Field Trials in 5G-Nr Aided Vehicle-Road-Cloud Integrated Systems: From the Perspective of Latency and Aoi

With the increase in the number of vehicles, vehicle-road-cloud integrated architecture is regarded as a key application of vehicle-to-everything (V2X) systems. The vehicle-road-cloud integrated architecture enables real-time communication of vehicle-to-vehicle, vehicle-to-infrastructure, vehicle-topedestrians, and vehicles-to-cloud, therefore significantly improving traffic efficiency. This paper constructs a field testing platform of vehicle-road-cloud integrated system, based on 5 G new radio (NR). We first introduce the deployment of test platforms for the vehicle, road, and cloud sides. Then, the data exchange procedure among the vehicle, road, and cloud sides is presented. Tailed for the time-sensitive requirement in NR-V2X applications, we propose a pre-scheduling design. Explicitly, the packets can be transmitted immediately, without the requirement of waiting for an uplink scheduling request (SR) slot. Finally, a comprehensive field trial is conducted to evaluate the latency and the age of information (Aol) performance, in peak and off-peak hours respectively. The testing result revealed that, the proposed prescheduling design can significantly reduce the end-to-end latency, and therefore also improve the AoI performance, guaranteeing the requirements of mission critical application in NR-V2X systems.

Authors

Institutions

Publication Details

Published
2025-04-24
DOI
https://doi.org/10.1109/icccbda64898.2025.11030493
Primary Topic
Vehicular Ad Hoc Networks (VANETs)
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Field Trials in 5G-Nr Aided Vehicle-Road-Cloud Integrated Systems: From the Perspective of Latency and Aoi

Ning Jia, Yanwen Wang, Jiajun Liu
Vehicular Ad Hoc Networks (VANETs)
article

Field Trials in 5G-Nr Aided Vehicle-Road-Cloud Integrated Systems: From the Perspective of Latency and Aoi

Ning Jia, Yanwen Wang, Jiajun Liu
article en

Abstract

With the increase in the number of vehicles, vehicle-road-cloud integrated architecture is regarded as a key application of vehicle-to-everything (V2X) systems. The vehicle-road-cloud integrated architecture enables real-time communication of vehicle-to-vehicle, vehicle-to-infrastructure, vehicle-topedestrians, and vehicles-to-cloud, therefore significantly improving traffic efficiency. This paper constructs a field testing platform of vehicle-road-cloud integrated system, based on 5 G new radio (NR). We first introduce the deployment of test platforms for the vehicle, road, and cloud sides. Then, the data exchange procedure among the vehicle, road, and cloud sides is presented. Tailed for the time-sensitive requirement in NR-V2X applications, we propose a pre-scheduling design. Explicitly, the packets can be transmitted immediately, without the requirement of waiting for an uplink scheduling request (SR) slot. Finally, a comprehensive field trial is conducted to evaluate the latency and the age of information (Aol) performance, in peak and off-peak hours respectively. The testing result revealed that, the proposed prescheduling design can significantly reduce the end-to-end latency, and therefore also improve the AoI performance, guaranteeing the requirements of mission critical application in NR-V2X systems.

Tongji University (CN), SAIC Motor (China) (CN)
Sustainable cities and communities
Openalex Percentile: Top 88%
Vehicular Ad Hoc Networks (VANETs)
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Field Trials in 5G-Nr Aided Vehicle-Road-Cloud Integrated Systems: From the Perspective of Latency and Aoi — Ning Jia, Yanwen Wang, et al. · (2025) | TGRS Research Map | TGRS