# Simulation-Based Optimization of Transport Efficiency of an Urban Rail Transit Network
## 3 Simulation Model
### Simulation Experiment Parameters Setting  
The simulation experiment is implemented on Beijing rail transit to explore the influence of various factors on network operation efficiency. The main features and problems of Beijing subway are as follows: (1) the continuous growth of network passenger volume has led to a sudden increase of pressure on operation and management departments; (2) the unreasonable layout of Beijing's urban functions is \begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Experimental Scheme** & **Experiment Description** & **Passenger Travel** & **Passenger** & **Per Capita Travel** \\  & & **Time/s** & **Flow/Person** & **Time/s** \\ \hline Deletion of Line 6 and & Benchmark scheme & 2,381,165,013 & 1,103,809 & 2157.226 \\ Changing Line & Construction of Changping & & & \\ Deletion of Line 6 & Line first & 2,524,073,485 & 1,155,816 & 2183.802 \\ Deletion of Changing Line & Construction of Line 6 first & 2,711,012,551 & 1,246,594 & 2174.736 \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Simulation results of line construction sequence. \begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Experimental Scheme** & **Increased Input/CNY** & **Penalty Travel Time/s** &
\begin{tabular}{c} **Travel Time** \\ **Saving/CNY** \\ \end{tabular} & **Transport Efficiency** \\ \hline Deletion of Line 6 and & - & 2,997,204,042 & - & - \\ the Changping Line & 1,632,890 & 2,920,555,841 & 766,482 & 0.469 \\ Deletion of the & 7,259,660 & 2,711,012,551 & 2,861,914 & 0.394 \\ Changing Line & & & & \\ \hline \hline \end{tabular}
\end{table} 
Table 5: Transport Efficiency calculation of line construction sequence. the main reason for the huge pressure on Beijing subway passenger flow; (3) the planning of Beijing subway network is insufficient; (4) the existing transport capacity allocation of Beijing subway trunk lines is too conservative; (5) the imbalance of passenger flow is very prominent; (6) the network transfers are at a large number; (7) the railway organization mode is single and the transfer is inconvenient; (8) the service level is not high because of the great influence between different parts of the network. Combined with the characteristics of the Beijing subway network, it can be considered that there are three main factors that have a great influence, namely, network scale, train departure density and passenger flow scale. By setting different levels of the three factors and combining them with each other, several experimental schemes can be obtained. These experimental schemes are simulated and compared, respectively, and the effects and adaptability of different optimization strategies are analyzed. 1. Rail network scale  
Based on the urban rail transit network of Beijing in 2015 and referring to the simulation experiment of the line construction sequence, Line 6 and the Changping Line are selected as the lines to be built. The simulation scenarios are set as shown in Table 4, and \"Original rail network\" means the largest network scale after the construction of the Changping Line and Line 6. 2. Train departure density scale  
Beijing subway Line 2, as a loop line, plays the role of dispersing the transfer passenger flow and relieving the transfer pressure. The adjustment of the departure density of Line 2 has a significant impact on the whole rail network. The simulation scenarios are set as follows. * \"Original\" means that the departure density of Line 2 remains unchanged. * \"Increased by 30 s\" means that the departure interval of Line 2 in the up and down direction from 7:00 to 9:00 during morning rush hours will be extended for 30 s, and the departure interval will remain unchanged in other periods. 3. Network passenger flow scale  
Different rail network scales and departure densities are suitable for different passenger flow scales. To explore the matching relationship between supply and demand, the simulation scenarios are set up as follows. * \"Increased by 10%\" means the input passenger flow of all stations in the whole rail network will increase by 10% at the same time.