# Reducing Safety Risks in Construction Tower Crane Operations: A Dynamic Path Planning Model
## 4 Discussion
The increase in path lengths observed with the TC-DWA method can be attributed to its focus on safety, as the algorithm actively adjusts its path in response to the detection of nearby workers. This aspect of TC-DWA enhances operational safety by prioritizing the avoidance of potential hazards, even if it results in a longer travel distance. In practical applications, the safety of workers on-site is paramount, and the trade-off between path length and safety becomes a critical consideration. The ability of TC-DWA to maintain a safety buffer around moving workers while still achieving successful load delivery positions it as a superior choice for tower crane operations in dynamic environments. Furthermore, the experiments conducted illustrate the dynamic capabilities of the TC-DWA algorithm in real-time scenarios. The algorithm's ability to adapt to unexpected changes in the environment--such as the sudden movement of workers--demonstrates its practical applicability and robustness. The simulations performed in this study underscore the importance of integrating real-time data from computer vision systems into the path planning process, as this can significantly enhance the algorithm's situational awareness and responsiveness. Through the safety risk monitoring of 20 segments of tower crane operation videos, which range from 1 to 3 min in length and have a frame rate of 24 frames per second (FPS), we observed an average of 286.6 safety hazard warnings per complete crane operation process. Considering the video frame rate, this equates to an average of 11.9 hazardous situations per video, posing safety risks to 3-4 workers. These findings underscore the prevalence of safety hazards in crane operations and the necessity for real-time monitoring systems. In situations where hazardous conditions are detected, the TC-DWA algorithm provides corresponding directional movement suggestions, effectively reducing the risks associated with tower crane operations. The algorithm's ability to dynamically adjust the crane's path in response to detected risks is a significant advancement in ensuring the safety of workers on construction sites. The integration of YOLOv8 for risk evaluation and the TC-DWA algorithm for path planning has demonstrated a synergistic effect in enhancing the safety of tower crane operations. The system not only detects potential hazards but also \begin{table}
\begin{tabular}{c c c c c} \hline \hline \multirow{2}{*}{**Method**} & \multirow{2}{*}{**Scenario**} & \multirow{2}{*}{**Metric**} & \multicolumn{2}{c}{**Path Length**} & \multicolumn{2}{c}{**Number of Obstacle**} \\  & & & **(m)** & **Avoidance Failures** \\ \hline \multirow{4}{*}{TC-DWA} & E1 & Mean & 71.22 & **0** \\  & E1 & SD & 16.51 & **0** \\  & E2 & Mean & 42.49 & **0** \\  & E2 & SD & 11.06 & **0** \\ \hline \multirow{4}{*}{APF} & E1 & Mean & **49.32** & 1.38 \\  & E1 & SD & **0.23** & 1.52 \\  & E2 & Mean & **31.19** & 1.62 \\  & E2 & SD & **0.44** & 1.47 \\ \hline \multirow{4}{*}{RRT} & E1 & Mean & 67.05 & 33.76 \\  & E1 & SD & 3.58 & 26.94 \\ \cline{1-1}  & E2 & Mean & 39.39 & 77.27 \\ \cline{1-1}  & E2 & SD & 1.70 & 20.26 \\ \hline \hline \end{tabular}
\end{table} 
Table 5: Experimental results obtained from TC-DWA and other comparative algorithms. actively participates in mitigating these risks by providing actionable guidance to operators. The study's results highlight the importance of integrating advanced computer vision and path planning algorithms into tower crane monitoring systems. The combination of real-time video analysis and dynamic path planning offers a new solution to improve safety standards in construction environments.