Construction and realization of simulation training environment based on AI-assisted simulation of real scenarios of dispatching and commanding operations

Abstract

Abstract Dispatch command business is an essential and important part of modern society's production and life. With the development of science and technology, the use of AI-assisted construction of simulation training environments is of enormous significance to the development and improvement of the dispatching command business. The study facilitates the acquisition and preprocessing of data from the three-dimensional scene used in the scheduling command simulation training, refines the details of the simulation environment using a multi-resolution hierarchical detail model, and enables the creation of a simulation training environment for the scheduling command using three-dimensional modeling and optimization technology. In this paper, the dispatching system trained in a simulation environment is better than other dispatching systems in terms of dispatching accuracy, starting difficulty, and feedback effectiveness. The satisfaction rate for scheduling demand on different subway lines is significantly better than other scheduling algorithms. As the sampling area expands, the FID and NRMSE values of the generated real map decrease, but the PSNR and NRMSE values increase. This paper generates a dispatching command simulation training environment with a fidelity level of “excellent” and a simulation quality that exhibits a high degree of realism and credibility.