## 3 Results  
### Intelligent Vehicle Infiltration Scenario Experiment  
#### 3.1.1 Intelligent Vehicle Infiltration Analysis  
The trends in the overall carbon emissions of the road and the carbon emissions of each lane under different intelligent vehicle infiltration rates obtained in the previous traffic scenarios are shown below.  
In Figure 4, the results indicate that the total road carbon emissions decreased as the infiltration rate of intelligent vehicles increased, with a higher rate of decrease. The carbon emissions for each lane show a similar trend, with the outer lane experiencing a significant decrease and a faster rate of decrease. The carbon emissions for the inner lane fluctuated but remained relatively stable, whereas those for the middle lane exhibited a consistent and stable decrease. The markings in the figure are intended to represent the results of different experiments, with each point being the average of ten experiments. The same applies to the following text.  
Intelligent vehicles, equipped with ACC/CACC systems for information acquisition and response to external stimuli, exhibit reduced reaction times and improved desired gaps. With the increasing presence of intelligent vehicles, the average admissible gap among vehicles on the road diminishes, resulting in enhanced road operations and a consequent reduction in carbon emissions associated with the rise in the penetration rate of intelligent vehicles. For vehicles requiring off-ramp exits, swift lane merging into the outer lane is achievable, contributing to congestion mitigation. Consequently, carbon emissions in both the outer and middle lanes exhibit a declining trend. However, the outer lane's capacity to accommodate vehicles bound for off-ramps is limited. When the middle lane accumulates a significant number of vehicles exiting, those choosing to continue on the main road opt for the more advantageous inner lane, thus experiencing a heightened inflow of mainline vehicles, leading to fluctuations in carbon emissions within the inner lane.  
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Experimental Category** & **Vehicle Type** & **Parameter Values** \\ \hline \multirow{8}{*}{Influence Factor Analysis} & Intelligent Vehicle & \multirow{8}{*}{\begin{tabular}{c} P = 0, 10\%, 20\%, 30\%, 40\%, 50\%, 60\%, 70\%, 80\%, 90\%, 100\% \\ \end{tabular} } \\  & Infiltration Rate & & 90\%, 100\% \\ \cline{2-3}  & \multirow{2}{*}{\begin{tabular}{c} Percentage of Vehicles Exiting \\ the Ramp \\ \end{tabular} } & Manual Vehicle & \multirow{2}{*}{\begin{tabular}{c} P = 40\%; \\ P\({}_{\text{off}}\) = 0\%, 10\%, 20\%, 30\%, 40\%, 50\%, 60\%, 70\%, 80\%, 90\%, 100\% \\ \end{tabular} } \\  & \multirow{2}{*}{\begin{tabular}{c} Dedicated Lane for \\ Autonomous Vehicles \\ \end{tabular} } & & \multirow{2}{*}{\begin{tabular}{c} P = 0, 10\%, 20\%, 30\%, 40\%, 50\%, 60\%, 70\%, 80\%, 50\%, 60\%, 70\%, 80\%, 90\%, 100\% \\ \end{tabular} } \\  & \multirow{2}{*}{\begin{tabular}{c} Scale of Electric Vehicle Fleet \\ Intelligent Vehicle Fleet \\ \end{tabular} } & Manual Vehicle & \multirow{2}{*}{\begin{tabular}{c} P = 40\%; \\ N = 1, 2, 3, 4 \\ \end{tabular} } \\  & & & \\ \hline \multirow{8}{*}{\begin{tabular}{c} Analysis of Carbon Emissions \\ in Electric Vehicle Fleets \\ \end{tabular} } & Desired Time Headway of & \multirow{8}{*}{\begin{tabular}{c} Manual Vehicle \\ (Fuel) \\ Intelligent Vehicle \\ \end{tabular} } & ta = 1.1 s; tc = 0.6, 0.9, 1.1 s; P = 0, 10\%, 20\%, 30\%, 40\%, 50\%, 60\%, 70\%, 80\%, 90\%, 100\% \\ \cline{1-1} \cline{3-3}  & \multirow{2}{*}{\
\begin{tabular}{c} Manual Vehicle \\ (Fuel) \\ Intelligent Vehicle (Electric) \\ \end{tabular} } & ta = 1.1 s; tc = 0.6, 0.9, 1.1 s; P = 0, 10\%, 20\%, 30\%, 40\%, 50\%, 60\%, 70\%, 80\%, 90\%, 100\% \\ \cline{1-1} \cline{3-3}  & & & 90\%, 100\% \\ \hline \multirow{2}{*}{
\begin{tabular}{c} Mixed Fleet Size \\ \end{tabular} } & & P = 40\%; \\ \cline{1-1} \cline{3-3}  & & & N = 1, 2, 3, 4 \\ \hline \hline \end{tabular}
\end{table}
Table 10: Summary of Simulation Designs.