# Path Planning Strategy for Implementing a Machine Control System in Grader Operations
## 5 Conclusions  
The construction industry is facing significant challenges in workforce availability, productivity, safety, and quality. To address these issues, efforts are being made to apply smart construction technologies. Similar to CAD (computer-aided design) and CAM (computer-aided manufacturing) systems in the manufacturing industry, the construction sector requires a foundation to establish a system in which earthwork BIM and construction equipment are seamlessly integrated and can operate automatically without human intervention. This study was conducted as part of the building of this foundation and presents the fundamental technology for realizing a grader that utilizes the MC system, one of the smart construction technologies. Its relevance to smart construction is enhanced by developing an algorithm that dynamically generates a working path for the grader, incorporating work heuristics based on initial site data and the earthwork BIM model. In previous studies, work paths were generated using grid cells, which typically guided construction equipment in straight lines. However, for complex models, this approach led to numerous blind spots where work could not be performed, and to avoid leaving the work zone, many additional work lines were required, increasing the number of iterations. In contrast, this study generated paths by directly considering the road's shape, rather than relying on grid cells, enabling more efficient path generation even for roads with complex geometries. Additionally, the concepts of redundancy and effective width were introduced to minimize the number of work lines along the road's shape, allowing for smoother movement of the construction equipment and ensuring continuous workflow. A safety line concept was also implemented to maintain a safe distance between the equipment and the work boundary, ensuring the equipment could operate safely within the designated work area. A case study conducted at real road construction sites in South Korea demonstrated that the algorithm can manage complex terrain conditions, including varying road widths and curves. This flexibility is crucial for ensuring optimal grader performance in a variety of working environments. Moreover, the algorithm's ability to minimize data transmission while maintaining high accuracy addresses the issue of data overload and communication delays in construction automation systems. One of the key innovations of this research is the incorporation of experienced grader operators' empirical knowledge into the algorithm, which reflects the human decision-making process accumulated on job sites. This enables the generation of paths that meet technical requirements while considering actual field work patterns. This human-machine collaboration marks a significant step forward in developing semi-autonomous construction systems. Figure 16: Motor grader work results. The findings of this study are not limited to graders and the algorithmic framework can be applied to other types of construction equipment, broadening the potential for MC technology in construction. However, this study has several limitations. The proposed algorithm relies on initial site data and static information, limiting its ability to adapt to real-time changes or unexpected site conditions. As a result, the path generation algorithm can only be effectively applied in controlled environments. Additionally, the path generation and testing were conducted over a relatively short distance and involved only a single grader, necessitating further testing on longer sections. The study also did not account for the collaboration of multiple machines, which is common in real-world construction sites. Future research should address path optimization and task scheduling for multiple machines working simultaneously. Finally, this research focused exclusively on path generation for grading tasks, and blade control was not considered within the scope of this study.