416 research outputs found

    VANET-Based Traffic Monitoring and Incident Detection System: A Review

    Get PDF
    As a component of intelligent transport systems (ITS), vehicular ad hoc network (VANET), which is a subform of manet, has been identified. It is established on the roads based on available vehicles and supporting road infrastructure, such as base stations. An accident can be defined as any activity in the environment that may be harmful to human life or dangerous to human life. In terms of early detection, and broadcast delay. VANET has shown various problems. The available technologies for incident detection and the corresponding algorithms for processing. The present problem and challenges of incident detection in VANET technology are discussed in this paper. The paper also reviews the recently proposed methods for early incident techniques and studies them

    A Study of V2V Communication on VANET: Characteristic, Challenges and Research Trends

    Get PDF
    Vehicle to Vehicle (V2V) communication is a specific type of communication on Vehicular Ad Hoc Network (VANET)  that attracts the great interest of researchers, industries, and government attention in due to its essential application to improve safety driving purposes for the next generation of vehicles. Our paper is a systematic study of V2V communication in VANET that cover the particular research issue, and trends from the recent works of literature. We begin the article with a brief V2V communication concept and the V2V application to safety purposes and non-safety purposes; then, we analyze several problems of V2V communication for VANET related to safety issues and non-safety issues. Next, we provide the trends of the V2V communication application for VANET. Finally, provide SWOT analysis as a discussion to identify opportunities and challenges of V2V communication for VANET in the future. The paper does not include a technical explanation. Still, the article describes the general perspective of VANET to the reader, especially for the beginner reader, who intends to learn about the topic

    Modeling and Performance Evaluation of Advanced Diffusion with Classified Data in Vehicular Sensor Networks

    Get PDF
    International audienceIn this paper, we propose a newly distributed protocol called ADCD to manage information harvesting and distribution in Vehicular Sensor Networks (VSN). ADCD aims at reducing the generated overhead avoiding network congestions as well as long latency to deliver the harvested information. The concept of ADCD is based on the characterization of sensed information (i.e. based on its importance, location and time of collection) and the diffusion of this information accordingly. Furthermore, ADCD uses an adaptive broadcasting strategy to avoid overwhelming users with messages in which they have no interest. Also, we propose in this paper a new probabilistic model for ADCD based on Markov chain. This one aims at optimally tune the parameters of ADCD, such as the optimal number of broadcaster nodes. The analytical and simulation results based on different metrics, like the overhead, the delivery ratio, the probability of a complete transmission and the minimal number of hops, are presented. These results illustrate that ADCD allows to mitigate the information redundancy and its delivery with an adequate latency while making the reception of interesting data for the drivers (related to their location) more adapted. Moreover, the ADCD protocol reduces the overhead by 90% compared to the classical broadcast and an adapted version of MobEyes. The ADCD overhead is kept stable whatever the vehicular density

    Cloud Computing in VANETs: Architecture, Taxonomy, and Challenges

    Get PDF
    Cloud Computing in VANETs (CC-V) has been investigated into two major themes of research including Vehicular Cloud Computing (VCC) and Vehicle using Cloud (VuC). VCC is the realization of autonomous cloud among vehicles to share their abundant resources. VuC is the efficient usage of conventional cloud by on-road vehicles via a reliable Internet connection. Recently, number of advancements have been made to address the issues and challenges in VCC and VuC. This paper qualitatively reviews CC-V with the emphasis on layered architecture, network component, taxonomy, and future challenges. Specifically, a four-layered architecture for CC-V is proposed including perception, co-ordination, artificial intelligence and smart application layers. Three network component of CC-V namely, vehicle, connection and computation are explored with their cooperative roles. A taxonomy for CC-V is presented considering major themes of research in the area including design of architecture, data dissemination, security, and applications. Related literature on each theme are critically investigated with comparative assessment of recent advances. Finally, some open research challenges are identified as future issues. The challenges are the outcome of the critical and qualitative assessment of literature on CC-V

    Towards Vehicle-to-everything Autonomous Driving: A Survey on Collaborative Perception

    Full text link
    Vehicle-to-everything (V2X) autonomous driving opens up a promising direction for developing a new generation of intelligent transportation systems. Collaborative perception (CP) as an essential component to achieve V2X can overcome the inherent limitations of individual perception, including occlusion and long-range perception. In this survey, we provide a comprehensive review of CP methods for V2X scenarios, bringing a profound and in-depth understanding to the community. Specifically, we first introduce the architecture and workflow of typical V2X systems, which affords a broader perspective to understand the entire V2X system and the role of CP within it. Then, we thoroughly summarize and analyze existing V2X perception datasets and CP methods. Particularly, we introduce numerous CP methods from various crucial perspectives, including collaboration stages, roadside sensors placement, latency compensation, performance-bandwidth trade-off, attack/defense, pose alignment, etc. Moreover, we conduct extensive experimental analyses to compare and examine current CP methods, revealing some essential and unexplored insights. Specifically, we analyze the performance changes of different methods under different bandwidths, providing a deep insight into the performance-bandwidth trade-off issue. Also, we examine methods under different LiDAR ranges. To study the model robustness, we further investigate the effects of various simulated real-world noises on the performance of different CP methods, covering communication latency, lossy communication, localization errors, and mixed noises. In addition, we look into the sim-to-real generalization ability of existing CP methods. At last, we thoroughly discuss issues and challenges, highlighting promising directions for future efforts. Our codes for experimental analysis will be public at https://github.com/memberRE/Collaborative-Perception.Comment: 19 page

    Reliable Message Dissemination in Mobile Vehicular Networks

    Full text link
    Les rĂ©seaux vĂ©hiculaires accueillent une multitude d’applications d’info-divertissement et de sĂ©curitĂ©. Les applications de sĂ©curitĂ© visent Ă  amĂ©liorer la sĂ©curitĂ© sur les routes (Ă©viter les accidents), tandis que les applications d’info-divertissement visent Ă  amĂ©liorer l'expĂ©rience des passagers. Les applications de sĂ©curitĂ© ont des exigences rigides en termes de dĂ©lais et de fiabilitĂ© ; en effet, la diffusion des messages d’urgence (envoyĂ©s par un vĂ©hicule/Ă©metteur) devrait ĂȘtre fiable et rapide. Notons que, pour diffuser des informations sur une zone de taille plus grande que celle couverte par la portĂ©e de transmission d’un Ă©metteur, il est nĂ©cessaire d’utiliser un mĂ©canisme de transmission multi-sauts. De nombreuses approches ont Ă©tĂ© proposĂ©es pour assurer la fiabilitĂ© et le dĂ©lai des dites applications. Toutefois, ces mĂ©thodes prĂ©sentent plusieurs lacunes. Cette thĂšse, nous proposons trois contributions. La premiĂšre contribution aborde la question de la diffusion fiable des messages d’urgence. A cet Ă©gard, un nouveau schĂ©ma, appelĂ© REMD, a Ă©tĂ© proposĂ©. Ce schĂ©ma utilise la rĂ©pĂ©tition de message pour offrir une fiabilitĂ© garantie, Ă  chaque saut, tout en assurant un court dĂ©lai. REMD calcule un nombre optimal de rĂ©pĂ©titions en se basant sur l’estimation de la qualitĂ© de rĂ©ception de lien dans plusieurs locations (appelĂ©es cellules) Ă  l’intĂ©rieur de la zone couverte par la portĂ©e de transmission de l’émetteur. REMD suppose que les qualitĂ©s de rĂ©ception de lien des cellules adjacentes sont indĂ©pendantes. Il sĂ©lectionne, Ă©galement, un nombre de vĂ©hicules, appelĂ©s relais, qui coopĂšrent dans le contexte de la rĂ©pĂ©tition du message d’urgence pour assurer la fiabilitĂ© en multi-sauts. La deuxiĂšme contribution, appelĂ©e BCRB, vise Ă  amĂ©liorer REMD ; elle suppose que les qualitĂ©s de rĂ©ception de lien des cellules adjacentes sont dĂ©pendantes ce qui est, gĂ©nĂ©ralement, plus rĂ©aliste. BCRB utilise les rĂ©seaux BayĂ©siens pour modĂ©liser les dĂ©pendances en vue d’estimer la qualitĂ© du lien de rĂ©ception avec une meilleure prĂ©cision. La troisiĂšme contribution, appelĂ©e RICS, offre un accĂšs fiable Ă  Internet. RICS propose un modĂšle d’optimisation, avec une rĂ©solution exacte optimale Ă  l'aide d’une technique de rĂ©duction de la dimension spatiale, pour le dĂ©ploiement des passerelles. Chaque passerelle utilise BCRB pour Ă©tablir une communication fiable avec les vĂ©hicules.Vehicular networks aim to enable a plethora of safety and infotainment applications. Safety applications aim to preserve people's lives (e.g., by helping in avoiding crashes) while infotainment applications focus on enhancing the passengers’ experience. These applications, especially safety applications, have stringent requirements in terms of reliability and delay; indeed, dissemination of an emergency message (e.g., by a vehicle/sender involved in a crash) should be reliable while satisfying short delay requirements. Note, that multi-hop dissemination is needed to reach all vehicles, in the target area, that may be outside the transmission range of the sender. Several schemes have been proposed to provide reliability and short delay for vehicular applications. However, these schemes have several limitations. Thus, the design of new solutions, to meet the requirement of vehicular applications in terms of reliability while keeping low end-to-end delay, is required. In this thesis, we propose three schemes. The first scheme is a multi-hop reliable emergency message dissemination scheme, called REMD, which guarantees a predefined reliability , using message repetitions/retransmissions, while satisfying short delay requirements. It computes an optimal number of repetitions based on the estimation of link reception quality at different locations (called cells) in the transmission range of the sender; REMD assumes that link reception qualities of adjacent cells are independent. It also adequately selects a number of vehicles, called forwarders, that cooperate in repeating the emergency message with the objective to satisfy multi-hop reliability requirements. The second scheme, called BCRB, overcomes the shortcoming of REMD by assuming that link reception qualities of adjacent cells are dependent which is more realistic in real-life scenarios. BCRB makes use of Bayesian networks to model these dependencies; this allows for more accurate estimation of link reception qualities leading to better performance of BCRB. The third scheme, called RICS, provides internet access to vehicles by establishing multi-hop reliable paths to gateways. In RICS, the gateway placement is modeled as a k-center optimisation problem. A space dimension reduction technique is used to solve the problem in exact time. Each gateway makes use of BCRB to establish reliable communication paths to vehicles

    FRIEND: A Cyber-Physical System for Traffic Flow Related Information Aggregation and Dissemination

    Get PDF
    The major contribution of this thesis is to lay the theoretical foundations of FRIEND — A cyber-physical system for traffic Flow-Related Information aggrEgatioN and Dissemination. By integrating resources and capabilities at the nexus between the cyber and physical worlds, FRIEND will contribute to aggregating traffic flow data collected by the huge fleet of vehicles on our roads into a comprehensive, near real-time synopsis of traffic flow conditions. We anticipate providing drivers with a meaningful, color-coded, at-a-glance view of flow conditions ahead, alerting them to congested traffic. FRIEND can be used to provide accurate information about traffic flow and can be used to propagate this information. The workhorse of FRIEND is the ubiquitous lane delimiters (a.k.a. cat\u27s eyes) on our roadways that, at the moment, are used simply as dumb reflectors. Our main vision is that by endowing cat\u27s eyes with a modest power source, detection and communication capabilities they will play an important role in collecting, aggregating and disseminating traffic flow conditions to the driving public. We envision the cat\u27s eyes system to be supplemented by road-side units (RSU) deployed at regular intervals (e.g. every kilometer or so). The RSUs placed on opposite sides of the roadway constitute a logical unit and are connected by optical fiber under the median. Unlike inductive loop detectors, adjacent RSUs along the roadway are not connected with each other, thus avoiding the huge cost of optical fiber. Each RSU contains a GPS device (for time synchronization), an active Radio Frequency Identification (RFID) tag for communication with passing cars, a radio transceiver for RSU to RSU communication and a laptop-class computing device. The physical components of FRIEND collect traffic flow-related data from passing vehicles. The collected data is used by FRIEND\u27s inference engine to build beliefs about the state of the traffic, to detect traffic trends, and to disseminate relevant traffic flow-related information along the roadway. The second contribution of this thesis is the development of an incident classification and detection algorithm that can be used to classify different types of traffic incident Then, it can notify the necessary target of the incident. We also compare our incident detection technique with other VANET techniques. Our third contribution is a novel strategy for information dissemination on highways. First, we aim to prevent secondary accidents. Second, we notify drivers far away from the accident of an expected delay that gives them the option to continue or exit before reaching the incident location. A new mechanism tracks the source of the incident while notifying drivers away from the accident. The more time the incident stays, the further the information needs to be propagated. Furthermore, the denser the traffic, the faster it will backup. In high density highways, an incident may form a backup of vehicles faster than low density highways. In order to satisfy this point, we need to propagate information as a function of density and time

    Fog Connectivity Clustering and MDP Modeling for Software-defined Vehicular Networks

    Get PDF
    Intelligent and networked vehicles cooperate to create a mobile Cloud through vehicular Fog computing (VFC). Such clouds rely heavily on the underlying vehicular networks, so estimating communication resilience allows to address the problems caused by intermittent vehicle connectivity for data transfers. Individually estimating the communication stability of vehicles, nevertheless, undergoes incorrect predictions due to their particular mobility patterns. Therefore, we provide a region-oriented fog management model based on the connectivity through vehicular heterogeneous network environment via V2X and C-V2X. A fog management strategy dynamically monitors nearby vehicles to determine distinct regions in urban centres. The model enables a software-defined vehicular network (\Gls{SDVN}) controller to coordinate data flows. The vehicular connectivity described by our model assesses the potential for vehicle communication and conducts dynamic vehicle clustering. From the stochasticity of the environment, our model is based on Markov Decision Process (MDP), tracking the status of vehicle clusters and their potential for provisioning services. The model for vehicular clustering is supported by 5G and DSRC heterogeneous networks. Simulated analyses have shown the capability of our proposed model to estimate cluster reliability in real-time urban scenarios and support effective vehicular fog management
    • 

    corecore