Radio resource management and path planning in intelligent transportation systems via reinforcement learning for environmental sustainability
Publikation: Beitrag in Buch/Konferenzbericht/Sammelband/Gutachten › Beitrag in Konferenzband › Beigetragen › Begutachtung
Beitragende
Abstract
Efficient and dynamic path planning has become an important topic for urban areas with larger density of connected vehicles (CV) which results in reduction of travel time and directly contributes to environmental sustainability through reducing energy consumption. CVs exploit the cellular wireless vehicle-to-everything (C-V2X) communication technology to disseminate the vehicle-to-infrastructure (V2I) messages to the Base-station (BS) to improve situation awareness on urban roads. In this paper, we investigate radio resource management (RRM) in such a framework to minimize the age of information (AoI) so as to enhance path planning results. We use the fact that V2I messages with lower AoI value result in less error in estimating the road capacity and more accurate path planning. Through simulations, we compare road travel times and volume over capacity (V/C) against different levels of AoI and demonstrate the promising performance of the proposed framework.
Details
| Originalsprache | Englisch |
|---|---|
| Titel | Innovation and Technological Advances for Sustainability |
| Redakteure/-innen | Salem Al-Naemi, Rachid Benlamri, Michael Phillips, Rehan Sadiq, Aitazaz Farooque |
| Seiten | 457-467 |
| Seitenumfang | 11 |
| Publikationsstatus | Veröffentlicht - 13 Nov. 2024 |
| Peer-Review-Status | Ja |
| Extern publiziert | Ja |
Externe IDs
| Scopus | 85210867354 |
|---|
Schlagworte
Ziele für nachhaltige Entwicklung
- SDG 7 – Erschwingliche und saubere Energie - MADDPG, AoI, Path planning, Resource management, V2X
ASJC Scopus Sachgebiete
- Erneuerbare Energien, Nachhaltigkeit und Umwelt - MADDPG, AoI, Path planning, Resource management, V2X
- Allgemeine Computerwissenschaft - MADDPG, AoI, Path planning, Resource management, V2X
Schlagwörter
- MADDPG, AoI, Path planning, Resource management, V2X