Dataset supports modeling of communication delays in cloud-connected vehicles, indicating safety implications.
Cloud-based intelligent connected vehicles (CICVs) rely on vehicle-to-network-to-vehicle (V2N2V) communication for cooperative planning and control (PnC), where communication delay directly influences control performance and safety. To support research on delay modeling and delay-aware control, we present CICV5G, a publicly available dataset of 5G communication delay for cloud-based CICV applications. The dataset comprises more than 150,000 synchronized records collected from field experiments at the Tongji Intelligent Vehicle Evaluation Base, covering diverse driving environments, network modes, and vehicle velocities. Each record includes network indicators (RSRP, SINR, Cell ID) and vehicle motion data (position, heading, velocity) with millisecond-level timestamps. All measurements were obtained through a real V2N2V loop using a 5G V2N2V testbed with both public and private networks. The dataset has been validated through statistical analysis of delay distributions and network consistency. CICV5G provides a reproducible foundation for developing communication delay models, delay prediction methods, and cloud-based planning and control strategies for CICVs.
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Zhang et al. (2026) studied this question.
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