## 4 Experimental Validation
### Improved BIT* Algorithm with Adaptive Parameter Optimization for Optimal Path Planning
#### 4.1.2 Improved BIT* Algorithm
In addition, the effectiveness of the energy equation in suppressing turning is also effectively validated, with a significant reduction in turning cost. This strategy effectively reduces the turning time and energy consumption of the Unmanned Surface Vehicle (USV), not only enabling \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Algorithm** & **Optimal Path Length** & **Number of Turns** & **Turning Cost** \\ \hline A* & 600 & 447 & 8586.00 \\ RRT* & 507.17 & 47 & 473.62 \\ Original BIT* & 460.23 & 26 & 75.43 \\ Enhanced BIT* & 430.75 & 24 & 40.95 \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Comparative results of enhanced BIT algorithm and other path planning algorithms *. \begin{table}
\begin{tabular}{c c c} \hline \hline
**Parameter Name** & **Description** & **Value** \\ \hline Start Point & Initial position & (0,0) \\ Goal Point & Target position & (299,299) \\ Number of Samples & Number of new sample points per iteration & 100 \\ Gaussian Std & Parameter controlling the Gaussian sampling distribution & 10 \\ Initial Radius & Initial search radius & 150 \\ Turning Weight & Weighting coefficient for turning cost & 0.5 \\ Tangent Point Distance & Distance to tangent point for arc path calculation & 3 \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Parameter settings for the improved BIT* algorithm. Figure 8: Detailed path view of A*. Figure 7: Detailed view of enhanced BIT* results. it to successfully avoid obstacles but also achieving smoother and more efficient path planning. This fully demonstrates that by incorporating the energy equation, the USV can utilize energy more efficiently, reduce unnecessary energy consumption, and maintain path continuity and stability. To further enhance path planning efficiency, this research also employed multi-threading technology to accelerate the computation process. Multi-threading technology, by processing multiple tasks in parallel, completes the path planning process in a shorter time, greatly improving computational speed. This method not only enhances the response speed of the USV but also provides strong support for real-time path planning and dynamic environment adaptation. Comprehensive experimental results demonstrate that the enhanced adaptive parameter optimization BIT* algorithm outperforms the original BIT* algorithm, RRT* algorithm, and A* algorithm in terms of optimal path length, path smoothness, and computational efficiency. This validates the effectiveness and superiority of the improvement strategies presented in this paper, providing a more reliable solution for efficient path planning of USVs in complex environments. The results in Figure 9 indicate that the path planning time decreases with the increase in the number of threads across different map sizes. This suggests that increasing the thread count can enhance computational throughput, and particularly for larger maps, more threads may be required to support more efficient path planning. However, while multi-threading technology is more efficient than the traditional BIT* algorithm, the communication and synchronization costs between threads also increase with the thread count. These additional overheads can negatively impact overall efficiency because thread management, data synchronization, and communication become more complex and time-consuming as the number of threads increases. Furthermore, hardware limitations are also a significant factor affecting multi-threading efficiency. For example, if the processor's core count is limited or the memory bandwidth is insufficient to support a large number of threads working in parallel, the advantages of multi-threading may not be fully realized. Therefore, when designing multi-threaded path planning algorithms, it is necessary to comprehensively consider the number of threads, hardware resources, and thread management overhead to achieve the optimal performance balance. Generally, multi-threading technology provides an effective means to improve the efficiency of path planning.