Relevant bibliographies by topics / Vehicle-to-vehicle (V2V) communication

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  1. Journal articles
  2. Dissertations / Theses
  3. Book chapters
  4. Conference papers
  5. Reports

Academic literature on the topic 'Vehicle-to-vehicle (V2V) communication'

Author: Grafiati
Published: 4 June 2021
Last updated: 31 January 2023

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Journal articles on the topic "Vehicle-to-vehicle (V2V) communication"

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Khan, Usman Ali, and Sang Sun Lee. "Distance-Based Resource Allocation for Vehicle-to-Pedestrian Safety Communication." Electronics 9, no. 10 (2020): 1640. http://dx.doi.org/10.3390/electronics9101640.

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Cellular Vehicle to Everything (V2X) has redefined the vehicular communication architecture as something that needs an ultra-reliable link, high capacity, and fast message delivery in vehicular networks. The V2X scenarios are broadly categorized as Vehicle to Vehicle (V2V), Vehicle to Infrastructure (V2I), Vehicle to Pedestrians (V2P), and Vehicle to Network (V2N). Vulnerable pedestrians belong to the V2P category and hence require an ultra-reliable link and a fast message delivery in case the moving vehicle is in the close proximity of the pedestrian. However, congestion in the network calls for an optimized resource allocation that would allow a fast and secure connection between a vehicle and the pedestrian. In this paper, we have proposed a distance-based resource allocation that classifies the pedestrians in different categories, performs a one-to-many weighted bipartite matching, and finally a reinforcement learning based power allocation.
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Pan, Bin, and Hao Wu. "Success Probability Analysis of C-V2X Communications on Irregular Manhattan Grids." Wireless Communications and Mobile Computing 2020 (August 19, 2020): 1–13. http://dx.doi.org/10.1155/2020/2746038.

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To overcome the shortcomings of Dedicated Short Range Communications (DSRC), cellular vehicle-to-everything (C-V2X) communications have been proposed recently, which has a variety of advantages over traditional DSRC, including longer communication range, broader coverage, greater reliability, and smooth evolution path towards 5G. In this paper, we consider an LTE-based C-V2X communications network in irregular Manhattan grids. We model the macrobase stations (MBSs) as a 2D Poisson point process (PPP) and model the roads as a Manhattan Poisson line process (MPLP), with the roadside units (RSUs) modeled as a 1D PPP on each road. As an enhancement architecture to DSRC, C-V2X communications include vehicle-to-vehicle (V2V) communication, vehicle-to-infrastructure (V2I) communication, vehicle-to-pedestrian (V2P) communication, and vehicle-to-network (V2N) communication. Since the spectrum for PC5 interface in 5.9 GHz is quite limited, cellular networks could share some channels to V2I links to improve spectral efficiency. Thus, according to Maximum Power-based Scheme, we adopt the stochastic geometry approach to compute the signal-to-interference ratio- (SIR-) based success probability of a typical vehicle that connects to an RSU or an MBS and the area spectral efficiency of the whole network over shared V2I and V2N downlink channels. In addition, we study the asymptotic characteristics of success probability and provide some design insights according to the impact of several key parameters on success probability.
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Hu, Bin, and Hamid Gharavi. "A Joint Vehicle-Vehicle/Vehicle-Roadside Communication Protocol for Highway Traffic Safety." International Journal of Vehicular Technology 2011 (April 27, 2011): 1–10. http://dx.doi.org/10.1155/2011/718048.

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A joint vehicle-vehicle/vehicle-roadside communication protocol is proposed for cooperative collision avoiding in Vehicular Ad Hoc Networks (VANETs). In this protocol, emergency warning messages are simultaneously transmitted via Vehicle-to-Vehicle (V2V) and Vehicle-to-Roadside (V2R) communications in order to achieve multipath diversity routing. In addition, to further improve communication reliability and achieve low latency, a Multi-Channel (MC) technique based on two nonoverlapping channels for Vehicle-Vehicle (V2V) and V2R (or R2V) is proposed. The simulation results demonstrate that the proposed joint V2V/V2R (R2V) communication protocol is capable of improving the message delivery ratio and obtaining low latency, which are very important merits for highway traffic safety.
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Liu, Yu, Xinzheng Wang, and Huiling Zheng. "5G-V2X Based Traffic Safety Warning System through Mobile Sensor and Wireless Communication." Journal of Physics: Conference Series 2083, no. 2 (2021): 022025. http://dx.doi.org/10.1088/1742-6596/2083/2/022025.

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Abstract This project designs a traffic safety early warning system based on 5G-V2X for the current situation of increasing traffic accidents in China, which concentrates on two modules of V2V (vehicle-to-vehicle), V2I (vehicle-to-road) for early warning system design, with OBU (vehicle communication unit) and RSU (roadside communication unit) based on 5G-V2X communication technology to establish vehicle-to-vehicle and vehicle-to-road interactive communication, and realize V2V collision warning and V2I traffic light emergency event warning at intersections through collision risk warning algorithm and intersection passage assistance algorithm, thus alerting drivers to avoid dangerous situations and reducing the incidence of traffic accidents.
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Yogarayan, Sumendra, Siti Fatimah Abdul Razak, Afizan Azman, and Mohd Fikri Azli Abdullah. "VEHICLE TO EVERYTHING (V2X) COMMUNICATIONS TECHNOLOGY FOR SMART MOBILITY IN MALAYSIA: A COMPREHENSIVE REVIEW." Journal of Southwest Jiaotong University 56, no. 4 (2021): 534–63. http://dx.doi.org/10.35741/issn.0258-2724.56.4.47.

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Vehicle to Everything (V2X) communication technology assesses the potential as the new phenomenon for Intelligent Transportation Systems (ITS) in the context of vehicle-to-vehicle (V2V), vehicle-to-infrastructure (V2I), vehicle-to-pedestrian (V2P), and vehicle-to-network (V2N). Dedicated Short-Range Communications (DSRC) is the conventional vehicular communication standard for ITS. The cellular network based on 4G/5G for ITS deployment has become a competitor to DSRC. Recent advancements in technologies have motivated the research community to develop a hybrid DSRC, and cellular networks approach to support reliable ITS applications. Nevertheless, as new techniques come forward, the technical and regulatory challenges may also vary across countries. Given that the existing comparative studies have not been covered as a whole, we evaluated the V2X communication technology to classify the adaptability of DSRC, cellular networks, and hybrid methods. The study also includes available V2X technology platforms and products. In addition, the challenges of deployments are also depicted in this study. The outcome indicates that many automotive industries and telecommunication providers recognize V2X substantial effect on ITS. The work is underway to decide which capabilities will be added since this is a long-term benefit for our future transportation.
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Yogarayan, Sumendra, Siti Fatimah Abdul Razak, Afizan Azman, and Mohd Fikri Azli Abdullah. "VEHICLE TO EVERYTHING (V2X) COMMUNICATIONS TECHNOLOGY FOR SMART MOBILITY IN MALAYSIA: A COMPREHENSIVE REVIEW." Journal of Southwest Jiaotong University 56, no. 4 (2021): 534–63. http://dx.doi.org/10.35741/issn.0258-2724.56.4.47.

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Vehicle to Everything (V2X) communication technology assesses the potential as the new phenomenon for Intelligent Transportation Systems (ITS) in the context of vehicle-to-vehicle (V2V), vehicle-to-infrastructure (V2I), vehicle-to-pedestrian (V2P), and vehicle-to-network (V2N). Dedicated Short-Range Communications (DSRC) is the conventional vehicular communication standard for ITS. The cellular network based on 4G/5G for ITS deployment has become a competitor to DSRC. Recent advancements in technologies have motivated the research community to develop a hybrid DSRC, and cellular networks approach to support reliable ITS applications. Nevertheless, as new techniques come forward, the technical and regulatory challenges may also vary across countries. Given that the existing comparative studies have not been covered as a whole, we evaluated the V2X communication technology to classify the adaptability of DSRC, cellular networks, and hybrid methods. The study also includes available V2X technology platforms and products. In addition, the challenges of deployments are also depicted in this study. The outcome indicates that many automotive industries and telecommunication providers recognize V2X substantial effect on ITS. The work is underway to decide which capabilities will be added since this is a long-term benefit for our future transportation.
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Han, Donghee, and Jaewoo So. "Energy-Efficient Resource Allocation Based on Deep Q-Network in V2V Communications." Sensors 23, no. 3 (2023): 1295. http://dx.doi.org/10.3390/s23031295.

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Recently, with the development of autonomous driving technology, vehicle-to-everything (V2X) communication technology that provides a wireless connection between vehicles, pedestrians, and roadside base stations has gained significant attention. Vehicle-to-vehicle (V2V) communication should provide low-latency and highly reliable services through direct communication between vehicles, improving safety. In particular, as the number of vehicles increases, efficient radio resource management becomes more important. In this paper, we propose a deep reinforcement learning (DRL)-based decentralized resource allocation scheme in the V2X communication network in which the radio resources are shared between the V2V and vehicle-to-infrastructure (V2I) networks. Here, a deep Q-network (DQN) is utilized to find the resource blocks and transmit power of vehicles in the V2V network to maximize the sum rate of the V2I and V2V links while reducing the power consumption and latency of V2V links. The DQN also uses the channel state information, the signal-to-interference-plus-noise ratio (SINR) of V2I and V2V links, and the latency constraints of vehicles to find the optimal resource allocation scheme. The proposed DQN-based resource allocation scheme ensures energy-efficient transmissions that satisfy the latency constraints for V2V links while reducing the interference of the V2V network to the V2I network. We evaluate the performance of the proposed scheme in terms of the sum rate of the V2X network, the average power consumption of V2V links, and the average outage probability of V2V links using a case study in Manhattan with nine blocks of 3GPP TR 36.885. The simulation results show that the proposed scheme greatly reduces the transmit power of V2V links when compared to the conventional reinforcement learning-based resource allocation scheme without sacrificing the sum rate of the V2X network or the outage probability of V2V links.
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Abdullah, Mohd Fikri Azli, Sumendra Yogarayan, Siti Fatimah Abdul Razak, Afizan Azman, Anang Hudaya Muhamad Amin, and Mazrah Salleh. "Edge computing for Vehicle to Everything: a short review." F1000Research 10 (July 7, 2022): 1104. http://dx.doi.org/10.12688/f1000research.73269.2.

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Vehicle to Everything (V2X) communications and services have sparked considerable interest as a potential component of future Intelligent Transportation Systems. V2X serves to organise communication and interaction between vehicle to vehicle (V2V), vehicle to infrastructure (V2I), vehicle to pedestrians (V2P), and vehicle to networks (V2N). However, having multiple communication channels can generate a vast amount of data for processing and distribution. In addition, V2X services may be subject to performance requirements relating to dynamic handover and low latency communication channels. Good throughput, lower delay, and reliable packet delivery are the core requirements for V2X services. Edge Computing (EC) may be a feasible option to address the challenge of dynamic handover and low latency to allow V2X information to be transmitted across vehicles. Currently, existing comparative studies do not cover the applicability of EC for V2X. This review explores EC approaches to determine the relevance for V2X communication and services. EC allows devices to carry out part or all of the data processing at the point where data is collected. The emphasis of this review is on several methods identified in the literature for implementing effective EC. We describe each method individually and compare them according to their applicability. The findings of this work indicate that most methods can simulate the EC positioning under predefined scenarios. These include the use of Mobile Edge Computing, Cloudlet, and Fog Computing. However, since most studies are carried out using simulation tools, there is a potential limitation in that crucial data in the search for EC positioning may be overlooked and ignored for bandwidth reduction. The EC approaches considered in this work are limited to the literature on the successful implementation of V2X communication and services. The outcome of this work could considerably help other researchers better characterise EC applicability for V2X communications and services.
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Abdullah, Mohd Fikri Azli, Sumendra Yogarayan, Siti Fatimah Abdul Razak, Afizan Azman, Anang Hudaya Muhamad Amin, and Mazrah Salleh. "Edge computing for Vehicle to Everything: a short review." F1000Research 10 (November 1, 2021): 1104. http://dx.doi.org/10.12688/f1000research.73269.1.

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Vehicle to Everything (V2X) communications and services have sparked considerable interest as a potential component of future Intelligent Transportation Systems. V2X serves to organise communication and interaction between vehicle to vehicle (V2V), vehicle to infrastructure (V2I), vehicle to pedestrians (V2P), and vehicle to networks (V2N). However, having multiple communication channels can generate a vast amount of data for processing and distribution. In addition, V2X services may be subject to performance requirements relating to dynamic handover and low latency communication channels. Good throughput, lower delay, and reliable packet delivery are the core requirements for V2X services. Edge Computing (EC) may be a feasible option to address the challenge of dynamic handover and low latency to allow V2X information to be transmitted across vehicles. Currently, existing comparative studies do not cover the applicability of EC for V2X. This review explores EC approaches to determine the relevance for V2X communication and services. EC allows devices to carry out part or all of the data processing at the point where data is collected. The emphasis of this review is on several methods identified in the literature for implementing effective EC. We describe each method individually and compare them according to their applicability. The findings of this work indicate that most methods can simulate the EC positioning under predefined scenarios. These include the use of Mobile Edge Computing, Cloudlet, and Fog Computing. However, since most studies are carried out using simulation tools, there is a potential limitation in that crucial data in the search for EC positioning may be overlooked and ignored for bandwidth reduction. The EC approaches considered in this work are limited to the literature on the successful implementation of V2X communication and services. The outcome of this work could considerably help other researchers better characterise EC applicability for V2X communications and services.
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Han, Biao, Sirui Peng, Celimuge Wu, Xiaoyan Wang, and Baosheng Wang. "LoRa-Based Physical Layer Key Generation for Secure V2V/V2I Communications." Sensors 20, no. 3 (2020): 682. http://dx.doi.org/10.3390/s20030682.

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In recent years, Vehicle-to-Vehicle (V2V) and Vehicle-to-Infrastructure (V2I) communication brings more and more attention from industry (e.g., Google and Uber) and government (e.g., United States Department of Transportation). These Vehicle-to-Everything (V2X) technologies are widely adopted in future autonomous vehicles. However, security issues have not been fully addressed in V2V and V2I systems, especially in key distribution and key management. The physical layer key generation, which exploits wireless channel reciprocity and randomness to generate secure keys, provides a feasible solution for secure V2V/V2I communication. It is lightweight, flexible, and dynamic. In this paper, the physical layer key generation is brought to the V2I and V2V scenarios. A LoRa-based physical key generation scheme is designed for securing V2V/V2I communications. The communication is based on Long Range (LoRa) protocol, which is able to measure Received Signal Strength Indicator (RSSI) in long-distance as consensus information to generate secure keys. The multi-bit quantization algorithm, with an improved Cascade key agreement protocol, generates secure binary bit keys. The proposed schemes improved the key generation rate, as well as to avoid information leakage during transmission. The proposed physical layer key generation scheme was implemented in a V2V/V2I network system prototype. The extensive experiments in V2I and V2V environments evaluate the efficiency of the proposed key generation scheme. The experiments in real outdoor environments have been conducted. Its key generation rate could exceed 10 bit/s on our V2V/V2I network system prototype and achieve 20 bit/s in some of our experiments. For binary key sequences, all of them pass the suite of statistical tests from National Institute of Standards and Technology (NIST).
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Dissertations / Theses on the topic "Vehicle-to-vehicle (V2V) communication"

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Ding, Ranran. "A Clustering-based Multi-channel Vehicle-to-Vehicle (V2V) Communication System." University of Cincinnati / OhioLINK, 2010. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1267545099.

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Hajimirsadeghi, Seyedsalar. "Vehicle to Vehicle Communication in Level 4 Autonomy." Scholarship @ Claremont, 2017. http://scholarship.claremont.edu/cmc_theses/1622.

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With the number of deaths, commute time, and injuries constantly rising due to human driving errors, it’s time for a new transportation system, where humans are no longer involved in driving decisions and vehicles are the only machine that decide the actions of a vehicle. To accomplish a fully autonomous world, it’s important for vehicles to be able to communicate instantly and report their movements in order to reduce accidents. This paper discusses four approaches to vehicle to vehicle communication, as well as the underlying standards and technology that enable vehicles to accomplish communicating.
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Kim, Taehyoung. "Assessment of Vehicle-to-Vehicle Communication based Applications in an Urban Network." Diss., Virginia Tech, 2015. http://hdl.handle.net/10919/53514.

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Connected Vehicle research has emerged as one of the highest priorities in the transportation systems because connected vehicle technology has the potential to improve safety, mobility, and environment for the current transportation systems. Various connected vehicle based applications have been identified and evaluated through various measurements to assess the performance of connected vehicle applications. However, most of these previous studies have used hypothetical study areas with simple networks for connected vehicle environment. This study represents connected vehicle environment in TRANSIMS to assess the performance of V2V communication applications in the realistic urban network. The communication duration rate and spatial-temporal dispersion of equipped vehicles are investigated to evaluate the capability of V2V communication based on the market penetration rate of equipped vehicles and wireless communication coverage in the whole study area. The area coverage level is used to assess the spatial-temporal dispersion of equipped vehicles for two study areas. The distance of incident information propagation and speed estimation error are used to measure the performance of event-driven and periodic applications based on different market penetration rates of equipped vehicles and wireless communication coverage in both morning peak and non-peak times. The wireless communication coverage is the major factor for event-driven application and the market penetration rate of equipped vehicles has more impact on the performance of periodic application. The required minimum levels of deployment for each application are determined for each scenario. These study findings will be useful for making decisions about investments on deployment of connected vehicle applications to improve the current transportation systems. Notably, event-driven applications can be reliably deployed in the initial stage of deployment despite the low level of market penetration of equipped vehicles.<br>Ph. D.
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Kim, Hoe Kyoung. "Development and evaluation of advanced traveler information system (ATIS) using vehicle-to-vehicle (V2V) communication system." Diss., Georgia Institute of Technology, 2010. http://hdl.handle.net/1853/33828.

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This research develops and evaluates an Advanced Traveler Information System (ATIS) model using a Vehicle-to-Vehicle (V2V) communication system (referred to as the GATIS-V2V model) with the off-the-shelf microscopic simulation model, VISSIM. The GATIS-V2V model is tested on notional small traffic networks (non-signalized and signalized) and a 6X6 typical urban grid network (signalized traffic network). The GATIS-V2V model consists of three key modules: vehicle communication, on-board travel time database management, and a Dynamic Route Guidance System (DRGS). In addition, the system performance has been enhanced by applying three complementary functions: Autonomous Automatic Incident Detection (AAID), a minimum sample size algorithm, and a simple driver behavior model. To select appropriate parameter ranges for the complementary functions a sensitivity analysis has been conducted. The GATIS-V2V performance has been investigated relative to three underlying system parameters: traffic flow, communication radio range, and penetration ratio of participating vehicles. Lastly, the enhanced GATIS-V2V model is compared with the centralized traffic information system. This research found that the enhanced GATIS-V2V model outperforms the basic model in terms of travel time savings and produces more consistent and robust system output under non-recurrent traffic states (i.e., traffic incident) in the simple traffic network. This research also identified that the traffic incident detection time and driver's route choice rule are the most crucial factors influencing the system performance. As expected, as traffic flow and penetration ratio increase, the system becomes more efficient, with non-participating vehicles also benefiting from the re-routing of participating vehicles. The communication radio ranges considered were found not to significantly influence system operations in the studied traffic network. Finally, it is found that the decentralized GATIS-V2V model has similar performance to the centralized model even under low flow, short radio range, and low penetration ratio cases. This implies that a dynamic infrastructure-based traffic information system could replace a fixed infrastructure-based traffic information system, allowing for considerable savings in fixed costs and ready expansion of the system off of the main network corridors.
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Ashraf, M. I. (Muhammad Ikram). "Radio resource management in device-to-device and vehicle-to-vehicle communication in 5G networks and beyond." Doctoral thesis, Oulun yliopisto, 2019. http://urn.fi/urn:isbn:9789526224626.

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Abstract Future cellular networks need to support the ever-increasing demand of bandwidth-intensive applications and interconnection of people, devices, and vehicles. Small cell network (SCN)-based communication together with proximity- and social-aware connectivity is conceived as a vital component of these networks to enhancing spectral efficiency, system capacity, and quality-of-experience (QoE). To cope with diverse application needs for the heterogeneous ecosystem, radio resource management (RRM) is one of the key research areas for the fifth-generation (5G) network. The key goals of this thesis are to develop novel, self-organizing, and low-complexity resource management algorithms for emerging device-to-device (D2D) and vehicle-to-vehicle (V2V) wireless systems while explicitly modeling and factoring network contextual information to satisfy the increasingly stringent requirements. Towards achieving this goal, this dissertation makes a number of key contributions. First, the thesis focuses on interference management techniques for D2D-enabled macro network and D2D-enabled SCNs in the downlink, while leveraging users’ social-ties, dynamic clustering, and user association mechanisms for network capacity maximization. A flexible social-aware user association technique is proposed to maximize network capacity. The second contribution focuses on ultra-reliable low-latency communication (URLLC) in vehicular networks in which interference management and resource allocation techniques are investigated, taking into account traffic and network dynamics. A joint power control and resource allocation mechanism is proposed to minimize the total transmission power while satisfying URLLC constraints. To overcome these challenges, novel algorithms are developed by combining several methodologies from graph theory, matching theory and Lyapunov optimization. Extensive simulations validate the performance of the proposed approaches, outperforming state-of-the-art solutions. Notably, the results yield significant performance gains in terms of capacity, delay reductions, and improved reliability as compared with conventional approaches<br>Tiivistelmä Tulevaisuuden solukkoverkkojen pitää pystyä tukemaan yhä suurempaa kaistanleveyttä vaativia sovelluksia sekä yhteyksiä ihmisten, laitteiden ja ajoneuvojen välillä. Piensoluverkkoihin (SCN) pohjautuvaa tietoliikennettä yhdistettynä paikka- ja sosiaalisen tietoisuuden huomioiviin verkkoratkaisuihin pidetään yhtenä elintärkeänä osana tulevaisuuden solukkoverkkoja, joilla pyritään tehostamaan spektrinkäytön tehokkuutta, järjestelmän kapasiteettia sekä kokemuksen laatua (QoE). Radioresurssien hallinta (RRM) on eräs keskeisistä viidennen sukupolven (5G) verkkoihin liittyvistä tutkimusalueista, joilla pyritään hallitsemaan heterogeenisen ekosysteemin vaihtelevia sovellustarpeita. Tämän väitöstyön keskeisinä tavoitteina on kehittää uudenlaisia itseorganisoituvia ja vähäisen kompleksisuuden resurssienhallinta-algoritmeja laitteesta-laitteeseen (D2D) ja ajoneuvosta-ajoneuvoon (V2V) toimiville uusille langattomille järjestelmille, sekä samalla mallintaa ja tuottaa verkon kontekstikohtaista tietoa vastaamaan koko ajan tiukentuviin vaatimuksiin. Tämä väitöskirja edistää näiden tavoitteiden saavuttamista usealla keskeisellä tuloksella. Aluksi väitöstyössä keskitytään häiriönhallinnan tekniikoihin D2D:tä tukevissa makroverkoissa ja laskevan siirtotien piensoluverkoissa. Käyttäjän sosiaalisia yhteyksiä, dynaamisia ryhmiä sekä osallistamismekanismeja hyödynnetään verkon kapasiteetin maksimointiin. Verkon kapasiteettia voidaan kasvattaa käyttämällä joustavaa sosiaaliseen tietoisuuteen perustuvaa osallistamista. Toinen merkittävä tulos keskittyy huippuluotettavaan lyhyen viiveen kommunikaatioon (URLLC) ajoneuvojen verkoissa, joissa tehtävää resurssien allokointia ja häiriönhallintaa tutkitaan liikenteen ja verkon dynamiikka huomioiden. Yhteistä tehonsäädön ja resurssien allokoinnin mekanismia ehdotetaan kokonaislähetystehon minimoimiseksi samalla, kun URLLC rajoitteita noudatetaan. Jotta esitettyihin haasteisiin voidaan vastata, väitöstyössä on kehitetty uudenlaisia algoritmeja yhdistämällä graafi- ja sovitusteorioiden sekä Lyapunovin optimoinnin menetelmiä. Laajat tietokonesimuloinnit vahvistavat ehdotettujen lähestymistapojen suorituskyvyn, joka on parempi kuin uusimmilla nykyisillä ratkaisuilla. Tulokset tuovat merkittäviä suorituskyvyn parannuksia erityisesti kapasiteetin lisäämisen, viiveiden vähentämisen ja parantuneen luotettavuuden suhteen verrattuna perinteisiin lähestymistapoihin
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Walker, Jonathan Bearnarr. "An Empirical Method of Ascertaining the Null Points from a Dedicated Short-Range Communication (DSRC) Roadside Unit (RSU) at a Highway On/Off-Ramp." Diss., Virginia Tech, 2018. http://hdl.handle.net/10919/85151.

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The deployment of dedicated short-range communications (DSRC) roadside units (RSUs) allows a connected or automated vehicle to acquire information from the surrounding environment using vehicle-to-infrastructure (V2I) communication. However, wireless communication using DSRC has shown to exhibit null points, at repeatable distances. The null points are significant and there was unexpected loss in the wireless signal strength along the pathway of the V2I communication. If the wireless connection is poor or non-existent, the V2I safety application will not obtain sufficient data to perform the operation services. In other words, a poor wireless connection between a vehicle and infrastructure (e.g., RSU) could hamper the performance of a safety application. For example, a designer of a V2I safety application may require a minimum rate of data (or packet count) over 1,000 meters to effectively implement a Reduced Speed/Work Zone Warning (RSZW) application. The RSZW safety application is aimed to alert or warn drivers, in a Cooperative Adaptive Cruise Control (CACC) platoon, who are approaching a work zone. Therefore, the packet counts and/or signal strength threshold criterion must be determined by the developer of the V2I safety application. Thus, we selected an arbitrary criterion to develop an empirical method of ascertaining the null points from a DSRC RSU. The research motivation focuses on developing an empirical method of calculating the null points of a DSRC RSU for V2I communication at a highway on/off-ramp. The intent is to improve safety, mobility, and environmental applications since a map of the null points can be plotted against the distance between the DSRC RSU and a vehicle's onboard unit (OBU). The main research question asks: 'What is a more robust empirical method, compared to the horizontal and vertical laws of reflection formula, in determining the null points from a DSRC RSU on a highway on/off ramp?' The research objectives are as follows: 1. Explain where and why null points occur from a DSRC RSU (Chapter 2) 2. Apply the existing horizontal and vertical polarization model and discuss the limitations of the model in a real-world scenario for a DSRC RSU on a highway on/off ramp (Chapter 3 and Appendix A) 3. Introduce an extended horizontal and vertical polarization null point model using empirical data (Chapter 4) 4. Discuss the conclusion, limitations of work, and future research (Chapter 5). The simplest manner to understand where and why null points occur is depicted as two sinusoidal waves: direct and reflective waves (i.e., also known as a two-ray model). The null points for a DSRC RSU occurs because the direct and reflective waves produce a destructive interference (i.e., decrease in signal strength) when they collide. Moreover, the null points can be located using Pythagorean theorem for the direct and reflective waves. Two existing models were leveraged to analyze null points: 1) signal strength loss (i.e., a free space path loss model, or FSPL, in Appendix A) and 2) the existing horizontal and vertical polarization null points from a DSRC RSU. Using empirical data from two different field tests, the existing horizontal and vertical polarization null point model was shown to contain limitations in short distances from the DSRC RSU. Moreover, the existing horizontal and vertical polarization model for null points was extremely challenging to replicate with over 15 DSRC RSU data sets. After calculating the null point for several DSRC RSU heights, the paper noticed a limitation of the existing horizontal and vertical polarization null point model with over 15 DSRC RSU data sets (i.e., the model does not account for null points along the full length of the FSPL model). An extended horizontal and vertical polarization model is proposed that calculates the null point from a DSRC RSU. There are 18 model comparisons of the packet counts and signal strengths at various thresholds as perspective extended horizontal and vertical polarization models. This paper compares the predictive ability of 18 models and measures the fit. Finally, a predication graph is depicted with the neural network's probability profile for packet counts =1 when greater than or equal to 377. Likewise, a python script is provided of the extended horizontal and vertical polarization model in Appendix C. Consequently, the neural network model was applied to 10 different DSRC RSU data sets at 10 unique locations around a circular test track with packet counts ranging from 0 to 11. Neural network models were generated for 10 DSRC RSUs using three thresholds with an objective to compare the predictive ability of each model and measure the fit. Based on 30 models at 10 unique locations, the highest misclassification was 0.1248, while the lowest misclassification was 0.000. There were six RSUs mounted at 3.048 (or 10 feet) from the ground with a misclassification rate that ranged from 0.1248 to 0.0553. Out of 18 models, seven had a misclassification rate greater than 0.110, while the remaining misclassification rates were less than 0.0993. There were four RSUs mounted at 6.096 meters (or 20 feet) from the ground with a misclassification rate that ranged from 0.919 to 0.000. Out of 12 models, four had a misclassification rate greater than 0.0590, while the remaining misclassification rates were less than 0.0412. Finally, there are two major limitations in the research: 1) the most effective key parameter is packet counts, which often require expensive data acquisition equipment to obtain the information and 2) the categorical type (i.e., decision tree, logistic regression, and neural network) will vary based on the packet counts or signal strength threshold that is dictated by the threshold criterion. There are at least two future research areas that correspond to this body of work: 1) there is a need to leverage the extended horizontal and vertical polarization null point model on multiple DSRC RSUs along a highway on/off ramp, and 2) there is a need to apply and validate different electric and magnetic (or propagation) models.<br>Ph. D.
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Sonklin, Kachane. "Studies of communication and positioning performance of connected vehicles for safety applications." Thesis, Queensland University of Technology, 2020. https://eprints.qut.edu.au/207089/1/Kachane_Sonklin_Thesis.pdf.

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Connected vehicles for safety applications play a significant role on reduction of the risks of road accidents. However, the performance of communication and positioning approaches is a major concern. This thesis establishes a connectivity framework based on publish-subscribe architecture for high-timeliness vehicle-to-vehicle data exchanges and determines the performance requirements for precise vehicle positioning for various safety use cases. Extensive experimental results demonstrated the performance benefits of the communication and positioning solutions for vehicle safety applications.
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Fasciani, Davide. "Real time processing in Simulink for Hardware in the Loop simulations of V2X." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2022.

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Vehicle-to-everything (V2X) communications allow vehicles to exchange messages useful for several scopes, including accident reduction and safety applications. This feature, in cooperation with advanced driver assistance systems (ADAS), needs to be tested and validated to guarantee optimal functionality. This thesis focuses on the development of a Simulink V2X simulation communication module, as an extension to the traffic simulator adopted as part of a validation platform, with the aim of interfacing it with hardware devices. The traffic simulator generates the scenario and controls, through a protocol defined in this activity, an external simulator, which in turn activates the exchange of V2X messages. The system is then tested by applying, as an example, a forward collision warning (FCW) application. More specifically firstly, simulations have been developed in a software in the loop (SiL) architecture; finally, a hardware in the loop (HiL) setup has been implemented, involving real on-board units (OBUs), with a tablet simulating human-to-machine interface (HMI).
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Choi, Junsung. "Feasibility Study and Performance Evaluation of Vehicle-to-Everything (V2X) Communications Applications." Diss., Virginia Tech, 2018. http://hdl.handle.net/10919/97248.

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Vehicular communications are a major subject of research and policy activity in industry, government, and academia. Dedicated Short-Range Communications (DSRC) is currently the main protocol used for vehicular communications, and it operates in the 5.9 GHz band. In addition to DSRC radios, other potential uses of this band include Wi-Fi, LTE-V, and communication among unlicensed devices. This dissertation presents an architecture and a feasibility analysis including field measurements and analysis for vehicle-to-train (V2T) communications, a safety-critical vehicular communication application. The dissertation also presents a survey of research relevant to each of several possible combinations of radio-spectrum and vehicular-safety regulations that would affect use of the 5.9 GHz band, identifies the most challenging of the possible resulting technical challenges, and presents initial measurements to assess feasibility of sharing the band by DSRC radios and other devices that operate on adjacent frequencies using different wireless communication standards. Although wireless technology is available for safety-critical communications, few applications have been developed to improve railroad crossing safety. A V2T communication system for a safety warning application with DSRC radios can address the need to prevent collisions between trains and vehicles. The dissertation presents a V2T early warning application architecture with a safety notification time and distance. We conducted channel measurements at a 5.86�"5.91-GHz frequency and 5.9-GHz DSRC performance measurements at railroad crossings in open spaces, shadowed environments, and rural and suburban environments related to the presented V2T architecture. Our measurements and analyses show that the DSRC protocol can be adapted to serve the purpose of a V2T safety warning system. The 5.9 GHz band has been sought after by several stakeholders, including traditional mobile operators, DSRC proponents, unlicensed Wi-Fi proponents and Cellular-Vehicle-to-Everything (C-V2X) proponents. The FCC and National Highway Traffic Safety Administration (NHTSA), the two major organizations that are responsible for regulations related to vehicular communications, have not finalized rules regarding this band. The relative merits of the above mentioned wireless communication standards and coexistence issues between these standards are complex. There has been considerable research devoted to understanding the performance of these standards, but in some instances there are gaps in needed research. We have analyzed regulation scenarios that FCC and NHTSA are likely to consider and have identified the technical challenges associated with these potential regulatory scenarios. The technical challenges are presented and for each a survey of relevant technical literature is presented. In our opinion for the most challenging technical requirements that could be mandated by new regulations are interoperability between DSRC and C-V2X and the ability to detect either adjacent channel or co-channel coexisting interference. We conducted initial measurements to evaluate the feasibility of adjacent channel coexistence between DSRC, Wi-Fi, and C-V2X, which is one of the possible regulatory scenarios. We set DSRC at Channel 172, Wi-Fi at Channel 169 for 20 MHz bandwidth and at Channel 167 for 40 MHz, and C-V2X at Channel 174 with almost 100% spectrum capacity. From the measurements, we observed almost no effects on DSRC performance due to adjacent channel interference. Based on our results, we concluded that adjacent channel coexistence between DSRC, C-V2X, and Wi-Fi is possible. DSRC systems can provide good communication range; however, the range is likely to be reduced in the presence of interference and / or Non-Line-of-Sight (NLoS) conditions. Such environmental factors are the major influence on DSRC performance. By knowing the relationship between DSRC and environmental factors, DSRC radios can be set up in a way that promotes good performance in an environment of interest. We chose propagation channel characteristics to generate DSRC performance modelling by using estimation methods. The conducted DSRC performance measurements and propagation channel characteristics are independent; however, they share the same distance parameters. Results of linear regression to analyze the relationship between DSRC performance and propagation channel characteristics indicate that additional V2T measurements are required to provide data for more precise modeling.<br>PHD
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Agrawal, Manas. "Leveraging Vehicle-to-Infrastructure Communications for Adaptive Traffic Signaling and Better Energy Utilization." The Ohio State University, 2013. http://rave.ohiolink.edu/etdc/view?acc_num=osu1372785316.

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Book chapters on the topic "Vehicle-to-vehicle (V2V) communication"

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Verma, Karan, Ashok Kumar, Leandro Melo de Sales, Sudesh Kumar, Ajay K. Sharma, and Nehul Singh. "Enabling Real-Time Vehicle-to-Vehicle (V2V) Communication for Intelligent Transportation System (ITS)." In Lecture Notes in Electrical Engineering. Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-19-1645-8_22.

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Othman, Norzalina, Lutfil Hadi Ideris, and Zainal Abidin Che Hassan. "Small Scale Prototype Development of Vehicle to Vehicle (V2V) Communication Using the Light Fidelity (LiFi) Technology." In Advanced Structured Materials. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-67750-3_25.

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Andrews, Scott. "Vehicle-to-Vehicle (V2V) and Vehicle-to-Infrastructure (V2I) Communications and Cooperative Driving." In Handbook of Intelligent Vehicles. Springer London, 2012. http://dx.doi.org/10.1007/978-0-85729-085-4_46.

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Gratzer, Alexander L., Alexander Schirrer, Sebastian Thormann, and Stefan Jakubek. "Platoon Control Concepts." In Energy-Efficient and Semi-automated Truck Platooning. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-88682-0_8.

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AbstractCooperative platoon control strategies utilise provided information from vehicle-to-everything (V2X) communication to reduce energy consumption and improve traffic flow and safety. In this chapter, a distributed control concept for cooperative platooning is developed that combines trajectory optimisation and local model-predictive control of each vehicle. The presented control architecture ensures collision safety by design, platoon efficiency and situational awareness with the option of exploiting V2X communication. The resulting platoon control performance is tested and validated in a realistic setting by utilising a co-simulation-based validation framework with detailed vehicle dynamics.
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Gratzer, Alexander L., Alexander Schirrer, Sebastian Thormann, and Stefan Jakubek. "Platoon Control Concepts." In Energy-Efficient and Semi-automated Truck Platooning. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-88682-0_8.

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AbstractCooperative platoon control strategies utilise provided information from vehicle-to-everything (V2X) communication to reduce energy consumption and improve traffic flow and safety. In this chapter, a distributed control concept for cooperative platooning is developed that combines trajectory optimisation and local model-predictive control of each vehicle. The presented control architecture ensures collision safety by design, platoon efficiency and situational awareness with the option of exploiting V2X communication. The resulting platoon control performance is tested and validated in a realistic setting by utilising a co-simulation-based validation framework with detailed vehicle dynamics.
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Janani, P., Siddhant Verma, S. Natarajan, and Aditya Kumar Sinha. "Automotive Vehicle-to-Everything (V2X) Communication Using IoT." In Information and Communication Technology for Sustainable Development. Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-13-7166-0_19.

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Janani, P., Siddhant Verma, S. Natrajan, and Aditya Kumar Sinha. "Automotive Vehicle to Everything (V2X) Communication Using IOT." In International Conference on Intelligent Data Communication Technologies and Internet of Things (ICICI) 2018. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-03146-6_31.

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Chandra, Shailesh, Mamta Kumari, and R. Thirumaleswara Naik. "Feeder Transit Service Efficiencies with Vehicle-to-Passenger (V2P) Communication." In Advances in Intelligent Systems and Computing. Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-2414-1_43.

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Ouaissa, Mariya, Mariyam Ouaissa, Meriem Houmer, Sara El Hamdani, and Zakaria Boulouard. "A Secure Vehicle to Everything (V2X) Communication Model for Intelligent Transportation System." In EAI/Springer Innovations in Communication and Computing. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-77185-0_6.

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Avcil, Muhammed Nur, and Mujdat Soyturk. "Data Offloading Approaches for Vehicle-to-Everything (V2X) Communications in 5G and Beyond." In Connected and Autonomous Vehicles in Smart Cities. CRC Press, 2020. http://dx.doi.org/10.1201/9780429329401-9.

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Conference papers on the topic "Vehicle-to-vehicle (V2V) communication"

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Hwang, Hyun-Yong, Sung-Min Oh, and Jaesheung Shin. "CAN gateway for fast vehicle to vehicle (V2V) communication." In 2015 International Conference on Information and Communication Technology Convergence (ICTC). IEEE, 2015. http://dx.doi.org/10.1109/ictc.2015.7354601.

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Sathya Narayanan, P., and C. Sheeba Joice. "Vehicle-to-Vehicle (V2V) Communication using Routing Protocols: A Review." In 2019 International Conference on Smart Structures and Systems (ICSSS). IEEE, 2019. http://dx.doi.org/10.1109/icsss.2019.8882828.

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Limbasiya, Trupil, and Debasis Das. "Secure message transmission algorithm for Vehicle to Vehicle (V2V) communication." In TENCON 2016 - 2016 IEEE Region 10 Conference. IEEE, 2016. http://dx.doi.org/10.1109/tencon.2016.7848485.

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Marcillo, Pablo, Ángel Leonardo Valdivieso Caraguay, and Myriam Hernandez-Alvarez. "Security in Vehicle-to-Infrastructure Communications." In 13th International Conference on Applied Human Factors and Ergonomics (AHFE 2022). AHFE International, 2022. http://dx.doi.org/10.54941/ahfe1002210.

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By 2020, the number of connected vehicles will reach 250 million units. Thus, one of five vehicles worldwide will count on any wireless connection. Functional areas such as telecommunications, infotainment, automatic driving, or mobility services will have to face the implications caused by that growth. As long as vehicles require exchanging information with other vehicles or accessing external networks through a communication infrastructure, these vehicles must be part of a network. A VANET is a type of mobile network formed by base stations known as Road Side Units (RSU) and vehicles equipped with communication units known as Onboard Units (OBU). The two modes of communication in a VANET are Vehicle to Vehicle (V2V) and Vehicle to Infrastructure (V2I). Some authors consider that V2I communication has more advantages than V2V communication because V2I communication provides services such as driving guidance or early warning for drivers. This consideration has meant that researchers show more interest in this mode of communication. Likewise, others affirm that the problem of V2I communication is its security. This review focuses on knowing the most relevant and current approaches on security in V2I communication. Among the solutions, we have authentication schemes based on Blockchain technology, Elliptic Curve cryptography, key insulation strategy, and certificateless aggregate signature technique. Also, we found security arquitectures and identification schemes based on SDN, NFV, and Fog / Edge / Cloud computing. The proposals focus on resolving issues such as the privacy-preserving, high computational work, regular updating and exposure of secret keys, large number of revoked pseudonyms lists, lack of scalability in networks, and high dependence on certification authorities. In addition, these proposals provide countermeasures or strategies against replay, message forgery, impersonation, eavesdropping, DDoS, fake information, modification, Sybil, man-in-the-middle, and spoofing attacks. Finally, we determined that the attacks in V2I communications mostly compromise security requirements such as confidentiality, integrity, authentication, and availability. Preserving privacy by reducing computational costs by integrating emerging technologies is the direction toward security in vehicular network points.
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Ding, Ranran, and Qing-An Zeng. "A clustering-based multi-channel Vehicle-to-Vehicle (V2V) communication system." In 2009 First International Conference on Ubiquitous and Future Networks (ICUFN). IEEE, 2009. http://dx.doi.org/10.1109/icufn.2009.5174290.

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Ilhan, Haci, Ibrahim Altunbas, and Murat Uysal. "Performance analysis and optimization of relay-assisted vehicle-to-vehicle (V2V) cooperative communication." In 2008 IEEE 16th Signal Processing, Communication and Applications Conference (SIU). IEEE, 2008. http://dx.doi.org/10.1109/siu.2008.4632593.

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Yousef, Mohamed, Ahmed Hosny, Wessam Gamil, et al. "Dual-Mode Forward Collision Avoidance Algorithm Based on Vehicle-to-Vehicle (V2V) Communication." In 2018 IEEE 61st International Midwest Symposium on Circuits and Systems (MWSCAS). IEEE, 2018. http://dx.doi.org/10.1109/mwscas.2018.8623896.

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Hadiwardoyo, Seilendria A., Subhadeep Patra, Carlos T. Calafate, Juan-Carlos Cano, and Pietro Manzoni. "An Android ITS Driving Safety Application Based on Vehicle-to-Vehicle (V2V) Communications." In 2017 26th International Conference on Computer Communication and Networks (ICCCN). IEEE, 2017. http://dx.doi.org/10.1109/icccn.2017.8038486.

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Viittala, Harri, Simone Soderi, Jani Saloranta, Matti Hamalainen, and Jari Iinatti. "An Experimental Evaluation of WiFi-Based Vehicle-to-Vehicle (V2V) Communication in a Tunnel." In 2013 IEEE 77th Vehicular Technology Conference (VTC Spring). IEEE, 2013. http://dx.doi.org/10.1109/vtcspring.2013.6691878.

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Kumar, Paras, and Kunwar Babar Ali. "Intelligent Traffic System using Vehicle to Vehicle (V2V) & Vehicle to Infrastructure (V2I) communication based on Wireless Access in Vehicular Environments (WAVE) Std." In 2022 10th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions) (ICRITO). IEEE, 2022. http://dx.doi.org/10.1109/icrito56286.2022.9964590.

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Reports on the topic "Vehicle-to-vehicle (V2V) communication"

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Kwiat, Paul, Eric Chitambar, Andrew Conrad, and Samantha Isaac. Autonomous Vehicle-Based Quantum Communication Network. Illinois Center for Transportation, 2022. http://dx.doi.org/10.36501/0197-9191/22-020.

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Quantum communication was demonstrated using autonomous vehicle-to-vehicle (V2V), as well as autonomous vehicle-to-infrastructure (V2I). Supporting critical subsystems including compact size, weight, and power (SWaP) quantum sources; optical systems; and pointing, acquisition, and tracking (PAT) subsystems were designed, developed, and tested. Novel quantum algorithms were created and analyzed, including quantum position verification (QPV) for mobile autonomous vehicles. The results of this research effort can be leveraged in support of future cross-platform, mobile quantum communication networks that provide improved security, more accurate autonomous sensors, and connected quantum computing nodes for next-generation, smart-infrastructure systems.
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