Digital multi-scale visual planning model of spatial-geographical landscape pattern of smart parks

Abstract

The current traditional multi-scale visual planning model mainly relies on existing a priori maps to realize visual planning, which leads to poor planning results due to the lack of establishment of reward functions. In this regard, a digital multiscale visual planning model for the geographic landscape pattern of smart parks is proposed. The AC algorithm is used to describe the observed state and update the planning strategy directly by maximizing the average return, and establish the planning reward function. In the experiments, the planning performance of the proposed model is verified. The analysis of the experimental results shows that the visual planning model constructed by the proposed method possesses a lower collision rate and the model has a better planning performance.