

Connected and autonomous vehicles (CAVs) have become a reality and represent a huge leap forward to improve our quality of life and traffic safety around the world. Driverless vehicles are a result of major advancements in both sensing and computation areas. By adding new communication capabilities, autonomous vehicles’ performance can even be improved. Further research efforts are required in the fields of vehicular networking, sensing, and autonomous driving, ranging from developments in sensors to computer vision or the use of 5G in self-driving vehicles.

This Special Issue focuses on the design, analysis, and implementation of smart sensing and communication issues, especially addressing autonomous vehicles. The objective is to provide an overview of the state of the art in the technological aspects of sensing, communications, computer vision, and artificial intelligence applied to CAVs.

More specifically, this Special Issue is seeking high-quality original contributions, soliciting high-level technical papers addressing the main research challenges related to the autonomous vehicles, sensing, and communications areas. Possible contributions should consist of original theoretical or practical analyses, never published elsewhere, and validated by simulations or real testbeds.

Potential topics include but are not limited to:

• Autonomous driving;
• Vehicular sensor networks;
• Sensor fusion in autonomous vehicles;
• 5G in vehicular networking;
• Multimedia communications in vehicular scenarios;
• Computer vision for autonomous vehicles;
• Content distribution in vehicular environments;
• Vehicular cloud computing and networking;
• Advanced services through vehicular communications;
• Security, trust, and privacy in vehicular communications;
• Models, simulators, and tools for intelligent transportation systems.

Prof. Francisco J. Martinez
Prof. Celimuge Wu
Prof. Syed Hassan Ahmed
Prof. Johann M. Marquez-Barja
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 papers will be 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 2000 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 driving
  • Vehicular networks
  • Vehicle sensing
  • 5G in the vehicular environment
  • Artificial Intelligence for autonomous driving
  • Computer vision for autonomous vehicles
  • Intelligent transportation systems

Published Papers (3 papers)

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Research

Open AccessArticle
A Novel Approach for Mixed Manual/Connected Automated Freeway Traffic Management
Sensors 2020, 20(6), 1757; https://doi.org/10.3390/s20061757 - 22 Mar 2020
Abstract
Freeway traffic management and control often rely on input from fixed-point sensors. A sufficiently high sensor density is required to ensure data reliability and accuracy, which results in high installation and maintenance costs. Moreover, fixed-point sensors encounter difficulties to provide spatiotemporally and wide-ranging [...] Read more.
Freeway traffic management and control often rely on input from fixed-point sensors. A sufficiently high sensor density is required to ensure data reliability and accuracy, which results in high installation and maintenance costs. Moreover, fixed-point sensors encounter difficulties to provide spatiotemporally and wide-ranging information due to the limited observable area. This research exploits the utilization of connected automated vehicles (CAVs) as an alternative data source for freeway traffic management. To handle inherent uncertainty associated with CAV data, we develop an interval type 2 fuzzy logic-based variable speed limit (VSL) system for mixed traffic. The simulation results demonstrate that when more 10% CAVs are deployed, the performance of the proposed CAV-based system can approach that of the detector-based system. It is demonstrated in addition that the introduction of CAVs may make VSL obsolete at very high CAV-equipment rates. Full article
(This article belongs to the Special Issue Sensor and Communication Systems Enabling Autonomous Vehicles)
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Open AccessArticle
SDN-based Handover Scheme in Cellular/IEEE 802.11p Hybrid Vehicular Networks
Sensors 2020, 20(4), 1082; https://doi.org/10.3390/s20041082 - 17 Feb 2020
Abstract
With the arrival of 5G, the wireless network will be provided with abundant spectrum resources, massive data transmissions and low latency communications, which makes Vehicle-to-Everything applications possible. However, VANETs always accompany with frequent network topology changes due to the highly mobile feature of [...] Read more.
With the arrival of 5G, the wireless network will be provided with abundant spectrum resources, massive data transmissions and low latency communications, which makes Vehicle-to-Everything applications possible. However, VANETs always accompany with frequent network topology changes due to the highly mobile feature of vehicles. As a result, the network performance will be affected by the frequent handover. In this paper, a seamless handover scheme is proposed where the Software-Defined Networking (SDN) and Mobile Edge Computing (MEC) technologies are employed to adapt to the dynamic topology change in VANETs. The introduction of SDN provides a global view of network topology and centralized control, which enables a stable transmission layer connection when a handover takes place, so that the upper layer performance is not influenced by the network changes. By employing MEC server, the data are cached in advance before a handover happens, so that the vehicle can restore normal communication faster. In order to confirm the superiority of our proposal, computer simulations are conducted from different aspects. The results show that our proposal can significantly improve the network performance when a handover happens. Full article
(This article belongs to the Special Issue Sensor and Communication Systems Enabling Autonomous Vehicles)
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Open AccessArticle
LoRa-Based Physical Layer Key Generation for Secure V2V/V2I Communications
Sensors 2020, 20(3), 682; https://doi.org/10.3390/s20030682 - 26 Jan 2020
Abstract
In recent years, Vehicle-to-Vehicle (V2V) and Vehicle-to-Infrastructure (V2I) communication brings more and more attention from industry (e.g., Google and Uber) and government (e.g., United States Department of Transportation). These Vehicle-to-Everything (V2X) technologies are widely adopted in future autonomous vehicles. However, security issues have [...] Read more.
In recent years, Vehicle-to-Vehicle (V2V) and Vehicle-to-Infrastructure (V2I) communication brings more and more attention from industry (e.g., Google and Uber) and government (e.g., United States Department of Transportation). These Vehicle-to-Everything (V2X) technologies are widely adopted in future autonomous vehicles. However, security issues have not been fully addressed in V2V and V2I systems, especially in key distribution and key management. The physical layer key generation, which exploits wireless channel reciprocity and randomness to generate secure keys, provides a feasible solution for secure V2V/V2I communication. It is lightweight, flexible, and dynamic. In this paper, the physical layer key generation is brought to the V2I and V2V scenarios. A LoRa-based physical key generation scheme is designed for securing V2V/V2I communications. The communication is based on Long Range (LoRa) protocol, which is able to measure Received Signal Strength Indicator (RSSI) in long-distance as consensus information to generate secure keys. The multi-bit quantization algorithm, with an improved Cascade key agreement protocol, generates secure binary bit keys. The proposed schemes improved the key generation rate, as well as to avoid information leakage during transmission. The proposed physical layer key generation scheme was implemented in a V2V/V2I network system prototype. The extensive experiments in V2I and V2V environments evaluate the efficiency of the proposed key generation scheme. The experiments in real outdoor environments have been conducted. Its key generation rate could exceed 10 bit/s on our V2V/V2I network system prototype and achieve 20 bit/s in some of our experiments. For binary key sequences, all of them pass the suite of statistical tests from National Institute of Standards and Technology (NIST). Full article
(This article belongs to the Special Issue Sensor and Communication Systems Enabling Autonomous Vehicles)
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