Showing papers on "Vehicular communication systems published in 2019"

A multiclass microscopic model for heterogeneous platoon with vehicle-to-vehicle communication

Abstract: Connected and autonomous (CA) vehicles have been verified to significantly improve traffic efficiency. However, there is still a long lifespan for heterogeneous traffic flow consisting of both human-driven and CA vehicles. Thus a deep understanding of the heterogeneous platoon dynamics is critical to the traffic stability issues for the deployment of CA vehicles in the near future. This paper aims to develop a multiclass microscopic model for a heterogeneous platoon which can explicitly demonstrate the interaction between human-driven and CA vehicles. Specifically, the consensus-based control algorithm is adopted to model the dynamics of CA vehicles and a typical car-following model is used to describe the dynamics of human-driven vehicles. We then theoretically and numerically study the linear stability condition of the heterogeneous platoon which takes into account the probabilistic delay in the communication, the penetration of the CA vehicles, and the relative order of the vehicle types in the platoon.

Game Theory Based Opportunistic Computation Offloading in Cloud-Enabled IoV

Abstract: With the growing popularity of the fifth-generation (5G) wireless systems and cloud-enabled Internet of Vehicles, vehicular cloud has been introduced as a novel mobile device computing mode, which enables vehicles to offload their computation-intensive tasks to neighbors. In this paper, we first present a 5G cloud-enabled scenario of vehicular cloud computing where a vehicular terminal works either as a service provider with idle computation resources or a requestor who has a computation-intensive task that can be executed either locally or offloaded to nearby providers via opportunistic vehicle-to-vehicle communications. Then, we study the following issues: 1) how to determine the appropriate offloading rate of requestors; 2) how to select the most appropriate computation service provider; 3) how to identify the ideal pricing strategy for each service provider. We address the above-mentioned problems by developing a two-player Stackelberg-game-based opportunistic computation offloading scheme under situations involving complete and incomplete information that primarily considers task completion duration and service price. We simplify the former case into a common resource assignment problem with mathematical solutions. For the latter case, Stackelberg equilibriums of the offloading game are derived, and the corresponding existence conditions are concretely discussed. Finally, a Monte-Carlo simulation-based performance evaluation shows that the proposed methods can significantly reduce the task completion duration while ensuring the profit of service providers, thus achieving mutually satisfactory computation offloading decisions.

A Game Theoretic Scheme for Optimal Access Control in Heterogeneous Vehicular Networks

Abstract: The heterogeneous vehicular networks (HetVNETs), which apply the heterogeneous access technologies ( e.g. , cellular networks and WiFi) complementarily to provide seamless and ubiquitous connections to vehicles, have emerged as a promising and practical paradigm to enable vehicular service applications on the road. However, with different costs in terms of latency time and price, how to optimize the connection along the vehicle’s trip toward the lowest cost represents fundamental challenges. This paper investigates the issue by proposing an optimal access control scheme for vehicles in HetVNETs. In specific, with different access networks, we first model the cost of each vehicle to download the requested content by jointly considering the vehicle’s requirements of the requested content and the features of the available access networks, including conventional vehicle to vehicle communication and the heterogeneous access technologies. A coalition formation game is then introduced to formulate the cooperation among vehicles based on their different interests (contents cached in vehicles) and requests (contents to be downloaded). After forming the coalitions, vehicles in the same coalition can download their requested contents cooperatively by selecting the optimal access network to achieve the minimum costs. The simulation results demonstrate that the proposed game approach can lead to the optimal strategy for the vehicle.

Virtual Edge Computing Using Vehicular Micro Clouds

Abstract: We will discuss the challenges and opportunities of the connected cars vision in relation to the need for distributed data management solutions ranging from the vehicle to the mobile edge and to the data centers. As a novel concept, vehicular micro clouds have been proposed that bridge the gap between fully distributed vehicular networks based on short range vehicle to vehicle communication and cellular based infrastructure for centralized solutions. We will discuss the need for vehicular micro clouds, followed by the architecture, formation of micro clouds, and feasibility of micro clouds. Furthermore, we will cover aspects of efficient data upload and download between cars and a data center facilitated by our micro cloud concept.

Pseudonym Management Through Blockchain: Cost-Efficient Privacy Preservation on Intelligent Transportation Systems

Abstract: Research into the established area of the intelligent transportation system is evolving into the Internet of Vehicles, a fast-moving research area, fuelled in part by rapid changes based on cyber-physical systems. It needs to be recognized that existing vehicular communication systems are susceptible to privacy vulnerabilities which require addressing. A practical challenge is that many vehicular communication applications and services make use of basic safety messages that contain the identity of the vehicle, location, and other personal data. A popular way of dealing with this privacy issue is to utilize a pseudonym change scheme to protect the vehicle's identity and location. However, many such schemes suffer that the cost grows and the certificate management difficulty raises with the number of pseudonyms generated and stored, casting doubt of the economic feasibility of that approach. We propose a decentralized blockchain-based solution for pseudonym management that overcomes these limitations. This scheme consists of pseudonym distribution and a shuffle operation, allowing the reuse of existing pseudonyms to different vehicles. The results reported here, including those from our simulations, demonstrate that the proposed scheme can reuse existing pseudonyms and achieve a better degree of anonymity at a lower cost than existing schemes.

A Path Loss Model for Vehicle-to-Vehicle Visible Light Communications

Abstract: The increasing adoption of LEDs in exterior automotive lighting makes visible light communication (VLC) a natural solution for vehicular networking. In this paper, we consider a vehicle-to-vehicle link and propose a path loss expression as a function of distance and different weather conditions. We conduct ray tracing simulations and verify the accuracy of proposed expression. We further use this expression to derive the achievable transmission distance for a targeted data rate while satisfying a given value of bit error rate. Numerical results are presented to demonstrate the achievable distances for single and dual photodetector deployment cases.

Data-Driven Network Simulation for Performance Analysis of Anticipatory Vehicular Communication Systems

Abstract: The provision of reliable connectivity is envisioned as a key enabler for future autonomous driving. Anticipatory communication techniques have been proposed for proactively considering the properties of the highly dynamic radio channel within the communication systems themselves. Since real world experiments are highly time-consuming and lack a controllable environment, performance evaluations and parameter studies for novel anticipatory vehicular communication systems are typically carried out based on network simulations. However, due to the required simplifications and the wide range of unknown parameters (e.g., Mobile Network Operator (MNO)-specific configurations of the network infrastructure), the achieved results often differ significantly from the behavior in real world evaluations. In this paper, we present Data-driven Network Simulation (DDNS) as a novel data-driven approach for analyzing and optimizing anticipatory vehicular communication systems. Different machine learning models are combined for achieving a close to reality representation of the analyzed system's behavior. In a proof of concept evaluation focusing on opportunistic vehicular data transfer, the proposed method is validated against field measurements and system-level network simulation. In contrast to the latter, DDNS does not only provide massively faster result generation, it also achieves a significantly better representation of the real world behavior due to implicit consideration of cross-layer dependencies by the machine learning approach.

Traffic-Aware Relay Vehicle Selection in Millimeter-Wave Vehicle-to-Vehicle Communication

Abstract: Line-of-sight (LOS) blockage is a crucial problem in millimeter-wave vehicle-to-vehicle communication due to its severe penetration loss and high vehicle mobility. In order to overcome the LOS blockage problem, in this letter, we propose using neighbor vehicles as relays to forward the blocked traffic flows. Specifically, a traffic-aware relay vehicle selection is investigated. First, analytic hierarchy process (AHP) is adopted to handle the situation that different traffic types have different preferences on the performances of rate, delay and data dropping ratio. Second, we introduce a coalitional game (CG) to evaluate the relative performances of the relay vehicles. Finally, by combining the results of AHP and CG, a heuristic relay selection scheme is devised by selecting the relay vehicle with the best rationality degree. Simulation results show that the proposed scheme can adapt to the requirements of different traffic types and improve the performances of rate, delay and data dropping ratio when LOS blockage occurs.

Efficient Data Dissemination for Urban Vehicular Environments

Abstract: Vehicular communication systems play an important role in the context of smart cities. Different applications are being proposed and evaluated to improve our daily driving in terms of safety and convenience. These applications require efficient data dissemination that guarantees full coverage with minimum overhead and delay. Existing data dissemination protocols often rely on extra communication to gather knowledge about the neighborhood and set the dissemination criteria accordingly. This extra communication poses serious overhead issues that affect the scalability of data dissemination, which is an essential criterion under high density scenarios. In this paper, we propose and evaluate an Efficient multi-directional Data Dissemination Protocol (EDDP), which considers the requirements of an urban vehicular environment without requiring the extra communication overhead. We rely only on simple local data to indicate the road condition for better dissemination performance. In this paper, the design considerations of urban layout include message format, broadcast suppression mechanism, and delay control. The EDDP utilizes the properties of the received messages along with positioning information to make decisions on suppressing broadcasts, with the objective of improving coverage in different directions without unnecessary transmissions. Simulation results show that the EDDP can effectively disseminate traffic data with a high data delivery ratio and a minimized overhead.

Fast Video Frame Correlation Analysis for Vehicular Networks by Using CVS–CNN

Abstract: In vehicular communication systems, due to limited computation power of vehicles, low-cost sampling technologies, such as compressed video sensing (CVS), have been proposed. However, after one-time coarse compressive sampling, it is difficult to obtain accurate temporal correlation between video frames. To address this issue, this paper proposes a correlation analysis model in the measurement domain by combining CVS and convolutional neural network (CNN), which is termed as “CVS–CNN.” Specifically, to analyze the temporal correlation of video frames in the measurement domain, we use CNN as a substitute for the pseudo-inverse transform of the measurement matrix and establish the correlation between the measurements of the block to be estimated and those of the neighboring non-overlapping blocks. The network parameters are trained to minimize the loss between the predicted and true measurements, and are assigned to the non-overlapping image blocks. The various experimental results demonstrate that the proposed CVS–CNN method significantly outperforms similar methods of analyzing the video frame correlation in accuracy, process speed, and robustness. This result indicates that the proposed method can be used in many potential applications, such as self-driving systems and in-car warning systems.

Multiclass information flow propagation control under vehicle-to-vehicle communication environments

Abstract: Most existing models for information flow propagation in a vehicle-to-vehicle (V2V) communications environment are descriptive. They lack capabilities to control information flow, which may preclude their ability to meet application needs, including the need to propagate different information types simultaneously to different target locations within corresponding time delay bounds. This study proposes a queuing-based modeling approach to control the propagation of information flow of multiple classes. Two control parameters associated with a vehicle, the number of communication servers and the mean communication service rate, are leveraged to control the propagation performance of different information classes. A two-layer model is developed to characterize the information flow propagation wave (IFPW) under the designed queuing strategy. The upper layer is formulated as integro-differential equations to characterize the spatiotemporal information dissemination due to V2V communication. The lower layer characterizes the traffic flow dynamics using the Lighthill–Whitham–Richards model. The analytical solution of the asymptotic density of informed vehicles and the necessary condition for existence of the IFPW are derived for homogeneous traffic conditions. Numerical experiments provide insights on the impact of the mean communication service rate on information spread and its spatial coverage. Further, a numerical solution method is developed to solve the two-layer model, which aids in estimating the impacts of the control parameters in the queuing strategy on the IFPW speed under homogenous and heterogeneous conditions. The proposed modeling approach enables controlling the propagation of information of different information classes to meet application needs, which can assist traffic managers to design effective and efficient traffic management and control strategies under V2V communications.

Vehicle-to-vehicle communication based on a peer-to-peer network with graph theory and consensus algorithm

Abstract: Vehicle-to-vehicle communication is an important part of the modern intelligent transportation system. Most of the existing vehicle networks are based on central structures, which are prone to single point of failures, and may consequently result in system paralysis. In order to increase the network fault tolerance and maintain the stability of the network system, the authors propose a vehicle network model based on the peer-to-peer (P2P) network. In this model, the base station and the roadside units will no longer be necessary facilities. The vehicles can be used as relays to directly participate in the exchange and transfer of information. The relay nodes (vehicles) are selected based on the degree distribution and the consensus algorithm. The real-time capability, efficiency and cost effectiveness of the proposed P2P model is verified through experimental results.

Experimental Evaluation of Intelligent Transport System with VLC Vehicle-to-Vehicle Communication

Abstract: Visible light communication (VLC) is suitable and natural candidate for vehicular communication. This paper presents the vehicle to vehicle communication system based on VLC technology utilizing light emitting diodes (LEDs) as a transmitter and photodiode as a receiver. The LEDs are present everywhere in outdoor and vehicles utilizing those for communication. Vehicular ad hoc networks are facilitated by empowering enormous applications to require both proficient and reliable data delivery. Low-latency, simple and cost-effective system is designed with less complexity and high consistency by employing off-the-shelf LEDs and photodiodes which mitigates the implementation of complex protocols of typical wireless communication systems. The signal is transmitted from one vehicle that will be received by another vehicle to make sensible steps and to maintain strategic distance to avoid accidents. In this paper, the performance analysis of VLC based vehicle to vehicle communication (V2V) is presented. The results show that 3.5 Mbps and 500 kbps of data rates have been achieved over the distance of 0.5 and 15 m respectively. Amplitude shift keying, frequency shift keying (FSK) and phase shift keying schemes are tested with non-return-zero coding scheme. Bit error rate, received optical power and received signal voltages are measured and analyzed in this paper for V2V communication. The FSK modulation is an efficient technique for long distance as it has lower losses compared to other techniques. Warning messages are displayed on liquid crystal display. The prototype is evaluated experimentally over the distance of 15 m using an array of LEDs to reduce the chances of accidents. Bit error rate of 10−11 for FSK modulation has been achieved with the signal to noise ratio value of 13 dB in this work. The results confirmed the performance of the proposed system and presented that VLC is a feasible technology for vehicular communication.

Could-based vehicular networks: a taxonomy, survey, and conceptual hybrid architecture

Abstract: In recent times, vehicular network research has attracted the attention of both researchers and the industry partly due to its potential applications in efficient traffic management, road safety, entertainment, etc. Resources such as communication, on-board unit, storage and computing units, and battery are generally installed in the vehicles participating in intelligent transportation systems. The need to maximize the utilization of these resources has also resulted in interest in cloud based vehicular networks (CVNs), an area of active research. This paper survey the CVNs literature published between 2010 and 2016. In addition, a taxonomy based on three main CVN categories, namely vehicular cloud computing (VCC), vehicle using cloud (VuC) and hybrid cloud (HC), is presented. In the taxonomy, we focus on related systems, architectures, applications and services. Although VCC has been extensively discussed in the literature, a comprehensive survey on the two other categories is lacking. Hence, this motivates our research. Through an extensive comparison of common characteristics among cloud computing, mobile cloud computing, VCC, VuC and HC and overview of the existing architectures, we present a conceptual HC architecture. Finally, we conclude the paper with open issues and challenges.

CNVPS: Cooperative Neighboring Vehicle Positioning System Based on Vehicle-to-Vehicle Communication

Abstract: One of the key components of the intelligent transport system is to provide a safe driving environment. The ability to quickly and accurately recognize the surrounding environments and neighboring vehicles is essential for the development of safety-related services to provide a safe driving environment. Currently, research in this field is being conducted based on the global positioning system (GPS), light detection and ranging, camera, and ranging sensors. However, the currently used sensors cannot recognize a wide range of vehicles because of their limited range of recognition. Moreover, GPS-based studies are highly affected by the surrounding environment because of the nature of GPS and have relatively high error rates and low rate of location information updates. The use of GPS-based location information for safety-related services can result in negative consequences. In this paper, we propose a new positioning system, called cooperative neighboring vehicle positioning system (CNVPS). The CNVPS rapidly identifies the locations of neighboring vehicles based on their information obtained through various sensors and shares this information with a wide range of neighboring vehicles over vehicle-to-vehicle communications. The CNVPS also compensates the position of a neighboring vehicle by applying the maximum likelihood estimation to the duplicated position observation of the other neighboring vehicles. The simulation results show that the CNVPS achieves approximately 370% improvement in location errors over GPS, assuming that the root-mean-squared error of GPS is 15 m. In addition, the proposed system has a location refresh cycle ten times faster than the existing GPS-based system.

Explicit Negotiation Method for Cooperative Automated Vehicles

Abstract: The cooperation of road traffic participants is desirable in order to increase overall efficiency and safety. Using the ITS-G5 standard, automated vehicles can exchange status information and negotiate conditions of cooperative maneuvers. This paper deals with a method for explicit negotiation of conflicting maneuvers between vehicles. For that, a cooperation method that contains an application level vehicle-to-vehicle communication procedure is established to enable traffic participants to reserve areas on the street precisely defined in position and time. The method is flexible and thus capable of being applied to various traffic situations. For the evaluation of the method, several traffic situations with multiple automated vehicles are simulated with and without the use of the cooperation method. The comparison between the cooperative and the non-cooperative scenarios shows a significant decrease of the travel time for a constant distance using the cooperation method.

A Vehicle-Assisted Data Offloading in Mobile Edge Computing Enabled Vehicular Networks

Abstract: With the emerging applications of vehicular networks, how to provide sufficient communication and computation supports are the two most important challenges for vehicular communication systems. Cloud-based vehicular networks and mobile edge computing frameworks have been proposed to relieve the computing burden of vehicles. However, for time-sensitive and computation-intensive applications with large input data size, e.g. image aided navigation, the data transmission process occupies large bandwidth, which may degrade the quality of service of all network users, especially in high density scenarios. Thus, in this paper we formulate a computation offloading problem for these time-sensitive and computation-intensive applications to minimize the data transmitted to the server. We propose two approaches to solve the formulated problem, i.e. a graph theory based method and a heuristic algorithm. Simulation results demonstrate that both algorithms can achieve near optimal solutions and greatly reduce the data volume transmitted to the server.

Predictive Cruise Control with Private Vehicle-to-Vehicle Communication for Improving Fuel Consumption and Emissions

Abstract: Future traffic information through vehicular communication allows connected and automated vehicles to optimize their speed trajectories and drive more safely and efficiently through predictive controllers. Sharing accurate information about the vehicle allows such controllers to perform best, but may raise privacy concerns. To improve privacy guarantee over the shared information while preserving its utility for predictive controllers, this article proposes a novel information perturbation mechanism, as opposed to the baseline of independently perturbing the data in each broadcast. Specifically, the mechanism is applied to the transmitted vehicle speed, and this perturbed data is used in an optimal speed planner to design a fuel and emissions efficient speed trajectory. Results show a deterioration of the controller performance when privacy is taken into consideration under the baseline method. With the proposed method, the controller performance is improved while providing the same privacy guarantee. It is shown that controller design is also affected by the choice of perturbation mechanism.

Evolution of Vehicular Communications within the Context of 5G Systems

Abstract: Vehicles and roads are starting to be connected and gradually moving towards fully autonomous vehicles and truly intelligent road infrastructure. This chapter investigates the evolution of vehicular communication systems towards fifth generation (5G) and how the applications and services follow that evolution. It also investigates the cellular‐based solution, and how it is evolving from LTE Release 14, the initial C‐V2X system, towards Release 16, the fully‐fledged 5G system. The chapter focuses in the co‐existence issues with dedicated short range communication and what other technologies contribute to efficient V2X services. It also focuses on the data dissemination on top of a vehicular communication platform that could support efficient cloud‐based Intelligent Transportation Services. The chapter examines how the evolution of V2X communication technologies is mirrored on the evolution of services it supports, from awareness to autonomous driving.

Simulation based Vehicle to Vehicle and base station communication

Abstract: Vehicle to Vehicle (V2V) communication plays a significant role in the Intelligent Transportation System (ITS) in Vehicular Ad hoc Networks (VANET) for which the usage of IOT in vehicles is increasing rapidly. Vehicles communicate with each other through wireless networks. However, the deployment of new generation of mobile networks 5G needs a major upgradation of its existing systems such as 4G, LTE and other infrastructure. Therefore, it is proposed to introduce advanced technology of 5G networks upgradation in Vehicle to Vehicle communication. Massive MIMO have the important role for the DSRC (Dedicated Short Range Communication) wireless technology. This mechanism works on the vehicle-to-vehicle communication such as the vehicle relative speed, range transmission etc., base station (tower) and RSU control and monitor of the vehicle to vehicle communication. In this research, the road styles such as square, straight, triangle and any other are designed and tested through simulation program using MATLAB 2017. The upcoming 5G technology for driverless V2V communication makes the journey easier and safer with full control.

A Deep Learning Based Resource Allocation Scheme in Vehicular Communication Systems

Abstract: In vehicular communications, intracell interference and the stringent latency requirement are challenging issues. In this paper, a joint spectrum reuse and power allocation problem is formulated for hybrid vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communications. Recognizing the high capacity and low-latency requirements for V2I and V2V links, respectively, we aim to maximize the weighted sum of the capacities and latency requirement. By decomposing the original problem into a classification subproblem and a regression subproblem, a convolutional neural network (CNN) based approach is developed to obtain real-time decisions on spectrum reuse and power allocation. Numerical results further demonstrate that the proposed CNN can achieve similar performance as the Exhaustive method, while needs only 3.62% of its CPU runtime.

Range Optimization for DSRC and 5G Millimeter-Wave Vehicle-to-Vehicle Communication Link

Abstract: The Dedicated Short Range Communications (DSRC) band (5.85-5.925 GHz) allocated for vehicle-to-vehicle (V2V) communication provides limited opportunities for high speed data transfer. Alternatively, high speed communication of at least 1Gbps is possible in the millimeter-wave (mm-wave) bands. To overcome the propagation losses associated with mmwave frequencies, high gain radio architectures are required. In this paper, we present a novel dual-band V2V receiver architecture for both DSRC and 28GHz communications. For each band, we optimized antenna gain and number of elements to maximize range and data rate. For simplicity, free space path loss model was used for link budget estimation. Results show that an antenna array of at least 9×9 element is required to achieve a maximum data rate of 27Mbps at 5.9GHz and a range of 867m. At 28GHz, the same 9×9 dual band array is capable of transmitting high speed signals at a rate of 1Gbps with coverage of 688m.

Concurrent Transmission Scheduling for Perceptual Data Sharing in mmWave Vehicular Networks

Abstract: Sharing perceptual data with other vehicles enhances the traffic safety of autonomous vehicles because it helps vehicles locate other vehicles and pedestrians in their blind spots. Such safety applications require high throughput and short delay, which cannot be achieved by conventional microwave vehicular communication systems. Therefore, millimeter-wave (mmWave) communications are considered to be a key technology for sharing perceptual data because of their wide bandwidth. One of the challenges of data sharing in mmWave communications is broadcasting because narrow-beam directional antennas are used to obtain high gain. Because many vehicles should share their perceptual data to others within a short time frame in order to enlarge the areas that can be perceived based on shared perceptual data, an efficient scheduling for concurrent transmission that improves spatial reuse is required for perceptual data sharing. This paper proposes a data sharing algorithm that employs a graph-based concurrent transmission scheduling. The proposed algorithm realizes concurrent transmission to improve spatial reuse by designing a rule that is utilized to determine if the two pairs of transmitters and receivers interfere with each other by considering the radio propagation characteristics of narrow-beam antennas. A prioritization method that considers the geographical information in perceptual data is also designed to enlarge perceivable areas in situations where data sharing time is limited and not all data can be shared. Simulation results demonstrate that the proposed algorithm doubles the area of the cooperatively perceivable region compared with a conventional algorithm that does not consider mmWave communications because the proposed algorithm achieves high-throughput transmission by improving spatial reuse. The prioritization also enlarges the perceivable region by a maximum of 20%.

Iterative greedy user clustering algorithm for D2D–relay in vehicular communication systems

Abstract: Device-to-device (D2D) communications help in improving the performance of wireless services in cellular networks via enabling cooperation among mobile users. Further, compared to traditional pairwise cooperation, cluster-wise cooperation can achieve even higher spectral and power efficiency. D2D clustering certainly can be a great supporting technology for the future of intelligent transportation. In this study, the authors investigate the D2D-relay clustering network in the vehicular scenario and propose a new clustering scheme named iterative greedy user clustering (IGUC). By exploiting those vehicles with better channel state, system resources can be saved. Here, they mainly focus on the question which is by applying D2D-relay clustering among vehicles, how much bandwidth could be saved in the uplink. This problem is mathematically formulated into a non-linear binary programming problem with the goal being minimum spectrum usage. Due to the NP-hardness, the low-complexity suboptimal algorithm IGUC is introduced to tackle it. Simulation results show that compared to the non-cooperative uplink system, IGUC saves a considerable proportion of the spectrum. Furthermore, clusters in denser and further areas tend to produce a higher gain. Influence of the fast time-varying characteristic of vehicular wireless channels is also investigated, upon which an adaptive switch mechanism is proposed to further facilitate IGUC.

Interference Tests of ITS-G5 Vehicle-to-Vehicle Communication Networks with Virtual Drive Tests

Abstract: Automotive communication systems have become a hot topic in the research field, especially with a focus towards connected vehicles. The potential of connected and automated driving promises an enormous increase of road safety and traffic efficiency. With this purpose, dedicated short range communication standards (e.g. ITS-G5) have been developed. These standards share spectral resources among all communication partners, which necessitates an evaluation of in-band interference. As one potentially powerful evaluation approach, the road and radio environment can be emulated instead of being accessed through field-operational tests, with major advantages like repeatability and convenience aspects. This paper describes a testing framework that employs a virtual-drive test approach for the evaluation of the performance of ITS-G5 equipment. According to the concept of virtual-drive testing, the road and radio environments have been emulated with regards to a realworld drive track. Packet loss measurements are presented for the evaluation of interference effects present in the communication. The results indicate that the virtual-drive test approach is suitable for testing automotive communication systems.

Performance modeling of SEAD protocol in vehicular environment

Abstract: Toward the growing number of the transport safety applications offered by VANET, a large amount of messages need to be efficiently disseminated between connected vehicles. The requirement for an efficient data dissemination in vehicular environment is ensuring the highest data reachability, using the minimum network resources within a short end to end delay. To meet these properties, researchers have addressed the data dissemination challenges, mainly the famous broadcast storm, which has lead to a wide variety of solutions. In this work, we present two Simple and Efficient Adaptive data Dissemination protocols called SEAD1 and SEAD2 that combine a probabilistic and a delay based approach. The originality of these protocols is that they can be adaptively tuned according to the VANET applications’ requirements. Therefore, a rigorous performance evaluation of the protocols is proposed through an analytic model and a large set of NS3 simulations. The analytic results show excellent fits to the simulation results which confirm the accuracy of the proposed model. Moreover, based on our analytic model we became able to thoroughly study the protocols parameters’ behavior and derive an accurate configuration. Thereby, a proper trade-off between the packet delivery ratio and the redundancy ratio is possible in attempt to tune the protocols performance according to the application criticality level.

Beamforming for Beaconing in V2V Communications

Abstract: The following manuscript studies the benefits and weaknesses of using beamforming for beaconing in a vehicle to vehicle communication scenario following the specifications of the IEEE 802.11p standard. This is done through a simulation in which the performance of a uniform linear array of two isotropic antennas is compared to an isotropic antenna with the same power in a two lane intercity highway. The use of beamforming results in an increase in the collisions in the network, but this is compensated through a larger number of vehicles being reached in the network. Therefore, more re-transmissions are possible in case of a collision, and a lower probability of losing information is expected, which results in more reliable communications.