### Simulation Results  
#### 4.5.1 Uniform Traffic Settings  
Figure 10 shows the effects of using various method combinations along the two routes, with route guidance the primary object. When no method was used, the EV encountered congestion at multiple locations. When the route guidance method was used, the EV was able to avoid traffic jams, thereby \begin{table}
\begin{tabular}{c c c c c c} \hline \hline  & \multicolumn{4}{c}{**Simulation set \#1**} \\ \hline  & Item 1 & Item 2 & Item 3 & Item 4 & Item 5 \\ RG & & V & V & V & V \\ TLP & & & & V & V \\ PC & & & V & & V \\ \hline  & \multicolumn{4}{c}{**Simulation set \#2**} \\ \hline  & Item 1 & Item 2 & Item 3 & Item 4 & Item 5 \\ RG & & & V & & V \\ TLP & & V & V & V & V \\ PC & & & & V & V \\ \hline  & \multicolumn{4}{c}{**Simulation set \#3**} \\ \hline  & Item 1 & Item 2 & Item 3 & Item 4 & Item 5 \\ RG & & & V & & V \\ TLP & & & & V & V \\ PC & & V & V & V & V \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Simulation design. reducing travel time. Next, the path clearing method included EV communication with other vehicles on the same road, allowing those vehicles to clear a lane for the EV. Time reduction when the path clearing method was included was small for both the short and long routes, since any low-congestion path chosen by the route guidance method diminished the path clearing method's effectiveness. The reduction in time resulting from traffic light preemption was more obvious because it almost completely eliminated waiting at intersections. Even when the route guidance method found a congestion-free or congestion-reduced path, traffic light preemption still made a significant contribution to time reduction. Figure 11 shows the effects of using various method combinations along the same two routes with traffic light preemption as the primary object. As shown, using this method by itself greatly reduced travel time, but adding other methods to it only contributed minor savings, with route guidance more effective than path clearing. This is because traffic light preemption reduced the possibilities of the EV and vehicles preceding it being blocked at intersections. As a result, path clearing nearly had no influence on reducing travel time, particularly for low vehicle densities. For high vehicle densities (e.g., 2000 vehicles), the influence is slightly more observable since path clearing allowed vehicles to clear a lane for the EV to  
Figure 11: Travel times of simulation set #2 for the (**A**) short route and (**B**) long route. Figure 10: Travel times of simulation set #1 for the (**A**) short route and (**B**) long route. quickly pass congested areas. Compared with path clearing, routing guidance could find a path with the shortest travel time, and thus made more contribution to time reduction. Figure 12 shows the effects of using various method combinations along the two routes with path clearing as the primary object. As shown, the EV did not save much time when this method was used by itself. As a possible explanation, two representative simulation results selected from the third simulation set are shown in Figure 13. The EV time-distance relationship in Figure 13A was observed in most simulation runs due to small differences resulting from vehicles pulling over to the side of the road to allow the EV to pass. However, advantages were erased when the EV encountered a traffic light. In a small number of cases the EV was able to cross the intersection quickly when vehicles yielded in time (Figure 13B). In summary, the traffic light preemption function was the most effective method, followed by the route guidance and path clearing functions. Travel times increased in all cases where the number of vehicles increased. The system struggled to plan better routes during peak periods and in traffic jams. However, when travel distance increased, the traffic light preemption function performed well because the EV was able to travel at full speed for most of the trip.