智能驾驶数字孪生仿真平台数据集

本数据集的核心价值在于结合了实际园区的高精度数字孪生模型与异构多传感器数据，并通过CENI网络实现了端云协同的数据交互流程。这为研究智能驾驶车辆与路侧基础设施（如灯杆上的传感器）间的协同感知、网内智能计算卸载以及大规模网络孪生技术提供了全面的数据基础。数据集的发布将有效推动智能驾驶系统在真实场景下的安全验证和性能优化，同时为数字孪生建模和多智能体协同研究提供可靠的基准平台。数据集共包括运行日志、系统运行截图与视频等文件，数据来源于智能驾驶数字孪生仿真平台运行，包括中国科学技术大学先进技术研究院的空间地图、数字孪生，园区内25个灯杆的传感器信息。

The core value of this dataset lies in the integration of high-precision digital twin models of real-world parks and heterogeneous multi-sensor data, along with an edge-cloud collaborative data interaction workflow implemented via the CENI network. This provides a comprehensive data foundation for research on collaborative perception between autonomous vehicles and roadside infrastructure (such as sensors mounted on lamp poles), in-network intelligent computation offloading, and large-scale network twin technologies. The release of this dataset will effectively facilitate safety verification and performance optimization of autonomous driving systems in real-world scenarios, while offering a reliable benchmark platform for digital twin modeling and multi-agent collaboration research. The dataset comprises files including operation logs, system operation screenshots, and videos. The data is sourced from the operation of the autonomous driving digital twin simulation platform, covering spatial maps and digital twin models provided by the Advanced Technology Research Institute of the University of Science and Technology of China (USTC), as well as sensor information from 25 lamp poles within the park.