Pushing Behavior in Ro‐Ro Passenger Ship Evacuations: A Social Force Model Analysis

The emergency scenarios of passenger ships are reproduced unrealistically by evacuation drills due to cost and safety limitations, and model simulation is an effective alternative method. To study the evacuation efficiency of an inclined ship, a deck of a Ro-Ro ship with 1065 passengers was modeled on a simulation platform developed based on a social force model (SFM). A series of inclined scenarios were produced by adding the walking speed attenuation factor to the individual parameters. Furthermore, the influence of crew’s guidance was considered in this model, and the effects on evacuation were also analyzed for the entire deck. The simulation results show that the larger the inclination angle is, the more evacuation time that is needed. When the largest inclination angle was 20°, the evacuation time increased by 32.6%. In addition, the participation of crew’s guidance in all of these scenarios significantly accelerated the evacuation efficiency, and this benefit was achieved by the evaluation of the exit flow and congestion level by crew. However, organizing orderly evacuations as soon as possible when the inclination angle is less than 15° and making maximum efforts to ensure evacuation success are still recommended. The findings provide useful insights into a large group of Ro-Ro passenger vessels under inclined emergency evacuation.

An investigation of fire evacuation performance in irregular underground commercial building affected by multiple parameters

Pedestrian movement modeling and simulation is an important way to formulate an emergency evacuation plan. The performance of the pedestrian movement model directly determines the accuracy of the simulation experiment results. Pedestrian movement in the real world is a very complicated process, and this process is susceptible to a variety of external factors (e.g. road conditions, visibility, etc.) and internal factors (e.g. psychological states, etc.) which making it difficult to model pedestrian movement. The social force model draws on the principles of mechanics and proposes a modeling scheme from the perspective of social force which greatly simplifies the process of pedestrian movement modeling. However, the traditional social force model considers the general situation of pedestrian movement and does not target the emergency evacuation scene, which has certain limitations. In this paper we start with the social force model and introduces the concepts of external guides and internal panic emotions to improves the model. In the scene, the influence of the attraction of the guide and the psychological state of the pedestrian on the movement process of the pedestrian are considered. So that the model is more suitable for the emergency evacuation scene with limited field of vision. It also provides a reference for emergency evacuation plans in public places. We take the subway station as the research object and uses Anylogic software to build simulation experiments. The experimental results show that the improved model we proposed in this paper is less than the traditional model in terms of evacuation time by 8.4%, and is better than the traditional model in terms of exit pedestrian density by 21.5%.

How to accurately simulate the real collective behavior of pedestrian evacuation remains an important issue in research of complex systems. The existing crowd simulation models in general assumed that pedestrians move directly towards the exit. In real life, however, there exist “cautious” pedestrians who fear trampling and crowding during evacuation, so we use an improved social force model to investigate how their presence influences evacuation dynamics. Simulation results reveal that the total evacuation time does not increase monotonically with the increment of the number of cautious pedestrians. Specifically, the presence of a moderate number of cautious pedestrians with rational psychological tolerance might substantially facilitate evacuation efficiency, compared with a conventional evacuation scenario. In addition, lower psychological tolerance promotes emergency evacuation, while increasing the tolerance threshold is conducive to slow evacuation. We hope that our research will provide some insights into the reasonable optimal strategies for emergency evacuation.

Influencing factors for exit selection in subway station evacuation

Pedestrian evacuation risk of subway stations is an important concern in city management, as it not only endangers public safety but also affects the efficiency of urban subway transportation. Determination of how to effectively evaluate the pedestrian evacuation risk of subway stations is of great significance to improve pedestrian safety. Previous studies about the pedestrian evacuation of subway station were primarily focused on pedestrian moving behaviors and the evacuation modeling, and the evacuation scenario is the regular subway operation. There is a dearth of studies to quantify the pedestrian evacuation risk in the evacuation process, especially the pedestrian evacuation risk quantitative characterization of subway station in large-scale sport activity. The current study develops a quantitative pedestrian evacuation risk assessment model that integrates pedestrian stampede probability and pedestrian casualty. Then several different simulation scenarios based on the social force model (SFM) are simulated to evaluate the pedestrian evacuation risk of the “Olympic Park Station” in Beijing, China. The results demonstrate that the pedestrian evacuation method, pedestrian stampede location, and distance from the stampede location to the ticket gate have a large impact on pedestrian evacuation risk. Then, the pedestrian evacuation scenarios with the lowest and highest risk for the “Olympic Park Station” in large-scale sport activity are determined. The findings have potential applications in pedestrian safety protection of subway station during large-scale sports activity.

Human behaviour and evacuation time for large underground comprehensive buildings during fire risk process

We study the pedestrian motion along a corridor in a nonpanic regime, as usually happens in evacuation scenarios in, e.g., schools, hospitals, or airports, by means of Monte Carlo simulations. We present a model, a combination of the well-known social force model (SFM) and Vicsek model (VM), that takes into account both model interactions, based on the relative position (SFM) and based on the velocity of the particles with some randomness (modulated by an external control parameter, the noise η, VM), respectively. To clarify the influence of the model ingredients we have compared simulations using (a) the pure Vicsek model (VM) with two boundary conditions (periodic and bouncing back) and with or without desired direction of motion, (b) the social force model (SFM), and (c) the model (SFM+VM). The study of steady-state particle configurations in the VM with confined geometry shows the expected bands perpendicular to the motion direction, while in the SFM and SFM+VM particles order in stripes of a given width w along the direction of motion. The results in the SFM+VM case show that w(t)≃t^{α} has a diffusivelike behavior at low noise η (dynamic exponent α≈1/2), while it is subdiffusive at high values of external noise (α<1/2). We observe the well-known order-disorder transition in the VM with both boundary conditions, but the application of a desired direction condition inhibits the existence of disorder as expected. Similar behavior is observed in the SFM case. For the SFM+VM case we find a susceptibility maximum which slowly increases with system size as a function of noise strength. This might be indicative of a order-disorder transition in the range of densities (ρε[1/12,1/9]) and speeds (v_{0}ε[0.5,2]) studied.

Emergency Evacuation Model and Algorithm in the Building with Several Exits

Emergency signage systems provide effective route guidance and evacuation information for pedestrians in case of emergencies such as fire, blackout, and explosion. This paper proposes a modified social force (SF) model to investigate crowd evacuation dynamics taking into account the influence of emergency signs. The perceiving probability model is formulated for the quantitative description of the probability that pedestrians can successfully notice the sign and clearly perceive the guidance information. Simulation experiments and controlled experiments are designed to calibrate the parameters of the proposed model. The effectiveness of the modified SF model is preliminarily verified by comparing the simulation results with experimental data and/or empirical results such as fundamental diagrams and self-organization phenomena. A case study of crowd evacuation simulations at a typical Beijing subway station is conducted to evaluate evacuation performance of three signage distribution schemes, i.e., Maximal Covering (MaxCover), Uniform, and Random, which are proposed by the maximal covering location and empirical approaches, as well as contrasted scheme without emergency signs. The effects of the quantity and distribution of emergency signs on crowd evacuation efficiency are studied quantitatively by simulations. The results show that installing emergency signs can improve evacuation efficiency no matter what distribution scheme is adopted. By choosing an appropriate distribution scheme i.e., MaxCover, the evacuation performance can be further improved and the evacuation time can be significantly reduced.

During mass evacuations, many psychological and physical factors are responsible for stampedes and other life threatening situations. Quantitative and qualitative analyses of these factors are of high importance while devising optimal strategies for evacuations. In this paper, we present an agent-based model that considers psychological and physical factors that cause panic in such situations. We have also simulated some simple evacuation scenarios and presented a method to identify possible bottlenecks and shortcomings in the environments during emergency evacuations. Our method also helps in evaluation and analysis of different evacuation strategies. To enable this analysis, we have used a rule-based roadmap approach, where critical nodes in the environment are identified by the evacuation planner and each node has a special rule according to the strategy of the planner. We evaluate different strategies on parameters, such as evacuation time and physical discomfort caused to the agents.

Enggano Island is situated above the southern segment of the Sunda megathrust, making it highly vulnerable to earthquake and tsunami hazards. In remote coastal villages, such as Kaana, the lack of adequate evacuation infrastructure presents significant challenges for disaster risk reduction. This study aims to evaluate tsunami evacuation strategies using an agent-based modeling approach implemented in a three-dimensional simulation environment. A purposive sampling survey involving 83 residents was conducted to collect socio-demographic data, tsunami awareness, preparedness levels, and evacuation preferences. These inputs were used to calibrate agent behavior and movement patterns to reflect realistic community dynamics in the simulation. The model simulates multiple evacuation configurations to examine survival rates and evacuation times under different spatial layouts, building distributions, and shelter capacity assumptions. Results show that horizontal evacuation via a single inland route leads to severe congestion and low survival outcomes, with only 8.2% of agents reaching safety within ten minutes. In contrast, the addition of vertical evacuation buildings significantly enhances evacuation performance, yielding survival rates above 90% under all conditions. Even when shelter capacity is limited to 70% of its full design, over 93% of agents are still able to evacuate successfully, although with increased delays. Vertical-only evacuation produces stable performance with average completion times of approximately five minutes. These findings emphasize the importance of integrating vertical shelters in strategic locations, optimizing route accessibility, and adapting building capacity to physical and demographic constraints. This study contributes to tsunami risk mitigation planning by offering empirical insights into evacuation dynamics in isolated island environments such as Enggano Island, Indonesia.

Humans do not Always Act Selfishly: Social Identity and Helping in Emergency Evacuation Simulation

Evacuation time prediction method for large cruise ships based on a deep extreme learning machine

Validation of advanced evacuation analysis on passenger ships using experimental scenario and data of full-scale evacuation