Izenburua
Performance comparison of IEEE 802.11p and LTE-V2X through field-tests and simulationsBeste instituzio
Eurecat Centre Tecnològic de Catalunyahttps://ror.org/033vfbz75
Bertsioa
Postprinta
Eskubideak
© 2024 IEEESarbidea
Sarbide bahituaArgitaratzailearen bertsioa
https://doi.org/10.1109/VNC61989.2024.10576013Non argitaratua
IEEE Vehicular Networking Conference (VNC) Pp. 81-88. Kobe, 29-31 mayo, 2024Argitaratzailea
IEEEGako-hitzak
Communication Technologiespower measurement
Laburpena
Vehicular communication is a key enabler in making Automated Vehicles (AVs) collaborate by sharing information, which complements on-board sensor information and facilitates precise vehicle control. T ... [+]
Vehicular communication is a key enabler in making Automated Vehicles (AVs) collaborate by sharing information, which complements on-board sensor information and facilitates precise vehicle control. This paper presents a tailored measurement campaign aimed at analyzing the performance of two vehicular communication technologies, namely IEEE 802.11p and LTE-V2X. Our study focuses on key metrics for cooperating AVs, such as end-to-end latency and packet delivery ratios. Additionally, we investigate the feasibility of channel coexistence, assessing the challenges associated with concurrent channel access. The results derived from field tests are correlated with simulations conducted on PLEXE and OpenCV2X, i.e., platforms used for simulating IEEE 802.11p and LTE-V2X, respectively. This combined methodology, comprising field tests and simulations, enables the attainment of replicable conclusions, which in turn enables better design choices. [-]
Finantzatzailea
Gobierno VascoGobierno Vasco
Comisión Europea
Programa
Ikertalde 2022-2023Elkartek 2023
H2020-ECSEL
Zenbakia
IT1451-22KK-2023-00019
101007350
Laguntzaren URIa
Sin informaciónSin información
https://doi.org/10.3030/101007350
Proiektua
Sin informaciónMovilidad Autónoma Confiable mediante Tecnologías de Explicabilidad y Evaluación de Inteligencia Artificial (AUTOTRUST)
AI-augmented automation for efficient DevOps, a model-based framework for continuous development At RunTime in cyber-physical systems (AIDOaRT)