## 3 Materials and Methods
### Simulation Model Calibration
#### 3.4.2 Simulation Model Calibration Method  
The calibration goal is that NRMSEs are below a specified threshold for all periods. The process of simulation model calibration is shown in Figure 5.  
First, the identification and correction of errors in road segment information are conducted: We start by loading the initial simulation demand over time onto the road network, obtaining simulation results for all time intervals, and assessing whether there are instances of generally higher or lower speeds compared to actual values over all or most time periods. This occurrence may stem from notable differences between the predetermined link capacity/speed limit and the actual functional value. During the link attribute calibration process, three links had significantly higher or lower simulated speeds than real-world observations. The speed limits of these links in the initial simulation (based on the preprocessing rule in Tables 3 and 4) are inherently lower than the actual speeds. It could result from errors in the speed limit information of the original network data. In  
Figure 5: Iterative calibration process. such cases, we use the street view feature of Amap to check their speed limit and make corrections accordingly. And for links where the simulated speeds are notably higher than the reality, we appropriately reduce their capacities to model real-world congestions. After the aforementioned calibration steps, the identification and elimination of the universal deviation between the simulated link speeds and the actual link speeds have been accomplished, thus completing the calibration of the supply aspect of the simulation model. Subsequently, taking into account the time-dependency of traffic flow, the calibration of OD pairs on road segments is conducted in a time-specific manner to adjust the travel demand on the links. The following steps are involved:  
Step 1: Calculation of overall error for the current time period. Commencing with the calibration of the first time period, we calculate the RMSE and NRSME between the average speeds of all links in the simulation and those in reality for the current time period t. If the NRSME falls below the threshold \\(\\gamma\\), it indicates that the error between the simulated average link speeds and the actual average speeds is within the permissible range for that time period. Subsequently, the travel demand for the fixed time period t is maintained, and calibration proceeds to the next time period (\\(t=t+1\\)) until \\(t=\\mathrm{T}\\) (the last time period). However, if the NRSME exceeds the threshold \\(\\gamma\\), calibration for the current time period continues. Step 2: Selection of key links for demand calibration. The deviation between the simulated and actual speeds is calculated as follows to obtain the deviation value \\(DV_{m,t}\\) for each link during the current time period \\(t\\). \\[DV_{m,t}=\\left|\\log_{C}S^{\\prime}_{m,t}/S_{m,t}\\right| \\tag{6}\\]  
where \\(DV_{m,t}\\) represents the deviation between the simulated and actual average speeds of link \\(m\\) during time period \\(t\\), \\(S^{\\prime}_{m,t}\\) is the average speed of link m in the simulation during time period \\(t\\), \\(S_{m,t}\\) is the average speed of link m in reality during time period \\(t\\), \\(C\\) is a deviation multiplier constant, set to 2 in this study. When the simulated and actual average speeds are identical, the deviation \\(DV_{m,t}\\) is 0, whereas, when the simulated average speed is half or double the actual average speed, the deviation \\(DV_{m,t}\\) is 1. Subsequently, the K links with the largest deviations are selected from the set of target links. A small value of K means that calibration is only conducted on a few road segments within the target set, leading to a slow and lengthy calibration process. Conversely, a large value of K can result in excessive adjustment of OD flows due to their potential impact on multiple target road segments, potentially leading to issues such as over-adjustment and insignificant results.