# Research on Automatic Generation of Park Road Network Based on Skeleton Algorithm
## 6 Discussion  
With the advent of the big data era, the convergence of computer technology and traditional design constitutes an inevitable trend; however, numerous challenges arise in the integration of the two. The generation of traditional road networks demands that designers complete it manually, entailing a considerable number of repetitive tasks. Shortcomings exist in the practical application of machine learning methods, where the generated roads lack inherent logic, fail to incorporate expert prior knowledge, and have insufficient explainability and extensibility.  
The objective of this study is to facilitate designers in undertaking road network design more proficiently. For policy makers, it is requisite to review and supervise design schemes to guarantee that they conform to the established policy goals and regulatory demands. The assistive design approach proposed in this study can offer urban planners and policy makers an opportunity to expeditiously explore potential planning schemes. For designers, the design of road networks is an extremely complex task that demands the consideration of numerous factors [52]. This study introduces graphical methods and integrates the merits of interactive design methods to automatically generate road network schemes while retaining the structured information among geographic elements, possessing excellent explanatory and interactive capabilities (Table 1).  
While this study has made strides in automating road network design to some extent, there are still inherent limitations. In the context of park road network design, it is crucial to also account for esthetic considerations [53; 54; 55], such as incorporating curved and zigzag road profiles to evoke a calming and visually pleasing effect. Thoughtfully integrated undulations and turning points can enhance the enjoyment of pedestrian experiences. However, algorithm-driven intelligent design tends towards standardized and repetitive patterns, facing challenges in fully capturing human esthetic perception and creativity. Further research is needed on how to manifest the personal style and intellectual depth of designers within their design schemes.  
Most studies on virtual road networks are typically conducted under flat terrain conditions. However, the undulating topography of the design site introduces variability to the scene and also presents challenges for road network design. Changes in road slope can significantly impact visitors' visual experience and overall perception of the park. Therefore, a thoughtful approach to designing roads that accommodate changes in elevation is essential for enhancing the landscape's appeal. In the future, advancements in technology  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline  & **Work Style** & **Domain Knowledge** & **Explainable** & **Interactivity** \\ \hline Traditional methods & Manual & Yes & Yes & No \\ Machine learning & automatic & No & No & No \\ Proposed method & automatic & Yes & Yes & Yes \\ \hline \hline \end{tabular}
\end{table}
Table 1: Method comparison.  
such as digital elevation models and machine learning could be leveraged to accurately reflect topographical variations within road networks. Furthermore, different types of roads can cater to specific functional areas within the park, including tour paths, walking paths, bicycle paths, etc., in order to meet diverse visitor needs. Current research primarily focuses on the macro-level generation of road networks with an emphasis on principles such as accessibility and connectivity. However, there is a need for more comprehensive research that delves into aspects beyond just the slope, width, and functional performance of roads.