## 5 Conclusions, Discussion, and Future Research Issues  
The transportation sector is regarded as a main culprit in greenhouse gas emission in the urban network, particularly idling vehicles waiting at signalized intersections. There have been many efforts to alleviate these adverse effects by utilizing more advanced information and communication technologies and enforcing emission regulations as well. Even though autonomous vehicles can be a promising technology to tackle vehicle idling, their environmental benefits obtain no attention compared with the safety and mobility issues. This study underlined that the CO\({}_{2}\) emitted by idling vehicles at signalized intersections accounts for a significant proportion of the citywide emissions, suggesting that controlling vehicle idling is an inevitable way to reduce CO\({}_{2}\) emissions. This study introduces an automatic vehicle idling control function that enables vehicles to autonomously decide vehicle idling control in the queue at signalized intersections and investigate its environmental benefits. This study attempts to introduce the basic algorithm of the automatic idling control function and investigate the environmental benefits of autonomous vehicles equipped with it based on the traffic signal information transmitted from the traffic signal controller under C-ITS by employing the microscopic mobility and emission simulator, VISSIM, VISSIM COM, and MOVES, in Haeundae-gu in Busan, Korea, as a case study. The most discernable point of this study from the existing works is to simultaneously take into account the queue length, reference time, and transmitted traffic signal information prior to determination of the vehicle idling control. According to the simulation outputs, the total saved idling time thanks to the automatic idling control function accounts for 47.6% of the total travel time and 94.3% of the total idling time, respectively. Also, it could reduce 23.6% and 94.3% of CO\({}_{2}\) emissions out of the total and idling amounts, respectively. In conclusion, the autonomous vehicles equipped with an automatic vehicle idling control function under C-ITS can play an important role in reducing the CO\({}_{2}\) emissions in the urban traffic network. Particularly, this study contributes to suggesting a novel methodology to compute the queue discharge time, utilized to determine whether to control vehicle idling or not, and utilizing on data about vehicle position in the queue, shockwave speed, reference time, and traffic signal information shared by V2I communication. In addition, although electric vehicles and low-emission vehicles are rapidly being distributed, they have not yet had a meaningful impact on the overall reduction of CO\({}_{2}\) emissions in urban areas to date. Therefore, the function proposed in this study can play a sufficient role in reducing CO\({}_{2}\) emissions in the process of expanding the market penetration rate of these vehicles. Therefore, this study strongly supports a logical basis on the assertive deployment of the automatic vehicle idling control function in major cities, especially those suffering from CO\({}_{2}\) emissions. Even though there is a drawback to the stop-and-go function, which is a representative technology of vehicle idling control introduced in Section 2, that is, it cannot reflect the queue discharge time and reference time and unconditionally controls vehicle idling whenever the vehicle stops, it is expected to significantly reduce CO\({}_{2}\) emissions. Intuitively, the automatic vehicle idling control function proposed in this study outperforms the stop \begin{table}
\begin{tabular}{c c} \hline \hline
**Item** & **Value** \\ \hline Total idling count & 113,986 times \\ Average idling count & 7.2 times/vehicle \\ Average idling time & 50.6 s/idling \\ Average idling emission & 142 kg/h/idling \\ Average controlled idling emission & 134 kg/h/idling \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Effects of the automatic vehicle idling control function at the individual idling level.