2.2. Scenario Construction
The scenario construction consists of two research steps: the experimental base scenario construction and the multi-software collaborative approach, respectively.
With reference to the Code for Fire Protection Design of Buildings, Code for the Design of Store Buildings, Uniform Standard for Design of Civil Buildings, Code for Fire Prevention in Design of Interior Decoration of Buildings, and other relevant design codes in China for commercial, metro, and public buildings, the Renmin Beilu Station, Chunxi Road Station, and Guanghua Park Station in Chengdu City are used as the basis for constructing the basic model of a connecting space, and this is combined with the results of the research and the summary of the literature to carry out the design. Minjie Li [
33] analyzed the congestion points through simulation experiments, counted the stopping positions of passenger flows going to commercial complexes from the underground direction, and finally summarized the key spatial nodes, such as access bifurcations, atrium entrances and exits, and plaza entrances and exits. This was based on the interview results of relevant experts from Chengdu Metro, China Southwest Architecture, China Railway First Survey and Design Institute Group Co., Ltd. (Chengdu, China), and the contents of relevant specifications. Therefore, the size of the channel connecting the space model established in this study was taken as 37.5 m × 6 m wide (the length of the channel center axis is 37.5 m); the area of 500 m
2 was selected as the base model of the atrium and plaza connecting space, taking into account the fact that the spatial scale affects the flow of passengers. It is concluded by the distribution of passenger flow by Massmotion that the distribution of the density of the people is more uniform when the aspect ratio is 1:1. The business case and site interface space were used as reference models to derive the experimental base scenarios. The final experimental base scenario model was based on 1:1 physical scale modeling to restore the real scenario as much as possible. The specific scenes are shown in
Table 2.
Depthmap10, as a spatial syntactic analysis software, performs the graphical analysis of the visibility of the spatial environment, and the results obtained from the drawn axial and convex spatial analysis models reflect the permeability, accessibility, and convenience of space. MassMotion11.5 is a passenger flow simulation software based on social force modeling algorithms developed by Oasys Arup in the UK, which can provide designers with a lot of clear information, such as the way pedestrian access equipment is used, the safety of the pedestrian space, and the phenomenon of crowded spaces. Based on the theory of spatial syntax, Luo combined quantitative data and correlation analysis to explore the impact of spatial accessibility and pedestrian flow on the vitality of underground space by taking the underground space connected to rail transit stations as an example. In this study [
34], Ma used Massmotion to simulate the 3D visual time of travelers on the wall, showing the focus of attention of the pedestrian’s field of view in his simulated visual time map and proposed a method to simulate the focus of attention of the view [
35].
Based on the above research, this study utilizes Depthmap10 to analyze the three scenarios to obtain the visual focus area and then combines this with the signage, passenger visual field, and Massmotion11.5 passenger flow line for the visual field superposition analysis so as to achieve the design of an appropriate location according to the Guidance Signage System.
2.2.1. Visual Field Overlap Analysis
Combining the above visual area division and the type of Guidance Signage System, a three-dimensional spatial coordinate system was created to divide the visual areas, and according to the nine-grid composition method in photographic composition techniques, a straight line was drawn along each of the X, Y, and Z axes in a single-point perspective scene to form a 3 × 3 × 3 three-dimensional spatial grid, so as to divide the screen into nine independent visual areas (
Figure 5), where each of these visual areas corresponds to a different location of the Guidance Signage System in the experimental scene.
Due to the continuity of the signage setup [
36], each path within the connecting space covers several nodes. When laying out the locations of the Guidance Signage System, it is necessary to select suitable points from these nodes as decision points for sign setting. In this study, the locations where pedestrians face difficulties or are most likely to be confused during path selection are defined as decision points.
In this paper, we first employ the spatial syntax software Depthmap10 to analyze the three kinds of connecting spaces in terms of their visual domain before subdividing the spatial plan into a grid, which covers the entire 2D visible area, and when setting the grid size, we balanced the calculation precision and the amount of operations, referring to the research of Zhou Xi [
37] and others, selecting a grid size of 1.0 m (the common size is 1–1.5 m). The structure of the visual integration degree calculation is shown in
Table 3, where the redder the color, the higher the visual integration degree, which indicates the greater visual visibility of the space. Secondly, the Massmotion11.5 software is used to simulate the passenger flow routes in the three connecting spaces (
Figure 6 and
Figure 7), and the ground-based Guidance Signage System is laid out in such a way as to avoid the passenger flow routes as much as possible. The results of the visual field analysis of the three kinds of spaces calculated by Depthmap and Massmotion software are shown in
Table 3.
2.2.2. Demonstration of Spatial Location of Standard Guidance Signage System
The experiment is based on the above nine different visual areas, the results of the visual field superposition analysis, and the actual application of the spatial layout of the situation, according to the guidance of the hanging type, attached type, and ground type to select the appropriate type of Guidance Signage System arranged in the simulation scene. Based on the literature [
38] and research analysis, it can be seen that the signage system used in the process due to the different node spaces makes people produce certain visual and behavioral habit differences; thus, in the study of the signage system of visual salience, due to the space of the different experimental scenes in the location of the setup area to make certain adjustments, in Teng’s study of the visual salience of guide signs in underground commercial streets, ergonomics, and human visual characteristics were combined to divide the experimental scene into nine parts that covered the entire visual area, We followed her delineation of visual areas, but unlike Teng’s study, the spatial location of the signs mentioned in this study in conjunction with the above was within a 5° angle upward from the horizon, disregarding the three areas below the horizontal line of sight, which were not the focus of our attention. Therefore, six areas were selected as the locations of the Guidance Signage System in the scenes of channel bifurcation (A01–A06), the atrium entrance and exit (B01–B06), and sunken plaza exit (C01–C06), and the corresponding research was carried out using the following specific scenarios.
2.3. Oculomotor Simulation Studies
- (1)
Experimental equipment
In this experiment, the Tobii Glasses2 ophthalmoscopic eye-tracking device was used as the experimental tool, which mainly consists of three parts: the headgear module, the recording module, and the external data processing, with a sampling rate of 50 Hz, a 1-point calibration, a scene camera with a resolution of 1920 × 1080 pixels, and a camera recording field of view ranging from 82° horizontally to 52° vertically.
- (2)
Experimental Participants
A total of 25 volunteers were recruited to participate in the simulation trial, including 10 males and 15 females, with an age distribution between 20 and 50 years old, all in good physical condition and without color blindness or color weakness. In the eye-tracking experiment, we strictly followed the ethical requirements of the study to ensure that the rights and interests of all participants were fully protected. All participants were informed of the purpose of the study, the experimental procedure, and the use of the data before data collection. Meanwhile, in order to protect the privacy of the participants, all the data were anonymized or de-identified, and any personally identifiable information will not be disclosed in any research results or public reports.
- (3)
Experimental stimulus material
The scene diagram in
Table 4 was used as the material for the 18-sheet visual experiment. In order to avoid the influence of color on location perception, the experimental scene was set in grey, the logo was a differentiated dark tone, and a blank page was used for the transition between each page. The research experiment is divided into four steps, and the specific flow is shown in
Figure 8.
2.4. Analysis of Results
After the completion of the experiment, the experimental data were collected and sorted out, and two samples that were not qualified due to missing recorded data were excluded; finally, twenty-three qualified sample data were obtained. The qualified data were processed in Tobii Pro Lab software (Version 24.21), the required hotspot maps and eye movement data were output and exported, and the data were summarized and analyzed.
The visualization hotspot map is mainly used to obtain the distribution of eye movement behaviors in space within a certain period of time, which can reflect a large number of regions in the stimulus that attract the subject’s attention, has a two-dimensional type of data representation, and has the size of the value measured by the eye-tracking device displayed in different colors, in which the red color indicates the most focused attention and the region of the longest duration of gaze, followed by yellow, and the green color indicates the region of the least focused attention; as can be seen from the resulting visualization hotspot map, darker the red area, the more attention and focus the Guidance Signage System has from the subjects.
As shown in
Table 5, which is the hotspot distribution map of different spatial location scenes, with the change in the deployment location, the distribution pattern of the hotspot map presents certain differences, and the comprehensive eye movement view of different spatial location scenes can be found as follows: ① For the same type of Guidance Signage System in different spatial scenes, the closer the layout position is to the pedestrian’s line of sight, the more attention it can attract and the more focused it is; the further away it is, the more dispersed it is. ② Combined with the human visual law to analyze the results of the experiment, it can be concluded that when people are observing objects, the line of sight tends to move along the direction from top to bottom and from left to right. The Guidance Signage System on the left side of the visual area is more likely to be noticed than that on the right side.
In summary, after analyzing the visual hotspot maps of each scene, it can be found that changes in the layout of the Guidance Signage System directly lead to different distribution patterns of the hotspot maps for each scene, which further confirms the viewpoints of hypothesis one: the location of the Guidance Signage System does have a significant impact on visual saliency. A reference basis is provided for the experimental results.
By analyzing the visualization hotspot map mentioned above, further in-depth investigation with the help of eye-tracking data can be conducted to clarify how the Guidance Signage System set in different locations affects visual saliency and reveals their roles. Yan Guoli [
39] and others, in a review article on eye movement indicators in the field of reading research, emphasized that the selection of appropriate and effective eye movement parameters as the basis of this study is the core of ensuring the quality and depth of eye movement research. Li investigated the effectiveness of prohibited safety sign locations in a coal mine environment by collecting data on the number of gaze points and the time of the first gaze [
40]. Li, H.X. selected first gaze time, the total access time, and a number of gaze points as indicators to explore the effectiveness of emergency signage during the evacuation of people in emergency situations [
41].This study is an exploratory study [
42], so the analysis of eye movement data such as first gaze time, the number of gaze points, duration of first gaze time, and so on (
Table 6) during the process of wayfinding indicates the visual perception of the subjects, and the different scenes are classified and sorted in combination with the experimental data (
Table 7). Changes in eye movement indices were statistically described and plotted on a line graph (
Figure 9 and
Figure 10).
In the study of the impact of the spatial location of the Guidance Signage System on visual salience, the time to first fixation is a crucial eye movement index. It directly reflects the degree of attention and attraction of the Guidance Signage System’s placement and can be used as an important basis for preliminary screening and assessment of the advantages and disadvantages of placement. However, in order to have a more comprehensive understanding of the influence of the location of the Guidance Signage System on visual saliency, it is also necessary to comprehensively consider other eye-movement indicators as well as other factors in the actual scene.
In the scene of the channel bifurcation, the TFF value of area A04 (middle left) is the smallest, which indicates that the Guidance Signage System was quickly noticed by the subjects, while its NF and DFF values were small relative to those of the signs in other locations. For the sign in area A02 (upper middle), although its TFF value is larger than that of area A04 (middle left), its NF and DFF values are the largest. Therefore, on balance, the visual prominence of the Guidance Signage System is greater when it is set in visual area A02 (upper center). In this way, based on the statistical frequency of the three eye movement indicators, it is concluded that in the atrium entrance/exit scenario, it is difficult for pedestrians to quickly notice the Guidance Signage System located above the visual area, which is due to the complex environment of the atrium, and the surrounding arrangement of the commercial area, which, to a certain extent, distracts the visual attention of pedestrians. The significance of the Guidance Signage System located in the visual area of B05 (lower right) is higher, which indicates that the closer the distance of the same type of Guidance Signage System is from the pedestrians’ line of sight, the easier it is to attract their attention; in the sunken plaza scenario, the significance of the Guidance Signage System is higher when it is set in the visual area of C05 (lower left). It is also confirmed that in the connecting space of different scenes, the location of the more visually salient Guidance Signage System varies, indicating that there is variability in the distribution of the focus of visual attention between different scenes.
When looking through
Figure 10, it can be noticed that the trend of the folds in the two charts (a) and (c) are similar. In these charts, the trends of TFF and DFF are synchronized. For example, in region A03, both TFF and DFF reach higher values, showing the stronger attraction of this region to observers. Regarding other regions such as A01, A06, etc., TFF and DFF show relatively consistent upward or downward trends, which indicates a strong correlation between visual attraction and dwell time in these regions [
43]. However, the situation in (b) is different. Although the values of TFF and DFF varied from region to region, there was a clear divergence in their trends. For example, region B04 has relatively low TFF and a high DFF value, implying that although visual attention is rapidly focused, the dwell time is longer. Conversely, region B05 showed the opposite situation, with higher TFF and lower DFF, possibly indicating that although the observer’s initial gaze was more rapid, interest in the region did not last long [
44].