## 5 Conclusions  
1. The method presented here represents a research method that is appropriate for the study of urban resident trips using multi-agent technology. This method illustrates the flow of people in any transportation facility at any time and can overcome the flaws of traditional mathematical and statistical models, such as difficulties in describing complex traffic and trip environments. \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Item** & **Average Walking Time (HToS)** & **Average Walking Time (SToW)** & **Average Total Walking Time** \\ \hline Simulation & 3 min 17 s & 2 min 54 s & 6 min 11 s \\ \hline \hline \end{tabular}
\end{table} 
Table 6: The walking time results from our simulation. HToS, home to metro stop; SToW, metro stop to workplace. \begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Item** & **Average** & **Average** & **Average Time of** & **Average Time of** & **Average Travel** \\
**Departure** & **Arrival** & **Boarding at the** & **Departure from the** & **Time (Without** \\
**Destination Metro Stop** & **Walking Time)** \\ \hline Simulation & 8:04:31 & 8:44:51 & 8:07:48 & 8:41:57 & 34 min 09 s \\ Reality & & & 8:13:01 & 8:39:46 & 36 min 45 s \\ Difference & & & \(-\)5 min 13 s & 2 min 11 s & \(-\)2 min 36 s \\ \hline \hline \end{tabular}
\end{table} 
Table 4: The differences between simulation and reality when going to work. \begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Item** & **Average** & **Average** & **Average Time of** & **Average Time of** & **Average Travel** \\
**Departure** & **Arrival** & **Boarding at the** & **Departure from the** & **Time (Without** \\
**Destination Metro Stop** & **Walking Time)** \\ \hline Simulation & 17:50:05 & 18:26:54 & 17:52:59 & 18:23:37 & 30 min 38 s \\ Reality & & & 18:21:46 & 18:56:12 & 34 min 26 s \\ Difference & & & \(-\)28 min 47 s & \(-\)32 min 35 s & \(-\)4 min12 s \\ \hline \hline \end{tabular}
\end{table} 
Table 5: The differences between simulation and reality when getting off work. A strategy for performing dynamic optimization of the departure times of metro users has been proposed to solve the two problems mentioned at the end of the Introduction. With this strategy, the average travel time becomes shorter, and there is no premature arrival when going to work and no late departure when getting off work. These results can provide the public with suggestions regarding their travel plans and allow commuters more time to do other things, such as sleeping, eating breakfast and shopping. 3. Furthermore, the severe congestion at some metro stops leads to long wait times during rush hour. Thus, the existing metro resources are still having difficulties in meeting the actual travel demand. These findings can provide suggestions to public transport management departments, such as to shorten the departure intervals and accelerate the speeds of train operation. The different parameter values of departure intervals and train speeds must be tested in our simulation tool to find better results. 4. There are several aspects of the problem that should be investigated in future research. First, large-scale simulations of other modes of travel, such as car or bus travel, should be tested in our simulation tools to better optimize commuters' departure times and travel routes. Second, the optimal departure interval for each metro line during rush hour should be found to assist in transport planning. It will increase the transportation capacity of metro system without wasting transportation resources. Finally, the person agents' travel strategies could be modified by introducing game theory to attempt to explore the Nash equilibrium of commuters' travel strategies. It will be the best travel strategies for any commuter in theory when taking metro during rush hour. We thank [PERSON], [PERSON], [PERSON], [PERSON] and [PERSON] for their help. In addition, this study is supported by the National Key Research and Development Programme of China (2016 YFC 0803106) and the National Natural Science Foundation of China (Project No.