## 7 Results and Discussion
Congestion is assumed to happen when an evacuee reaches a node with a non-zero queue length. To evaluate if the novel goal functions improve the QoS for different categories of evacuees, we compare the results with [PERSON]'s algorithm and the original CPN algorithm with the distance metric. Figure 6 shows the average evacuation time of the three algorithms, and the error bars represent the maximum and minimum egress time of ten experiments. The results confirm that CPN with the time metric achieves the average shortest evacuation time among the three metrics. Furthermore, both CPN-based algorithms can accomplish an evacuation process faster than [PERSON]'s algorithm in low occupancy rates (30 and 60 evacuees), while gaining a similar number of survivors. However, the three metrics achieve comparable results in high population densities (90 and 120 evacuees), with a slight advantage to CPN with the time metric. This is mainly caused by the congestion formed at the bottlenecks of the network. A large amount of evacuees have to queue for a long time at the central staircase between the ground floor and the first floor before they can reach the ground floor. The maximum queue length at this staircase can attain 25 for [PERSON]'s algorithm and 20 for CPN with the distance metric. Interestingly, although the value for CPN with the time metric is 16, alternate congestion will form near the exits as the egress becomes a new bottleneck. It indicates that in a high density environment, the bottlenecks in the system can significantly affect the average evacuation time. In other words, though the CPN with the time metric can accelerate the process for civilians to arrive in the vicinity of exits, it cannot significantly reduce the average evacuation time under the equivalent departure rate of the exits. Figure 7 shows the average health value of survivors among [PERSON]'s algorithm, CPN with the distance metric and CPN with the safety metric. The initial health value of each evacuee is 100 units, and if a civilian perishes, its health value will become zero. The results show that CPN with the safety metric achieves the highest mean health value among the three algorithms, while gaining the greatest number of survivors. The average energy consumption of each electric powered wheelchair is shown in Figure 8. Compared with [PERSON]'s algorithm and CPN with the distance metric, CPN with the energy metric consumes the least energy on average. This metric is useful for evacuation in both emergency and standard conditions. Figure 6: The average evacuation time of ten iterations in arbitrary time units. The error bars represent the min/max values found in the 10 simulations. In order to evaluate the performance of routing diverse categories of evacuees with different metrics, we develop a scenario that contains four types of evacuees: aged people, young people, children or ill people and disabled people in electric powered wheelchairs. The population ratio of the four categories of civilians is 2:5:2:1, and the speed ratio is 0.8:1:0.8:1.5. The aged people are set to a distance threshold to mimic their limited physical strength. If the displacement exceeds the distance threshold, the moving speed will reduce to one half of the initial velocity. Disabled people in wheelchairs are set at an analogous battery power limitation. If the battery power depletes, the wheelchairs will stop. In addition, the initial health value of children or ill people is 80 percent of the health level of other categories. Besides [PERSON]'s algorithm and CPN with the distance metric, CPN with the time metric is also employed as a comparison for its good performance in the first experiment. The results in Figure 9 show that CPN with four metrics performs best, because it provides routes that suffice the QoS needs of different categories of evacuees. Hence, fewer evacuees will perish, due to the lack of physical strength and the depletion of battery power.