## 2 Related Work  
### Emergency Navigation  
Because evacuation drills are high-priced, time-consuming and cannot be reproduced, most research employs macroscopic or microscopic simulation models to characterise real evacuations. However, the diversity in the physical attributes of occupants is rarely taken into account. For example, cellular automata models, such as [12], discretize given structures into uniform \"cells\" that can hold one person. This approach can precisely model the influence of an individual's physical dimensions, but is ineffective in depicting the movement speed and direction, due to the discrete spatial structure [13]. Moreover, evacuees are assumed to have identical physical conditions, and the movement rules are determined by cells. Flow-based models [14; 15; 16; 17; 18; 19] hypothesise evacuee movement as continuous flows, and civilians are assumed to have identical physical attributes. Potential maintenance approaches [20; 21; 22] concentrate on establishing safe escape paths and do not take individual ability into consideration. Particle-based algorithms, such as the \"magnetic model\" in [23], make use of the analogy between particle motions and evacuee movements, but ignore personal requirements, as well as the effect of crowd behaviours. The multi-agent models can customise physical attributes for individuals and imitate complex phenomena efficiently. However, a majority of previous work has focused on studying crowd dynamics. Although simulations in [24] are based on a multi-agent framework that employs evacuation agents with physical, psychological and moving attributes, health factors, such as initial health values and resistance to hazard, which are influenced by gender, age, _etc._, are not considered.  
Current emergency navigation algorithms explore paths with a single characteristic, such as safest paths, shortest paths or quickest paths. Reference [20] uses \"artificial potential fields\" to establish a self-organizing sensor network with artificial forces and directs users to the safest path. Exits and dangerous zones generate attractive forces and repulsive forces, respectively, and evacuees move under the actuation of the resultant force. In [22], a multi-path routing protocol is proposed based on the temporally ordered routing algorithm [25] to guide evacuees to egresses through safer paths. Each actuator is assigned with an altitude in accordance with its hops to the nearest exit, and egress routes are formed along actuators with a higher altitude to actuators with a lower altitude. In addition, a manual navigation map is defined to eliminate the impractical paths caused by the radio's penetration capacity. Combining the definition of effective length with [PERSON]'s algorithm, [26] presents a decentralized evacuation system with decision nodes (DNs) and sensor nodes (SNs) to compute the shortest routes in real time, while opportunistic communications-based [27] emergency evacuation systems [28] have the advantage of being more robust to network attacks [29] that often accompany emergencies caused by malicious acts. By considering the evacuation planning problem as a minimum cost network flow problem [30,31], EVACNET+[14, 15, 16] converts the original evacuation network to a time-expended network to obtain the quickest routes. The optimal solution is produced by using linear programming methods. To reduce the computational cost of this kind of approach, [32] replaces the linear programming algorithm with a heuristic A*algorithm.