Stampede Accidents Research Articles

Study on pedestrian evacuation simulation model considering group behavior

As a crowded place on the university campus, the cafeteria inevitably has many safety hazards, such as fire accidents caused by open flames and large appliances, stampede accidents caused by overcrowding during peak dining hours, etc. Therefore, studying pedestrian evacuation in university campus cafeterias is particularly necessary. Pedestrians on campus mostly travel in groups. Previous studies mainly used continuous models to discuss pedestrian group evacuation behavior. In this study, based on the cellular automaton pedestrian evacuation simulation model, the floor field calculation method was improved. A cellular automaton pedestrian evacuation simulation model considering group behavior was established and applied to the evacuation scenario of students in a university campus cafeteria. The study found that under the different group configurations, the pedestrian ratios, and the pedestrian densities, the pedestrian evacuation efficiency had significant differences. The results showed that when the different group configurations existed in the scenario, the higher the proportion of the pedestrians with three-person front-to-back group configurations, the higher the evacuation efficiency. When only one type of the group configuration existed in the scenario, at low pedestrian density, the evacuation efficiency of the individual pedestrian groups was higher compared to the other six group configurations. While at high pedestrian density, the evacuation efficiency of the three-person front-to-back group configurations was higher. These findings provided important references for pedestrian evacuation in university campus cafeterias and provided insights for the simulation research of group pedestrian evacuation models, contributing to enhancing campus safety management and ensuring the safety of teachers, students, and staff.

An extended model for crowded evacuation considering stampede on inclined staircases

An extended floor field cellular automata (FFCA) model considering the stampede accidents on inclined staircases is proposed to study shoving behavior and pedestrian dynamics. In this model, two stampede evolution pathways are investigated: Pedestrians falling after losing balance, and falling directly due to being crowded. The results show that this model could trigger some characteristics of real irrational evacuation processes, such as: (1) the mutual crowding and shoving among pedestrians; (2) the unbalance phenomenon on inclined staircases; (3) the effect of pedestrians falling like dominoes, which is consistent with the findings of most stampede investigations to some extent. The proposed model considers the impact of fallen pedestrians on the movement of ordinary pedestrians, which shows a reduction in the overall evacuation efficiency. Moreover, the steeper the slope, the greater the risk and severity of injuries during the crowded evacuation in this scenario. Additionally, falling phenomena of pedestrians show a certain lag related to the state of unbalance. Unbalanced pedestrians tend to appear from the rear to the front successively, and fallings often occur some time later the onset of unbalance, progressing from front to rear. This pattern reflects the “domino effect” among pedestrians. Lastly, unbalanced pedestrians constitute a significant portion of the total injured pedestrians. Considering the time delay of fallings after being unbalanced, the importance of early emergency response and intervention during crowded evacuations is emphasized. It is expected to provide some theoretical support for safety management.

Urban rail transit disruption management based on passenger guidance and extended bus bridging service considering uncertain bus running time

Disruptions occurring at an urban rail transit (URT) system can severely affect its normal operations, and an effective bus bridging service (BBS) is able to help to reduce the negative effects. Transit operators usually arrange BBS to depart from the disrupted stations to evacuate the stranded passengers. However, the overload of passengers at the disrupted stations, especially at turnover and transfer stations, may incur the secondary operation disruptions such as stampede accidents. To mitigate the negative effects of disruptions and reduce the number of passengers stranded at the disrupted stations, the strategy based on the passenger guidance and extended BBS (E-BBS) is introduced in this paper. Different from the widely applied standard BBS running within the disrupted links, E-BBS runs among the normal operating stations or between the normal operating stations and the disrupted stations. A mixed integer linear programming model is developed in this paper to guide the stranded passengers and design an optimal E-BBS solution to transport them. Considering the bi-directional running trains along the disrupted links, a dynamic decision framework is developed to manage the disruptions. Given the impacts of the high uncertainty on bus running time which could affect the performance of E-BBS, a robust model is proposed to obtain more reliable travel guidance and E-BBS schemes. Numerical experiments based on Chengdu subway system in China are conducted. The results indicate that the proposed model can obtain optimal travel guidance and E-BBS solutions in a timely manner. When the uncertainty on bus running time is ignored, the total travel cost for affected passengers is reduced 14.20 % on average with the aid of the optimal travel guidance and E-BBS solutions. Moreover, the number of passengers gathering at the disrupted stations decreases by 36.80 %. The robust model can obtain more reliable travel guidance and E-BBS schemes in consideration of uncertain bus running time. The proposed model shows great potential to effectively mitigate the negative effects of disruptions and help to enhance the capability of a URT system to respond to disruptions.

Dynamic coupling model of FDS and cellular automata considering trampling behavior

Fire accidents usually cause large casualties. In this paper, a fire evacuation model based on the dynamic coupling of FDS and CA, which dynamically couples disaster data and evacuation behavior, is designed to reflect the impact of disaster factors on the pedestrian evacuation process in real-time. Furthermore, pedestrians are divided into two categories, one type of pedestrians will choose to move against the wall to reduce the risk of stampede accidents, and the other type of pedestrian will evacuate to the exit according to the normal movement method. And considering the role of information transmission between pedestrians, the two types of pedestrians will transform into each other. In addition, the concept of pedestrian crowding, support, and friction is introduced and viewed as an influencing factor of normal pedestrian falls. Set the panic value as the influencing factor of the efficiency of pedestrian information transmission and the death probability of downed pedestrians. The impact of pedestrian density, pedestrian walking behavior towards walls, evacuation response time, information propagation radius, heat release rate of the fire source, and the interference of smoke on the pedestrians' visibility range on evacuation outcomes has been discussed through numerical simulations. The analysis shows that although the presence of pedestrians walking against the wall will slightly increase the evacuation time, when the available evacuation time allows, the risk of a stampede will be greatly reduced; The increase in evacuation response time will aggravate the panic psychology of pedestrians and increase the risk of stampede accidents; The increase of the pedestrian information transmission radius will reduce the risk of a stampede, and the effect is more obvious when the pedestrian density is smaller; Selecting building materials with lower heat release rates can effectively reduce the risk of fire incidents; The restriction of visibility range by smoke seriously endangers pedestrian safety and reduces the efficiency of evacuation.Our research results can play a reference and guide for future building disaster prevention design and public safety research.

Forecasting Short-Term Passenger Flow of Subway Stations Based on the Temporal Pattern Attention Mechanism and the Long Short-Term Memory Network

Rational use of urban underground space (UUS) and public transportation transfer underground can solve urban traffic problems. Accurate short-term prediction of passenger flow can ensure the efficient, safe, and comfortable operation of subway stations. However, complex and nonlinear interdependencies between time steps and time series complicate such predictions. This study considered temporal patterns across multiple time steps and selected relevant information on short-term passenger flow for prediction. A hybrid model based on the temporal pattern attention (TPA) mechanism and the long short-term memory (LSTM) network was developed (i.e., TPA-LSTM) for predicting the future number of passengers in subway stations. The TPA mechanism focuses on the hidden layer output values of different time steps in history and of the current time as well as correlates these output values to improve the accuracy of the model. The card swiping data from the Hangzhou Metro automatic fare collection system in China were used for verification and analysis. This model was compared with a convolutional neural network (CNN), LSTM, and CNN-LSTM. The results showed that the TPA-LSTM outperformed the other models with good applicability and accuracy. This study provides a theoretical basis for the pre-allocation of subway resources to avoid subway station crowding and stampede accidents.

Analyzing dynamic risk of stampede in stadium: A quantitative method considering the various status of risk factors in whole process

With the increase of large-scale mass activities, stampedes of deaths and injuries easily occur. The bidirectional qualities between the state's shifting combinations of different risk factors and accidents must be more thoroughly analyzed. The triangular fuzzy number and the Bayesian network are applied in the study to construct a risk analysis model for stadium stampede accidents. 46 accident samples and 24 risk factors closely related to activities were collected for the study. The results show that 7 factors, including audience mood, vulnerable groups, retrograde crowd, abnormal person, flammable and explosive material, walkway in stadium, and special time period, are more likely to cause stampede incidents. When the factors related to the live audience are added together in the most dangerous state, the probability value of the activity safe state decreases from 86% to 31%. In particular, the mood state of the audience, ranging from the more excited to crazy, is most sensitive to stampede. In addition, four major causal chains are obtained. The two risk factors, crowd flow limitation measures and safe entrance and exit, contributed most significantly to the stampede when the personnel volume ratio began to exceed 80% or when the security entrances and exits were partially closed. The model constructed in this paper can dynamically demonstrate the rules between the transition combinations of different states of risk factors and stampede. It will provide some theoretical basis for the process safety management of large-scale mass activities in stadiums.

An extended model describing pedestrian evacuation considering pedestrian crowding and stampede behavior

In recent years, stampede accidents have occurred frequently, resulting in significant casualties and property losses. In this paper, an extended cellular automata model is designed to investigate the behavior of pedestrian stampedes. The concept of pedestrian crowding, support, and friction is introduced and viewed as an influencing factor of normal pedestrian falls Besides, the state of pedestrians after falling to the ground is analyzed. The fallen pedestrians may return to normal or be trampled to death. Through the numerical simulation, the stampede phenomenon in pedestrian evacuation in public places is explored, and the influences of pedestrian density, pedestrian distribution mode, exit setting, and obstacles at the exit on the evacuation results are discussed. The analysis demonstrates that the greater the pedestrian density, the more the pedestrians fall to the ground and die. Moreover, pedestrians are more likely to die after falling to the ground with the increase in pedestrian density. At the beginning of the evacuation, the risk of the pedestrian stampede in decentralized distribution is less than that in centralized distribution. The exit is located on the left or right of the center of the wall when the pedestrian density is small, making it less dangerous than the middle position. The safety is higher when the number of exits is large. Additionally, the existence of obstacles at the exit can reduce the risk of stampede accidents when the pedestrian density is small. Our research reveals the mechanism and influencing factors of the trampling process to a certain extent, playing a reference and guiding role for future research.

Risk analysis of stampede in sporting venues based on catastrophe theory and Bayesian network

With the continuous increase of large-scale activities, it is easy to occur serious stampedes. This study focuses on sporting venues to study stampede accidents in large-scale activities for quantitative and dynamic risk analysis. A comprehensive risk analysis model for stampede accidents is established containing 96 nodes that take into account human error, site failure, environmental impact, and management deficiency, and it is applicable for most sports venues as the relevant inputs can be consistent with reality. First, the bow-tie method is applied for risk identification, and the catastrophe theory is introduced to better handle the expert system and statistics to establish the Bayesian network. Then, scenario analysis is implemented to dynamically predict the consequences, and sensitivity analysis is conducted to quantitatively identify the critical factors of the stampedes. It is identified that the failure of emergency lighting and indicating signs contribute more to the occurrence of a stampede, and the effective emergency measures are critical to reducing the casualties and economic losses. This paper could quantitatively assess the stampede risks and find out the critical hazards of stampede accidents in detail to provide technical and managerial support for most sports venues.

Acceleration-critical density time-delay model for crowd stability analysis based on Lyapunov theory

Crowd stability analysis is one of research hotspots to alleviate the severe situation of stampede accidents worldwide. Different from the conventional analysis models for crowd stability based on pedestrian density, this study analyses the characteristics of external disturbances and internal obstacle disturbance based on Lyapunov's theory. The critical range of crowd acceleration in crowd evacuation is obtained, a crowd merging acceleration-critical density time delay model is established, and a stability criterion of acceleration vector based on Lyapunov is obtained based on Lyapunov stability analysis. This provides new information for ensuring the stability of crowd movement in public places, assessing the stability of the crowd in the area, and taking reasonable protection and guidance measures prior to instability of a crowd flow.

Human stampede causative factors and cluster risk: A multi-dimensional analysis based on ISODATA and Fuzzy Theory

Although the interest in statistical analysis of human stampedes has increased to explore the characteristics of accidents, more effort is needed to address the complexity of causative factors and their relations to risk, due to their variability and uncertainty in each case. This study aims to examine the causative factors of human stampedes for different groups of cluster risk by introducing a combined method, the Iterative Self-organizing Clustering Algorithm (ISODATA) and Fuzzy Theory. Totally about 215 cases were collected to construct a structured dataset, and characteristics of human stampedes including accident site, accident consequence, accident type, manmade factors, hardware factors, environment factors and management factors were considered for this analysis. Results show that factors such as accident type has similarity with single-dimensional analysis, while accident site in the highest risk cluster has a different distribution with the proportion of temples 39% and schools 28% which is contrary to the highest 23% of stadiums in single-dimensional analysis. It was concluded that the site with high incidence of stampede accidents did not necessarily have a high degree of risk, due to it had a high frequency of accidents but causes little casualties. Based on model results, control points for different sites are recommended according to the characteristics of different cluster risk. This paper provides a quantitative method to compare and analyze the causative factors of different risk clusters, which has relative comparative significance and improves the accuracy of judging the risk degree that can provide basis for human stampede prevention and management.

A high-density crowd state judgment model based on entropy theory.

A high-density crowd state is prone to cause large-scale crowd stampede accidents that seriously threaten the people's security and property. The key to preventing crowd congestion is to accurately predict the location and time of crowd events, particularly when there is a high density of people. In this paper, the entropy theory is used to characterize the state of a crowded system. The theoretical entropy Sr and the actual entropy S of the crowd system are obtained according to the area occupied by the different crowd state The maximum entropy value and the actual entropy value under different conditions of the system are compared to judge the state of crowded extent. The results show that the model is practical and effective. According to the situation of the crowd, different management and evacuation measures are considered to prevent the occurrence of crowd accidents.

Observational characteristics of pedestrian flows under high-density conditions based on controlled experiments

High-density crowds are associated with high risks such as stampede accidents. Therefore, it is important to understand the dynamics of high-density crowds. We performed experiments in both a 1.5-m-wide ring corridor and a single-file circular track to study pedestrian flow dynamics under high-density conditions. For the wide-track experiment, we examined global densities as high as 9 ped/m2. Our main findings were as follows. (i) The middle section of our unidirectional fundamental diagram exhibited a clear similarity to that of a single-file pedestrian flow, which enabled us to distinguish two different kinds of congested pedestrian flow. (ii) The unidirectional fundamental diagram for a high-density situation was quantitatively nearly the same as that observed in the empirical data. (iii) In the absence of a bottleneck, typical stop-and-go patterns did not emerge in the unidirectional flow on the 1.5-m track. Instead, some high-density clusters propagating downstream can be observed. (iv) In the bidirectional flow experiments, three different lane formation processes were observed. The processes were quite quick, even under very dense conditions. (v) When three lanes formed, the bidirectional flow rate was much larger than the unidirectional flow rate due to the inhomogeneous distribution of pedestrians across different lanes. (vi) At high densities, the unidirectional and bidirectional flow rates were nearly the same. However, a bottleneck emerged in the bidirectional flow due to the variable width of the opposite streams. Our study helps to achieve a better understanding and modeling of the dynamics of high-density pedestrian flows.

Propagation characteristics of the pedestrian shockwave in dense crowd: Experiment and simulation

Crowd shockwave is a very common phenomenon in dense crowd, which is likely to cause crowd destabilization and stampede accidents. Several researches on crowd shockwave have been reported, but its explicit concept and particular mechanism need to be further investigated. In the paper, the main causes and the definition of crowd shockwave were proposed based on experimental observation and existing accident information. Combined with the experiment scenario, a crowd shockwave simulation model was established based on the social force theory. In order to understand the transmission mechanism of crowd shockwave, the amplitude that is indicated by the maximum density, the propagation speed and the duration of the crowd shockwave were acquired and analyzed based on the density waves from the simulation. Meanwhile, the simulation results were verified by the experiment. The outcomes can offer a few relevant control strategies to eliminate or reduce the crowd shockwave, thereby prevent trampling accidents.

Fundamental diagrams for pedestrian traffic flow in controlled experiments

Heavy casualties in stampede accidents in recent years have brought new challenge to crowd management and public safety as well. Therefore, a series of controlled experiments were conducted to investigate traffic dynamics of pedestrians in this paper. The fundamental diagrams for unidirectional flow, bidirectional counter flow, bidirectional cross flow and four-directional cross flow are surveyed by using the improved Voronoi diagram measurement method. The maximum specific flow and the optimal density are obtained from the density–flow relation. Furthermore, difference of fundamental diagrams for different pedestrian flows is also discussed. Evolution of individual density and individual velocity in the Voronoi cell is explored and the dangerous area for pedestrians is identified. Movement efficiency under different densities is investigated when passing through the intersection. The study is helpful to develop a modular approach that serves as a basis for the planning and evaluation of large scale public events.

Stampede Prevention Design of Primary School Buildings in China: A Sustainable Built Environment Perspective.

In China, crowd stampede accidents usually take place within crowded areas in middle and primary schools. The crowd stampede risk is particularly related to the architectural design such as the staircase design, the layout of crowded places, obstacles, etc. Through the investigation of building design in several primary schools, the relationship between the sustainable layout of crowded places (e.g., toilets, canteens, playgrounds, staircases) and the crowd stampede risk of students are introduced via agent-based simulations. In particular, different experimental scenarios are conducted on stairs in the primary buildings. The evacuation processes are recorded by video camera and spatial stepping characteristics (e.g., foot clearance, step length, mass center, the distance between the mass center and ankle, and etc.) are extracted from the video. Dynamic steady ability is investigated by adopting the margin of stability, quantified by the instantaneous difference between the edge of the base of support and extrapolated vertical projection of the mass center. Based on the sustainable built environment principles and historical data of students, this paper focuses on an in-depth analysis of the staircase design aiming at preventing the crowd stampede risk.

The occurrence laws of campus stampede accidents in China and its prevention and control measures

Stampede accidents have become the major threat to campus security in China. In order to grasp the occurrence regularity of campus stampede accidents in China and to prevent the accidents, statistical analysis methods and case analysis methods were employed to study the temporal and spatial characteristics and inducing factors of campus stampede accidents in China during 2000–2014. The results showed that the occurrence frequency and casualties of campus stampede accidents in China had larger inter-annual changes and presented a decreasing trend overall. Autumn had the largest occurrence frequency and casualties, respectively, accounting for 63 and 74%; winter took the second; and spring and summer were the least. Campus stampede accidents in China were distinct in week variation and an existed Monday phenomenon. Monday had the largest occurrence frequency and casualties, respectively, accounting for 32.4 and 23.1%. Campus stampede accidents in China mostly occurred in south-central China, and in the northwest and southwest borderlands. 92.3% of stampede accidents occurred on stairs. Primary schools had the highest occurrence frequency and casualties, occupying 71.2 and 60.7%. Education fund input, student–teacher ratio, and students’ enrollment had significant impact on campus stampede accidents in China.

A minor modification in the model for describing congestion and recovery along evacuation paths

In an emergency evacuation, evacuation paths are often prone to congestion, possibly resulting in congestion and stampede accidents. From the viewpoint of crowd behavior, relations between crowd density and pedestrian speed and between crowd density and the crowd flow rate are established, and crowd movement along evacuation paths is analyzed. A basic model of crowd movement along evacuation paths is developed and allows detailed analysis of the effect of the initial crowd density on congestion. Finally, the relationship between crowd congestion density and speed of recovery and a method of calculating the time of congestion disappearance are presented. This research will assist on-site management in preventing possible crushing and stampede accidents during large-scale social activities.

An Emergency Evacuation Model Based on Computer Vision Smart Inducing in Hotel Stampede Environment

Stampede accidents in hotel crowded area will cause disorder in flow information. As we know, flow density and direction of movement have strong nonlinearity and mutation. This paper proposes a complex network model for rapid evacuation based on computer vision smart inducing. On basis of images' process, the paper fully considers the mutation of flow and direction by the mutation operator of flow direction, and increases the evacuation speed by extracting mutation parameter of local area and feeding back it to control terminal. The experiment results show that the proposed algorithm improves the accuracy and speed of evacuation in hotel stampede environment.

Causes of hospitalization of pilgrims during the Hajj period of the Islamic year 1423 (2003)

BACKGROUNDApproximately 2 to 3 million pilgrims perform Hajj every year. Planning for health care requires knowledge of the pattern of diseases, complications, and outcome of pilgrims who require hospitalization during the Hajj period.METHODSIn a cross-sectional study we compiled data on all patients admitted to 1487 beds in four hospitals in Mena (793 beds) and three hospitals in Arafat (694 beds) from the seventh to the thirteenth day of the Hajj season of the Islamic year 1423, corresponding to 8 to 14 February 2003.RESULTSOf 808 patients hospitalized, most (79%) were older than 40 years. There was no sex preponderance. A total of 575 (71.2%) patients were admitted to medical wards, 105 (13.0%) to surgical wards, and 76 (9.4%) to intensive care units. Most patients (84.8%) had one acute medical problem. Pneumonia (19.7%), ischemic heart disease (12.3%), and trauma (9.4%) were the most common admitting diagnoses. More than one third (39%) had co-morbid conditions. A total of 644 (79.7%) patients were discharged from the hospital in stable condition to continue therapy in their residential camps, 140 (17.3%) were transferred to other hospitals in Makkah for specialized services or further care, 19 (2.3%) were discharged against medical advice, and 5 (0.7%) patients died.CONCLUSIONThis study provided information on the most common causes of hospitalization, pattern of diseases, and required medical services for pilgrims in Hajj. It is hoped that this data will be of help to health sector planners and officials to provide optimal and cost-effective health care services to pilgrims in Hajj.