Future cooperative autonomous vehicles will be able to organize into flexible platoons to improve both the efficiency and the safety of driving. However, platooning requires dependable coordination through the periodic wireless exchange of control messages. Therefore, challenging propagation scenarios as found, e.g., in dense urban areas, may hinder coordination and lead to undesirable vehicle behavior. While reconfigurable intelligent surfaces (RISs) have been advocated as a solution to improper coverage issues, no system-level simulation exists that accounts for realistic road mobility and communication aspects. To this end, we present one such simulator built on top of the OMNeT++-based PLEXE and Veins frameworks. Specifically, our contribution is a simulator that takes into account vehicle mobility, physical layer propagation, RIS coding, and networking protocols. To test our simulator, we implement an RIS-assisted autonomous platoon merging maneuver taking place at an intersection where the absence of any RIS would limit successful communications to an area dangerously close to the intersection itself. Our results validate the simulator as a feasible tool for system-level RIS-assisted cooperative autonomous vehicle maneuvering, and ultimately show the benefit of RIS as roadside infrastructure for wireless coverage extension.

Enabling Cooperative Autonomous Driving Through mmWave and Reconfigurable Intelligent Surfaces / Segata, Michele; Lestas, Marios; Casari, Paolo; Saeed, Taqwa; Tyrovolas, Dimitrios; Karagiannidis, George K.; Liaskos, Christos. - (2023), pp. 32-39. (Intervento presentato al convegno Wireless On demand Network Systems and Services Conference tenutosi a Madonna di Campiglio, Italy nel 30th January-1st February 2023) [10.23919/WONS57325.2023.10062109].

Enabling Cooperative Autonomous Driving Through mmWave and Reconfigurable Intelligent Surfaces

Segata, Michele
Primo
;
Casari, Paolo;
2023-01-01

Abstract

Future cooperative autonomous vehicles will be able to organize into flexible platoons to improve both the efficiency and the safety of driving. However, platooning requires dependable coordination through the periodic wireless exchange of control messages. Therefore, challenging propagation scenarios as found, e.g., in dense urban areas, may hinder coordination and lead to undesirable vehicle behavior. While reconfigurable intelligent surfaces (RISs) have been advocated as a solution to improper coverage issues, no system-level simulation exists that accounts for realistic road mobility and communication aspects. To this end, we present one such simulator built on top of the OMNeT++-based PLEXE and Veins frameworks. Specifically, our contribution is a simulator that takes into account vehicle mobility, physical layer propagation, RIS coding, and networking protocols. To test our simulator, we implement an RIS-assisted autonomous platoon merging maneuver taking place at an intersection where the absence of any RIS would limit successful communications to an area dangerously close to the intersection itself. Our results validate the simulator as a feasible tool for system-level RIS-assisted cooperative autonomous vehicle maneuvering, and ultimately show the benefit of RIS as roadside infrastructure for wireless coverage extension.
2023
18th IEEE/IFIP Conference on Wireless On demand Network Systems and Services (WONS 2023)
Piscataway, NJ USA
Institute of Electrical and Electronics Engineers (IEEE)
978-3-903176-56-0
979-8-3503-2026-8
Segata, Michele; Lestas, Marios; Casari, Paolo; Saeed, Taqwa; Tyrovolas, Dimitrios; Karagiannidis, George K.; Liaskos, Christos
Enabling Cooperative Autonomous Driving Through mmWave and Reconfigurable Intelligent Surfaces / Segata, Michele; Lestas, Marios; Casari, Paolo; Saeed, Taqwa; Tyrovolas, Dimitrios; Karagiannidis, George K.; Liaskos, Christos. - (2023), pp. 32-39. (Intervento presentato al convegno Wireless On demand Network Systems and Services Conference tenutosi a Madonna di Campiglio, Italy nel 30th January-1st February 2023) [10.23919/WONS57325.2023.10062109].
File in questo prodotto:
File Dimensione Formato  
segata2023enabling.pdf

accesso aperto

Tipologia: Post-print referato (Refereed author’s manuscript)
Licenza: Tutti i diritti riservati (All rights reserved)
Dimensione 750.2 kB
Formato Adobe PDF
750.2 kB Adobe PDF Visualizza/Apri
Enabling_Cooperative_Autonomous_Driving_through_mmWave_and_Reconfigurable_Intelligent_Surfaces.pdf

Solo gestori archivio

Tipologia: Versione editoriale (Publisher’s layout)
Licenza: Tutti i diritti riservati (All rights reserved)
Dimensione 769.65 kB
Formato Adobe PDF
769.65 kB Adobe PDF   Visualizza/Apri

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11572/370349
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 2
  • ???jsp.display-item.citation.isi??? 1
social impact