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Our journal welcomes not only original high-quality papers covering the theoretical, experimental and operational aspects of electrical and electronics engineering in mobile radio, motor vehicles and land transportation, but also industry-focused publication focusing on research findings and suggesting ideas that may be useful to those conducting similar research.
Below, we highlight two featured peer-reviewed articles:
Automated Vehicle Marshalling (AVM) is a pioneering technology, introducing the world's first functionally safe V2X service. Co-authored by leading industry practitioners and researchers from AUDI AG, BMW AG, Continental Automotive Systems, Ford Motor Company, Ford-Werke GmbH, German Aerospace Centre, Mercedes-Benz AG, Robert Bosch GmbH, Toyota Motor North America, Universidad Miguel Hernandez de Elche, and Volkswagen AG, the first paper reviews the current deployment status and AVM-enabled use cases, highlighting the growing maturity and real-world adoption of this technology
The second paper, co-authored by researchers from University of Piraeus, University of the Aegean, and University of West Attica, provides a comprehensive up-to-date review of the integration of Software-Defined Radio (SDR) technology in Unmanned Aerial Vehicles (UAV)-based systems, encompassing the latest techniques, methodologies, and challenges.
We’ve provided short summaries of these feature articles, written in accessible language that we hope will make your reading experience enjoyable.
Automated Vehicle Marshalling: The First Functionally Safe V2X Service for Connected Automated Driving
Florian Schiegg, Miguel Sepulcre, Joseph A. Urhahne, Patrick Haag, John Kenney, Vladislav Kats, Edmir Xhoxhi, Syed Amaar Ahmad, Gokulnath Thandavarayan, Julia Rainer, Georg A. Schmitt, Sebastian Hahn, Kent Young, Krishna Bandi, Niklas Ambrosy, Felix Hess, and Javier Gozalvez
Full article: IEEE Open Journal of Vehicular Technology, Volume 6
Summary by Syed Amaar Ahmad: In this paper, we introduce Automated Vehicle Marshalling (AVM) as a new innovative technology to wirelessly control, steer and guide regular vehicles inside large parking lots or industrial facilities - without any human driver. The unique aspect of AVM is that unlike self-driving cars as shown in mainstream media, where a vehicle must use its onboard sensors such as cameras, radars and ultrasonics to detect objects and obstructions to move, this new technology requires vehicles to maneuver entirely through a wireless radio link. An infrastructure of sensors installed in such geofenced facilities can do all the detection and then wirelessly command and control a vehicle to safely move or stop. Our work presents ongoing work to develop and standardize the technology so that all automakers can enable their vehicles to avail AVM for the benefit of their customers.
Software-Defined Radio Deployments in UAV-Driven Applications: A Comprehensive Review
Emmanouel T. Michailidis, Konstantinos Maliatsos, and Demosthenes Vouyioukas
Full article: IEEE Open Journal of Vehicular Technology, Volume 5
Summary by Emmanouel Michailidis: This paper explores how Unmanned Aerial Vehicles (UAVs), more widely known as drones, can become smarter, more secure, and more versatile by using a flexible radio technology called Software-Defined Radio (SDR). Instead of being limited by fixed hardware, SDR lets UAVs adjust their communication methods and signal processing tasks through software. This makes it easier for them to switch between missions, adapt to changing environments, and protect themselves from threats such as signal jamming or hacking. The paper brings together the latest research and real-world examples where SDR has been used in UAVs for communication, surveillance, and disaster response. What makes this paper special is that it's the first to fully focus on how SDR and UAV technologies work together, highlighting both the benefits and the challenges. Moreover, this paper offers practical insights for engineers, researchers, and developers looking to build the next generation of intelligent and secure UAVs.
Our paper walks through the key building blocks, showing how to shrink powerful large language models so they fit on a small flight computer, how to fuse text-based commands with sensor data (camera, LiDAR, GPS) in real-time, and how to verify that the drone’s “understanding” remains reliable under changing conditions (for example, poor lighting or spotty connectivity). By mapping out concrete solutions, such as onboard fine-tuning techniques, multimodal sensor-fusion strategies, and lightweight trust-check layers; we provide a roadmap for transforming today’s drones into truly conversational, adaptive machines.
In a nutshell, this work shows how to fuse advanced large language “brains” with aerial robots in a hands-on, deployable way going beyond theory to tackle real-world hurdles like limited onboard computing, reliable sensor-language fusion, and trustworthy AI output. Instead of simply reviewing past efforts, we offer a clear, step-by-step blueprint that empowers engineers and researchers to build drones that don’t just fly but they can “talk” to us, understand complex instructions, and reason through missions as naturally as having a conversation.
Announcement of the publication of the IEEE OJVT Special Issue on OTFS
Orthogonal time frequency space (OTFS) modulation and delay-Doppler (DD) signal processing is an emerging technology aimed at addressing challenges in hostile wireless communication environments. These environments include scenarios like mobile communications on aircraft, satellite communications, vehicle-to-vehicle communications, and underwater acoustic communications, where traditional modulation techniques like OFDM struggle due to severe delay and Doppler effects.
OTFS modulation operates in the DD domain instead of the conventional time-frequency domain, offering advantages such as enhanced resilience against Doppler and delay effects, lower peak-to-average power ratio, reduced signaling overhead, and robustness against synchronization errors. It is considered a promising technology for 6G wireless systems.
We are very happy to have a few leading researchers in this research area, namely Qin Tao (Hangzhou Normal University), Shuangyang Li (Technical University of Berlin), Weijie Yuan (Southern University of Science and Techonology), Slawomir Stanczak (Fraunhofer Heinrich Hertz Institute), Emanuele Viterbo (Monash University), and Xianbin Wang (Western University), to publish a special issue in our journal, IEEE Open Journal of Vehicular Technology, that emphasizes the importance of OTFS modulation and DD signal processing in advancing wireless communication technologies, particularly for 6G systems, and encourages further research in this field.
The special issue features five articles covering various aspects of OTFS:
- Performance Evaluation: Proposes a novel framework for evaluating OTFS system performance using multiple indicators
- Channel Coding: Introduces a hybrid coding scheme combining LDPC and Hadamard codes to improve performance in high-mobility scenarios
- Real-World Applications (article 1, article 2): Explores OTFS in adaptive cruise control systems and symbiotic radio systems, leveraging deep learning and reinforcement learning for improved functionality.
- Integration with 6G Technology: Surveys the use of reconfigurable intelligent surfaces (RIS) in OTFS systems, discussing advancements, challenges, and future directions.
About the IEEE Open Journal of Vehicular Technology (OJVT)
The IEEE OJVT covers the theoretical, experimental and operational aspects of electrical and electronics engineering in mobile radio, motor vehicles and land transportation. A brief summary of these fields of interest are as follows:
- Mobile radio shall include all terrestrial mobile services
- Motor vehicles shall include the components and systems and motive power for propulsion and auxiliary functions
- Land transportation shall include the components and systems used in both automated and non-automated facets of ground transport technology
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