Analyzing Crowd Emotional Contagion in Metro Emergencies Through the Lens of the Weber–Fechner Law: Predictions Based on Computational Techniques Applied to Science

The spread of panic can swiftly trigger group behaviors, leading to public security incidents and significant social hazards. Increasing attention is being paid to the impact of human psychology and behavior on the evolution and management of emergencies. Drawing on the Weber–Fechner Law, we proposed an emotional contagion model to explore the dynamics of crowd panic during metro emergencies, focusing on the interplay of emotional levels and stimuli. Key influencing factors such as crowd density, personality traits, official interventions, and evacuation rates are analyzed. Additionally, a case study is conducted to validate the model’s effectiveness in quantifying emotions and characterizing the emotional contagion of crowd panic. Numerical results reveal that the initial intensity of panic stimuli significantly impacts peak panic levels, while contagion duration plays a minor role. Panic intensifies with increased crowd density, with sensitive individuals being more susceptible to extreme emotions, escalating negative contagion. Official intervention proves crucial in mitigating panic, though its effect is transient in enclosed environments. Evacuation rate minimally affects emotional contagion during the train’s motion but becomes pivotal post-arrival. Highly panicked passengers evacuate quickly, necessitating timely interventions to prevent secondary panic on platforms. This highlights the importance of immediate, effective control measures to manage panic dynamics and ensure public safety.