This special issue summarizes the research findings of the “Crowd Control Adaptive to Individual and Group Attributes” project, which is selected as a full-scale research project under the “Development of the Crisis Navigator for Individuals” prioritized theme of the JST Mirai Program.^*

Despite the lingering memory of the 2022 crowd accident in Itaewon, South Korea, similar accidents have occurred worldwide, including the firework display in Akashi, Japan, and the Love Parade in Germany. Addressing this social issue is imperative. To significantly reduce the risk of crowd accidents, this project aimed to elucidate the mechanism underlying human flow stagnation and establish a method to effectively guide the flow of people. Our approach involves creating a mathematical model that can estimate the flow of people by considering individual and group attributes, such as wheelchair and group behavior, to accurately predict flow stagnation. Based on these predictions, we developed a system that provides individuals with information on movement and utilizes technology to guide crowd flow, drawing principles from game theory and nudge theory. This system is characterized by integrating information on human flow, environmental factors, simulation results for predicting future conditions, and crowd control measures within the Crowd Management Platform as a Service (CMPaaS). Furthermore, we conducted demonstration tests at shopping malls, train stations, and event venues, and found that it offers valuable guidance to achieve risk reduction effects at real-world sites.

In this special issue, the first paper presents an overview of the newly created crowd management platform. Thereafter, it is organized into 16 articles presenting current research results categorized under Simulation, Theory, Control, Experiment, and Data Analysis, followed by a note on visitor trajectories in indoor facilities.

We anticipate that the outcomes of this study will facilitate interdisciplinary research in this field and promote the social implementation of crowd management platforms to prevent crowd accidents, thus creating a society where everyone can move safely, securely, comfortably, and efficiently.

^* Mirai means “Future” in Japanese. The program is administered by the Japan Science and Technology Agency (JST) and funded by the Ministry of Education, Culture, Sports, Science and Technology (MEXT).

Managing crowds is important not only during evacuation in disasters such as earthquakes and fires but also during normal situations. In particular, places where many people gather every day, such as stations or event venues, need such management to prevent crowd accidents. Moreover, efficient guidance that prevents people from waiting or queuing can improve facility services and lead to business opportunities. In this study, we propose a crowd management platform to prevent crowd accidents and provide efficient guidance to visitors. Specifically, we integrate real-time observations of crowd conditions, predictions, and risk assessments through simulation and crowd control in collaboration with security and facility managers. We also present the results of operating this platform in actual fields, which contribute to and support the safety and comfort of individuals.

Crowd management at large-scale events and specific facilities is a critical issue from the perspectives of safety and service quality improvement. Traditional methods for crowd management often rely on empirical knowledge, which has limitations in quickly grasping the on-site situation and making decisions on the spot. In this study, we developed a real-time crowd flow prediction and visualization platform incorporating an agent-based crowd simulation and an advanced crowd management system called crowd management platform as a service. In a case study focused on the area around the Tokyo Dome, we demonstrated that capturing pedestrian flow allows for accurate predictions of congestion at the nearest train station up to 10 min in advance. Moreover, the time required to predict the situation 20 min ahead for 3,000 agents was 1 min and 35 s, confirming the feasibility of real-time processing. To enhance the accuracy and reliability of the simulation results, a sensitivity analysis considering errors in pedestrian flow measurement revealed that simple linear models cannot capture the complexity of crowd dynamics adequately. Notably, the agent-based simulation replicated stop-and-go wave patterns observed in actual measurements under specific crowd conditions, confirming the advantage of using agent-based simulations. Finally, we proposed a method that enables facility managers and security personnel to conduct a more comprehensive evaluation. This method integrates their existing experience with the aggregated display of multiple simulation results, which includes consideration of errors in pedestrian flow measurement through a visualization platform.

To prevent crowd incidents, it is important to share information among stakeholders from the planning stage of crowd management. However, numerous stakeholders are typically involved in crowd management for events, and it is difficult for each stakeholder to understand and agree on their goals, roles, responsibilities, and plans. Additionally, given the vast number of scenarios, it is also difficult to consolidate plans in an efficient and effective manner. Therefore, we devised the simulation-based agile approach (SBAA) methodology, which is characterized by “collaboration with stakeholders,” “responding to plan changes,” and “identifying quality requirements for operations through iterative proposals and agreements.” The first two characteristics are consistent with the Agile Manifesto, which has proven successful as a software development methodology. We participated in the creating of a crowd control plan for a local fireworks display and put SBAA into practice. The SBAA methodology and the effectiveness of SBAA in practice are discussed herein.

Tsunamis resulting from earthquakes can cause extensive damage, including infrastructure destruction, injuries, and fatalities. To address these risks, numerous tsunami evacuation simulations have been conducted to assess evacuation strategies and identify issues, particularly in Japan, where the Nankai Trough earthquake is anticipated, affecting underground malls in urban areas. Our previous research primarily focused on evacuating from underground to the surface, neglecting surface evacuation. Therefore, this study extended the previous study to include horizontal evacuation following the exit from the underground mall to ground level. It also considered the impact of pedestrian road crossings as interactions with vehicular traffic within the simulation to enhance realism and verify the evacuation risk. The study also explores scenarios where evacuation guide stairs are unavailable, comparing the effectiveness of alternative staircases in the evacuation plan. Results indicate that while using alternative staircases temporarily increases the number of evacuees reaching the surface, road crossings on evacuation routes become significant bottlenecks, leading to surface congestion and delayed evacuations. This raises doubts about the effectiveness of alternative staircases and highlights the need to consider alternative evacuation routes as a secondary plan. Additionally, the study reveals that reduced pedestrian flow at road crossings can significantly impact on evacuation times. Ultimately, this study demonstrated that achieving a short evacuation time from underground malls to the ground level might not always yield the best evacuation plan. It underscored the importance of considering aboveground factors in evacuation planning to ensure safety in the event of a tsunami caused by an earthquake.

Regulated egress is often conducted after large events to avoid extreme congestion at stations around event venues. In regulated egress, people are divided into several groups and egress in order. By controlling the number of groups and the time interval between each group’s egress, managers can mitigate the congestion at the stations. In this study, a mathematical model was developed to identify the effective regulated egress. level of discomfort (LOD) was used to evaluate the performance of the regulated egress instead of the total egress time. LOD is the product of the function of density and duration of egress and represents the accumulated discomfort through the egress. A questionnaire survey was conducted to determine the LOD function parameters. Under the assumed conditions, the results of the calibrated model indicated that effective regulated egress could be conducted by dividing the people into two or three groups, which is presumable in terms of management in the real world. In addition to the main result for the effective number of groups, the robustness of the model was confirmed by comparing the results of the two types of LOD functions. In other words, the effective number of groups does not strongly depend on the detailed form of the LOD functions.

When designing crowd control through simulations, the appropriate crowd-control medium (objects used to convey control information, e.g., signages or security guards) and information should be selected, considering the crowd’s compliance with control instructions. However, there is still scope for further research on the influence of control medium and information on compliance behavior. Therefore, in this study, we measured the effectiveness of medium and information in guiding participants’ route choices by conducting a crowd experiment using virtual reality. The experimental findings confirmed that in terms of control medium, the guidance proffered by security guards was more effective than signage, with the odds of compliance rate approximately 1.54 times greater. Regarding control information, Guide control (direct guidance instruction) was more effective and received approximately 1.22 times greater odds of compliance rate than Advise control (indirect guidance through information presentation). Crowd-control designers can use the results obtained in this study to evaluate the effectiveness of control measures in crowd simulations.

In tourist facilities, managing ticket sales can reduce congestion imbalances. This study reports on the results of a pilot experiment conducted at Kaiyukan in Osaka, one of the largest aquariums in Japan. The experiment utilized pre-sale ticket data for controlling admission time intervals, smoothing the number of admissions through dynamic pricing, and predicting visitor numbers. The study reviewed the effectiveness of each of these approaches to alleviate congestion inside Kaiyukan. We then report on a method to predict the number of visitors from the pre-sale conditions of Kaiyukan admission tickets. It was found that setting entry times to 15-minute intervals was most operationally advantageous for the Kaiyukan. Moreover, the behavioral effects induced by variable pricing were more effective when prices were changed based on time slots rather than on a daily basis. Compared to the Holt–Winters’ method, we were able to maintain stable prediction accuracy even during consecutive holidays and long school vacation seasons.

For railroad operators with a highly public nature, ensuring the safety of passengers and revitalizing the areas along the line are both tasks to be accomplished. To enhance passenger safety, it is necessary to keep congestion levels below a certain level on platforms and trains. Since traffic congestion generally occurs at certain times, such as in the morning, it is important to disperse traffic congestion during rush hours. In the past, railroad operators have encouraged passengers to voluntarily commute off-peak, but this has not worked as an incentive for passengers simply by improving comfort. Because of this failure, rail operators are considering a method of setting fare prices based on the time of day and congestion levels. However, past studies suggest that few users change their behavior because those who choose the time of day to use the railroads do not always coincide with the fare payers. Therefore, we devised a crowd management system in which coupons redeemable at stores along the rail line are given directly to the customers, encouraging voluntary off-peak commuting and stimulating the local economy. This system features dynamic updating of coupon ranks based on congestion forecast information from measured congestion levels to enhance the effectiveness of the service. The results of a three-month verification experiment that cooperated with Shizuoka Railway confirmed that 7.1% of passengers took congestion avoidance actions and that passengers who obtained coupons got off at a specific station an average of 29% more often.

Urban centers are getting crowded, public transportation is becoming congested, and mass events are attracting an increasing number of people. Crowd disasters are not rare, and to prevent them the careful planning of pedestrian facilities and collaboration among stakeholders in the organization of events are crucial. When communication and coordination among stakeholders are sufficient, safety can usually be achieved; however, even in such cases, unexpected situations may occur. Automated crowd-control methods are required to address such situations. However, little is known about how crowd behavior can be influenced without direct human intervention. In this study, we investigated the use of environmental stimuli to modify pedestrian behavior (more specifically, route choice) in an educational facility. Colors, lights, signs, and sounds were used to influence route selection. The results show that light and, in part, LED information displays are somehow effective and could be valid candidates to pave the way for automated crowd control systems (especially for night events). The experiment presented here considers low crowd density. However, we believe that this could help encourage the balanced use of space by pedestrians under normal conditions and establish good practices. In turn, this can delay the creation of high densities, which are often the cause of fatalities in crowd disasters, and provide staff with time for intervention.

Accurately evaluating pedestrian congestion is crucial for evidence-based improvements in various walking environments. Tracking pedestrian movements in real-world settings often leads to incomplete data collection. Despite this challenge, pedestrian congestion with missing data has not been extensively addressed in existing research. This study examined the impact of missing data on density, speed, and congestion number in the course of evaluating pedestrian congestion. While density is the most commonly used index, speed and congestion number proved more robust.

In event management, preventing excessive overcrowding is not only essential for providing comfort but also crucial for ensuring safety. However, understanding the crowd dynamics of participants in outdoor events can be challenging. One of the primary reasons is the limited availability of sensing systems suitable for outdoor use. Challenges include the need for power outlets and adapting to dynamic environmental conditions and unclear event boundaries. Consequently, there is still uncertainty about which measurements can be conducted to scientifically manage crowding based on sound principles. Therefore, there is a need for systems that are capable of discerning spatial and temporal heterogeneity in density and accurately estimating the number of people in regions of interest in both sparse and congested areas. In this study, we propose a novel approach for measuring and understanding crowd states at outdoor events. We designed a highly portable measurement system utilizing Bluetooth technology to monitor crowd density in real time, ensuring uninterrupted data collection even in remote event locations. This system stands out for its ability to operate effectively under diverse weather and lighting conditions without power outlets, making it highly adaptable to various outdoor settings. In our experiments, conducted at four distinct outdoor event locations, we used a 360° camera and LiDARs to validate the system. For instance, we deployed the system at 40-m intervals in a shopping district during a high-density parade. This deployment enabled us to capture the movement of the crowd and estimate the total number of people within the district. A key finding was the system’s capability to detect temporal and spatial congestion in both sparse and crowded areas. The system’s potential to estimate crowd sizes and manage diverse outdoor events marks an advancement over traditional methods like cameras and LiDARs.

In some natural parks, introducing a shuttle bus system as an alternative to private cars can help reduce congestion and protect nature. This study examines the pilot program to effectively induce visitors to switch to the shuttle bus, while examining the visitors’ understanding of the expansion of the restricted vehicle section in Shiretoko National Park—a World Natural Heritage site known for its rich natural resources, especially as a high-density habitat for brown bears. There are concerns about conflicts between visitors and brown bears that appear along roads. Visitor restrictions, such as limited access to transportation, limit the use of a place and alter the behavior and experience. Therefore, careful consideration is needed before introducing visitor restrictions. The results of our questionnaire survey of visitors indicated that most favored the expansion of the shuttle bus section. The choice experiment revealed that the guides on the bus and an optional experience encouraged visitors to switch to the shuttle buses. Nonetheless, awareness of the pilot program was low, and some visitors preferred their cars, indicating the need for further promotion of awareness and understanding of these new measures.

Understanding how visitors respond to crowding is crucial for ensuring the success, safety, and overall enjoyment of large-scale exhibitions. However, despite its significance, limited research has explored this issue. To address this gap, we conducted a questionnaire survey in 2022 and 2023 for visitors to exhibitions held at the Tokyo Big Sight Convention Center. Our research aims to explore the level of consistency between perceived and actual crowding, levels of discomfort in crowded situations, tolerance levels for crowding, and behaviors to avoid crowded situations. The results revealed significant changes in visitor perceptions across the two-year period. Notably, the acceptable crowd density in 2023 increased by 13% compared to 2022. This change in level of tolerance for crowding might have been influenced by the COVID-19 pandemic and other contextual factors that altered visitors’ perceptions toward crowding. Interestingly, despite these perceptual changes, behaviors to avoid crowded situations remained consistent across both years. The most common response was that no special action was taken to avoid crowded situations. These findings underscore that perceptions and behaviors related to crowding in the context of large-scale exhibitions are not uniform. Our findings offer several implications and insights for crowd management, which event organizers can use to devise strategies aimed at enhancing visitors’ experiences and effectively managing crowding in large-scale exhibitions.

Human crowd behavior is an intriguing example of collective behavior where global dynamics emerge from interindividual interactions. Although most studies of human crowds assume that all individuals are independent, the presence and impact of social groups, such as friends or families, have recently been explored. Spatial structures resulting from group behavior and decision-making processes are key aspects of social groups, and how such structures are formed and the impact of these are largely unknown, especially in the scenario of crowd evacuations. Here we experimentally show that in the vicinity of exits, dyads and triads form a representative formation, which would attenuate a disadvantage of small groups that are typically regarded as moving obstacles toward the evacuation dynamics. In laboratory experiments on crowd evacuations regarding small group behavior, we first observed no noticeable differences of egress time between monads and groups, which is contrary to a naïve intuitiveness but in agreement with recent experimental observations. To resolve this contradiction, a detailed analysis focusing on behavior in front of exits suggests that group members constitute a straight-line structure vertical to the exit. Our findings offer a new perspective on how adaptive small group behavior emerges during crowd evacuation.

This study analyzed behavioral changes in South Korean individuals during the COVID-19 pandemic due to movement restrictions and examined their psychological effects. Attributes considered include age and gender, place of residence, and characteristics of the residential environment and communities they came into contact with, which are considered important factors in individuals’ psychological changes. The results showed that in terms of psychological change, the negative effects were more significant for attributes such as age and gender than for spatial characteristics such as residential area and type of residence. In addition, depression was found in specific gender and age groups. In particular, those in their 20s were found to be more depressed than those in their 30s and 40s, even though they were less prone infection with COVID-19 than older adults. Through the findings of this study, we have discovered materials and factors that should be taken into account when preparing policies to limit the motion of people in circumstances similar to a pandemic.

The novel coronavirus (COVID-19) pandemic has been a major global event. Countless restrictions and recommendations have revealed novel insights into the everyday lives of people, which are far from uniform across cultures. In this explorative study, the mood perception of people from “individualistic” (Finland) and “collectivistic” (Japan and South Korea) cultures were studied via self-administered questionnaires at the time of major social restrictions (spring–summer of 2020) when the sociocultural effect of the pandemic was at its strongest. A simple measure of “recent mood perception” forms the core of the analysis, against which various factors were analyzed. Such coarse measures fit well with cross-cultural research, for more specific experiences typically do not translate very well between cultures. Somewhat surprisingly, almost no “constant” measures (e.g., occupation, household structure) proved to be significantly correlated with recent mood, whereas the degree of “changes” in personal situation (time spent home, number of people met, and so on, before and after the outbreak) proved to be significant factors, highlighting contextuality and mindset. Further, difference between “individualistic” and “collectivistic” cultures was also observed. These results highlight the vital importance of not only observing consistent phenomena but also recognizing changes and understanding the unique perspectives and experiences individuals have of them. Depending on the context, an objectively same thing can evoke vastly different perceptions.

We used LiDAR to detect and track people in an exhibition facility for better crowd management. The results were treated as time series data and visualized using a web application. In addition, we verified visitors’ stopping points to quantify interest in various exhibits, and found that by checking the time visitors spent in front of exhibits in 10-second intervals, the places in the exhibition hall that interested visitors could be visualized. The results suggest that the time classified as viewing is not necessarily longer, but that a threshold that takes into account the facilities and routes within the exhibition facility should be set.

The literature on the appropriate education criteria for training young emergency responders in developing countries is scarce. A gap exists between general education and emergency responder education regarding the criteria used for designing education courses and evaluating students. This study reviewed the criteria used at the University of Fire Prevention and Fighting in Vietnam. Although the university had used Bloom’s taxonomy, one of the well-known evaluation criteria for general education programs, in addition to the professional criteria for emergency management, only the bottom three levels of the taxonomy were considered. The authors designed a new training course to prepare and conduct landslide rescue exercises, and applied all six levels of Bloom’s taxonomy to evaluate students’ performance and responses. The course included lectures, an exercise, and a hot debriefing session for 52 third-year students. Consideration of all levels of Bloom’s taxonomy enabled the identification of differences in learning performance between exercise participants and observers among the students. The evaluation results based on the general and professional education criteria differed regarding the performance of students with work experience. This study showed that the full use of Bloom’s taxonomy could help improve firefighters’ training courses. Assessing students from different perspectives using both general and professional education evaluation criteria is important for measuring students’ diverse abilities.

Monitoring wastewater quality at the inlet of a wastewater treatment plant provides an overview of the health of the community connected to the respective wastewater treatment plant. Wastewater monitoring has been increasingly recognized as a valid tool in pandemic risk management, especially during the coronavirus disease 2019 (COVID-19) crisis. However, the results of wastewater monitoring are not yet fully utilized in the decision-making process of public governance across most of the Asia-Pacific region. This study explored the potential of geographic information systems to map the results of wastewater monitoring and provide a common operating picture for swift and informed decision-making, especially in times of disasters. By creating an online dashboard tool, we found that an additional merit of mapping wastewater monitoring is that it allows overlaying various other information, such as evacuation shelters, onto the same map. As the service areas of wastewater treatment plants, or sewersheds, are not necessarily aligned with geopolitical boundaries, mapping provides opportunities for re-calculating wastewater monitoring results at the city or district levels. The potential for recalculation is also applicable to overlayed information, indicating that information from wastewater monitoring may be used to assess disaster preparedness or multi-hazard risks. The dashboard prototype was discussed with government officials and feedback was obtained. We aim to further develop the findings so that the information from wastewater monitoring can be shared on a platform, such as the shared information platform for disaster management, in the future for effective risk governance.

The distribution of the ambient dose equivalent rate (i.e., air dose rate) after a nuclear disaster is crucial for zoning contaminated areas to facilitate authorities’ effective decision making. Several countries are considering a gradual characterization strategy where airborne measurement is performed first followed by ground measurement (i.e., via manborne or carborne surveys). Nonetheless, potential differences might emerge in country-specific air dose rate assessment methods. Explaining these discrepancies can improve and converge existing methodologies. The Japan Atomic Energy Agency (JAEA) and the French Institute for Radiological Protection and Nuclear Safety (IRSN), which are organizations involved in post-nuclear accident crisis management, jointly performed air dose rate measurements in 2019 at contaminated sites around the Fukushima Daiichi Nuclear Power Station. The similarities and differences between the two organizations’ methods and results were quantitatively assessed by comparing the average air dose rates obtained within a grid created with a geographic information system, and the reasons for the differences between the organizations’ results were investigated. The air dose rates obtained by the manborne measurements varied depending on the calibration method. Comparing the air dose rate assessment methods and mapping techniques used in different countries will contribute to developing international guidelines for recommending the best method for determining air dose rates.

Universities were the only educational institutions that restricted in-person lectures during the prolonged coronavirus disease 2019 (COVID-19) pandemic. This study is the first attempt to estimate the effects of restricting in-person lectures on containing the spread of COVID-19. Our investigation was conducted on Japanese universities since their various lecture styles are suitable for our analysis. A multiple-event study negative binomial regression model was employed, and the results showed that restricting the ratio of in-person lectures had limited effects on decreasing COVID-19 infections among university students. For example, if universities restrict almost all in-person lecture from a rate of over half of in-person lectures, the number of student infections would decline by 5.5 per 10,000 students between seven weeks before and after the change. Other lecture style changes had even smaller differences. In addition, we estimated the effect of the start of long breaks on the number of infections and found that they lead to a relatively higher level of infections regardless of lecture styles at the end of semesters. This implies that students are more likely to be infected outside than in class.

The middle reach of the Helmand River is prone to floods, and flood hazard analysis is necessary to manage the flood risk. As the study site is a less-developed basin where available geographical and hydrological data are limited, we must utilize available limited data to conduct the flood hazard analysis. A frequency analysis of the annual peak flow rate was performed using available hydrological data for making representative flood hydrographs. A land-use map is derived by classifying recent Landsat images. Digital elevation model derived by Advanced Land Observing Satellite, roughness coefficient correlated with the land-use map, and the representative flood hydrographs are fed into hydraulic model HEC-RAS 2D. Flood inundation area, depth, and velocity for different flood return periods are estimated. Based on local hazard intensity and vulnerability, risk maps for evacuation and vulnerability of crops on the floodplain are obtained. Spatial flood risk characteristics differ at the upstream and downstream reaches because of distinct floodplain topography. Flood countermeasures for each reach are proposed based on the spatial characteristics of the flood risk. To provide risk information for residents within the region, the flood hazard, risk, and damage maps derived in this study are published as a web map application and a mobile native application.

Landslides govern the evolution of landforms and pose a serious threat across the globe, especially in mountainous areas. In the northwestern area of Vietnam, a slow-moving landslide occurred near an important economic road corridor in Caumay Ward, Sapa Town, Laocai Province. In December 2019, some serious cracks were observed at a construction site near this landslide. Since this phenomenon could cause not only loss of life but also damage to the properties located downhill, the construction was abandoned until the slope was rehabilitated. Geological investigations, laboratory tests, and surface displacement monitoring were conducted to understand the failure mechanism. The analysis results showed that the anthropogenic activities associated with the rising groundwater level due to frequent rainfall events, owing to climate change, had contributed to the sliding of the sloping soil mass. The rehabilitation works at the failed area were conducted chronologically in two stages: (1) backfilling at the downhill area; demolishing two villas located within the sliding area to reduce surcharge; constructing an anchor system in the uphill area, and (2) constructing the anchored wall at the downhill area. During the rehabilitation works, the Caumay landslide was observed to initially undergo gradual movement and then stabilize at the end of the first stage of the rehabilitation works. The rehabilitation techniques adopted at the failed site were validated using both numerical analysis and field measurements. The anchor reinforcement methodology adopted in this study is expected to help agencies and the public in stabilizing landslide-prone areas for residential and other infrastructure construction.