## 3 AMO Model Construction
### Agent-Based Multimode Dynamic Traffic Simulation Model
#### 3.2.1 Pre-Trip Decision Model  
In the pre-trip decision model, individual travelers determine their departure time and travel mode based on incentive and penalty mechanisms, personal preferences, time costs, and economic budget. These decisions are influenced by the heterogeneity of individual preferences and constraints, leading to diverse and complex decision-making behaviors. The steps involved in the decision-making process are as follows:  
1. Calculate the generalized cost of each travel mode and establish the initial state of the transportation network. This stage includes three singular travel modes (private car, bus, and metro) and two combined transfer modes (private car to bus (C+B) and private car to metro (C+M)). During the morning peak hours, commuters face stringent timing requirements, necessitating arrival at their destination before a specified time set by their workplace. Therefore, arriving either early or late incurs a certain time cost. In this study, the generalized costs of each travel mode are quantified in monetary terms, encompassing costs associated with being early or late, on-route travel time, and direct travel expenses, as detailed in Equation (6):  
\[C_{n,t}^{m}=\eta v_{e}[t_{w}-(t+t_{t})]+(1-\eta)\sigma_{l}[(t+t_{t})-t_{w}]+v_{ t}*t_{t}+o_{m} \tag{6a}\] \[o_{m}=\left\{ \begin{array}{c}\sum\limits_{a}l*d_{a},\qquad m=\text{car}\\ f_{bus},\qquad m=\text{bus}\\ f_{metro},\qquad m=\text{metro}\\ \sum\limits_{a}l*d_{a}+f_{metro}+f_{bus}+P_{a},\qquad m=\text{P}+\text{R}\\ \end{array} \right.\] (6b) \[P_{n}(m)=\frac{\exp\bigl{(}-\theta_{1}C_{n,t}^{m}\bigr{)}}{\sum\limits_{m}exp \bigl{(}-\theta_{1}C_{n,t}^{m}\bigr{)}} \tag{6c}\]  
where \(C_{n,t}^{m}\) represents the generalized travel cost for traveler \(n\) choosing travel mode \(m\) at time \(t\); \(t_{w}\) refers to the designated start time for work as set by the employer; \(t_{t}\) is the travel time; \(v_{e}\), \(v_{t}\), and \(v_{t}\), respectively, signify the time value for arriving early, late, and on-route; and \(\eta\) is a 0-1 indicator variable, representing whether the travel arrives early. When \(t_{w}-(t+t_{t})\geq 0\), it indicates that the traveler arrives on time or early, and \(\eta=1\). When \(\text{t}_{w}-(t+t_{t})<0\), it means the traveler is late, and \(\eta=0\). \(o_{m}\) represents the travel cost. \(P_{n}(m)\) is the probability that traveler \(n\) chooses travel mode \(m\). \(\theta_{1}\) is a discrete choice parameter for mode selection. Travelers in the network make their mode choices based on the generalized costs linked to their initial travel times. Those who opt for bus or metro follow predetermined, fixed routes. On the other hand, travelers who select private cars engage in a more dynamic decision-making process while on-route, which will be elaborated upon later in this paper. For every traveler, the initial choice of travel mode and the specific routes taken are systematically recorded. Each road's average travel time is calculated at 10 min intervals to assess the network's traffic state. These data serve as an indicator of the initial traffic state of the network at each given time interval. (2) The user's travel decision after the implementation of the TRS  
Following the implementation of the TRS, the decision-making process for users becomes more intricate, involving adjustments to travel time and decisions on how to utilize the reservation system. The specific steps are as follows:  
Set the total number of road reservations. The central principle of the TRS is to adjust individual travel times to enhance the efficiency of matching traffic supply with demand. Setting a reasonable reservation volume for each road ensures smooth traffic flow while maximizing the total traffic volume of the road, thereby preventing the wastage of road resources. This study considers setting a road's peak hour traffic capacity as its hourly reservation quota. Additionally, this total number is evenly distributed across each 10 min time window.