## 5 Conclusions  
This research sought to analyze the escalator infrastructure in urban railway stations. To this, the behavior of passengers was studied through video cameras, detection techniques, and simulation tools, taking the Santiago Metro, Chile, as a pilot study. \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Number of Passengers** & \begin{tabular}{c} **Maximum** \\ **Density** \\ **[Passengers/m2]** \\ \end{tabular} & \
\begin{tabular}{c} **Maximum Flow** \\ **[Passengers/min]** \\ \end{tabular} &
\begin{tabular}{c} **Average Speed of** \\ **Passengers [m/s]** \\ \end{tabular} & **LOS Defined in [13]** \\ \hline
339 & \(1.55\) & \(80.74\) & \(0.60\) & E \\
301 & \(1.48\) & \(68.32\) & \(0.59\) & D \\
264 & \(1.48\) & \(80.74\) & \(0.61\) & D \\
226 & \(1.58\) & \(74.53\) & \(0.60\) & D \\
188 & \(1.47\) & \(74.53\) & \(0.66\) & D \\
151 & \(1.34\) & \(65.22\) & \(0.60\) & D \\
113 & \(1.10\) & \(55.90\) & \(0.56\) & D \\
76 & \(0.57\) & \(31.05\) & \(0.65\) & B \\
38 & \(0.51\) & \(27.95\) & \(0.65\) & A \\ \hline \hline \end{tabular}
\end{table} 
Table 6: Level of service when passengers are walking along the escalator. \begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Number of Passengers** & \begin{tabular}{c} **Maximum** \\ **Density** \\ **[Passengers/m2]** \\ \end{tabular} & \
\begin{tabular}{c} **Maximum Flow** \\ **[Passengers/min]** \\ \end{tabular} &
\begin{tabular}{c} **Average Speed of** \\ **Passengers [m/s]** \\ \end{tabular} & **LOS Defined in [13]** \\ \hline
339 & \(2.15\) & \(74.53\) & \(0.45\) & F \\
301 & \(2.10\) & \(71.43\) & \(0.45\) & F \\
264 & \(2.06\) & \(74.53\) & \(0.45\) & F \\
226 & \(2.03\) & \(74.53\) & \(0.45\) & F \\
188 & \(2.15\) & \(77.64\) & \(0.46\) & F \\
151 & \(1.67\) & \(62.11\) & \(0.46\) & E \\
113 & \(1.85\) & \(68.32\) & \(0.46\) & E \\
76 & \(1.25\) & \(52.79\) & \(0.46\) & D \\
38 & \(0.67\) & \(31.05\) & \(0.47\) & C \\ \hline \hline \end{tabular}
\end{table} 
Table 5: Level of service when passengers are standing on both sides of the escalator. Passenger behavior on escalators is influenced by cultural and environmental conditions. However, the passenger flow, density, and other cultural conditions can be quantified and evaluated on escalators, which makes it possible to determine their real capacity in a specific place. Through a review of the state of the art and the observation of cases on escalators of the Santiago Metro, the variables that most influenced passenger behavior were identified. In this pilot study, it was observed that the behavior of passengers influenced the usage of the escalator infrastructure. When passengers board the escalator, they keep a separation step between each one and therefore respect the personal space around their bodies. A pattern of passenger distribution was also observed between those who decide to stand or those who walk along the escalator. In addition, it is relevant to understand the relationship between the trip's purpose and the type of passenger, which may affect the behavior of passengers on the escalator (e.g., peak vs. off-peak hours). Based on these variables, a simulation framework was developed that uses an agent-based approach to reproduce the observed behavior in a simplified way. The use of a simulation framework has allowed us to understand the relationship between different conditions and the behavior of passengers, considering specific environmental and cultural conditions. In addition, it could be evaluated how the capacity differs from the one declared by the manufacturer and the value established in consideration of Fruin's level of service. This paper is considered as a pilot study, and therefore, further studies are needed to analyze some situations that were observed partially in the field studies such as passengers starting to walk at the end of the escalator or depending on the empty space around them, among other situations which were not totally analyzed in this research.