## 4 Results
### Recommendations and Discussion  
As part of the analysis, reviewing the variations that occur in terms of flow, it is evident that the higher the demand, the higher the density. However, when passengers walk along the escalator, a lower density is reached compared to the case when passengers are standing. The explanation for this lies in the behavior of passengers on the escalator and the use of the infrastructure. Similar to [10,14,18], it was found that the density, flow, and behavior of passengers are the most important variables that affect the capacity of escalators. When passengers stand on both sides of the escalator, they are located one step in between, maximizing the density. However, when passengers walk along the escalator, they use more space within it, which increases the effective area that is used by passengers, and therefore, the maximum density decreases because the same space is used by fewer passengers, which in turn reduces the discomfort of passengers. In terms of travel time, it is clear that when passengers walk on the escalator, a lower evacuation time is obtained. This is caused by the passengers moving along the escalator reaching a higher flow. However, when the density along the escalator reaches a high level, it is more difficult to walk, and therefore, the time to evacuate the escalator could be reduced. The maximum flow obtained when passengers were standing on both sides of the steps was 60 passengers/min, reaching a density of 2 passengers/m\({}^{2}\) on the escalator. However, if passengers could walk along the escalator, the flow could reach up to 80 passengers/min, reaching a density of 1.5 passengers/m\({}^{2}\). This is summarized in the following tables which are classified according to Fruin's level of service (LOS) [13]. It is important to notice that the LOS = E is defined as capacity. As observed in Tables 5 and 6, the LOS is reported for different demand levels (the number of passengers boarding the escalator), in which the case of passengers walking along the escalator generated an improvement in the LOS compared to the situation when the passengers were standing on both sides of the steps. Figure 9: Interface using the simulation framework to understand the relationship between the different conditions and the behavior of passengers on the escalator (each colored dot represents a passenger moving toward the escalator). As a consequence, to improve the usage and efficiency of this infrastructure, it is recommended to allow passengers to walk along the escalator and request passengers to stand to the right. But also, it is recommended to implement some crowd management measures to prevent passengers from forming a large queue at the entrance of the escalator (e.g., avoid a bottleneck by marking on the floor where to be located before boarding the escalator). In summary, this study provides three main results which may be a valuable contribution to the literature:  
* The use of video cameras and detection techniques. This study included the open-source software Datafromsky ([[https://datafromsky.com/](https://datafromsky.com/)]([https://datafromsky.com/](https://datafromsky.com/)), access date: 2 August 2023) which may be an alternative to [PERSON] and [PERSON] [29], who analyzed a subway station using the Yolo artificial vision library. These researchers expanded the use of Datafromsky which has been widely used in traffic analysis [35]. * The behavior effect for the same escalator considering different periods of time. For example, the relationship between the trip's purpose and the type of passenger could be found. The results show that passengers may estimate the relevance of crowding to travel time, which could help to understand the relationship between congestion, comfort, and perceived security [36]. In addition, this study expands on what has been reported by other authors in terms of the perception of travel time and its impact on the well-being of passengers using the metro system [37]. * The development of a simulation framework.