# Using Machine Learning to Predict Pedestrian Compliance at Crosswalks in Jordan
## 3 Materials and Methods  
Data were collected from nine signalized intersections located in three major governorates of Jordan: Amman (the capital), Irbid, and Zarqa. The selected cities for this study were identified based on their dense population and high vehicle registration rates compared to other cities in Jordan. The locations are situated in areas with significant pedestrian activity and traffic flow. Each selected intersection is a typical four-leg configuration with fixed cycle lengths and two-way traffic. These intersections have three lanes per direction and a speed limit of 60 km/h, allowing for bidirectional pedestrian flow. The major crosswalk exhibiting the highest pedestrian traffic was selected from each intersection for pedestrian crossing behavior \"detailed\" analysis. Table 1 shows the characteristics of selected sites. The video camera locations were adept at detecting pedestrians as they entered and exited the crosswalk, precisely capturing their movements (Figure 1). Data on pedestrian crossing behaviors were collected during working days, from Sunday to Thursday, to maintain consistency and avoid the varied conditions typical of weekends and peak pedestrian flows. The minimum sample size was analyzed to ensure adequate population representation. A total of 2437 pedestrians were identified and recorded from the video footage. The video recordings provided comprehensive data on various aspects of pedestrian crossing behavior. Table 2 presents the variables extracted from the videos, along with their respective descriptions. \begin{table}
\begin{tabular}{c c c c c c c c c c c} \hline \hline \multirow{2}{*}{**Intersection**} & \multirow{2}{*}{
\begin{tabular}{c} **Crosswalk** \\ **Length (m)** \\ \end{tabular} } & \multicolumn{2}{c}{**Signal Time (Min.Sec)**} & \multicolumn{2}{c}{**Signal Traffic**} & \multicolumn{2}{c}{**Presence of**} & \multicolumn{2}{c}{**Median**} & \multicolumn{2}{c}{**No. of**} & \multirow{2}{*}{**Coordinates**} \\ \cline{2-2} \cline{5-10}  & & **R** & **Y** & **G** & & & & & & & \\ \hline Int.1 & 15 & 1:07 & 0.02 & 0.29 & 1:37 & Yes & 2.4 & 499 & \(32.554758^{\circ}\) \\  & & & & & & & & & & \\ \hline Int.2 & 24.17 & 1:37 & 0.03 & 0.30 & 1.7 & Yes & 3.7 & 208 & \(32.551354^{\circ}\) \\  & & & & & & & & & & \\ \hline Int.3 & 24 & 1:17 & 0.03 & 0.30 & 1:46 & Yes & 2 & \(202\) & \(32.534805^{\circ}\) \\  & & & & & & & & & & \\ \hline Int.4 & 23.4 & 1:45 & 0.03 & 0.32 & 2:08 & Yes & 2 & \(301\) & \(32.53167^{\circ}\) \\  & & & & & & & & & & \\ \hline Int.5 & 19.3 & 1:22 & 0.02 & 0.26 & 1:51 & Yes & 2.5 & 422 & \(32.556741^{\circ}\) \\  & & & & & & & & & & \\ \hline Int.6 & 24 & 3.01 & 0.03 & 0.49 & 3:45 & Yes & 4.5 & 204 & \(31.956671^{\circ}\) \\  & & & & & & & & & & \\ \hline Int.7 & 21 & 1:42 & 0.03 & 0.38 & 2:24 & Yes & 2.5 & 308 & \(31.96512^{\circ}\) \\  & & & & & & & & & & \\ \hline Int.8 & 34.4 & 1:45 & 0.03 & 0.28 & 2:17 & Yes & 3 & 200 & \(32.086010^{\circ}\) \\  & & & & & & & & & & \\ \hline Int.9 & 28.2 & 1:41 & 0.02 & 0.28 & 2:17 & Yes & 2 & \(200\) & \(32.088627^{\circ}\) \\  & & & & & & & & & & \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Characteristics of selected intersections.