10:00 AM - 10:15 AM
[HTT17-10] Analysis of Small-Scale Crowd Flow in Pedestrian Spaces
Keywords:crowd flow
1.Introduction
During the COVID-19 pandemic, migration to the Tokyo area decreased due to the impact of the virus, with a rise observed again in 2022 and 2023. As more people concentrate in large cities, local activities resume, contributing to the revitalization of urban areas. This has a significant effect on public spaces, where people's behavior influences the surrounding environment. Additionally, the risk of future disasters, particularly ocean trench earthquakes, is increasing. In such scenarios, simultaneous evacuations can be difficult, and understanding human behavior is key for improving evacuation route planning and drills.
Moreover, the rise in tourism and an aging population have led to an increase in bicycle traffic. This has resulted in a growing number of accidents between pedestrians and bicycles, especially on sidewalks. Addressing the safe coexistence of pedestrians and cyclists is crucial in urban planning.
2.Purpose
This study aims to visualize how people's behavior affects surrounding traffic. During rush hour or times when roads and public transport are crowded, people's behavior differs from when they are alone. This phenomenon, referred to as small-scale crowd flow, increases the risk of accidents. By understanding these behaviors, we can better manage crowd movement and reduce potential dangers.
3.Traffic environment hazards
In the preliminary survey, we examined pedestrian and bicycle traffic at a site with dedicated paths for both. A 5-minute video survey was conducted, summarizing key data, including 1) the location of the road used, 2) the direction of travel, and 3) the status of entry into adjacent roads. The results revealed that pedestrians often exhibit complex behaviors when passing bicycles, such as going around or slipping through gaps. Additionally, when people form groups, their movement becomes more erratic, causing them to enter other parts of the road.
4.Visualizing small-scale crowd movements
Building on the preliminary survey, we focused on small-scale crowd flow at a crosswalk where group formation is visible. Pedestrians were filmed three times while the light was green, their coordinates extracted to measure their movements. The findings showed that when the crowd density increased, the flow tended to form a linear shape. Conversely, when density decreased, the crowd dispersed. This indicated that crowd density plays a significant role in shaping pedestrian behavior.
GIS were used to analyze the data, employing multiple ring buffer and kernel density estimations to determine when individuals would take evasive action to avoid collisions. The multiple ring buffer was set at a distance of 22.5 cm, totaling 180 cm, with a bandwidth of 90 cm for kernel density estimation. When an approaching person interacts with multiple buffers and kernel estimates, the data is added to their coordinates. The results showed that the shapes of the multiple ring buffers were similar across surveys, though the slope and constants of the approximation curve varied depending on the area.
The study found that pedestrians typically maintained a distance of 45 cm or more when passing each other. However, when the density reached 0.6 or more, individuals were generally unable to pass without walking around one another.
5.Summary
This study demonstrates that small-scale crowd flows take on a linear shape when density is high and tend to disperse when density is low. This highlights that small-scale crowd flows behave differently from large crowds. By examining these flows based on the characteristics of the area and sidewalk design, we can better understand pedestrian behavior, which can help improve urban planning to manage crowd dynamics and ensure safety.
During the COVID-19 pandemic, migration to the Tokyo area decreased due to the impact of the virus, with a rise observed again in 2022 and 2023. As more people concentrate in large cities, local activities resume, contributing to the revitalization of urban areas. This has a significant effect on public spaces, where people's behavior influences the surrounding environment. Additionally, the risk of future disasters, particularly ocean trench earthquakes, is increasing. In such scenarios, simultaneous evacuations can be difficult, and understanding human behavior is key for improving evacuation route planning and drills.
Moreover, the rise in tourism and an aging population have led to an increase in bicycle traffic. This has resulted in a growing number of accidents between pedestrians and bicycles, especially on sidewalks. Addressing the safe coexistence of pedestrians and cyclists is crucial in urban planning.
2.Purpose
This study aims to visualize how people's behavior affects surrounding traffic. During rush hour or times when roads and public transport are crowded, people's behavior differs from when they are alone. This phenomenon, referred to as small-scale crowd flow, increases the risk of accidents. By understanding these behaviors, we can better manage crowd movement and reduce potential dangers.
3.Traffic environment hazards
In the preliminary survey, we examined pedestrian and bicycle traffic at a site with dedicated paths for both. A 5-minute video survey was conducted, summarizing key data, including 1) the location of the road used, 2) the direction of travel, and 3) the status of entry into adjacent roads. The results revealed that pedestrians often exhibit complex behaviors when passing bicycles, such as going around or slipping through gaps. Additionally, when people form groups, their movement becomes more erratic, causing them to enter other parts of the road.
4.Visualizing small-scale crowd movements
Building on the preliminary survey, we focused on small-scale crowd flow at a crosswalk where group formation is visible. Pedestrians were filmed three times while the light was green, their coordinates extracted to measure their movements. The findings showed that when the crowd density increased, the flow tended to form a linear shape. Conversely, when density decreased, the crowd dispersed. This indicated that crowd density plays a significant role in shaping pedestrian behavior.
GIS were used to analyze the data, employing multiple ring buffer and kernel density estimations to determine when individuals would take evasive action to avoid collisions. The multiple ring buffer was set at a distance of 22.5 cm, totaling 180 cm, with a bandwidth of 90 cm for kernel density estimation. When an approaching person interacts with multiple buffers and kernel estimates, the data is added to their coordinates. The results showed that the shapes of the multiple ring buffers were similar across surveys, though the slope and constants of the approximation curve varied depending on the area.
The study found that pedestrians typically maintained a distance of 45 cm or more when passing each other. However, when the density reached 0.6 or more, individuals were generally unable to pass without walking around one another.
5.Summary
This study demonstrates that small-scale crowd flows take on a linear shape when density is high and tend to disperse when density is low. This highlights that small-scale crowd flows behave differently from large crowds. By examining these flows based on the characteristics of the area and sidewalk design, we can better understand pedestrian behavior, which can help improve urban planning to manage crowd dynamics and ensure safety.