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C-AVOID

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Connected Autonomous Vehicles Orchestrated with Intelligent Decisions

Connected Vehicles (CVs) represent a potentially disruptive yet beneficial change to our transportation systems. Wireless communication capabilities on vehicles enable a better understanding of the environment complementing on-boa... ver más

30/09/2022

UCY

146K€

Presupuesto del proyecto: 146K€

Líder del proyecto

UNIVERSITY OF CYPRUS No se ha especificado una descripción o un objeto social para esta compañía.

TRL 4-5

Fecha límite participación Sin fecha límite de participación.

Financiación concedida El organismo H2020 notifico la concesión del proyecto el día 2022-09-30

WF-02-2019: Widening Fellowships

I+D

Cerrada hace 5 años

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Información adicional privada

No hay información privada compartida para este proyecto. Habla con el coordinador.

1 Participantes

UCY

145.94K€ | Lider

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Duración del proyecto: 24 meses Fecha Inicio: 2020-09-29
Fecha Fin: 2022-09-30

Líder del proyecto

UNIVERSITY OF CYPRUS No se ha especificado una descripción o un objeto social para esta compañía.

TRL 4-5

Presupuesto del proyecto 146K€

Fecha límite de participación Sin fecha límite de participación.

Descripción del proyecto Connected Vehicles (CVs) represent a potentially disruptive yet beneficial change to our transportation systems. Wireless communication capabilities on vehicles enable a better understanding of the environment complementing on-board sensors and increase the potentials of autonomous vehicles. For this reason, communication among vehicles has always played an important role in safety applications and an extended body of research is present on, e.g., collision avoidance or autonomous vehicles coordination. Almost all state-of-the-art approaches take for granted the wireless link, ignoring the communication load and the processing latency that such algorithms may imply. Furthermore, state-of-the-art coordination algorithms rely on very strong assumptions, e.g., the exact knowledge of the position of the vehicles in the system. C-AVOID aims at filling these gaps, building a realistic framework that exploits a specific wireless technology, i.e., the new generation of cellular networks (5G). 5G shows undeniable potential for transportation systems thanks to (i) low end-to-end latency; (ii) edge computational capabilities of the Multi-Access Edge Computing (MEC) platform. Prompt and detailed information based on the direct feedback of connected cars allows to create a profile of typical driver maneuvers and decisions and of localization uncertainties, representing the building block of the new safety applications presented in C-AVOID. Processing latency and communication load will be taken into account through a MEC-enable hardware-in-the-loop simulator, and event-triggering communication will be proposed to counterattack possible application requirement violations. C-AVOID will be carried out by the Experienced Researcher (ER), which has extensive familiarity with networking performance evaluation and system optimization. The ER will collaborate with supervisor Prof. Ellinas, which experience in Telco systems and patent procedures ensure the overall success of this action.

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