## 3 Simulation Experimental Design
### Bus Dwell Time Model  
During the morning peak hours (around 7:30-8:30), bus dwelling data were collected by video detection in Gulou District, Nanjing, Jiangsu, which spans working days from 19 October 2021, to 23 October 2021. The dataset involves four bus stops (see their geographic locations in Figure 3); of that, the No. 1 bus stop and No. 3 bus stop have a single berth, and the No. 2 bus stop and No. 4 bus stop have double berths. No. 1 bus stop and No. 4 bus stop are bus bay stops and No. 2 bus stop and No. 3 bus stop are curbside bus stops. These four bus stops keep considerable distances from intersections, which can neglect the interaction between the bus stop and nearby intersections. Table 1 shows the details related to the four bus stops.  
The dwell time of all buses serving at the four bus stops is extracted from the collected data, and the proportion of each dwell period to the total dwell time is depicted in Figure 4. As can be seen in Figure 4, the dwell time of the four bus stops is mainly distributed from 30 to 80 s, and the total dwell time of the No. 4 bus is longer than that of the other three stops, which is close to the square with large traffic flow.  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline \multirow{2}{*}{**No.**} & \multicolumn{2}{c}{**Bus Stop (Number of**} & \multirow{2}{*}{**Direction**} & \multirow{2}{*}{**Bus Routes**} & \multirow{2}{*}{**Acquisition**} & \multirow{2}{*}{**Flow**} \\  & **Bus Berths)** & & & & **Data** & **Rate** \\ \hline \multirow{2}{*}{1} & Qingliangmen & \multirow{2}{*}{W\(\rightarrow\)E} & Routes 60, 303, 317 & 99 & 1384 \\  & Street–Guanzi Bridge & & & Routes 23, 60, 133, & & \\ \multirow{2}{*}{2} & Central South Village & \multirow{2}{*}{W\(\rightarrow\)E} & 303, 511 & \multirow{2}{*}{127} & \multirow{2}{*}{1460} \\  & Phoenix Garden City & \multirow{2}{*}{N\(\rightarrow\)S} & Routes 18, 57, 204 & 87 & 1402 \\ \multirow{2}{*}{4} & Jiangdong North & \multirow{2}{*}{S\(\rightarrow\)N} & Routes 9, 23, 39, 56, & \multirow{2}{*}{137} & \multirow{2}{*}{1571} \\  & Road–Dongbao Road & & 510, 511 & & \\ \hline \hline \end{tabular}
\end{table}
Table 1: Details of bus routes associated with four bus stops.  
Figure 3: Locations of four bus stops for dwell time data collection. (Image Source: Google Maps).  
To further analyze the transit operation characteristics with the collected data, this paper uses the distribution fitting analysis approach [46] to find the optimal appropriate probability distribution for bus dwelling time. This paper adopts the K-S test statistic at a significance level of 0.05 for the goodness-of-fit test based on the data from the four bus stops in the peak hour of each workday. By simulating 23 probability distribution models, six distributions with well-fitted results described in Table 2 are selected as the candidate probability distributions. This table shows that the generalized extreme value (gen. extreme value) distribution is the best from the K-S test results (\(p\)-values) of the six candidate probability distributions. Therefore, the probability density function of the gen. extreme value distribution is utilized to fit the bus dwelling time.