BEGIN:VCALENDAR VERSION:2.0 PRODID:-//wp-events-plugin.com//7.2.3.1//EN BEGIN:VEVENT UID:688@lincs.fr DTSTART;TZID=Europe/Paris:20220310T090000 DTEND;TZID=Europe/Paris:20220311T180000 DTSTAMP:20250416T140657Z URL:https://www.lincs.fr/events/international-workshop-on-v2x/ SUMMARY:LINCS-NEMO WORKSHOP on V2X DESCRIPTION:\nLINCS-NEMO workshop on vehicular networks\n\n\n\nProgram\n\nMARCH 2022\, THURSDAY 10TH AND FRIDAY 11TH \;(9AM – 6PM)\n\nTo make our vehicles smarter and our roads safer\, communications are of paramount importance: vehicles will communicate with other vehicles (V2V)\, with the infrastructure (V2I)\, and with everything (V2X). Enabling and exploiting V2X communication at scale is still facing a huge amount of challenges\, at all levels of the network protocol stack\, in terms of global network architecture\, up to the design of advanced next-generation applications.\n\nThis international workshop will bring together researchers from the industry and Academia working on a wide class of topics including models and performance of the physical communication channel at different bands\, vehicle positioning and sensing\, 5G networks for V2X\, overall network architecture\, services on top of V2X and their requirements\, edge computing for vehicular applications\, etc.\n\nOrganization Committee\n\n\n François Baccelli (Inria)\n Andrea Araldo (Télécom-SudParis)\n Anna Frisone (LINCS)\n\n\nTHE WORKSHOP WILL BE HELD IN A PRESENCE-REMOTE \;HYBRID \;FORM AT \;LINCS \;– 23 AVENUE D’ITALIE\, 75013 PARIS\n\nINTERACTIVE MAP FOR LUNCH OPTIONS CLOSE TO THE LINCS [CREDITS TO ALESSANDRO SPALLINA]\nhttps://www.google.com/maps/d/edit?mid=1L-wdmqbhM9Btn2DPITTox41e Tl2SmQJk&\;usp=sharing\nConfirmed speakers:\nOnur ALTINTAS \;– \;Toyota \;: “Cooperation in Automation”\n\n\nConnected\, automated\, shared and electric (CASE) continues to be the dominant keyword in the automotive industry. In this talk we will briefly look into the general computing and communications vision supporting CASE and summarize recent developments in connected vehicles area\, including emerging standards.\n\nCarla CHIASSERINI \;– \;PoliTo \;: “Crowd-sourcing learning: Leveraging Connected Cars in ML Tasks”\n\nOne of the fundamental components of many applications in the automotive domain is represented by a machine learning (ML) task. At the same time\, vehicles are becoming mobile\, powerful computers that can gather\, share\, and process data\; thus\, they can not only consume services\, but also contribute to enabling ML-based applications. This can be enacted through distributed learning approaches\, according to which the learning process is split among a number of computing nodes. Distributed learning\, however\, may lead to significant communication overhead\, or to learners converging to different models. In this talk\, we therefore introduce a new distributed learning scheme that\, with the assistance of the network edge\, aims at exploiting the vehicles’ data and computing capabilities\, while enabling an accurate learning process. Further\, the talk will discuss different approaches to distributed learning and edge computing that can effectively involve connected vehicles.\n\nChang-sik CHOI \;– \;Hongik University \;: “Stochastic Geometry for Modeling and Analysis of Vehicular Networks”\n\nIn this lecture\, I will talk about recent work on the modeling and analysis of vehicular networks based on stochastic geometry.  \;I will cover a few topics such as SIR of vehicle-to-all communications\, data harvesting based on vehicles\, and an analytical framework for blockage. This lecture aims to provide a high-level idea on mathematical frameworks such as the Cox point process\, random graphs\, and Boolean model\, to characterize vehicular network architectures and to identify new challenges therein.\n\nHarpreet DHILLON \;– \;VirginiaTech \;“Poisson Line Cox Process: Distributional Properties and Applications to Vehicular Networks”\n\nIn this talk\, we present a doubly-stochastic model for vehicular networks\, termed the Poisson Line Cox Process (PLCP)\, in which the layout of the roads is modeled as a Poisson line process (PLP) and the wireless nodes\, such as vehicles and roadside units\, are modeled as independent Poisson point processes (PPPs) on each road. We will first share a brief historical perspective of PLP tracing back to a question posed by Neils Bohr that inspired early work on line processes. We will then discuss the construction of PLCP and a few representative distributional properties to highlight its analytical tractability. The rest of the talk will focus on the applications of PLCP to vehicular networks. Our specific focus will be on the rate and coverage analysis of a comprehensive cellular vehicle-to-everything (C-V2X) setup consisting of vehicular nodes\, roadside units\, and macrocellular base stations. As a part of this analysis\, we will also discuss some results related to the load served by macrocellular base stations and roadside units that will rely on understanding the intersection of PLP with the typical cell of an independent Poisson Voronoi tessellation modeling the service regions of macrocellular base stations. We will conclude the talk with a comparison of this model with the one used in 3GPP simulation studies. Time permitting\, we will also discuss the problem of shortest path distance distribution in PLCP and its potential applications to vehicular networks.\n\nFalko DRESSLER \;– \;TU Berlin \;: “From Vehicular Networking to 5G and Mobile Edge Computing to 6G and Virtual Edge Computing”\n\nWe 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. Vehicular networking solutions have been investigated for more than a decade but recent standardization efforts just enable a broad use of this technology to build large scale Intelligent Transportation Systems (ITS). Modern 5G networks promise to provide all means for communication in this domain\, particularly when integrating Mobile Edge Computing (MEC). However\, it turns out that despite the many advantages\, it is unlikely that such services will be provided with sufficient coverage. As a novel concept\, vehicle micro clouds have been proposed that bridge the gap between fully distributed vehicular networks based on short range device to device communication and 5G-based infrastructure. Using selected application examples\, we assess the advantages of such systems. We conclude the talk by shedding light on future virtual edge computing concepts that will enable edge computing even considering minimal deployment and coverage of 5G MEC.\n\nThierry ERNST \;– \;YoGoKo \;: “Cooperative ITS standards and technologies for automated connected &\; cooperative mobility”\n\nIn this talk\, Dr. Thierry Ernst is going to highlight the technologies and standards developed for Cooperative Intelligent Transport Systems (C-ITS) services\, i.e. services developed to share data between vehicles\, other road users\, the roadside infrastructure\, the urban infrastructure\, and control and service centers in the cloud. This sharing of data is essential to improve road safety and traffic efficiency and to develop many other innovative value added services for mobility of people and goods\, including but not limited to connected cooperative and automated mobility (CCAM). This presentation will particularly highlight standards developed at ISO\, CEN and ETSI under deployment in Europe and other regions in the world. C-ITS services under deployment rely on the ITS station communication and data management architecture. This architecture combines localized communication technologies (without support of telecom infrastructure) together with networked communication technologies (with support of telecom infrastructure) and facilities to manage and share data between various service domains and stakeholders. \;\n\nNuria GONZÁLEZ PRELCIC \;– \;NC State \;: “Integrating sensing and communication in millimeter wave vehicular networks”\n\nWireless networks are incorporating millimeter wave spectrum and beyond. This\, together with MIMO \; technology using large antenna arrays\, provides the key ingredients to develop integrated communication and sensing systems that exploit the similarities between the required hardware\, \; the signal processing algorithms or the sensing and communication channels. This is especially relevant in vehicular networks\, given the wealth of sensors available in a vehicular environment and the impact on safety that sensing capabilities can provide. In this talk\, I provide an overview of machine learning and signal processing techniques that enable different types of integration between sensing and communication. First\, I describe alternative strategies that pursue a fruitful collaboration among collocated sensing and communication modules which may be using different hardware or radio resources. I discuss algorithms for sensor-aided millimeter wave communication that significantly reduce the overhead associated with link configuration and reconfiguration or enable early blockage detection and array reconfiguration. Then I review the opposite setting: sensing aided by communications and its applications\, where communication provides information for enhanced sensing. Leveraging communication for sensing gives a new perspective on joint communication\, tracking and localization at mmWave frequencies. Throughout the talk\, I make the case that time is right for communication and sensing to be considered together. I also explain why communication and sensing will likely to be the defining physical layer feature of 6G.\n\nMartin HAENGGI \;– \;Notre Dame \;: “Transdimensional Modeling and Reliability Analysis of Vehicular Networks on General Street Systems”\n\nDue to their rapidly changing topology\, vehicular networks are naturally modeled and analyzed using tools from stochastic geometry. If links are required to be highly reliable\, as in vehicular safety messaging\, it is essential to find the maximum link density or distance or transmit probability that can be accommodated under a reliability constraint. To answer these questions\, standard spatial averages are inadequate\; instead\, meta distributions (distributions of conditional distributions) need to be derived\, which is considerably harder. To do so while maintaining wide generality in the underlying street system we propose an approximate approach based on transdimensional models\, which are a union of one- and two-dimensional point processes. This leads to significant simplifications and allows for a unified treatment of models with finite and infinitely long streets and intersections of arbitrary order.\n\nRobert HEATH \;– \;NC State \;: “Beam training in V2X leveraging machine learning”\nMillimeter-wave (MmWave) vehicular communication enables massive sensor data sharing in vehicular systems\, leading to enhances in automation\, safety\, transportation efficiency and infotainment. Estimating and tracking beams in mmWave vehicular communication\, however\, is challenging due to the use of large antenna arrays and high mobility in the vehicular context. In this talk\, I introduce data-driven approaches for beam training that leverage position information or underlying channel statistics to reduce training overhead. Data driven machine learning is valuable for V2X given the underlying correlations that can be exploited as vehicles travel similar paths through the environment.\n \;\nVincenzo MANCUSO \;– \;IMDEA Networks \;: “Edge-assisted platooning control and optimization”\n\nGrouping vehicles into platoons promises to improve road capacity\, driver safety\, and fuel consumption. However\, when large platoons have to allow for cross traffic maneuvers\, e.g.\, because of highway junctions\, the ability to control single large platoons is not sufficient\, and chaining smaller platoons becomes necessary. To this aim we study how to harmonically coordinate the maneuvers of multiple platoons and define a multi-platoon control architectures\, analyzing costs and benefits of multi-platooning and investigating on the feasibility of edge-controlled multi-platoons. We also consider distributed machine learning tools to handle the platoon control as a virtual network function residing at the edge of a cellular network. Using simulation\, we show that multi-platoons can be effectively controlled as long as the latency between individual platoon managers and the multi-platoon manager is kept below a few tens of milliseconds. Instead\, the latency between vehicles and managers is one order of magnitude less critical.\n\nTien viet NGUYEN \;– \;Qualcomm \;: “V2X at Qualcomm”\n\nNowadays\, with the proliferation of electronics components\, vehicles on the roads are becoming ever smarter and more connected. At Qualcomm technology\, we pioneer the ubiquitous 5G connection between vehicles to the cloud\, V2X communication among vehicles and infrastructure to provide maximum benefits to the transportation ecosystem. In this talk\, we would like to showcase three examples where such connectivity improves the safety\, positioning\, and enhanced user experience. In the first example\, we provide an example where the ubiquitous 5G connection helps to address the issue of vehicular radar interference. The second example demonstrates how V2X communication can augment positioning in scenarios where GNSS is not available. In the third example\, we show how such communication can improve safety and driver experience by providing real time information about traffic conditions and road hazards.\n\nVitaly PETROV \;– \;Nokia Bell Labs \;: “Terahertz Band Vehicular Communications”\n\nFuture smart connected vehicles are envisioned to incorporate high-data rate communications and high-resolution radar sensing capabilities operating in the millimeter-wave and (sub-)terahertz (THz) frequencies. This lecture will cover the recent progress in developing terahertz band wireless systems focusing on vehicular setups. The specifics of THz wireless channel are first revealed. Then\, several aspects are discussed related to the design of reliable and efficient solutions for physical and link layers. Finally\, some open research problems in the area are outlined.\n\nOyunchimeg SHAGDAR \;– \;VEDECOM \;: “Message Redundancy and Congestion Control for V2X Collective Perception Service”\n\nOne of the key roles of C-ITS is to contribute in extending perception of vehicles and road users so that they can avoid potential accidents. Such an extended perception is built by information exchange among vehicles\, pedestrians\, and infrastructure using different types of messages including Cooperative Awareness Message (CAM) and Collective Perception Message (CPM). The data carried by these messages are critical\, however\, they can be resource-consuming and may contain highly redundant information. In this work\, we propose a context-aware CPM generation schemes that take into account message contents and roadside infrastructure availability. An extensive simulation has been carried out to evaluate the performances of the schemes. The results present remarkable performance improvements provided by the schemes\, particularly in terms of Packet Delivery Ratio (PDR)\, CBR (Channel Busy Ratio)\, and awareness rate compared to the conventional non-context-aware CPM generation strategy.\n\nHenk WYMEERSCH \;– \;Chalmers \;: “Radio-Localization for 5G and Beyond 5G V2X”\n\nIncreases in carrier frequencies and bandwidths\, driven by high-rate communication applications have led to vastly improved capabilities for user positioning. With research underway towards 6G\, opportunities for integrating positioning and sensing into the communication system have become even more apparent. The aim of this talk is to provide an overview of this evolution\, focusing on 5G and 6G. The talk will comprise 3 main parts: first\, the foundations of radio-based positioning are introduced. Second\, we go deeper into 5G positioning\, covering both the standard approaches\, as well as more forward-looking potential modifications. In the last part\, we consider 6G from the perspective of positioning and sensing\, highlighting some of the novel enablers\, methods\, potentials\, but also the corresponding challenges.\n\n \;\nGiven the limited number of places due to anti-covid restrictions\, we invite you to register through the \;link \;here below \;to receive the details of the \;Zoom streaming. We’ll keep you posted about the possibility to attend in presence.\nRegistration LINK\n \;\n\n \; ATTACH;FMTTYPE=image/jpeg:https://www.lincs.fr/wp-content/uploads/2022/02/ V2X-image.png CATEGORIES:Other Worshops,Workshop LOCATION:LINCS + Zoom\, 23 avenue d'Italie\, Paris\, 75013\, France X-APPLE-STRUCTURED-LOCATION;VALUE=URI;X-ADDRESS=23 avenue d'Italie\, Paris\, 75013\, France;X-APPLE-RADIUS=100;X-TITLE=LINCS + Zoom:geo:0,0 END:VEVENT BEGIN:VTIMEZONE TZID:Europe/Paris X-LIC-LOCATION:Europe/Paris BEGIN:STANDARD DTSTART:20211031T020000 TZOFFSETFROM:+0200 TZOFFSETTO:+0100 TZNAME:CET END:STANDARD END:VTIMEZONE END:VCALENDAR