Enhancements of V2X communication in support of cooperative autonomous driving

Hobert, Laurens; Festag, Andreas; Llátser, Ignacio; Altomare, Luciano; Visintainer, Filippo; Kovács, András

doi:10.1109/mcom.2015.7355568

Cited by 297 publications

(142 citation statements)

References 11 publications

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“…Kim and Seo [92] highlight spatially secure group communication (SSGC) as a key issue in enabling secure cooperative multiple unmanned autonomous vehicle (UAV) control [98]. An analytical framework is developed to model the dynamics of multiple UAVs and SSGC.…”

Section: Recent Advances In Cvnmentioning

confidence: 99%

Cooperative Vehicular Networking: A Survey

Ahmed

Gharavi

2018

IEEE Trans. Intell. Transport. Syst.

229

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With the remarkable progress of cooperative communication technology in recent years, its transformation to vehicular networking is gaining momentum. Such a transformation has brought a new research challenge in facing the realization of cooperative vehicular networking (CVN). This paper presents a comprehensive survey of recent advances in the field of CVN. We cover important aspects of CVN research, including physical, medium access control, and routing protocols, as well as link scheduling and security. We also classify these research efforts in a taxonomy of cooperative vehicular networks. A set of key requirements for realizing the vision of cooperative vehicular networks is then identified and discussed. We also discuss open research challenges in enabling CVN. Lastly, the paper concludes by highlighting key points of research and future directions in the domain of CVN.

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Section: Recent Advances In Cvnmentioning

confidence: 99%

Cooperative Vehicular Networking: A Survey

Ahmed

Gharavi

2018

IEEE Trans. Intell. Transport. Syst.

229

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“…g (s [1] ) y [1] g (s [1] ) s [2] s [3] s [1] W [3] x g y g ψ [1] L [3] s [1] bsr,in s [1] icr,in s [1] cr,in s [1] cr,out s [1] icr,out (0, 0) Fig. 1: Schematic of the intersection in the global frame, (xg, yg), with its origin (0, 0) at the center of the intersection.…”

Section: A Vehicle Kinematicsmentioning

confidence: 99%

“…Automated vehicles (AV) today either operate in a reactive way by solely basing their actions on sensor readings or exploit an uncertain estimate of future motion trajectories of other road users to be more proactive. With vehicleto-vehicle (V2V) communication, more reliable information about future trajectories of the surrounding traffic can be adopted to operate the AV more efficiently [1]. Especially in intersections, throughput could significantly be improved when, instead of using traffic lights or signs, vehicles would negotiate intersection crossing using V2V communication.…”

Section: Introductionmentioning

confidence: 99%

Nonlinear Model Predictive Control for Distributed Motion Planning in Road Intersections Using PANOC

Katriniok

Sopasakis

Schuurmans

et al. 2019

2019 IEEE 58th Conference on Decision and Control (CDC)

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The coordination of highly automated vehicles (or agents) in road intersections is an inherently nonconvex and challenging problem. In this paper, we propose a distributed motion planning scheme under reasonable vehicleto-vehicle communication requirements. Each agent solves a nonlinear model predictive control problem in real time and transmits its planned trajectory to other agents, which may have conflicting objectives. The problem formulation is augmented with conditional constraints that enable the agents to decide whether to wait at a stopping line, if safe crossing is not possible. The involved nonconvex problems are solved very efficiently using the proximal averaged Newton method for optimal control (PANOC). We demonstrate the efficiency of the proposed approach in a realistic intersection crossing scenario. A. Katriniok is with Ford Research

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“…Cooperative perception is realized by exchanging sensor data between vehicles and Roadside Units (RSUs) and is necessary to widen or enhance the visibility area of HD maps [64], [65]. Sensors within a RSU mounted at a lamppost allow, due to the bird's eye view, a more accurate localization of objects.…”

Section: Scenario/use Cases and Requirementsmentioning

confidence: 99%

Where, When, and How mmWave is Used in 5G and Beyond

Sakaguchi

Haustein

Barbarossa

et al. 2017

IEICE Trans. Electron.

173

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SUMMARYWireless engineers and business planners commonly raise the question on where, when, and how millimeter-wave (mmWave) will be used in 5G and beyond. Since the next generation network is not just a new radio access standard, but also an integration of networks for vertical markets with diverse applications, answers to the question depend on scenarios and use cases to be deployed. This paper gives four 5G mmWave deployment examples and describes in chronological order the scenarios and use cases of their probable deployment, including expected system architectures and hardware prototypes. The first example is a 28 GHz outdoor backhauling for fixed wireless access and moving hotspots, which will be demonstrated at the PyeongChang Winter Olympic Games in 2018. The second deployment example is a 60 GHz unlicensed indoor access system at the Tokyo-Narita airport, which is combined with Mobile Edge Computing (MEC) to enable ultra-high speed content download with low latency. The third example is mmWave mesh network to be used as a micro Radio Access Network (µ-RAN), for cost-effective backhauling of small-cell Base Stations (BSs) in dense urban scenarios. The last example is mmWave based Vehicular-to-Vehicular (V2V) and Vehicular-to-Everything (V2X) communications system, which enables automated driving by exchanging High Definition (HD) dynamic map information between cars and Roadside Units (RSUs). For 5G and beyond, mmWave and MEC will play important roles for a diverse set of applications that require both ultra-high data rate and low latency communications. key words: millimeter wave, MEC, 28GHz, 60GHz, mesh network, V2V/V2X, automated driving, future forecast

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Enhancements of V2X communication in support of cooperative autonomous driving

Cited by 297 publications

References 11 publications

Cooperative Vehicular Networking: A Survey

Cooperative Vehicular Networking: A Survey

Nonlinear Model Predictive Control for Distributed Motion Planning in Road Intersections Using PANOC

Where, When, and How mmWave is Used in 5G and Beyond

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