## 3 Method
### Research Procedure  
This study concentrated on motorcycle crashes involving young adults (under 30 years of age) and compared crashes on local roads in urban and rural areas (specified using the municipal area, which includes the central business district of each district and some densely populated sub-districts). The data analysis procedures are illustrated in Figure 3. The process began by filtering data from all road crash types down to local roads. Next, crashes involving motorcycles and riders under 30 years of age were selected. To separate urban and rural areas, a geospatial information system was employed to aid in selection based on the principle of location-based choices. In cases where crashes overlapped with municipalities (within a radius of 1 km), such incidents were classified as urban area crashes. The results of this identification are displayed in Figure 4.  
Upon obtaining the data, it was converted into code by setting INJURY as 1 for a fatal motorcycle crash (including fatalities at the scene and after hospitalization) and 0 for other injuries (serious injuries and minor injuries) [26]. All other variables were coded as binary. For example, for gender, 1 represents male and 0 represents female. A description of the variables can be found in Table 2.  
Figure 3: Research procedure. \(\overline{\mathbf{\mathsf{T}}}\) Indicates the data filtering.  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline \multirow{2}{*}{**Variable**} & \multirow{2}{*}{**Description**} & \multicolumn{2}{c}{**Urban Roadways**} & \multicolumn{2}{c}{**Rural Roadways**} \\ \cline{2-5}  & **Mean** & **S.D.** & **Mean** & **S.D.** & **Mean** & **S.D.** \\ \hline INJURY & 1 if fatal injury, 0 otherwise & 0.170 & 0.376 & 0.126 & 0.331 \\ \hline GENDER & \(1\) if male young adult motorcyclist (yam), 0 if female yam & 0.716 & 0.451 & 0.720 & 0.449 \\ \hline FOREIGN & 1 if foreigner, 0 if Thai & 0.027 & 0.162 & 0.025 & 0.155 \\ \hline AT\_FAULT & 1 if is at-fault, 0 otherwise & 0.752 & 0.432 & 0.796 & 0.403 \\ \hline LOCAL\_ADDRESS & 1 if local address same crash scenes, 0 otherwise & 0.621 & 0.485 & 0.727 & 0.446 \\ \hline HELMET & 1 if wearing helmet, 0 otherwise & 0.502 & 0.500 & 0.412 & 0.492 \\ \hline DRUNK & 1 if under influence of alcohol, 0 otherwise & 0.094 & 0.292 & 0.133 & 0.339 \\ \hline UNILCENSE & 1 if unlicensed after, 0 license rider & 0.045 & 0.207 & 0.049 & 0.215 \\ \hline EXCES\_SPEED\_LIMT & 1 if exceeding the speed limit, 0 otherwise & 0.266 & 0.442 & 0.242 & 0.428 \\ \hline VIOLATION & 1 if involved traffic sign/signal/wrong direction violation, 0 otherwise & 0.013 & 0.115 & 0.006 & 0.078 \\ \hline ILLEGAL\_OVERTAKING & 1 if illegal/improper overtaking, 0 otherwise & 0.009 & 0.094 & 0.006 & 0.078 \\ \hline MOBIE\_USE & 1 if using mobile phone, 0 otherwise & 0.003 & 0.050 & 0.006 & 0.077 \\ \hline ASLEEP & 1 if fallen asleep/fatigue, 0 otherwise & 0.002 & 0.048 & 0.003 & 0.059 \\ \hline CUTTING\_FRONT & 1 if hitting vehicles cutting in front; 0 otherwise & 0.169 & 0.375 & 0.131 & 0.338 \\ \hline CURVE & 1 if horizontal curve, 0 straight road & 0.089 & 0.285 & 0.163 & 0.370 \\ \hline \hline \end{tabular}
\end{table}
Table 2: Variable description.  
Figure 4: Crash Locations (**a**) young rider crashes on local urban roads, (**b**) young rider crashes on local rural roads.