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CGRA-CA for NR-V2X
- Citation Author(s):
- Submitted by:
- Zhexin Xu
- Last updated:
- Sun, 01/19/2025 - 08:55
- DOI:
- 10.21227/a77r-n520
- Data Format:
- License:
5 Views- Categories:
- Keywords:
Abstract
This dataset supports the evaluation of the Cooperative Greedy Response Algorithm for Collision Avoidance (CGRA-CA) in NR-V2X networks. The data include real-world traffic-flow measurements collected from urban intersections and expressways in Fuzhou, China, during peak traffic hours. Parameters such as vehicle counts, trajectories, and signal timing are included. These data were integrated into the SUMO simulation framework to replicate diverse traffic scenarios, enabling the analysis of the CGRA-CA algorithm's performance in optimizing V2V communication efficiency, minimizing response cycles, and reducing packet collisions under various conditions. The dataset is critical for advancing research in vehicular communication and intelligent transportation systems.
The uploaded dataset includes vehicular topology files and link weight matrix files for urban intersection scenarios and expressway scenarios. Users can utilize MATLAB or Python to read and process these files. The vehicular topology files represent the connectivity between vehicles, while the link weight matrices define the communication link quality between vehicle pairs. After loading these files, users can apply their own file transmission or response algorithms based on the provided topology and link weights. This dataset is ideal for evaluating and benchmarking algorithms in vehicular communication and network optimization studies.
