The effectiveness of autonomous vehicles relies on reliable perception capabilities. Despite significant advancements in artificial intelligence and sensor fusion technologies, current single-vehicle perception systems continue to encounter limitations, notably visual occlusions and limited long-range detection capabilities. Collaborative Perception (CP), enabled by Vehicle-to-Vehicle (V2V) and Vehicle-to-Infrastructure (V2I) communication, has emerged as a promising solution to mitigate these issues and enhance the reliability of autonomous systems. Beyond advancements in communication, the computer vision community is increasingly focusing on improving vehicular perception through collaborative approaches. However, a systematic literature review that thoroughly examines existing work and reduces subjective bias is still lacking. Such a systematic approach helps identify research gaps, recognize common trends across studies, and inform future research directions. In response, this study follows the PRISMA 2020 guidelines and includes 106peer-reviewed articles. These publications are analyzed based on modalities, collaboration schemes, and key perception tasks. Through a comparative analysis, this review illustrates how different methods address practical issues such as pose errors, temporal latency, communication constraints, domain shifts, heterogeneity, and adversarial attacks. Furthermore, it critically examines evaluation methodologies, highlighting a misalignment between current metrics and CP’s fundamental objectives. By delving into all relevant topics in-depth, this review offers valuable insights into challenges, opportunities, and risks, serving as a reference for advancing research in vehicular collaborative perception.

Augmented Reality (AR) and edge computing can be used to enhance Vulnerable Road User (VRU) safety, leveraging a greater degree of interaction with the user and presenting real-time warning notifications, a use case that demands low latency for critical warnings. However, a new Multi-Access Edge Computing (MEC) system that distributes computational needs across edge nodes within the infrastructure is needed to meet these low-latency requirements. This paper proposes a microservice architecture designed to process data from various sources, including awareness and perception messages from road users and smart city sensors, through multiple communications technologies such as ITS-GS and 5G. This work employs peer-to-peer decentralized communications to perform seamless inte-gration and real-time processing, ensuring timely and relevant warnings for VRUs. Real-world road tests conducted in the Aveiro Tech City Living Lab in Aveiro, Portugal, and in commercial V2X equipment in the Autonomous Driving Test Field Baden-Wurttemberg in Karlsruhe, Germany, showed a maximum end-to-end latency of 110 ms, showcasing the system's capabilities in real-life demanding use cases and the system's interoperability.

Today, noise pollution and road anomalies are one of the most significant problems for city authorities. Moreover, one of the biggest sources of this noise is car noise, especially tire-road noise. With the widespread use of electric vehicles, engine noise has been reduced to a minimum. Many engineering fields are carrying out studies to monitor this noise and road condition in tires, roads and car mechanics. The objectives are to improve passenger comfort, to ensure maneuverability and speed control of unmanned vehicles in accordance with road conditions, to reduce accidents and road-related vehicle damage, and to reduce noise pollution. The most important part of these studies is tire-road noise and road condition monitoring with AI. In this article, we examine the existing studies on tire-road, the open-source data problem in this field, the solution proposal, the detection of road-related problems, and the studies on noise estimation in this field. It also aims to provide a road map on existing databases, data processing, and smart decision-making in this field and to support future studies in this field.

Reliable information about traffic attributes, including vehicle type, speed range, and direction, is essential for traffic management and intelligent transportation systems (ITS). Although radar- and camera-based solutions can provide accurate data, they are often expensive, vulnerable to environmental conditions, and may raise privacy concerns.In this study, we investigate passive acoustic sensing as a cost-effective and privacy-preserving alternative. Using stereo vehicle pass-by noise encoded as Mel-Frequency Cepstral Coefficients (MFCCs), we simultaneously classify vehicle type, speed range (inferred from road-specific speed limits), and movement direction. Three modeling strategies are evaluated: (1) traditional machine learning on time-averaged MFCCs, (2) a hybrid model combining ResNet50-based feature extraction with LightGBM classification, and (3) end-to-end convolutional neural networks (CNNs), including a lightweight multi-task variant enhanced with attention mechanisms.Experiments are conducted on the public IDMT-Traffic dataset, comprising 17,506 stereo audio clips. Our multi-task CNN achieves the best overall performance with only 646K parameters, reaching approximately 99% accuracy across all three tasks. These results highlight the viability of stereo acoustic sensing as a lightweight, scalable, and privacy-preserving solution for real-time traffic perception and V2X infrastructure support.

Vehicle-to-everything (V2X) communication plays a crucial role in enabling collaborative intelligence among autonomous vehicles, by utilizing paradigms such as Federated Learning (FL). However, the dynamic and decentralized nature of vehicular networks poses challenges, particularly in maintaining model convergence and robustness without centralized coordination. In this paper, we propose a dynamic Practical Byzantine Fault Tolerant consensus mechanism tailored for decentralized FL in vehicular environments. Our method optimizes federated averaging by addressing the high mobility and intermittent connectivity of vehicles. Through simulations, we evaluate its performance against baseline method, demonstrating improved resilience, efficiency, and adaptability in the presence of adversarial conditions.

Augmented Reality (AR) holds great potential for enhancing pedestrian’s urban experiences; however, its use in road traffic poses safety concerns due to potential distractions from interacting with AR interfaces. This paper investigates the effectiveness of AR applications for assisting pedestrians in crossing scenarios, against traditional crossing methods, by incorporating a collision warning system that uses an arrow to indicate the direction of a potential danger, and a virtual traffic light showing whether it is safe to cross. By leveraging Vehicle-to-Everything (V2X) communications within the living lab of Aveiro, Portugal, we conducted a user study to evaluate involved workloads, perceived safety and system usability in a realistic scenario. The findings from our study involving 20 participants reveal significant improvements in pedestrians’ perceived safety and a decrease in the perceived workload when using AR for pedestrian crossings, with both collision warning systems and virtual traffic lights demonstrating excellent usability.

E-bikes are recognized for their sustainable transportation benefits. However, the higher speeds associated with e-bikes pose an increased risk of potential accidents and hinder fluid riding in swarms with conventional bicycles. In this paper, we analyze the accuracy of maintaining an unknown speed, assess the associated workload, and investigate the self-reported speeds of e-bike cyclists in order to adapt the electric assistance to dynamic speed limits based on the surrounding traffic conditions. Our results from a pilot study with 15 participants show that the accuracy of maintaining a speed limit through active motor control and the associated workload are influenced by factors such as the level of electrical assistance and the perception of motor disengagement. E-bike cyclists using higher levels of electrical assistance demonstrated more accurate target speed maintenance. On average, participants consistently underestimated adapted speed limits, which were also influenced by the level of electrical support.

Cooperative Intelligent Transportation System (C-ITS) is a prime example of Cyber-Physical System (CPS)-Internet of Things (IoT), in that the mechanics are combined with electronic, information technologies, and Vehicle-to-everything (V2X) communication. In that respect, C-ITS inherits the unique properties of CPS-IoT, known as open connectivity and runtime adaptivity. This means that C-ITS can change its behavior or structure at runtime, which creates unknowns and uncertainties during system development. Moreover, IT solutions, such as Artificial Intelligence (AI)/Machine Learning (ML), Open Source Software (OSS), and Commercial-off-the-shelf (COTS) components, are used in automotive systems to foster innovation. However, these solutions often lack the guarantees that are necessary for safety-relevant applications. All aspects considered, this paper identifies the gaps between industry and research by examining state-of-the-art safety standards and literature and analyzing the limitations in safeguarding C-ITS using the Shuttle2X project as an example.

Formal models for the safety validation of autonomous vehicles have become increasingly important. To this end, we present a safety framework for longitudinal automated driving. This framework enables the calculation of minimum safe inter-vehicular distances for arbitrary ego vehicle control policies in a computationally efficient manner. We use this framework to enhance and generalize the Responsibility-Sensitive Safety (RSS) [1] model and models based on it, which fail to cover situations where the ego vehicle has a higher decelerating capacity than its preceding vehicle.

As Connected and Automated Vehicles (CAVs) introduce new maneuvers like platooning on the roads, manual drivers face challenges in adapting to reduced headway distances and automated behaviors.These interactions can affect safety and traffic flow, making it essential to study how drivers respond to CAVs in such scenarios.To address this, we present our virtual reality (VR) driving simulator, which replicates highway environments with automated vehicle platoons.By measuring objective data such as steering inputs, lane changes, and headway distance, we aim to analyze manual drivers' performance in proximity to automated platoons.Our configurable mobile system allows for diverse testing conditions and provides valuable insights to advance Cooperative, Connected, and Automated Mobility (CCAM) technologies, contributing to improved road safety and design.Furthermore, we briefly review related works, discuss the design and functionality of the simulator, and provide an outlook on future research directions.

Communication between road users is crucial, as miscommunication and misunderstandings can lead to accidents, often bearing serious consequences in case Vulnerable Road Users (VRU) are involved. In this article we focus on communication solutions directed towards one particular group of VRUs, namely pedestrians. Various approaches for communication from vehicles to pedestrians have been proposed, including external Human-Machine Interfaces and Vehicle-to-Everything (V2X) communication. Surprisingly, these works are rarely looked at together. Therefore we jointly survey these separate fields as a starting point for the development of effective methods for interactions between vehicles and pedestrians. We argue that merging the perspectives of different fields can be beneficial as their approaches often complement each other.

While rare, it is widely accepted that autonomous vehicles (AVs) will find themselves in dilemma scenarios involving vulnerable road users (VRUs). The ethics of these dilemma situations have been debated extensively in the context of trolley problem-like scenarios. What has not been noted is the inherent unfairness implicit in many of these discussions in which VRUs are seen as passive by-standers with no say as to what befalls them. Rather than simply remaining still in a collision scenario, VRUs can (and often do) take action that needs to be accounted for. If we are to increase fairness on public roads, it is important that AVs communicate with VRUs. This paper presents a highly theoretical discussion on the possibility of using communication tools (such as the V2X system) and techniques (derived from the science of human-machine interaction) to elicit positive responses from VRU during inevitable AV collisions. The paper begins with a brief ethical exploration of fairness in the context of current debates surrounding AV collisions. We progress to discuss possible technical solutions to AV-VRU communication, as well as the types of audio, visual, and tactile communication strategies necessary in critical scenarios.

The success in the adoption of autonomous vehicles is dependent on their ability to solve rarely occurring safety-critical corner cases. Vehicular communications (V2X) aim at improving safety and efficiency of autonomous driving by adding the capability of explicit inter-vehicular information exchange. We argue that V2X enables another important function, namely the support of ethical driving decisions. In this article, we explain our envisioned methodology of an ethical cooperative driving interaction protocol design (including what to communicate and how to act based on the received information). Cooperative manoeuvring empowered by the ethical V2X is a new research direction we promote in the autonomous driving research agenda.

The current Cellular V2X (C-V2X) standard for direct communication between vehicles is based on the so called Semi-Persistent Scheduling (SPS) algorithm. It is based on the multiple access structure of 5G New Radio (NR) and exploits sensing and persistence to realize a randomized multiple access. We consider the application of SPS to support periodic broadcast traffic where no acknowledgments are provided. Persistence is a key feature, which consists of a node using the same resource for its transmissions for multiple frames. The specific resource used is randomly selected from among those that are perceived to be idle, and reselected anew after a randomized number of frames. We define a model to gain insight into the interplay between persistence and key performance metrics for the type of traffic considered, namely probability of successful delivery and Age of Information (AoI). A core version of the model is validated against simulations and used to show that there exists an optimal level that minimizes AoI. The model is then extended to account for a distance-dependent propagation model, allowing further insight into the effects of the interplay between sender-receiver distance and persistence. Finally, an even more detailed model is investigated, using ns-3-based simulations. This further analysis confirms the qualitative behaviors revealed by the analytical model and provides more insight into the complex interactions of system parameters and channel characteristics. The obtained results help to identify the limits of SPS, opening the way to system-principled parameter optimization and design of more powerful variants of the multiple access scheme.

V2X Collective Perception is the principle of exchanging sensor data among V2X-capable stations, such as vehicles or roadside units, by exchanging lists of perceived objects in the 5.9 GHz frequency band for road safety and traffic efficiency. An object can be anything relevant to traffic safety, e.g., vehicles or pedestrians. The current standardization of Collective Perception in Europe considers filtering objects for transmission based on their locally perceived dynamics and freshness to preserve channel resources. However, two remaining problems of object filtering are: information redundancy and adapting object filtering to the available channel resources. In this paper, we combine redundancy mitigation and congestion control-aware filtering. We evaluate the performance of the resulting object filtering techniques by realizing realistic, large-scale simulations of a mid-size city in Germany. We assess the performance using a scoring metric. The results show better information redundancy control and adjustable channel usage for object filtering.

Motivated by the expectation that robot presence at crime scenes will become increasingly prevalent, the question arises of how they can protect humans in their care or vicinity. The current paper delves into the concept of “robot self-defense” and explores whether a robot should be tele-operated or autonomous, and how humans perceive imperfections in robot performance. To gain insight into how people feel, an online survey was conducted with 180 participants, who watched six videos of a robot defending a victim. The study provides insights into trust in human-robot interactions and sheds light on the complex dynamics involved in robot self-defense. The results indicate that people found a tele-operated robot to be more accepted, and that attempting to help but failing is more acceptable than just observing.

We argue that an information exchange between vehicles via the vehicular communications is the foundation for ethical driving. In other words – autonomous vehicles must be cooperative to be able to resolve ethical dilemmas in a multi-vehicle scenario. We show this by exploring the minimal setting of a longitudinal driving in a formation of three vehicles.

Would it be okay for a robot to hurt a human, if by doing so it could protect someone else? Such ethical questions could be vital to consider, as the market for social robots grows larger and robots become increasingly prevalent in our surroundings. Here we introduce the topic of “robot self-defense”, which involves the use of force by a robot in response to violence, to protect a human in its care. To explore this topic, we conducted a preliminary analysis of the literature, as well as brainstorming sessions, which led us to formulate an idea about how people will perceive robot self-defense based on the perceived risk of loss. Additionally, we propose a study design to investigate how the general public will perceive the acceptability of a robot using self-defense techniques. As part of this, we describe some hypotheses based on the assumption that the perceived acceptability will be affected by both the entities involved in a violent situation and the amount of force that is applied. The proposed scenarios will be used in a future survey to evaluate participants' perception of a social robot using self-defense techniques under varying circumstances, toward stimulating ideation and discussion on how robots will be able to help people to live better lives.

Robots are being designed to communicate with people in various public and domestic venues in a helpful, discreet way. Here, we use a speculative approach to shine light on a new concept of robot steganography (RS), that a robot could seek to help vulnerable populations by discreetly warning of potential threats. We first identify some potentially useful scenarios for RS related to safety and security -- concerns that are estimated to cost the world trillions of dollars each year -- with a focus on two kinds of robots, an autonomous vehicle (AV) and a socially assistive humanoid robot (SAR). Next, we propose that existing, powerful, computer-based steganography (CS) approaches can be adopted with little effort in new contexts (SARs), while also pointing out potential benefits of human-like steganography (HS): although less efficient and robust than CS, HS represents a currently-unused form of RS that could also be used to avoid requiring computers or detection by more technically advanced adversaries. This analysis also introduces some unique challenges of RS that arise from message generation, indirect perception, and effects of perspective. For this, we explore some related theoretical and practical concerns for selecting carrier signals and generating messages, also making available some code and a video demo. Finally, we report on checking the current feasibility of the RS concept via a simplified user study, confirming that messages can be hidden in a robot's behaviors. The immediate implication is that RS could help to improve people's lives and mitigate some costly problems -- suggesting the usefulness of further discussion, ideation, and consideration by designers.

Could a social robot use force to prevent violence directed toward humans in its care?–Might crime be eradicated, or conversely could excessive use of force proliferate and human dignity become trampled beneath cold robotic wheels? Such speculation is one part of a larger, increasingly important question of how social robots will be expected to behave in our societies, as robotic technologies develop and become increasingly widespread. Here, to gain some insight into this topic of "robot self-defense", we proposed a simplified heuristic based on perceived risk of loss to predict acceptability, and conducted a user survey with 304 participants, who watched eight animated videos of robots and humans in a violent altercation. The results indicated that people largely accept the idea that a humanoid robot can use force on attackers to help others. Furthermore, self-defense was perceived as more acceptable when the appearance of the defender was humanoid rather than mechanical, and when the force disparity between attacker and defender was high. The immediate suggestion is that it could be beneficial to re-examine common assumptions that a robot should never harm or risk harming humans, and to discuss and consider the possibilities for robot self-defense.

Due to the ability to support a wide range of applications and to involve infrastructure elements, connected and automated vehicles (CAVs) technology has played an important role in the development of cooperative intelligent transport systems. Thus, with the available sensing system, CAVs can perceive the surrounding environment. Indeed, due to the involvement of CAVs, communication of vehicles to other related devices using vehicle-to-everything (V2X) communication plays critical roles. This paper summarizes the research and development trends when proposing driving models, with a particular attention to highway on-ramp merging scenarios. The challenges and future research directions are also presented.

In this paper, we conceptualise and propose integrating UAVs with Intelligent Transportation Systems (ITS) based on using the Cooperative-ITS (C-ITS) framework. We start by discussing the state of the art and pinpointing some of the reasons for integration and the applications that the envisaged integration would enable. Next, we recall the critical aspects of the state of the art C-ITS connectivity and discuss how seamless integration of UAVs into C-ITS can be achieved. Notably, we show that encapsulation of UAVs in C-ITS does not imply significant changes for the currently existing mechanisms and data formats. Finally, we discuss some of the open research challenges related to the integration and operation of the integrated systems and pinpoint some mechanisms which can help to address these.

Autonomous vehicles (AVs) are crucial robotic systems that promise to improve our lives via safe, efficient, and inclusive transport–while posing some new challenges for the education of future researchers in the area, that our current research and education might not be ready to deal with: In particular, we don’t know what the AVs of the future will look like, practical learning is restricted due to cost and safety concerns, and a high degree of multidisciplinary knowledge is required. Here, following the broad outline of Active Student Participation theory, we propose a pedagogical approach targeted toward AVs called CAR that combines Creativity theory, Applied demo-oriented learning, and Real world research context. Furthermore, we report on applying the approach to stimulate learning and engagement in a master’s course, in which students freely created a demo with 10 small robots running ROS2 and Ubuntu on Raspberry Pis, in connection to an ongoing research project and a real current problem (SafeSmart and COVID-19). The results suggested the feasibility of the CAR approach for enabling learning, as well as mutual benefits for both the students and researchers involved, and indicated some possibilities for future improvement, toward more effective integration of research experiences into second cycle courses.

Today's vehicles are expected to interact with each other to improve road safety and efficiency. We refer here to the LTE-V standard defined by 3GPP Release 14. In particular, we consider the platoon scenario where a vehicle, acting as a leader, coordinates the movement of a group of vehicles. LTE-V Mode 3 is assumed where the eNB has the control of the allocation of V2V transmission resources to the platoon. V2V communications adopt the underlay mode, reusing the resources of common cellular users. This paper provides an analytical model to determine the V2V link outage probability, the Cooperative Awareness Message (CAM) loss probability after a generic number of reattempts, and the mean number of transmission attempts to deliver the CAM message successfully, taking shadowing correlation effects into account. This model has been validated using simulations.

A platoon consists of a string of vehicles traveling close together. Such tight formation allows for increased road throughput and reduced fuel consumption due to decreased air resistance. Furthermore, sensors and control algorithms can be used to provide a high level of automation. In this context, safety - in terms of no rear-end collisions - is a key property that needs to be assured. We investigate how vehicle-to-vehicle communication can be used to reduce inter-vehicle distances while guaranteeing safety in emergency braking scenarios. An optimization-based modeling scheme is presented that, under certain restrictions, provides an analytical calculation of inter-vehicle distances for safe braking. In contrast to earlier simulation-based approaches, the framework allows for computationally efficient solutions with explicit guarantees. Two approaches for computing braking strategies in emergency scenarios are proposed. The first assumes centralized coordination by the leading vehicle and exploits necessary optimal conditions of a constrained optimization problem, whereas the second - the more conservative solution - assumes only local information and is distributed in nature. We illustrate the usefulness of the approaches through several computational simulations.

Cooperative awareness basic services are key components of several Connected Autonomous Vehicles (CAV) functions. We present a rigorous approach to the analysis of cooperative awareness basic services in a CAV setup. Our approach addresses a major challenge in the traditional analysis techniques of such services, namely, coming up with effective scenarios that can meaningfully cover their various behaviours, exercise the limits of these services and come up with a quantitative means for design-space exploration.Our approach integrates model-based testing and search-based testing to automatically generate scenarios and steer the scenario generation process towards generating inputs that can lead to the most severe hazards. Additionally we define other objectives that maximise the coverage of the model and the diversity of the generated test inputs. The result of applying our technique to the analysis of cooperative awareness services leads to automatically generated hazardous scenarios for parameters that abide by the ETSI ITS-G5 vehicular communications standard. We show that our technique can be used as an effective design-space exploration method and can be used to design adaptive protocols that can mitigate the hazards detected through our initial analysis.

Reliable and scalable wireless transmissions for Internet of Vehicles (IoV) are technically challenging. Each vehicle, from driver-assisted to automated one, will generate a flood of information, up to thousands of times of that by a person. Vehicle density may change drastically over time and location. Emergency messages and real-time cooperative control messages have stringent delay constraints while infotainment applications may tolerate a certain degree of latency. On a congested road, thousands of vehicles need to exchange information badly, only to find that service is limited due to the scarcity of wireless spectrum. Considering the service requirements of heterogeneous IoV applications, service guarantee relies on an in-depth understanding of network performance and innovations in wireless resource management leveraging the mobility of vehicles, which are addressed in this article. For single-hop transmissions, we study and compare the performance of vehicle-to-vehicle (V2V) beacon broadcasting using random access-based (IEEE 802.11p) and resource allocation-based (cellular vehicle-to-everything) protocols, and the enhancement strategies using distributed congestion control. For messages propagated in IoV using multihop V2V relay transmissions, the fundamental network connectivity property of 1-D and 2-D roads is given. To have a message delivered farther away in a sparse, disconnected V2V network, vehicles can carry and forward the message, with the help of infrastructure if possible. The optimal locations to deploy different types of roadside infrastructures, including storage-only devices and roadside units with Internet connections, are analyzed.

The automotive domain is rapidly changing in the last years. Among the different challenges OEMs (i.e. the vehicle manufacturers) are facing, vehicles are evolving into systems of systems. In fact, over the last years vehicles have evolved from disconnected and “blind” systems to systems that are (i) able to sense the surrounding environment and (ii) connected with other vehicles, the city, pedestrians, cyclists, etc. Future transportation systems can be seen as a System of Systems (SoS). In an SoS, constituent systems, i.e. the units that compose an SoS, can act as standalone systems, but their cooperation enables new emerging and promising scenarios. While this trend creates new opportunities, it also poses a risk to compromise key qualities such as safety, security, and privacy. In this paper we focus on the automotive domain and we investigate how to engineer and architect cars in order to build them as constituents of future transportation systems. Our contribution is an architectural viewpoint for System of Systems, which we demonstrate based on an automotive example. Moreover, we contribute a functional reference architecture for cars as constituents of an SoS. This reference architecture can be considered as an imprinting for the implementations that would be devised in specific projects and contexts. We also point out the necessity for a collaboration among different OEMs and with other relevant stakeholders, such as road authorities and smart cities, to properly engineer systems of systems composed of cars, trucks, roads, pedestrians, etc. This work is realized in the context of two Swedish projects coordinated by Volvo Cars and involving some universities and research centers in Sweden and many suppliers of the OEM, including Autoliv, Arccore, Combitech, Cybercom, Knowit, Prevas, ÅF-Technology, Semcom, and Qamcom.

Drive-thru-Internet is a scenario in cooperative intelligent transportation systems (C-ITSs), where a road-side unit (RSU) provides multimedia services to vehicles that pass by. Performance of the drive-thru-Internet depends on various factors, including data traffic intensity, vehicle traffic density, and radio-link quality within the coverage area of the RSU, and must be evaluated at the stage of system design in order to fulfill the quality-of-service requirements of the customers in C-ITS. In this paper, we present an analytical framework that models downlink traffic in a drive-thru-Internet scenario by means of a multidimensional Markov process: the packet arrivals in the RSU buffer constitute Poisson processes and the transmission times are exponentially distributed. Taking into account the state space explosion problem associated with multidimensional Markov processes, we use iterative perturbation techniques to calculate the stationary distribution of the Markov chain. Our numerical results reveal that the proposed approach yields accurate estimates of various performance metrics, such as the mean queue content and the mean packet delay for a wide range of workloads.

An approach to constructing discrete models of packet losses suitable for a wide variety of communication network applications is studied. It is based on estimating parameters of probabilistic automata described via so-called pseudo-Markov chains. The new technique is applied both to approximating a discrete time analog process at the output of known channel models and to the experimental data stream. Comparison of models is performed by computing probabilities of more than m losses out of n transmitted packets (P (≥ m, n)). It is shown that for the Rician fading channel with exponential correlation and correlation determined by a Bessel filter, the obtained rank-two and rank-three discrete modes, respectively, provide high accuracy coincidence of P (≥ m, n) performances. The rank-three discrete model computed on the experimental data stream obtained from the LTE network provides significantly better approximation of P (≥ m, n) performance than that obtained by the Baum-Welch algorithm.

Realistic network simulations are necessary to assess the performance of any communication system. In this paper, we describe an implementation of a channel model for vehicle-to-vehicle (V2V) communication in the OMNeT++/Plexe simulation environment. The model is based on previous extensive measurements in a V2V multilink highway scenario and cover line-of-sight (LOS) as well as obstructed LOS (OLOS) scenarios, which occurs when one or more vehicles obstruct the LOS component. The implementation captures both the temporal autocorrelation and the joint multilink cross-correlation processes to achieve a realistic behavior. Preliminary results show that the implementation now generates stochastic large-scale fading with an autocorrelation function that agrees well with measured data. A representation of the cross-correlation process is now implemented through proper channel model selection since the geometry and location of objects are known in Plexe. We also show the impact of the suggested V2V physical layer (PHY) on the performance evaluation results observed at the facilities layer. As a metric, we use the data age, which is a measure how old the information about a vehicle is. When considering the autocorrelation in simulations, the experienced data-age increases. Examples show an increase of the 10% percentile data-age from 0.1~s to 1.5~s, which may affect the application performance significantly in critical situations.

In the recent years, vehicular adhoc networks (VANETs) can be an attractive choice for collecting and transferring the healthcare data of the passengers to the remote healthcare centers. In VANETs, some of the intermediate nodes may act as relay nodes in which case, these networks are called as vehicular relay networks (VRNs). However, the transmitted information in VRNs can be captured by intruders during transmission. Moreover, an attacker can launch selective forwarding, blackhole, and sinkhole attacks in the network, which may in turn degrade the network performance parameters like high end-to-end delay, low packet delivery ratio (PDR) and network throughput. Hence, to address these issues, a secure data dissemination scheme using VRNs is proposed. In the proposed scheme, first, a secure vehicular medical relay network system is designed for the users belonging to disconnected rural areas. The collected information is filtered at zonal levels before transmission to a nearby road side units, which further pass it to the incoming vehicles. Second, a secure passenger health monitoring network is designed which continuously monitors health services of the passengers traveling in different vehicles. The information collected through small body sensors installed in the vehicles act as data sets that is forwarded to the on-board monitoring unit within the vehicle. This collected data is then transmitted to centralized healthcare centers for processing by using VRNs. Lastly, a strong elliptic curve cryptography-based cryptographic solution is designed for secure communication among different vehicles. The performance of the proposed scheme is evaluated in various network scenarios with respect to different selected parameters, such as throughput, network delay, PDR, jitter, transmission and computation overheads, and key distribution overhead. The obtained results indicate that the proposed scheme provides improvement of 52% in average delay and 5% in PDR. This further indicates effective message delivery even with high mobility of the vehicles.

Important signal processing techniques need that the response of the different elements of a sensor array have specific characteristics. For physical systems this often is not achievable as the array elements’ responses are affected by mutual coupling or other effects. In such cases, it is necessary to apply array interpolation to allow the application of ESPRIT, Forward Backward Averaging (FBA), and Spatial Smoothing (SPS). Array interpolation provides a model or transformation between the true and a desired array response. If the true response of the array becomes more distorted with respect to the desired one or the considered region of the field of view of the array increases, nonlinear approaches become necessary. This work presents two novel methods for sector discretization. An Unscented Transform (UT) based method and a principal component analysis (PCA) based method are discussed. Additionally, two novel nonlinear interpolation methods are developed based on the nonlinear regression schemes Multivariate Adaptive Regression Splines (MARS) and Generalized Regression Neural Networks (GRNNs). These schemes are extended and applied to the array interpolation problem. The performance of the proposed methods is examined using simulated and measured array responses of a physical system used for research on mutual coupling in antenna arrays.

With rapid developments of sensor, wireless and mobile communication technologies, Mobile Healthcare Social Networks (MHSNs) have emerged as a popular means of communication in healthcare services. Within MHSNs, patients can use their mobile devices to securely share their experiences, broaden their understanding of the illness or symptoms, form a supportive network, and transmit information (e.g., state of health and new symptoms) between users and other stake holders (e.g., medical center). Despite the benefits afforded by MHSNs, there are underlying security and privacy issues (e.g., due to the transmission of messages via a wireless channel). The handshake scheme is an important cryptographic mechanism, which can provide secure communication in MHSNs (e.g., anonymity and mutual authentication between users, such as patients). In this paper, we present a new framework for the handshake scheme in MHSNs, which is based on hierarchical identity-based cryptography. We then construct an efficient Cross-Domain HandShake (CDHS) scheme that allows symptoms-matching within MHSNs. For example, using the proposed CDHS scheme, two patients registered with different healthcare centers can achieve mutual authentication and generate a session key for future secure communications. We then prove the security of the scheme, and a comparative summary demonstrates that the proposed CDHS scheme requires fewer computation and lower communication costs. We also implement the proposed CDHS scheme and three related schemes in a proof of concept Android app to demonstrate utility of the scheme. Findings from the evaluations demonstrate that the proposed CDHS scheme achieves a reduction of 18.14 and 5.41 percent in computation cost and communication cost, in comparison to three other related handshake schemes.

Vehicular Ad hoc networks (VANET) are a key element of cooperative intelligent transport systems. One of the challenges in VANETs is dealing with awareness and congestion due to the high amount of messages received from the vehicles in communication range. As VANETs are used in critical applications, congestion on the receiver side caused by the buffering of the packets is a safety hazard. In this paper, we propose a streamwise queuing system on the receiver side and show how it improves the timeliness of the messages received and maintains the awareness of the system in a congestion situation.

We consider mutual discovery of asynchronous wireless transceivers with a fixed activity ratio. On-off activity patterns are slotted, and repeat in discovery frames. For discovery it has to be guaranteed that the activity patterns of two transceivers are not overlapping. We design necklace codes determining activity patterns to guarantee discovery within a discovery frame, so that two asynchronous transceivers always have non-overlapping activity patterns. The number of distinct patterns is analyzed as a function of discovery frame length, and on-off activity ratio. As an application example, we consider the discovery problem for vehicle-to-vehicle communication. To guarantee discovery of far-away vehicles, discovery sequences providing processing gain, and necklace coded activity patterns are needed. We find that billions of discovery code identities can be provided with a repetition frequency that is high enough to guarantee a missed discovery probability less than 10-6.

Long-term evolution (LTE)/long-term evolution advanced (LTE-A) are emerging communication technologies on the way toward 5G telecommunication systems. Ubiquitous adoption of connectivity in between different kinds of sensors, wearable devices, and other low-power equipment raises an importance of the energy-efficient wireless communications. In LTE/LTE-A, the discontinuous reception mechanism (DRX) aims at power saving of user equipment (UE) devices. In this paper, we present an analysis of DRX, which is novel in two dimensions. First, our analytical approach is different from existing ones due to the use of Markov chain instead of the semi-Markov ones. Secondly, along with the generic traffic models, we also analyze the efficiency of DRX for military training application systems, what has not been done before. We suggest few practical recommendations regarding the DRX parameters tuning also.

Presents the introductory editorial for this issue of the publication.

Vehicular ad-hoc networks (VANETs) has gained a significant attention during the last decades both from industrial and academia communities. Novel VANET enabled active safety automotive applications are heavily dependent on reliability and security of underlying intervehicle communication protocols. The error-prone nature of the wireless channel and its openness to external invasions as well as dynamic VANET environment, impose the need for intensive studies before applications like platooning or collision avoidance can become a part of our daily life. The aim of this special issue is to encompass research advances in all areas of reliability and security in VANETs.

Because of the space and time dynamics of moving vehicles, network connectivity is an important performance metric to affect packet delivery in Vehicular Ad Hoc Networks (VANETs). Grouping vehicles into platoons in VANETs can improve road safety, change the network connectivity, and even reduce channel access collisions. Unfortunately, network connectivity is often ignored in the design of exiting MAC protocols for VANETs. In this paper, we analyze the connectivity probability and present a connectivity-aware Medium Access Control (MAC) protocol for platoon-based VANETs. A multi-priority Markov model is presented to derive the relationship between the connectivity probability and the system saturated throughput. Based on variable traffic status and network connectivity, a multi-channel reservation scheme is adopted to dynamically adjust the length of the Control CHannel (CCH) interval and the Service CHannel (SCH) interval for the improvement of the system performance, in terms of network throughput and the priority packet transmission opportunities for platoons. As a result, some important observations to the design and analysis of such communication systems are provided.

A military training radio network requires support for a large number of mobile nodes with heterogeneous traffic and real-time requirements. We propose a deterministic protocol and an admission control using real-time analysis for a centralized radio network with a multichannel base station. The admission control implements an algorithm for frequency allocation to mobile nodes, and guarantees timely treatment of real-time traffic. The proposed online heuristic frequency allocation algorithm is compared to other known heuristic algorithms: round robin over channels and fill one channel first. The goal with the heuristic algorithms is to maximize the number of supported mobile nodes. Our results show that when the high utilization part of the traffic have shorter deadlines it is advantageous to differentiate different types of nodes onto separate frequencies, whilst if the deadline is increased it is advantageous to mix different types of nodes on each frequency.

Vehicular Ad Hoc Networks (VANETs) can provide safety and non-safety related applications and services to improve the passenger safety and comfort. Due to the space and time dynamics of moving vehicles, network connectivity is an important performance metric to indicate the quality of the network and the user's satisfaction. Grouping vehicles into platoons in the highway can improve road safety, reduce fuel consumption, and decrease traffic congestion. In this paper, we study the connectivity characteristic of platoon-based VANETs. The connectivity probabilities are analyzed for the Vehicle-to-Vehicle (V2V) and Vehicle-to-Infrastructure (V2I) communication scenarios. The relationships between the connectivity probability and the key parameters are investigated, including the traffic density, the coverage of the ordinary vehicle, the coverage of the platoon, the coverage of the Road Side Unit (RSU), the distance between two adjacent RSUs and the ratio of the platoon in the VANET. The results can help the transport system designer to control the traffic on the highway to satisfy the connectivity requirement. Analysis results show that the connectivity probability can be significantly improved when there are platoons in a network.

IEEE 1609.4 protocol defines a channel switching mechanism to enable a single radio operating efficiently on multiple channels to support both safety and non-safety services. Basic safety message (BSM) is transmitted only through the control channel at regular intervals. In this paper, we propose an analytic model based on interacting semi-Markov process (SMP) to evaluate both Medium Access Control (MAC) and application level performance and reliability of safety message broadcasting incorporating the impact of multi-channel operations. Message service time distribution is derived using Laplace-Stieltjes transform based on the proposed model. Due to the cyclic interactions between the SMP models for vehicles contending the same channel, fixed-point iteration is used to obtain converged solutions. Subsequently, MAC and application-level performance and reliability metrics are derived based on the converged solutions. Channel fading with path loss is taken into consideration in this derivation. The analytic models are validated through extensive simulations in NS2 to verify the effectiveness and accuracy of our proposed fixed-point iteration based model decomposition. The effects of channel switching mechanism and channel fading are also evaluated by comparing with other analytic models.

Overtaking on rural roads may cause severe accidents when oncoming traffic is detected by a driver too late, or its speed is underestimated. Recently proposed cooperative overtaking assistance systems are based on real-time video transmission, where a video stream captured with a camera installed at the windshield of a vehicle is compressed, broadcast through the wireless channel, and displayed to the drivers of vehicles driving behind. In such a system, it is of ultimate importance to deliver video information about the opposite lane with low end-to-end latency and good visual quality. In this paper, we propose reallocating the wireless channel resources in favor of the part of the captured video frame containing the image of the oncoming vehicle. To achieve this goal, we apply automotive radar for oncoming vehicle detection, and we use the image of this vehicle as a region-of-interest (ROI) for the video rate control. We present the theoretical framework, which describes the basics of such an approach and can serve as a useful guideline for the future practical implementation of the overtaking assistance systems. The benefits of our proposal are demonstrated in relation to the practical scenario of H.264/Advance Video Coding (AVC), IEEE 802.11p/Wireless Access for Vehicular Environments (WAVE) intervehicle communication standards, and currently used automotive radars.

Recent advances in mobile devices and network technologies have set new trends in the way we use computers and access networks. Cloud Computing, where processing and storage resources are residing on the network is one of these trends. The other is Mobile Computing, where mobile devices such as smartphones and tablets are believed to replace personal computers by combining network connectivity, mobility, and software functionality. In the future, these devices are expected to seamlessly switch between different network providers using vertical handover mechanisms in order to maintain network connectivity at all times. This will enable mobile devices to access Cloud Services without interruption as users move around. Using current service delivery models, mobile devices moving from one geographical location to another will keep accessing those services from the local Cloud of their previous network, which might lead to moving a large volume of data over the Internet backbone over long distances. This scenario highlights the fact that user mobility will result in more congestion on the Internet. This will degrade the Quality of Service and by extension, the Quality of Experience offered by the services in the Cloud and especially multimedia services that have very tight temporal constraints in terms of bandwidth and jitter. We believe that a different approach is required to manage resources more efficiently, while improving the Quality of Service and Quality of Experience of mobile media services. This paper introduces a novel concept of Cloud-Based Mobile Media Service Delivery in which services run on localized public Clouds and are capable of populating other public Clouds in different geographical locations depending on service demands and network status. Using an analytical framework, this paper argues that as the demand for specific services increases in a location, it might be more efficient to move those services closer to that location. This will prevent the Internet backbone from experiencing high traffic loads due to multimedia streams and will offer service providers an automated resource allocation and management mechanism for their services.

Overtaking on rural roads often becomes dangerous when oncoming traffic is detected by the driver too late or its speed is underestimated. Up-to-date proposals for cooperative overtaking assistance systems rely either on the beaconing of status messages or on real-time video transmission. The beaconing-based system provides limited information to the driver about the upcoming traffic in the form of warnings. Introduction of the video-based system can extend the amount of driver information, thus, increasing the reliability of the assistance. However, when two platoons of vehicles are meeting each other, the quality of the video information can undergo significant degradation since a common multiple access communication channel is used. In this paper we demonstrate that the performance of a video-based overtaking assistant can be significantly improved if codec channel adaptation is undertaken by exploiting the information from the beacons about any forthcoming increase in the load of the multiple access channel used. The benefits of our approach are demonstrated in relation to the practical scenario of H.264/AVC video coding and IEEE 802.11p/WAVE inter-vehicle communication standards.

Broadcasting of data and control packets is expected to be crucial in vehicular environments. Both safety-related and non-safety applications rely on broadcasting for the exchange of data or status and advertisement messages. According to the specifications of the IEEE 802.11p/WAVE (Wireless Access in Vehicular Environments) standard, vehicles tune into a common frequency during the control channel (CCH) interval, where most of the broadcasting traffic is expected to be delivered. The rest of the time, vehicles switch to one of the available service channels (SCHs) for non-safety related data exchange. Although the WAVE channel switching could heavily affect the network performance, it has not been widely investigated in the literature. In this paper, an analytical model is designed for characterizing the losses of broadcast packets by explicitly accounting for the WAVE channel switching. Loss probabilities have been derived as a function of contention window size, number of vehicles and channel errors.

In vehicular ad-hoc networks (VANETs) beaconing is one of the core communication modes, which is designed to advertise the presence of a car to its neighborhood. For practical applications the delivery of beacons containing the speed, the direction and the position of a car should be organized both timely and successfully. IEEE 802.11p is the most recent developing international standard, which specifies the physical (PHY) and the medium access control (MAC) protocols for car-to-car and car-to-infrastructure communication and is expected to lay the foundation for safety-related and infotainment applications in future VANETs. In previous works, it has been shown that the requirements of safety-related applications for the mean beacon transmission delay could be met for typical cases, but the corresponding probability of a successful beacon reception does not attain the required threshold. In this paper, we present a novel analytical method based on Markov chain for car-to-car communication analysis and investigate the influence of the beacon generation rate on the probability of a successful beacon reception in an IEEE 802.11p-based network.

Active safety in vehicular environment can be achieved by means of installation of the wireless equipment on the boards of cars. Design of highly efficient protocols for car-to-car communications is a challenging task. If an emergency situation happens on the road, the information about it should be disseminated to the stakeholders with low delay and high reliability. In this paper, we derive a theoretical lower bound for the mean message transmission delay in multi-hop vehicular ad-hoc networks.

The IEEE 802.16 standard specifies two contention-based mechanisms for the OFDMA physical layer to transmit bandwidth requests from subscriber station to base station: the standard mechanism is based on Slotted Aloha with a truncated binary exponential backoff; the alternative one is based on CDMA. This paper describes the CDMA-based contention mechanism and presents an analytic model to compute its performance in terms of delay and consumed resources. The tunable parameters for the CDMA-based random access procedure are the number of ranging subchannels, the number of codes per ranging subchannels, and the detection threshold. An optimal configuration is derived for a given load in terms of the request arrival rate.

In this paper we propose a novel model for the capacity analysis on the reservation-based random multiple access system, which can be applied to the medium access control protocol of the emerging WiMax technology. In such a wireless broadband access system, in order to support QoS, the channel time is divided into consecutive frames, where each frame consists of some consequent mini-slots for the transmission of requests, used for the bandwidth reservation, and consequent slots for the actual data packet transmission. Three main outcomes are obtained: first, the upper and lower bounds of the capacity are derived for the considered system. Second, we found through the mathematical analysis that the transmission rate of reservation-based multiple access protocol is maximized, when the ratio between the number of mini-slots and that of the slots per frame is equal to the reciprocal of the random multiple access algorithm's transmission rate. Third, in the case of WiMax networks with a large number of subscribers, our analysis takes into account both the capacity and the mean packet delay criteria and suggests to keep such a ratio constant and independent of application-level data traffic arrival rate.

IEEE 802.16 protocols for metropolitan broadband wireless access systems have been standardized recently. According to the standard, a subscriber station can deliver bandwidth request messages to a base station by numerous methods. This paper provides both the simulation and analytical models for the investigation of specified random access method, which is compared with centralized polling and station- grouping mechanisms. Based on the assumptions of Bernoulli request arrival process and ideal channel conditions, the mean delay of a request transmission is evaluated for varying number of transmission opportunities and different arrival rates.

Recently, the IEEE has standardized the 802.16 protocol for metropolitan broadband wireless access systems. According to the standard, the random access scheme based on the slotted binary exponential backoff algorithm is used in this system for initial ranging and bandwidth requests transmission. This paper provides both the simulation and analytical models for the investigation of the random access in IEEE 802.16. Based on the assumption of finite number of subscriber stations and ideal channel conditions the delay is evaluated for varying number of transmission opportunities and different backoff window sizes