Design, Implementation, and Empirical Validation of a Framework for Remote Car Driving Using a Commercial Mobile Network

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Título: Design, Implementation, and Empirical Validation of a Framework for Remote Car Driving Using a Commercial Mobile Network
Autor/es: Saez-Perez, Javier | Wang, Qi | Alcaraz-Calero, Jose M. | Garcia-Rodriguez, Jose
Grupo/s de investigación o GITE: Arquitecturas Inteligentes Aplicadas (AIA)
Centro, Departamento o Servicio: Universidad de Alicante. Departamento de Tecnología Informática y Computación
Palabras clave: Autonomous driving | Teledriving | Car control
Fecha de publicación: 3-feb-2023
Editor: MDPI
Cita bibliográfica: Saez-Perez J, Wang Q, Alcaraz-Calero JM, Garcia-Rodriguez J. Design, Implementation, and Empirical Validation of a Framework for Remote Car Driving Using a Commercial Mobile Network. Sensors. 2023; 23(3):1671. https://doi.org/10.3390/s23031671
Resumen: Despite the fact that autonomous driving systems are progressing in terms of their automation levels, the achievement of fully self-driving cars is still far from realization. Currently, most new cars accord with the Society of Automotive Engineers (SAE) Level 2 of automation, which requires the driver to be able to take control of the car when needed: for this reason, it is believed that between now and the achievement of fully automated self-driving car systems, there will be a transition, in which remote driving cars will be a reality. In addition, there are tele-operation-use cases that require remote driving for health or safety reasons. However, there is a lack of detailed design and implementation available in the public domain for remote driving cars: therefore, in this work we propose a functional framework for remote driving vehicles. We implemented a prototype, using a commercial car. The prototype was connected to a commercial 4G/5G mobile network, and empirical experiments were conducted, to validate the prototype’s functions, and to evaluate its performance in real-world driving conditions. The design, implementation, and empirical evaluation provided detailed technical insights into this important research and innovation area.
Patrocinador/es: This research was funded in part by the EU Horizon 2020 5G-PPP 5G-INDUCE project (“Open cooperative 5G experimentation platforms for the industrial sector NetApps”) under grant number H2020-ICT-2020-2/101016941, by the EU Horizon Europe INCODE project (“Programming platform for intelligent collaborative deployments over heterogeneous edge-IoT environments”) under grant number HORIZON-CL4-2022-DATA-01-03/101093069, and by the EU Horizon Europe project INCODE: programming platform for intelligent collaborative deployments over heterogeneous edge-IoT environments (HORIZON-CL4-2022-DATA-01-03/101093069).
URI: http://hdl.handle.net/10045/131844
ISSN: 1424-8220
DOI: 10.3390/s23031671
Idioma: eng
Tipo: info:eu-repo/semantics/article
Derechos: © 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Revisión científica: si
Versión del editor: https://doi.org/10.3390/s23031671
Aparece en las colecciones:Investigaciones financiadas por la UE
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