# Towards Explainable Pedestrian Behavior Prediction:
## 5 Experimental Results and Discussion
### Experiment 4--Features Ablation  
This experiment aimed to _explore the relationship between different pedestrian features and their impact on prediction performance._ It built upon the best performing configurations from Experiment 1, specifically **J14K** and **P80K**. To assess the significance of each feature, the input data for the fuzzy rule mining process was systematically modified by removing one feature at a time from **J14K** and **P80K**. This approach allowed us to evaluate how the absence of each feature influenced the predictor's accuracy. Table 6 presents the results of the different configurations tested:  
According to the results, the most influential feature for JAAD was **Proximity**, while for PIE, the most critical features were **Distance** and **Action**. This conclusion is based on \begin{table}
\begin{tabular}{l c c c c c c c c} \hline \hline \multirow{2}{*}{**Configuration**} & \multirow{2}{*}{**Rules**} & \multicolumn{2}{c}{\(JAAD_{all}\)} & \multicolumn{2}{c}{\(JAAD_{beh}\)} & \multicolumn{2}{c}{\(PIE_{all}\)} & \multicolumn{2}{c}{\(PIE_{beh}\)} \\ \cline{3-10}  & & **A** & **F** & **A** & **F** & **A** & **F** & **A** & **F** \\ \hline J14K & 58 & 0.72 & 0.75 & 0.72 & 0.76 & 0.73 & 0.50 & 0.73 & 0.52 \\ J14K-NotDistance & 56 & 0.69 & 0.73 & 0.69 & 0.74 & 0.71 & 0.45 & 0.72 & 0.49 \\ J14K-NotProximity & 45 & 0.48 & 0.34 & 0.46 & 0.35 & 0.63 & 0.32 & 0.63 & 0.33 \\ J14K-NotAction & 50 & 0.65 & 0.69 & 0.46 & 0.70 & 0.68 & 0.48 & 0.67 & 0.51 \\ J14K-NotAttention & **54** & **0.74** & **0.77** & **0.73** & **0.77** & 0.73 & 0.49 & 0.73 & 0.52 \\ J14K-NotOrientation & 46 & 0.71 & 0.74 & 0.71 & 0.75 & 0.75 & 0.51 & 0.75 & 0.54 \\ J14K-NotZebraCross & 51 & 0.72 & 0.75 & 0.70 & 0.76 & 0.76 & 0.51 & 0.77 & 0.54 \\ \hline P80K & 36 & 0.58 & 0.54 & 0.56 & 0.54 & 0.54 & 0.54 & 0.81 & 0.57 \\ P80K-NotDistance & 36 & 0.63 & 0.57 & 0.61 & 0.57 & 0.79 & 0.45 & 0.78 & 0.45 \\ P80K-NotProximity & 31 & 0.55 & 0.49 & 0.53 & 0.49 & 0.82 & 0.55 & 0.82 & 0.57 \\ P80K-NotAction & 17 & 0.51 & 0.38 & 0.50 & 0.38 & 0.82 & 0.51 & 0.82 & 0.53 \\ P80K-NotAttention & **25** & 0.55 & 0.50 & 0.54 & 0.51 & **0.83** & **0.56** & **0.83** & **0.59** \\ P80K-NotOrientation & 15 & 0.54 & 0.45 & 0.52 & 0.46 & 0.83 & **0.56** & 0.83 & 0.57 \\ P80K-NotZebraCross & 22 & 0.55 & 0.52 & 0.54 & 0.53 & 0.82 & 0.55 & 0.82 & 0.59 \\ \hline \hline \end{tabular}
\end{table} 
Table 6: Experiment 4—features ablation results. Accuracy (A) and F1 score. Bold values indicate the best performance for each evaluation metric across the different configurations. \begin{table}
\begin{tabular}{l c c c c c c c c} \hline \hline \multirow{2}{*}{**Configuration**} & \multirow{2}{*}{**Rules**} & \multicolumn{2}{c}{\(JAAD_{all}\)} & \multicolumn{2}{c}{\(JAAD_{beh}\)} & \multicolumn{2}{c}{\(PIE_{all}\)} & \multicolumn{2}{c}{\(PIE_{beh}\)} \\ \cline{3-10}  & & **A** & **F** & **A** & **F** & **A** & **F** & **A** & **F** \\ \hline J8K & 62 & 0.72 & 0.75 & 0.72 & 0.76 & 0.73 & 0.50 & 0.73 & 0.52 \\ J8 KR1 & 66 & 0.63 & 0.68 & 0.63 & 0.69 & 0.70 & 0.39 & 0.65 & 0.40 \\ J8 KR2 & 80 & 0.73 & 0.76 & 0.73 &  
the drop in prediction performance observed when these features were removed from the input data during the fuzzy rule learning process (i.e., the **J14K-NotProximity** and **P80K-NotDistance** configurations). The significant decline in accuracy highlights the essential role these features play in pedestrian behavior prediction. Additionally, during cross-testing, it was observed that Orientation and the Zebra crossing label from JAAD and the Distance from PIE had a negative impact on the results. This suggests that these features are not consistently represented across datasets. Variability in how these features are defined and labeled in different datasets can introduce inconsistencies, reducing the predictor's ability to generalize across different environments. To further investigate the relationship between features and pedestrian behavior, a correlation analysis was conducted using data from the **J14K** and **P80K** configurations.