Group Stratification and Differentiated Guidance Strategies in Emergency Evacuation

Problem Description
During emergency evacuations in large public spaces (e.g., stadiums, subway stations), a crowd is not a homogeneous whole but exhibits significant differences. For instance, individuals vary in mobility (e.g., the elderly, children, people with disabilities), familiarity with the environment (e.g., tourists vs. regular visitors), and psychological state (e.g., level of panic), all of which can affect evacuation efficiency. This problem requires the design of a stratified guidance strategy that identifies group differences and implements differentiated interventions to optimize overall evacuation efficiency and reduce risks of stampedes or congestion.

Problem-Solving Process

1. Analysis of Group Stratification Dimensions

   • Mobility Stratification: Categorize people based on physical conditions into high mobility (healthy adults), medium mobility (elderly with walking aids), and low mobility (wheelchair users, children). Identification can be done via surveillance video or sensors (e.g., heat maps) detecting movement speed and gait differences.
   • Environmental Familiarity Stratification: Differentiate between familiar individuals (regulars) and unfamiliar individuals (tourists) using mobile signaling data or questionnaire surveys (in pre-set scenarios). Familiar individuals may choose shortcuts autonomously, while unfamiliar ones rely more on signs or guides.
   • Psychological State Stratification: Utilize heart rate monitoring (wearable devices) or behavioral analysis (e.g., wandering, pushing) to classify groups as calm, anxious, or panicked. Panicked individuals are prone to irrational behavior (e.g., moving against the flow).

2. Differentiated Risk Modeling

   • Establish an evacuation time function for each group type. For example: set the speed of low-mobility groups at 30%-50% of an average person's speed; panicked groups may have a 20% increase in reaction time due to decision delays.
   • Use simulation tools (e.g., AnyLogic) to model mixed-group evacuations and identify bottleneck areas. For instance, panicked groups can easily cause congestion at exits, and unfamiliar groups concentrating at junctions may lead to uneven path utilization.

3. Design of Stratified Guidance Strategies

   • Physical Diversion: Set up dedicated gentle-slope ramps or elevators for low-mobility groups, isolated from main evacuation routes, to prevent them from being impacted by high-speed flows. For example, reserve wheelchair-accessible routes in stadium stands leading directly to ground level.
   • Differentiated Information Delivery:
     • Send augmented reality (AR) navigation signals to unfamiliar groups, overlaying virtual arrows to indicate the shortest path;
     • Deliver calming instructions (e.g., voice broadcasts saying "Please follow the blue lights and proceed slowly") to panicked groups to prevent blind following.
   • Dynamic Resource Allocation: Increase the deployment of guides in areas identified with high panic density, using gestures or fluorescent batons to enforce directional分流 (diversion of traffic flow).

4. Strategy Verification and Iteration

   • Adjust parameters through Agent-based Modeling simulations. For example, test the global evacuation times of two strategies: "first guide high-mobility groups for rapid evacuation, then assist low-mobility groups" versus "mixed-group guided evacuation."
   • Introduce fairness metrics: Ensure waiting times for low-mobility groups do not exceed a threshold (e.g., 20% of total evacuation time), avoiding excessive牺牲 (sacrifice) of efficiency for vulnerable groups.

Key Points Summary

• Stratification should be based on quantifiable characteristics (e.g., speed, location data), not subjective classification;
• Differentiated strategies must balance efficiency and fairness, preventing marginalization of vulnerable groups;
• Dynamically monitor changes in group distribution (e.g., spread of panic) and adjust guidance plans in real-time.