## 4 Results and Discussions
### Hotspots Analysis Results
\begin{table}
\begin{tabular}{p{113.8 pt} p{113.8 pt} p{113.8 pt}} \hline
**The Variables** & **Definition** & **Indicator** & **Definition** \\ \hline Horizontal Alignment & It is described as consisting of a series of straight lines, and circular curves & Radius of curve (R) & The radius of the circle determines the curve’s “sharpness” or “flatness” \\ \hline \multirow{4}{*}{\begin{tabular}{} \end{tabular} } & \multirow{2}{*}{\begin{tabular}{} \end{tabular} } & Length of curve (L) & The distance between the point of curve (PC) and the point of tangent \\ \cline{2-2}  & & Intersection angle (I) & The tangents’ direction change, equivalent to the central angle of the curve \\ \cline{2-2}  & & & \\ \cline{2-2}  & & & \\ \cline{2-2}  & & & \\ \cline{2-2}  & & & \\ \cline{2-2}  & & & \\ \hline \multirow{4}{*}{\begin{tabular}{} \end{tabular} } & \multirow{4}{*}{\begin{tabular}{} \end{tabular} } & Length of vertical curve & The distance between beginning of vertical curve (BVC) to end of vertical curve (EVC) \\ \cline{2-2}  & & K-value & The vertical curve’s length in terms of A’s percentage change \\ \cline{2-2}  & & & \\ \cline{2-2}  & & & \\ \cline{2-2}  & & & \\ \cline{2-2}  & & & \\ \cline{2-2}  & & & \\ \cline{2-2}  & & & \\ \cline{2-2}  & & & \\ \cline{2-2}  & & & \\ \cline{2-2}  & & & \\ \cline{2-2}  & & & \\ \hline \multirow{4}{*}{\begin{tabular}{} \end{tabular} } & \multirow{4}{*}{\begin{tabular}{} \end{tabular} } & The smallest distance exposed to a driver’s view on a two-way road that enables him to safely pass another vehicle ahead while avoiding traffic coming from the opposite direction is known as overtaking or passing sight distance \\ \cline{2-2}  & & & \\ \cline{2-2}  & & & \\ \cline{2-2}  & & & \\ \cline{2-2}  & & & \\ \hline \multirow{4}{*}{\begin{tabular}{} \end{tabular} } & \multirow{4}{*}{\begin{tabular}{} \end{tabular} } & \multirow{4}{*}{\begin{tabular}{} \end{tabular} } & The number of intersections on the road section \\ \cline{2-2}  & & & \\ \cline{2-2}  & & & \\ \cline{2-2}  & & & \\ \cline{2-2}  & & & \\ \hline \multirow{4}{*}{\begin{tabular}{} \end{tabular} } & \multirow{4}{*}{\begin{tabular}{} \end{tabular} } & \multirow{4}{*}{\begin{tabular}{} \end{tabular} } & The number of injuries that usually result in death, either directly or as a result of complications, within one month of the injury’s occurrence (secondary data) \\ \cline{2-2}  & & & \\ \cline{2-2}  & & & \\ \cline{2-2}  & & & \\ \cline{2-2}  & & & \\ \cline{2-2}  & & & \\ \cline{2-2}  & & & \\ \hline \multirow{4}{*}{\begin{tabular}{} \end{tabular} } & \multirow{4}{*}{\
\begin{tabular}{} \end{tabular} } & \multirow{4}{*}{
\begin{tabular}{} \end{tabular} } & It is calculated by taking exposure data such as traffic volume and road length into account \\ \cline{2-2}  & & & \\ \cline{2-2}  & & & \\ \cline{2-2}  & Severity index & & & \\ \cline{2-2}  & & & & \\ \cline{2-2}  & & & & \\ \hline \end{tabular}
\end{table} 
Table 1: Definition of the latent variables and the indicators. Figure 6 shows a spatial map of road accident hotspots created with Getis Ord \(G_{i}\). The analysis identifies 80 accident hotspots along the Jordan Desert Highway. The map identifies the points on the map that are statistically significant for causing accidents as hotspots with a confidence level of 99% (\(G_{i}\)-bin = 3), 95% (\(G_{i}\)-bin = 2), and 90% (\(G_{i}\)-bin = 1). \begin{table}
\begin{tabular}{l l l l l l l} \hline
**Point Number** & **Severity Index** & **Level Ranges** & **Z-Score** & \(p\)**-Value** & \(G_{i}\)**-Bin** & **Location** \\ \hline
1 & 76 & High & 5.550 & 0.000 & 3 & 36\({}^{\circ}\)316.162\({}^{\prime\prime}\) E 31\(