## 5 Conclusions  
Merging is considered one of the main factors that cause traffic congestion on freeways. Makkah Road, the study area for this research, also has operational problems with a reduction in speed to less than 40 km/h because of consecutive on and off-ramps. Therefore, this research evaluated the applicability of implementing RM in one on-ramp. For this base scenario (current situation), four additional main scenarios with eight sub-scenarios under scenario three were chosen and compared using a microsimulation model, VISSIM. To determine the best scenario, or to recommend that a certain scenario is better than the base scenario, the four criteria below were applied:  
1. The scenario must work for all current volume on the on-ramp in the study area;
2. In the scenario, the average queue length of the on-ramp must not exceed the maximum storage length (310 m);
3. The average queue length on the freeway must be less than the current situation;
4. The average speed must be higher than the current one. However, considering the time value of the local drivers, total benefits gained from the changes in traffic volume and average speed (travel time) must be compared alongside the total costs for \begin{table}
\begin{tabular}{c c c c c c c c c c c c} \hline \hline \multirow{2}{*}{**Ave. Queue (m)**} & \multirow{2}{*}{**BS**} & \multirow{2}{*}{**AS-1**} & \multirow{2}{*}{**AS-2**} & \multicolumn{8}{c}{**AS-3**} & \multirow{2}{*}{**AS-4**} \\ \cline{5-12}  & & & **2V2R** & & & & & & & & & \\ \hline \multirow{2}{*}{On-ramp} & \multirow{2}{*}{287.6} & 1000 & 0.0 & 491.7 & 422.2 & 485.7 & 175.8 & 471.7 & 164.3 & 273.8 & 468.3 & 290.6 \\  & & N/A & (\(-10\%\)) & (71.0\%) & (46.8\%) & (68.9\%) & (\(-38.9\%\)) & (64.0\%) & (\(-42.9\%\)) & (\(-4.8\%\)) & (62.8\%) & (1.0\%) \\ \hline \multirow{2}{*}{Freeway} & \multirow{2}{*}{236.2} & 0.0 & 1.5 & 9.4 & 85.6 & 19.4 & 41.0 & 30.9 & 240.7 & 132.7 & 62.5 & 50.1 \\  & & (\(-100\%\)) & (\(-99.4\%\)) & (\(-96.0\%\)) & (\(-63.8\%\)) & (\(-91.8\%\)) & (\(-82.6\%\)) & (\(-86.9\%\)) & (19.9\%) & (\(-438.8\%\)) & (\(-73.5\%\)) & (\(-78.8\%\)) \\ \hline \hline \end{tabular}
\end{table} 
Table 6: Average queue length results of each scenario. \begin{table}
\begin{tabular}{c c c c c c c c c c c c} \hline \hline \multirow{2}{*}{**Ave. Speed (km/h)**} & \multirow{2}{*}{**BS**} & \multirow{2}{*}{**AS-1**} & \multirow{2}{*}{**AS-2**} & \multicolumn{8}{c}{**AS-3**} & \multirow{2}{*}{**AS-4**} \\ \cline{5-12}  & & & **2V2R** & & & & & & & & & \\ \hline \multirow{2}{*}{Freeway} & \multirow{2}{*}{36.7} & 69.9 & 66.7 & 63.3 & 49.7 & 60.5 & 45.0 & 56.3 & 42.1 & 43.3 & 53.1 & 49.4 \\  & & (90.4) & (81.7) & (72.3\%) & (35.2\%) & (64.8\%) & (22.5\%) & (53.1\%) & (14.6\%) & (17.7) & (44.5\%) & (34.6\%) \\ \hline \hline \end{tabular}
\end{table} 
Table 5: Average speed results of each scenario. Figure 6: Inputs for the queue counters in VISSIM. the installation, operation, and maintenance of the RM on the site. Through this economic analysis, the agreeable criteria on the volume and average speed will be determined. From the scenario analysis using the microsimulation model, only four scenarios satisfied the first two criteria. They are 4V3R, 5V3R, 5V4R sub-scenarios of the third main scenario (fixed time RM operation, AS-3), and the fourth main scenario (traffic responsive RM operation using ALINEA model, AS-4). Three out of the four (AS-3-4V3R, AS-3-5V4R and AS-4) were better than the current situation (base scenario) even with the third and fourth evaluation criteria. However, when compared to the base scenario, from the viewpoint of average queue length on the freeway, the 4V3R scenario showed the biggest drop (236.2 m\(\rightarrow\)41.0 m) among the three. From the average speed point of view, the AS-4 had the greatest improvement (36.7 km/h\(\rightarrow\)49.4 km/h). However, the 4V3R scenario also indicated an improved result (36.7 km/h\(\rightarrow\)45.0 km/h). Based on the goal and objectives of this study, a summary of the research results is listed as follows:  
1.