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Information acquisition from target perception represents the key enablingtechnology of the Internet of Automatic Vehicles (IoAV), which is essential forthe decision-making and control operation of connected automatic vehicles(CAVs). Exploring target information involves multiple operations on data,e.g., wireless sensing (for data acquisition), communication (for datatransmission), and computing (for data analysis), which all rely on theconsumption of time-space-frequency-computing (TSFC) multi-domain resources.Due to the coupled resource sharing of sensing, communication, and computingprocedures, the resource management of information-oriented IoAV is commonlyformulated as a non-convex NP-hard problem. In this article, further combiningthe integrated sensing and communication (ISAC) and computing, we introduce theintegrated sensing, communication, and computing (ISCC), wherein the TSFCresources are decoupled from the specific processes and shared universallyamong sensing, communication, and computing processes. Furthermore, theinformation-oriented resource trading platform (IRTP) is established, whichtransforms the problem of ISCC resource management into a resource-informationsubstitution model. Finally, we embed the employment topology structure in IoAVinto neural network architecture, taking advantage of the graph neural network(GNN) and multi-worker reinforcement learning, and propose the dynamic resourcemanagement strategy based on the asynchronous advantage GNN (A2GNN) algorithm,which can achieve the convergence both of information gain maximization andresource consumption minimization, realizing efficient information-orientedresource management.

Integrated Sensing, Communication, and Computing: An Information-oriented Resource Transaction Mechanism