Discussions about wonder and awe began many centuries ago; here, we mention, among others, important contributors to that discussion, Carson, Keats, and Einstein. Our focus, however, are with three panel discussions that constitute the series “The Power of Wonder: Modern Marvels in the Age of Science.”

The increase in the safety and privacy of automated vehicle drivers against hazardous cyber-attacks will lead to a considerable reduction in the number of global deaths and injuries. In this sense, the European Commission has focused attention on the security of communications in high-risk systems when receiving a cyber-attack such as automated vehicles. The project SerIoT comes up as an possible solution

Cooperative, Connected and Automated Mobility (CCAM) is expected to leverage the full potential of wireless communications. With the growing adoption of 5G and its support for Vehicle-to-Everything (V2X) communications, beamformed vehicular communications at millimeter-wave (mmWave) bands are expected to enable the most demanding connected driving applications. Beamformed V2X links present the challenge

In this research paper, a framework has been proposed to guarantee Quality-of-Service for vehicular networks, considering an environment where many types of services are simultaneously offered to the users. This proposed framework needs to be robust, cooperative and secure in nature. For having such characteristics in a solution, three modules have been proposed and amalgamated. First module takes

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Due to a production error, in the original article [1], Figs. 1, 2 and 3 were incorrectly published. We apologize for this error. The correct figures, with their corresponding captions, are shown below: Fig. 1. Schematic representation of MAVs with fixed single (a) or double (b) rotors. Fig. 2. Hierarchical flight control architecture for MAVs with fixed rotors. PC: position controller; AC: attitude

Reliable communication is a competitive task for broadband vehicular communications due to the fact that multiform interference has been introduced to the existing broadband transmission, which promotes the development of cognitive vehicular communication systems. To facilitate the improvement of the anti-jamming performance for the coexistence of diverse interference and signals in wireless heterogeneous

In vehicular network communications, the privacy and authentication requirements are necessary to design efficient solutions that not only ensure the authentication of the traffic-related messages, but also prevent attackers from affecting the driver's privacy, and in the meanwhile reduce the computation and communication costs. In this paper, we investigate ring signature and aggregate concepts in

Vehicular Ad Hoc Networks (VANET) are self-organized wireless network for Intelligent Transportation Systems (ITS) that allow vehicles to collaborate with each other, to improve driving efficiency and enhance traffic safety without centralized infrastructure. Vehicles are equipped with sensors, global positioning systems (GPS) and communication systems to perform the tasks related to safety, efficiency

The support of edge computing for vehicular technologies gained increasing momentum with 5G to fulfill efficient offloading tasks from vehicles towards the edge nodes. Accordingly, vehicles demanding powerful computation and large storage resources will be directed to communicate with the nearest edge computing nodes hosted at a wireless 5G new generation nodes (gNBs) or a road side units (RSUs). To

The characteristics of physical constraints and widespread communication of vehicle platoon system render it vulnerable to physical intrusion or cyber attacks. To enhance the fault-tolerant ability and detection accuracy of the software-defined networking enabled vehicle platoon system, we present a novel attack detection method based on invariant state set, which models both control strategies and

With the rise of both embedded technologies and the Internet of Things (IoT) integration, it is increasingly possible to realize complex systems in which, for example, vehicles are connected to the IoT domain capable of interacting directly with applications on mobile or embedded devices. In this work, a Machine to Machine (M2M) based platform able to recognize the driving style will be presented.

While much has been observed regarding hypothermia by way of environmental exposure, it is modern day medicine that deployed hypothermia as a therapeutic. From the early 1930s, when Temple Fay deployed “refrigeration” to treat pain, to the work of Wilfred Bigelow and Charles Drew, who utilized hypothermia in open heart surgery—the opportunities seemed endless. However, questions arose surrounding appropriate

The Internet of Vehicles (IoV) is a disruptive technology that has a great impact on people's lifestyle and activities. Fully autonomous vehicles are the next generation of connected cars. However, IoV systems suffer from several security threats that could offset the intended advantages. To address the security and privacy issues, several cryptographic and non-cryptographic security solutions should

Nowadays, traffics on the roads are getting more and more congested due to the fast-rising number of vehicles and the increasing need of citizens for mobility. Accidents happen frequently and result great loss of lives and properties. Internet of Vehicles (IoVs), as an important part of Internet of Things (IoTs), is placed high hope for enhancing traffic safety and controlling the damage caused by

In vehicular ad hoc networks (VANETs), data propagation is quite challenging due to the high mobility of vehicles, the instability of communication links, and the inherent topology changes. This paper presents FWDP, a fuzzy logic-based vehicle weighting model (VWM) for scheduling prioritized data in VANETs. FWDP employs roadside units (RSUs) to dominate the frequent topology changes and manage the

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This issue’s column is devoted to the M. Barry Carlton Award. The M. Barry Carlton Award acknowledges what is judged to be the best paper in the IEEE TRANSACTIONS ON AEROSPACE AND ELECTRONIC SYSTEMS (TAES). To help identify and assess what TAES paper is best, the Carlton Award considers papers published four years earlier in TAES. As such, this year’s Carlton Award is the 2017 M. Barry Carlton Award

The nine papers in this special section focus on meta-level and adversarial tracking. A plethora of well-established tracking algorithms aim to estimate, over time, the latent kinematic state (e.g., position, velocity, higher order kinematics, or any other spatiotemporal characteristic) of a single or multiple targets based on the available sensory observations, including from several sources. Here

Modern tracking problems require fast, scalable, and robust solutions for tracking multiple targets from noisy sensor data. In this article, an algorithm that has linear computational complexity with respect to the number of targets and measurements is presented. The method is based on the propagation of the first two factorial cumulants of a point process. The algorithm is demonstrated for tracking

This article is focused on estimating a quantity of interest in the context of military impact assessment that we shall call adversarial risk. We formulate the adversarial risk as a function of the multiobject state describing a group of weapons, and propose two approaches to estimate it using multiobject filters. The first, optimal, approach is tailored to filters for point processes, and produces

Internet of Vehicles (IoV) finds a prime application in road safety via emergency message transmission which helps drivers take an intelligent decision on the road. However, as malicious nodes can pose serious challenges, particularly on highway traffic, trust management is essential for excluding malicious nodes from the network. In order to transfer emergency messages efficiently, we consider different

One important design goal of 6G networks is adapting to complex heterogeneous scenarios and providing a stable and reliable transmission channel for specific applications such as vehicular communication. To achieve this, scholars attempt to use heterogeneous wireless networks around a vehicle to improve the reliability of 6G network transmission through multipath transmission schemes and network coding

Advances in communications, smart transportation systems, and computer systems have recently opened up vast possibilities of intelligent solutions for traffic safety, convenience, and effectiveness. Artificial Intelligence (AI) is currently being used in various application domains because of its strong potential to help enhance conventional data-driven methods. In the area of Vehicular Ad hoc NETworks

Employing machine learning into 6G vehicular networks to support vehicular application services is being widely studied and a hot topic for the latest research works in the literature. This article provides a comprehensive review of research works that integrated reinforcement and deep reinforcement learning algorithms for vehicular networks management with an emphasis on vehicular telecommunications

Research on smart connected vehicles has recently targeted the integration of vehicle-to-everything (V2X) networks with Machine Learning (ML) tools and distributed decision making. Among these convergent paradigms, Federated Learning (FL) allows the vehicles to train a deep ML model collaboratively, by exchanging model parameters (i.e., neural network weights and biases), rather than raw sensor data

Air-to-Ground (A2G) communication is considered as a significant enabler technology in next-generation networks. To make this a reality, a comprehensive understanding of the A2G channels is vital. This paper presents an Elevation Angle (EA) based two-ray mean path loss model for the A2G channels. In particular, we present closed-form expressions for the path loss with respect to the elevation angle

The Internet of Vehicles (IoV) is a distributed network that enables vehicles to connect to each other and to various infrastructure and smart devices, in order to exchange data and provide important services. The highly dynamic environment of the IoV offers a lot of opportunities but at the same time makes the network susceptible to a large number of security attacks. In this paper, we propose a framework

As 5G networks are being deployed the key constraints of 5G networks have been highlighted, which encourages the probing research of 5G and beyond networks as the next-generation solutions. Especially for vehicular networks which require a network topology with very low latency and high reliability. 5G Vehicular networks offer higher reliability, lower latency, and secure and efficient communication

With the deployment of 5G, researchers and experts begin to look forward to 6G. They predict that 6G will be the key driving force for information interaction and social life after 2030. With the help of artificial intelligence (AI), 6G will be a highly autonomous closed-loop network, and will make up for 5G's shortcomings in communications, computing and global coverage, achieving “AI of things (AIoT)”