SEE-V2X: C-V2X Direct Communication Dataset: An Application-Centric Approach

Cellular-vehicle-to-everything (C-V2X) technology has been increasingly adopted by the research community, automotive industry, and government agencies as the next key technology to enhance transportation safety and efficiency. Recent years have also witnessed emerging C-V2X-based applications, connecting sensors on vehicles (V2V), from the infrastructure (V2I), and carried by pedestrians (V2P), to enable novel capabilities such as cooperative perception, sustainable transportation, and remote operations. While researchers have made successful strides in simulating these promising applications, the disconnect with real-world C-V2X performance often renders ungrounded assumptions, resulting in huge barriers towards deployment. In this paper, we aim to build and release a real-world C-V2X dataset, SEE-V2X, using commercial off-the-shelf standard compliant C-V2X radios. Emulating the traffic patterns of popular C-V2X applications, we investigate the gap between the demand and reality. Beyond throughput and latency, SEE-V2X contains cross-layer details, offers insight into the resource scheduling and allocation mechanism in various situations, and reveals the impact of nuanced configuration. Our preliminary analysis shows that severe packet collision and jitter can easily happen, indicating opportunities to avoid performance degradation with careful and subtle configuration. SEE-V2X dataset and the analysis tools are available at https://cisl.ucr.edu/SEE-V2X/.

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Publication Details

Published
2025-05-04
DOI
https://doi.org/10.1145/3715014.3722077
Primary Topic
Vehicular Ad Hoc Networks (VANETs)
Type
article
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article

SEE-V2X: C-V2X Direct Communication Dataset: An Application-Centric Approach

Zhaowei Tan, Hang Qiu, Ruoshen Mo, Bo Wu
Vehicular Ad Hoc Networks (VANETs)
article

SEE-V2X: C-V2X Direct Communication Dataset: An Application-Centric Approach

Zhaowei Tan, Hang Qiu, Ruoshen Mo, Bo Wu
article en

Abstract

Cellular-vehicle-to-everything (C-V2X) technology has been increasingly adopted by the research community, automotive industry, and government agencies as the next key technology to enhance transportation safety and efficiency. Recent years have also witnessed emerging C-V2X-based applications, connecting sensors on vehicles (V2V), from the infrastructure (V2I), and carried by pedestrians (V2P), to enable novel capabilities such as cooperative perception, sustainable transportation, and remote operations. While researchers have made successful strides in simulating these promising applications, the disconnect with real-world C-V2X performance often renders ungrounded assumptions, resulting in huge barriers towards deployment. In this paper, we aim to build and release a real-world C-V2X dataset, SEE-V2X, using commercial off-the-shelf standard compliant C-V2X radios. Emulating the traffic patterns of popular C-V2X applications, we investigate the gap between the demand and reality. Beyond throughput and latency, SEE-V2X contains cross-layer details, offers insight into the resource scheduling and allocation mechanism in various situations, and reveals the impact of nuanced configuration. Our preliminary analysis shows that severe packet collision and jitter can easily happen, indicating opportunities to avoid performance degradation with careful and subtle configuration. SEE-V2X dataset and the analysis tools are available at https://cisl.ucr.edu/SEE-V2X/.

University of California, Riverside (US)
Openalex Percentile: Top 92%
Vehicular Ad Hoc Networks (VANETs)
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