## 3 Method
### Part One: CNDP  
As with previous studies, the CNDP initially belongs to the complex network analysis, and subsequent research methodologies have been extended based on the initial method. This study also adopts the same methodology; a foundational CNDP model is initially constructed to calculate the necessary evaluation indicators. The steps are as follows. Step 1: Constructing a topological network model based on urban agglomeration transportation networks. Users consider differences in cost, time, and safety with regard to transportation modes. To reflect these differences, multiple networks should be constructed to represent the characteristic differences in various transportation modes [35,36]. This paper suggests obtaining a set of geographic points V for from OpenStreetMap using OSMNX in megacities. The set of geographic points V is decomposed into the following geographic point sets: \(V_{\text{highway}}\), which includes all nodes in the study; \(V_{\text{expressway}}\), which includes the entrances and exits of expressways; \(V_{\text{subway}}\), which includes subway stations for urban rail transit; \(V_{\text{railway}}\), which includes train stations; and \(V_{\text{high-speed railway}}\), which includes high-speed rail stations. The transportation infrastructure network E within the area can be obtained through OSMNX, including the expressway segment set \(E_{\text{expressway}}\), the regular-speed highway segment set \(E_{\text{regular-speed highway}}\), the high-speed railway segment set \(E_{\text{high-speed railway}}\), the regular-speed railway segment set \(E_{\text{regular-speed railway}}\), and the urban rail transit segment set \(E_{\rm subway}\). As long as the data sources are from the same time period, the transportation network array \(G\) can be constructed as follows. \[G=\Big{\{}G_{Highway},G_{road},G_{highrailway},G_{railway},G_{subway}\Big{\}}\text {Taking }G_{highway}\text{ as an example, }G_{highway}=(V_{highway},E_{highway}) \tag{1}\]  
Step 2: Select a random user, along with a starting point, an endpoint, and a mode of transportation. Record the time they spend on their journey. The CNDP is the earliest complex network analysis and also the foundation of all complex network analyses. Currently, a large number of network evaluation indicators are designed for on-demand use in subsequent research [37; 38]. This study focuses on the logistics efficiency of urban transportation infrastructure, and the average transportation time is selected as the metric for measurement based on the suggestions from [PERSON] and [PERSON] [39; 40]. The more efficient the transportation infrastructure system in a megacity, the lower the average transportation time. To calculate the average path time and retain the extension possibility of the model, [PERSON] suggests that randomly selected paths should be applied to calculate the average path time, resulting in a travel information group (TI) as shown in (2) [41]. Based on the proportion of freight and passenger transport by highways, expressways, railways, and high-speed railways in that year, a mode of transportation is randomly selected to determine a network from \(G_{\rm highway}\), \(G_{\rm expressway}\), \(G_{\rm railway}\), \(G_{\rm high-speed railway}\), and \(G_{\rm subway}\). Then, the starting point \(s\) and ending point \(e\) are randomly chosen among the nodes. [PERSON]'s algorithm is used to obtain the shortest path. The average travel time  
Figure 1: The methodology system. of a randomly selected path \(t\) and the route group \(p\) of the shortest path are obtained by selecting the average speed of the selected transportation and the shortest path, thereby obtaining the travel information group. Owing to the combination of the [PERSON] and A* algorithms, the shortest algorithm is a traditional method used for obtaining the shortest path between two points in a complex network. For detailed calculation processes, the papers by [PERSON] (1973) and [PERSON] (1982) can be used as references [42; 43].