# Path Planning Based on Obstacle-Dependent Gaussian Model Predictive Control for Autonomous Driving
## 4 Experiment
### Experimental Results
#### 4.3.3 Experiment Scenario 3  
Scenario 3 is an experiment in a complex environment. This experiment demonstrates the test results of an Ego mobile robot path planning operation in a situation with two obstacle mobile robots. It is divided into two experiments. The first experiment is conducted with both obstacles stopped. The second experiment consists of dynamic obstacles and static obstacles. The experiment was conducted 10 times. (1) Two Static Obstacles  
The two obstacles are at \(p_{{}_{X}}=220\) and \(p_{{}_{Y}}=383\) and at \(p_{{}_{X}}=530\) and \(p_{{}_{Y}}=335\). The Ego mobile robot moves at a speed of 2.5 m/s. The experimental results are displayed in Figure 25.  
Table 10 presents the acceleration in Figures 26 using comfort indicators. The results demonstrate that the ODG MPC works more comfortably than the PF and PF MPC algorithms. Regarding the distance to the obstacle, Figures 27 and 28, and Table 11, demonstrate that the ODG MPC works more stably around obstacles than the other algorithms. At the first obstacle, the obstacle avoidance operation operates 26.6% farther than the PF algorithm and 8.42% farther than the PF MPC algorithm. The results indicate that the second obstacle is operated by avoiding obstacles 11.9% farther than the PF algorithm and 26.7% farther than the PF MPC algorithm. \begin{table}
\begin{tabular}{c c c c} \hline \multirow{2}{*}{**Experiment**} & \multicolumn{3}{c}{**Algorithm**} \\ \cline{2-4}  & **ODG MPC (cm)** & **PF (cm)** & **PF MPC (cm)** \\ \hline No. 1 & 4.973 & 1.613 & 1.748 \\ \hline No. 2 & 4.138 & 3.907 & 2.435 \\ \hline No. 3 & 4.264  
Figure 26: Results of the acceleration from Scenario 3 for two static obstacles. \begin{table}
\begin{tabular}{c c c c} \hline
**Comfort Level (Score)** & **ODGMPC** & **PF** & **PFMPC** \\ \hline Comfortable (10) & 10.85\% & 8.06\% & 9.04\% \\ \hline A little uncomfortable (8) & 11.04\% & 6.47\% & 7.61\% \\ \hline Fairly uncomfortable (6) & 11.95\% & 9.81\% & 8.58\% \\ \hline Uncomfortable (4) & 23.57\% & 16.28\% & 12.76\% \\ \hline Very uncomfortable (2) & 26.81\% & 16.07\% & 22.56\% \\ \hline Extremely uncomfortable (0) & 15.78\% & 43.31\% & 39.46\% \\ \hline Average Comfort Level Score & **4.16** & 2.88 & 2.99 \\ \hline \end{tabular}
\end{table} 
Table 10: Average result scores for 10 experiments with two static obstacles. Figure 25: Results of the path from Scenario 3 for two static obstacles. Figure 28: Results of the obstacle distance from Scenario 3 for static Obstacle 2. \begin{table}
\begin{tabular}{c c c c c c c} \hline
**Distance (cm)** & \multicolumn{3}{c}{**Obstacle 1 (\(S_{1}\))**} & \multicolumn{3}{c}{**Obstacle 2 (\(S_{2}\))**} \\ \hline
**Experiment** & **ODG MPC** & **PF** & **PF MPC** & **ODG MPC** & **PF** & **PF MPC** \\ \hline No. 1 & 4.391 & 2.989 & 2.940 & 4.986 & 3.924 & 3.790 \\ \hline No. 2 & 4.403 & 3.265 & 3.297 & 4.672 & 4.573 & 2.076 \\ \hline No. 3 & 3.998 & 3.587 & 3.030 & 5.231 & 4.325 & 4.249 \\ \hline No. 4 & 3.536 & 3.050 & 4.329 & 4.839 & 4.229 & 4.407 \\ \hline No. 5 & 4.082 & 3.223 & 3.399 & 4.932 & 4.263 & 3.631 \\ \hline No. 6 & 3.682 & 3.512 & 4.472 & 5.022 & 4.132 & 4.334 \\ \hline No. 7 & 3.670 & 2.907 & 4.003 & 4.316 & 4.430 & 4.072 \\ \hline No. 8 & 4.940 & 3.013 & 4.522 & 5.334 & 4.612 & 4.118 \\ \hline No. 9 & 3.895 & 3.360 & 3.395 & 4.677 & 4.678 & 3.775 \\ \hline No. 10 & 4.047 & 3.198 & 4.098 & 4.837 & 4.463 & 4.07 \\ \hline Average Value & **4.064** & 3.210 & 3.749 & **4.885** & 4.363 & 3.853 \\ \hline \end{tabular}
\end{table} 
Table 11: Results of the minimum distance from Scenario 3 for two static obstacles. Figure 27: Results of the obstacle distance from Scenario 3 for static Obstacle 1. (2) One Dynamic Obstacle and One Static Obstacle  
The Ego mobile robot moves at a speed of 2.5 m/s, and the first obstacle moves at a speed of 1.5 m/s at \(p_{X}=220\) and \(p_{Y}=383\). The second hurdle lies at \(p_{X}=530\) and \(p_{Y}=335\).