Details
| Originalsprache | Englisch |
|---|---|
| Titel des Sammelwerks | 2023 IEEE 98th Vehicular Technology Conference, VTC 2023-Fall - Proceedings |
| Herausgeber (Verlag) | Institute of Electrical and Electronics Engineers Inc. |
| ISBN (elektronisch) | 9798350329285 |
| Publikationsstatus | Veröffentlicht - 2023 |
| Veranstaltung | 98th IEEE Vehicular Technology Conference, VTC 2023-Fall - Hong Kong, China Dauer: 10 Okt. 2023 → 13 Okt. 2023 |
Publikationsreihe
| Name | IEEE Vehicular Technology Conference |
|---|---|
| ISSN (Print) | 1550-2252 |
Abstract
The deployment of Connected Vehicles (CVs) has made significant progress in recent times. CVs have expanded beyond the scope of sending self-information or updates solely about their immediate surroundings. With the introduction of new services in Release 2 they are now progressing towards cooperative perception and driving. Additionally, the standardization process for the Vulnerable Road User Awareness Message (VAM) has reached a stable version from the European Telecommunication Standardization Institute. Extensive testing for new services and technologies in the domain of vehicular communication is crucial but costly in real-life mass deployment. Hence, scientists use simulation platforms for more affordable testing. In this work we present a new lightweight dataset-based simulation framework (LiDaSim), providing an interface for real-world data recordings. We showcase the framework capabilities by integrating Release 2 services. We demonstrate that our simulator is especially valuable when deploying techniques or conducting measurements that necessitate a highly realistic movement of traffic participants. The results are compared with another established simulator, showing significant differences in terms of generation frequencies and triggering reasons for Cooperative Awareness Messages (CAMs) and VAMs. As a result, this divergence leads to a shift in the necessary channel requirements during the implementation.
ASJC Scopus Sachgebiete
- Informatik (insg.)
- Angewandte Informatik
- Ingenieurwesen (insg.)
- Elektrotechnik und Elektronik
- Mathematik (insg.)
- Angewandte Mathematik
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- Apa
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- BibTex
- RIS
2023 IEEE 98th Vehicular Technology Conference, VTC 2023-Fall - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2023. (IEEE Vehicular Technology Conference).
Publikation: Beitrag in Buch/Bericht/Sammelwerk/Konferenzband › Aufsatz in Konferenzband › Forschung › Peer-Review
}
TY - GEN
T1 - LiDaSim
T2 - 98th IEEE Vehicular Technology Conference, VTC 2023-Fall
AU - Xhoxhi, Edmir
AU - Wolff, Vincent Albert
AU - Orychshenko, Alexey
N1 - Publisher Copyright: © 2023 IEEE.
PY - 2023
Y1 - 2023
N2 - The deployment of Connected Vehicles (CVs) has made significant progress in recent times. CVs have expanded beyond the scope of sending self-information or updates solely about their immediate surroundings. With the introduction of new services in Release 2 they are now progressing towards cooperative perception and driving. Additionally, the standardization process for the Vulnerable Road User Awareness Message (VAM) has reached a stable version from the European Telecommunication Standardization Institute. Extensive testing for new services and technologies in the domain of vehicular communication is crucial but costly in real-life mass deployment. Hence, scientists use simulation platforms for more affordable testing. In this work we present a new lightweight dataset-based simulation framework (LiDaSim), providing an interface for real-world data recordings. We showcase the framework capabilities by integrating Release 2 services. We demonstrate that our simulator is especially valuable when deploying techniques or conducting measurements that necessitate a highly realistic movement of traffic participants. The results are compared with another established simulator, showing significant differences in terms of generation frequencies and triggering reasons for Cooperative Awareness Messages (CAMs) and VAMs. As a result, this divergence leads to a shift in the necessary channel requirements during the implementation.
AB - The deployment of Connected Vehicles (CVs) has made significant progress in recent times. CVs have expanded beyond the scope of sending self-information or updates solely about their immediate surroundings. With the introduction of new services in Release 2 they are now progressing towards cooperative perception and driving. Additionally, the standardization process for the Vulnerable Road User Awareness Message (VAM) has reached a stable version from the European Telecommunication Standardization Institute. Extensive testing for new services and technologies in the domain of vehicular communication is crucial but costly in real-life mass deployment. Hence, scientists use simulation platforms for more affordable testing. In this work we present a new lightweight dataset-based simulation framework (LiDaSim), providing an interface for real-world data recordings. We showcase the framework capabilities by integrating Release 2 services. We demonstrate that our simulator is especially valuable when deploying techniques or conducting measurements that necessitate a highly realistic movement of traffic participants. The results are compared with another established simulator, showing significant differences in terms of generation frequencies and triggering reasons for Cooperative Awareness Messages (CAMs) and VAMs. As a result, this divergence leads to a shift in the necessary channel requirements during the implementation.
KW - Intelligent Transportation Systems
KW - VANET simulation
KW - Vulnerable Road User Awareness Message
UR - http://www.scopus.com/inward/record.url?scp=85181168812&partnerID=8YFLogxK
U2 - 10.1109/VTC2023-Fall60731.2023.10333499
DO - 10.1109/VTC2023-Fall60731.2023.10333499
M3 - Conference contribution
AN - SCOPUS:85181168812
T3 - IEEE Vehicular Technology Conference
BT - 2023 IEEE 98th Vehicular Technology Conference, VTC 2023-Fall - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 10 October 2023 through 13 October 2023
ER -