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• The fire risk model is established. • The Dynamic Avoid Smoking A-Star (DASA-Star) algorithm is constructed. • The evacuation path planning of subway station fire environment is simulated. • The algorithm simulation verifies the effectiveness of DASA-Star algorithm. Considerable casualties can easily be caused once a fire occurs in a metro station, and a safe and effective evacuation path in time should be provided, taking on critical significance in the rapid evacuation of the crowd. In existing research, crowd evacuation paths have been generally planned without considering the fire environment and the real-time effect of fire products on the evacuation paths, such that the planned paths do not fit the realistic environment of crowd evacuation. An algorithm is proposed in this study to dynamically plan evacuation paths in fire scenarios in metro stations. First, the equivalent length of the path under the effect of fire on evacuation speed is determined in accordance with the effects of ambient temperature, visibility, and CO concentration, and then the fire risk model is built. Second, the fire risk model is incorporated into the A-Star algorithm, and the evaluation function of the A-Star algorithm is optimized, such that the determined path is capable of avoiding areas with higher fire risk. Subsequently, a dynamic update mechanism considering time factor is introduced to update the search environment information data of the algorithm in real time for dynamic path planning, with the aim of coping with the dynamically changing fire environment. Lastly, the A-Star algorithm is optimized, and the Dynamic Avoid-Smoke A-Star (DASA-Star) algorithm is built. As indicated by the simulation results, the DASA-Star algorithm is capable of making a trade-off between the fire risk and geometric length of the path in an underground station fire scenario and achieving dynamic planning of evacuation paths based on FDS fire simulation results. Accordingly, the algorithm conforms to the real-time requirements of path planning under fire conditions, and it is capable of more effectively planning the optimal evacuation path under the effect of fire. [ABSTRACT FROM AUTHOR]

Pedestrian behavior in emergency situations is an important part of emergency management, and crowd evacuation simulation provides a low-cost and low-risk method for investigating pedestrian evacuation dynamics by describing pedestrian evacuation behavior and predicting evacuation outcomes under hypothetical situations. This study proposed a modified social force model that combines dynamic hazard and emotional contagion frameworks to investigate the effect of panic on pedestrian evacuation dynamics under heterogeneous personality trait distributions. First, the emotional contagion framework was improved, and an updated emotional model was developed considering personality characteristics. Second, the individual self-driving force in the social force model was transformed from a physical drive mode to a psychological drive mode by introducing panic factors. Lastly, new rules for the spread of panic within small groups were formulated based on the important influence of small group behavior on evacuation. The simulation results confirmed the feasibility of analyzing crowd evacuation from the perspective of social psychology, and revealed that the spread of panic was closely related to the distribution of personality characteristics, individual walking speed, exit usage, evacuation efficiency, and small groups. In addition, the model could reproduce self-organizing behavior in crowd evacuation, such as fast is slow and herd behavior. Further, the results revealed that moderate panic can help improve evacuation efficiency, whereas excessive panic can result in uneven utilization of exits. In addition, the presence of small groups in panic crowds increased the crowd evacuation time. • The social force model was improved using personality traits and panic emotions. • Personality distribution traits affects panic propagation and evacuation efficiency. • A threshold for quantified panic to affect crowd evacuation was studied. • Intimate small groups are not susceptible to panic. [ABSTRACT FROM AUTHOR]

Small groups are a derivative of multiple social structures and relationships. Researchers have found that in natural disasters or other emergencies, people often escape as a social group. Based on this research background, we conducted an evacuation experiment to study the effect of this behavioral patterns of small groups on crowd evacuation. A total of 60 pedestrians were selected by extracting their trajectories, individual walking distances, evacuation times, and group shape. Then, we calculated and analyzed average speed and evacuation entropy. The results indicated that the presence of small groups inhibit crowd evacuation efficiency, especially when the proportion of small groups reached 30%. However, when above 30%, this degree of inhibition showed a decreasing trend, which may be caused by the regular convergence of small group members. It was also observed that although the evacuation time slightly increased when the group percentage reached 40%, but the overall evacuation became more orderly. We also observed the side-by-side structure and triangular structure of small groups in the experiment. This study deepens our understanding of crowd evacuation dynamics, reveals more information about pedestrian behavior, and proposes effective crowd guidance strategies. • The mixed crowd evacuation experiments were conducted. • Evacuation entropy was introduced and applied. • Evacuation routes and shortest path were quantified. • Side-by-side behavior and triangular patterns of behavior were observed. [ABSTRACT FROM AUTHOR]

Safety hazards cannot be ignored during the promotion of local economic development in chemical parks. In a crowded chemical industrial park, heavy casualties and serious economic losses may be incurred in a toxic gas leak accident. Accordingly, the location of emergency shelters and occupant escape routes in chemical parks during gas leakage accidents were examined in this study. Additionally, the risk of leakage in chemical parks throughout the year was assessed by selecting the average values of wind direction, wind speed and temperature across four seasons, and criteria for selecting emergency shelters were set according to the minimum risk of toxic gas leakage throughout the year. Moreover, a 30,000 t/a carbon-five separation construction project was adopted as a case study, where instantaneous leakage of an auxiliary raw material liquid ammonia storage tank occurred. The Floyd algorithm was then used to calculate the evacuation paths for people at multiple sources and multiple endpoints. The influence of the dynamic diffusion of toxic gas around the leakage source point on evacuation route safety was thoroughly analyzed, and occupant evacuation plans were employed in the chemical park based on the shortest evacuation path with the least impact from toxic gases. The findings produced by this study may provide reliable technical support guidance for safety evacuation in regard to toxic gas leakage accidents for personnel in chemical industry parks. [ABSTRACT FROM AUTHOR]