Autonomous driving paper index
The Role of Data Governance in CPS Stability from an Information Economics Perspective
One-line summary
Cyber-physical systems rely on stable connections between the physical and digital worlds, but everything depends on the data linking the two.
Engineering notes
Key topics: autonomous driving, control. See the paper for implementation details and experimental results.
Chinese explanation / 中文解读
中文解读待补充：本站会优先为端到端自动驾驶、BEV感知、3D目标检测、轨迹预测、路径规划、LiDAR感知等高价值论文补充中文说明。
Original abstract
Cyber-physical systems rely on stable connections between the physical and digital worlds, but everything depends on the data linking the two. If the data isn't trustworthy, the whole system falters. Engineers have spent years studying CPS stability with control theory and computer science, but there's a blind spot: the economic incentives and information structures shaping how data flows and gets used. That's a big gap. This study tackles the problem head-on by building a framework grounded in information economics. It argues that data governance—things like quality control, security, standards, and ownership—acts as the backbone for these systems. By connecting governance mechanisms to key concepts from information economics, like reducing information asymmetry or making contracts whole, the paper shows that good governance doesn't just patch technical holes. It also lowers internal coordination costs, keeps opportunistic behavior in check, and pushes groups toward smarter decisions. In short, the paper offers a fresh perspective that blends technical and economic thinking. It lays out a way to understand and strengthen the resilience of complex, data-driven engineering systems.
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