In order to verify the evacuation model in this paper and analyze the advantages and disadvantages of the model performance, it is necessary to investigate and obtain evacuation scene data and build an evacuation network topology for the evacuation scene. The evacuation environment used in this paper is the three-tier cruise ship given in the European “SAFEGUARD” project [
27]. The number, type, speed, and evacuation strategy of pedestrians in different areas are set in the evacuation environment. Based on the evacuation environment of the cruise ship, this paper verifies the rationality of the model through the simulation of the evacuation. Based on the data of the cabin, stairs, passage, bar area, assembly area, and storage area of the cruise ship, this research completes the construction of the cruise ship model. The construction diagram of the first layer is shown in
Figure 1.
2.1. Networking of the Cruise Ship Model
In order to meet the application environment of the evacuation model in this paper, the two-dimensional cruise ship model needs to be converted into an evacuation network topology. After investigating the ways of transforming network topology of large-scale buildings, the steps for constructing an evacuation network topology are as follows:
Read cruise ship data;
Set up nodes for the centers of different areas in the cruise ship;
Judge whether different areas are connected to each other;
Connect the central points of the interconnected areas.
According to the functions of different facilities in the cruise ship, the cruise ship can be divided into bars, restaurants, stairs, shopping areas, cabins, storage areas, passages, decks, and other areas. These areas can be connected by passages or doors. Therefore, this method first selects the center points of these areas, and then judges whether there are doors or passages between different areas to determine the connectivity between the areas. Finally, doors and passages are used to connect central points and then an evacuation network topology is generated. In addition, in order to study the impact of path capacity constraints and evacuation priority on evacuation, it is necessary to set up the fire location and the exit as the prerequisite for evacuation simulation. In the “SAFEGUARD” project, pedestrians were designated to flee to assembly area C. Assembly area C contains the rescue materials needed for emergency evacuation, so this paper takes the node leading to assembly area C as the exit. The materials in the ship are generally non-flammable, and the place where a fire occurs is often the luggage of tourists. Therefore, this paper uses the storage area as the place where the fire broke out.
2.2. Description of Evacuation Network Topology Attributes
In this paper, the evacuation network topology is represented by , where represents the set of nodes in the evacuation network topology, represents the set of paths, represents the collection of the length and width of each side. This paper defines as the first node of the path and as the end node of the path. represents the length and width of each path. represents the length of the path, and its value is the distance between the first node and end node. represents the width of the path, and its value is the shortest distance between the sides of the path. Assuming that there are nodes in total, there is .
If the evacuation network topology is to be applied to the evacuation model of this paper, the attributes defined by the above nodes and paths are not enough to meet the requirements. In order to use the priority evacuation model in this paper to simulate the evacuation on the evacuation network topology, this paper expands the attributes of nodes and paths. The detailed descriptions are shown in
Table 1 and
Table 2.
In the description of node attributes 1,
n represents the total number of nodes; m represents the total number of paths. In the description of the path attributes in
Table 2, the calculation equation of area
and the crowd density
on the path are as shown in Equations (1) and (2). In addition,
indicates that the path has the highest risk level.
indicates that the path has lower risk level.
means the path is safe.
In Equation (2),
represents the total number of people on the path
, and
is determined by the location attributes of all evacuees at each moment. Through looking up the literature [
28], it is found that the speed of evacuation of people is closely related to the crowd density of the path. The setting of the attribute
is to provide the moving speed of people during evacuation.
This paper focuses on the impact of setting path capacity constraints and evacuation priority on the evacuation results. The method of determining the risk level of the path can be simplified. The judgment of risk level of the path can be based on the value of visibility, CO concentration, and temperature. Zhu et al. [
29] studied the impact of these indicators on evacuation. In the actual evacuation, the temperature sensor, CO sensor, and visibility sensor can be used to detect the fire situation of each path. In addition, the sprinkler and smoke exhaust system can reduce and control a certain degree of fire. The influence of these three indicators on the evacuation coefficient [
29] is shown in Equations (3)–(5).
Equation (3):
is the visibility of the evacuees, meter; Equation (4):
is the volume fraction of
, %;
is the evacuee’ exposure time, min. In Equation (5):
is the actual temperature of the fire site,
;
is the maximum escape speed, m/s;
is the temperature at which personnel feel uncomfortable, 30
in the paper;
is the temperature at which personnel are injured, 60
in the paper;
represents the temperature that caused serious injury to personnel, 120
in the paper. The smaller
, the greater the impact on the evacuee’ moving speed. According to the range divided by Equations (3)–(5) corresponding to the three indicators of degrees of influence on evacuation, three risk levels of the path are defined according to the range, as shown in
Figure 2.
In
Figure 2,
means that the risk level of the path is low, which is a safe state;
means that the risk level of the path is relatively high, which is a relatively dangerous state;
means that the risk level of the path is high, which is a dangerous state. When constructing the network topology for some other large buildings, the extended attributes of this paper can be used as a reference, such as crowd density, the shortest route, the types of nodes, and the risk level of paths. These extended attributes are conducive to the research of evacuation algorithms and can be applied to large buildings with similar evacuation structures [
30].
2.3. Cruise Ship Data and Evacuation Network Topology
According to the above definition and through the PyroSim software, the fire numerical analysis is carried out, and three indicators are monitored based on each node of the network topology. The first-tier cruise evacuation network topology constructed is shown in
Figure 3, which is an evacuation network topology formed by connecting the central points of different regions. Since the fire area is generally in the storage area, the storage area corresponds to node 6. Therefore, this paper assumes that node 6 is the fire node. In addition, node 14 is connected to the aggregation area, and it is assumed that node 14 is an exit node. The fire simulation data is obtained by detecting the fire product index of each node in the network topology, and the risk level of the path at different times is defined as the highest risk level of the nodes at both nodes of the path, as shown in
Figure 4.
Table 3 includes the moment of all nodes when the risk level changes over time.
In
Table 3, T1 represents the moment when the path risk level becomes relatively dangerous, and T2 represents the moment when the path risk level becomes dangerous. None indicates that each node cannot reach a relatively dangerous state or a dangerous state during the entire fire process. The data in
Table 3 can be used to determine the path risk level corresponding to all moments after the fire occurs.