## 3 Simulation Experiments
### Datasets
#### 3.1.2 Data Preprocessing
Traffic conditions: The dataset includes traffic data for both peak and non-peak hours. The \"Holidays or Not\" column indicates whether the data were collected on a holiday. In this example, the data were collected on a non-holiday. The dataset also includes data collected during peak hours (e.g., morning rush hour from 7:00 to 9:00 and evening rush hour from 17:00 to 19:00). 3. Temporal variability: The dataset considers temporal variability by including data collected at different times of the day (morning, afternoon, and evening). The \"Time\" column shows the specific time of data collection, allowing for analysis of traffic flow patterns throughout the day. In this example, the data were collected between 11:00 and 11:50, which is during the midday period. The above table uses Donxin Street as an example. Between 11:00 a.m. and 11:50 a.m., the traffic flow on Donxin Street showed an increasing trend from 172 to 192 vehicles, while the average speed decreased from 32 to 27 km/h, suggesting that traffic congestion may have been caused by rainfall. During the period, the temperature increased from 16.7 \({}^{\circ}\)C to 18.5 \({}^{\circ}\)C, the atmospheric pressure fluctuated between 702 and 704.6 mbar, and the relative humidity at the ground level stayed around 37% before decreasing to 35%. There was no wind and continuous rainfall throughout the observation period, visibility remained above 10 km, and the sky was sparsely cloudy. Table 7 shows the data distribution for different weather scenarios and time periods. \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Collection Period** & **Weather Condition** & **Time of Day** & **Number of Samples** & **Specific Observations** \\ \hline January 2021 & Sunny & Morning (6 a.m.–12 p.m.) & 2345 & No holidays, typical traffic \\ January 2021 & Sunny & Afternoon (12 p.m.–6 p.m.) & 2123 & No holidays, typical traffic \\ January 2021 & Sunny & Evening (6 p.m.–12 a.m.) & 1876 & No holidays, typical traffic \\ January 2021 & Snowy & Morning (6 a.m.–12 p.m.) & 1234 & Snowstorm, increased traffic accidents \\ January 2021 & Snowy & Afternoon (12 p.m.–6 p.m.) & 1456 & Snowstorm, increased traffic accidents \\ January 2021 & Snowy & Evening (6 p.m.–12 a.m.) & 1098 & Snowstorm, increased traffic accidents \\ April 2021 & Rainy & Morning (6 a.m.–12 p.m.) & 1567 & No holidays, typical traffic \\ April 2021 & Rainy & Afternoon (12 p.m.–6 p.m.) & 1678 & No holidays, typical traffic \\ April 2021 & Rainy & Evening (6 p.m.–12 a.m.) & 1456 & No holidays, typical traffic \\ July 2021 & Foggy & Morning (6 a.m.–12 p.m.) & 1345 & No holidays, typical traffic \\ July 2021 & Foggy & Afternoon (12 p.m.–6 p.m.) & 1234 & No holidays, typical traffic \\ July 2021 & Foggy & Evening (6 p.m.–12 a.m.) & 1123 & No holidays, typical traffic \\ October 2021 & Sunny & Morning (6 a.m.–12 p.m.) & 2456 & No holidays, typical traffic \\ October 2021 & Sunny & Afternoon (12 p.m.–6 p.m.) & 2345 & No holidays, typical traffic \\ October 2021 & Sunny & Evening (6 p.m.–12 a.m.) & 2098 & No holidays, typical traffic \\ \hline \hline \end{tabular}
\end{table} 
Table 7: Summary of data distribution across different weather scenarios and time periods. This table provides a summary of the data distribution across different weather scenarios and time periods. The collection period column indicates the specific month and year of data collection. The weather condition column classifies the weather conditions (e.g., sunny, rainy, snowy, foggy). The Time of Day column categorizes the time into morning, afternoon, evening, and night. The number of samples column shows the total observations collected under each weather and time combination. The specific observations column notes any extraordinary events, such as holidays or unusual congestion. The dataset used in this study is designed to capture typical and atypical traffic patterns across different times of the year and weather conditions.