A Virtual Interactive Design Method for Building Wayfinding Signage System Based on PSO Algorithm

Abstract

This invention relates to a virtual interactive design method for a building wayfinding signage system based on the PSO algorithm. The invention pertains to the field of spatial pathfinding and interactive design technology. It involves constructing a virtual 3D model of a building space based on survey data, collecting materials and establishing a building wayfinding signage design library, and building a virtual reality scene. Within the virtual reality scene, eye-tracking experiments are conducted to collect visual data and behavioral trajectories of the participants. A first round of optimization is performed based on the PSO particle swarm optimization algorithm. Interactive design is then completed within the virtual reality scene, and the participants' subjective evaluations and design results are collected to perform a second round of optimization on the building wayfinding signage design library, generating a recommended design library. Finally, the final design results and the recommended design library are collected, packaged, and stored according to participant identity information and experiment time, providing data reference for subsequent related designs.

Description

TECHNICAL FIELD

[0001] The application relates to the technical field of spatial route finding and interaction design, and is a virtual interaction design method for a building guide sign system based on a PSO algorithm. BACKGROUND

[0002] A guide sign system is an important communication language between a building and a user. In today's complex and three-dimensional building environment, a sign system with good guiding effect can help users quickly and accurately reach the destination in a complex building environment. However, due to the differences in thinking and information barriers between designers and users, many guide sign designs in buildings have problems such as imperfect sign systems, non-standard sign forms, and poor information continuity. The traditional method of solving the guide sign design problem is to collect problems through user route finding experiments, questionnaires, and field interviews after the building is completed and used, and then make modifications. Such a “post-evaluation” and “patching” method has the disadvantages of low efficiency, high experimental cost, and the need for repeated modifications, so new technologies need to be introduced to improve design production efficiency and optimize guide sign design results.

[0003] Virtual reality technology is a technology that generates an interactive three-dimensional environment by comprehensively utilizing computer technology and provides an immersive feeling. With its excellent environmental immersion and flexible interactivity, virtual reality technology provides a new perspective and possibility for experimental research in the fields of urban and building space information processing and cognition. Compared with field experiments, the virtual experiment method can realize pre-implementation evaluation of the guide sign system design scheme through the immersive perception experience of the user. That is, the objective data of the route finding behavior are obtained by using experimental testing means, and the subjective evaluation of the user is combined to convert the “post-evaluation” of the guide sign design into “pre-evaluation”, avoid unreasonable phenomena after application, and improve the design production efficiency.

[0004] Meanwhile, in order to pursue intelligent optimization design and improve design feedback efficiency, the interactive design of the building guide sign in the virtual environment can be combined with machine learning optimization algorithms to realize continuous self-updating. The machine learning algorithms currently applied to related fields include ant colony algorithm, simulated annealing algorithm, PSO particle swarm algorithm, genetic algorithm, and the like. Among these algorithms, the IPSO interactive particle swarm algorithm has an advantage in solving optimization problems due to its stronger information sharing mechanism and simpler variable range. In 2019, Zhang Yuxuan et al. used the IPSO algorithm on the indoor decoration material collocation scheme, successfully introduced user experience and aesthetic preference into the early stage of design, and improved indoor comfort; meanwhile, machine learning was used to reduce frequent user interaction and improve design optimization efficiency. SUMMARY

[0005] The present application is to overcome the deficiencies of the prior art, the present application is to realize the effectiveness of building guide sign in virtual environment and interactive design, so as to provide data support and reference for designers, and efficiently improve the design method of building guide sign, the present application provides a kind of virtual interactive design method of building guide sign system based on PSO algorithm.

[0006] It should be noted that, in this paper, relational terms such as first and second are used merely to distinguish one entity or action from another, without necessarily requiring or implying any such actual relationship or order between such entities or actions. Moreover, the terms "comprising", "including" or any other variant thereof are intended to cover non-exclusive inclusion, so that a process, method, article or apparatus including a series of elements includes not only those elements, but also other elements not explicitly listed or inherent to such process, method, article or apparatus.

[0007] A kind of virtual interactive design method of building guide sign system based on PSO algorithm, the method comprises the following steps:

[0008] Step 1: establish virtual roaming scene based on research data, including establishing three-dimensional building scene, building guide sign design library and Unity virtual environment;

[0009] Step 2: complete wayfinding eye movement in virtual reality scene, collect visual data and behavior trajectory of experimental personnel, determine the objective efficiency value E O of building guide sign system;Based on PSO particle swarm optimization algorithm, the first round optimization is carried out to building guide sign design library using E O

[0010] Step 3: complete interactive design in virtual reality scene, collect subjective evaluation and design results of experimental personnel on building guide sign system, calculate the subjective efficiency value E S of building guide sign system;The second round optimization is carried out to building guide sign design library using E S , and recommended design library is generated;

[0011] Step 4: collect final design results and recommended design library, and store them according to the identity information and experimental time of experimental personnel as tags, to provide data reference for design.

[0012] Preferably, the step 1 is specifically:

[0013] Step 1.1: scan existing building using 3D infrared scanner, take photos of building interior environment, and build preliminary building model;Through research, collect conventional building guide sign design materials, build building guide sign model and building guide sign design library;​

[0014] Step 1.2: Import the preliminary architectural model and the architectural guide sign model into Unity 3d software to edit, including creating a scene, editing a map, adding a rigid body and a physical collision;

[0015] Step 1.3: Bind the architectural guide sign model with the architectural guide sign design database to achieve synchronous changes and prepare for subsequent interactive design.

[0016] Preferably, the step 2 is specifically:

[0017] Step 2.1: Use the Open XR toolkit and XR interaction Toolkit resource package carried by Unity3D software to make a virtual scene roaming function controlled by a handle; make a UI interactive interface to complete the virtual route search experiment function; write a first-person camera tracking code to complete behavior trajectory acquisition;

[0018] Step 2.2: Complete the route search eye movement experiment in the virtual scene, collect the visual information of the experimental personnel during virtual roaming through the eye movement tracking component; collect the behavior trajectory of the experimental personnel through the trajectory tracking code;

[0019] Step 2.3: Combine the visual information and the behavior trajectory to obtain the continuity, readability and saliency indicators of the architectural guide sign system; and calculate the objective efficiency value E O of the architectural guide sign system.

[0020] The calculation method of the objective efficiency value E O is as follows:

[0021] The objective efficiency value of the guide sign is obtained by summing up the continuity indicator, the readability indicator and the saliency indicator after removing the dimension by the normalization method, and is calculated by the following formula:

[0022]

[0023] Wherein, CT(n) is the continuity indicator, min n CT(n) and max n CT(n) are the minimum and maximum values of the continuity indicator, RW(n) is the readability indicator, min n RW(n) and max n RW(n) are the minimum and maximum values of the readability indicator, CS(n) is the saliency indicator, min n CS(n) and max n CS(n) are the minimum and maximum values of the saliency indicator.

[0024] Step 2.4: Based on the PSO particle swarm optimization algorithm, the three indicators of the building guide sign system are used to calculate E O Unfold the first round of optimization of the building guide sign design library.

[0025] Preferably, the continuity indicator of the building guide sign system is calculated based on the experimental personnel behavior trajectory, and the continuity and readability indicators of the building guide sign system are calculated based on visual information separation. The calculation method is as follows:

[0026] First, calculate the shortest path D1(n) between each two continuously arranged building guide signs in the building guide sign system; call the behavior trajectory data to record the actual walking path D2(n) of the experimental personnel between each two continuously arranged building guide signs, and finally calculate the continuity indicator CT(n) of the building guide sign system by formula 1:

[0027]

[0028] Preferably, the first round of optimization is as follows:

[0029] Step S1, set the building guide sign design library as the particle swarm to be optimized, and each building guide sign system design corresponds to each particle to be optimized; initialize the particle swarm to take the continuity, readability and salience indicators of the guide sign system as the position X I , according to X I Performance evaluation fitness f;

[0030] Step S2, record the individual historical optimal fitness f p and the global historical optimal fitness f g of the particle swarm, and take the positions corresponding to the fitness values as the individual historical optimal position X and the global historical optimal position X

[0031] Step S3, calculate the particle update speed by the following formula:

[0032]

[0033] wherein, is the particle speed generated in the new round of iteration, and ω is the inertia parameter; is the particle speed generated in the last round of iteration, C1 and C2 are learning parameters, is the individual historical optimal position of the particle; is the particle position generated in the last round of iteration, is the global historical optimal position of the particle

[0034] Step S4, update the particle position by the following formula:

[0035]

[0036] wherein, is the particle position generated in the new round of iteration, is the particle position generated in the last round of iteration, is the particle velocity generated in the new round of iteration;

[0037] Step S5, re-evaluate the fitness value of the particle, compare whether the fitness value of each particle is better than the individual historical optimal fitness value f p good, if yes, replace; at the same time, recalculate the global optimal fitness value of the particle, compare whether the global optimal fitness value of the particle is better than the global historical optimal fitness value f g good, if yes, replace;

[0038] Step S6, repeat steps S3-S5 until the optimization requirement is met; output the optimized global optimal value of the particle and the continuity, readability and significance index of the design particle represented by the updated particle position in step S4 change, the corresponding guiding sign design and guiding sign model are updated synchronously.

[0039] Preferably, the step 3 is specifically:

[0040] Step 3.1: make interactive design function in Unity3D software, take building guiding sign model as interactive object, realize that guiding sign design library can be modified;

[0041] Step 3.2: complete interactive design in virtual scene, collect experimental personnel interactive design achievements; experimental personnel fill in experimental evaluation table, collect subjective evaluation of building guiding sign system;

[0042] Step 3.3: combine experimental personnel subjective evaluation and interactive design achievements, calculate subjective efficiency value E S of building guiding sign system; get score Eva(n) of each part of guiding sign system in experimental evaluation table, and calculate the total value according to the following formula, which is the subjective efficiency value E S

[0043]

[0044] Wherein, Eva(i) is subjective score;

[0045] Step 3.4: use E S As a reference, the second round of optimization is carried out on the building guiding sign design library, and the recommended design library is generated.

[0046] A virtual interactive design system for a building wayfinding signage system based on the PSO algorithm, the system comprising: a roaming scene simulation module, a virtual interactive design module, and a data acquisition and storage module;

[0047] The roaming scene simulation module includes a 3D building model, builds a building wayfinding sign design library, and simulates a wayfinding roaming scene.

[0048] The virtual interactive design module includes virtual pathfinding experiments, interactive design of building wayfinding signs, and intelligent design optimization.

[0049] The data acquisition and storage module collects and stores the visual information, subjective evaluations, and interaction design results of the experimenters, providing a reference for the optimized design of building wayfinding signs.

[0050] A virtual interactive design system for building wayfinding signage based on the PSO algorithm, the system comprising:

[0051] The virtual scene creation module builds a virtual roaming scene based on survey data, including the creation of a 3D architectural scene, a building wayfinding sign design library, and a Unity virtual environment.

[0052] The first round of optimization module completes pathfinding eye tracking within the virtual reality scene, collects visual data and behavioral trajectories of the experimenters, and determines the objective efficiency value E of the building wayfinding signage system. O Based on the PSO particle swarm optimization algorithm, using E O The first round of optimization was carried out on the building wayfinding signage design library;

[0053] The interaction design module completes the interaction design within a virtual reality scene, collects subjective evaluations and design results from experimenters regarding the building wayfinding signage system, and calculates the subjective efficiency value E of the building wayfinding signage system. S Use E S A second round of optimization was conducted on the building wayfinding signage design library to generate a recommended design library.

[0054] The verification module collects the final design results and the recommended design library, and packages and stores them according to the experimenter's identity information and experiment time to provide data reference for the design.

[0055] A computer-readable storage medium having a computer program stored thereon, which is executed by a processor to implement a virtual interactive design method for a building wayfinding signage system based on the PSO algorithm.

[0056] A computer device comprises a memory and a processor, the memory stores a computer program, when the processor runs the computer program stored in the memory, the processor executes a building guide sign system virtual interactive design method based on a PSO algorithm.

[0057] The present application has the following beneficial effects:

[0058] The present application is a building guide sign system virtual interactive design method based on a PSO algorithm, a virtual building space three-dimensional model is built based on investigation data, materials are collected and a building guide sign design library is established, and a virtual reality scene is constructed; a wayfinding eye movement experiment is completed in the virtual reality scene, visual data of the experiment personnel are collected, and then a building guide sign objective efficiency value E O is calculated; based on a PSO particle swarm optimization algorithm, E O is used to optimize the building guide sign design library for one round; interactive design is completed in the virtual reality scene, subjective evaluation of the experiment personnel on the building guide sign system and design results are collected, and based on the two, a building guide sign subjective efficiency value E S is calculated; E S is used to optimize the building guide sign design library for two rounds, and a recommended design library is generated; the final design results and the recommended design library are collected, and are packaged and stored according to the experiment personnel identity information and the experiment time as tags, to provide data reference for subsequent related design. BRIEF DESCRIPTION OF DRAWINGS

[0059] In order to more clearly illustrate the specific embodiments of the present application or the technical solutions in the prior art, the drawings needed in the specific embodiments or the prior art description will be briefly introduced below, and obviously, the drawings in the following description are some embodiments of the present application, and those skilled in the art can also obtain other drawings according to these drawings without creative labor.

[0060] Fig. 1 The flowchart of the building guide sign system virtual interactive design method based on the PSO algorithm;

[0061] Fig. 2 The composition diagram of the building guide sign system virtual interactive design method based on the PSO algorithm;

[0062] Fig. 3 The running flowchart of the PSO particle swarm optimization algorithm. DETAILED DESCRIPTION

[0063] The technical solutions of the present application will be described clearly and completely below in conjunction with the drawings. Obviously, the described embodiments are only some of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative efforts belong to the scope of the present application.

[0064] In the description of the present application, it should be noted that the terms "center", "upper", "lower", "left", "right", "vertical", "horizontal", "inner", "outer", and the like indicate the orientation or positional relationship shown in the drawings, and are only for the convenience of describing the present application and simplifying the description, and do not indicate or imply that the device or element referred to must have a particular orientation, be constructed and operated in a particular orientation, and therefore cannot be understood as a limitation of the present application. In addition, the terms "first", "second", "third" are only for descriptive purposes and cannot be understood as indicating or implying relative importance.

[0065] In the description of the present application, it should be noted that unless otherwise explicitly specified and limited, the terms "mounting", "connection", "connection" should be understood broadly, for example, it can be fixedly connected, or it can be detachably connected, or integrally connected; it can be mechanically connected, or it can be electrically connected; it can be directly connected, or it can be indirectly connected through an intermediate medium; it can be the communication inside two elements. For those skilled in the art, the specific meaning of the above terms in the present application can be understood according to the specific circumstances.

[0066] In addition, the technical features involved in the different embodiments of the present application described below can be combined with each other as long as they do not conflict with each other.

[0067] The present application is described in detail below in conjunction with specific embodiments. Specific embodiment one:

[0069] According to Figs. 1-3 As shown in the drawings, the specific optimization technical solution adopted by the present application to solve the above technical problems is: the present application relates to a virtual interactive design method of a building guide sign system based on a PSO algorithm.

[0070] A virtual interactive design method of a building guide sign system based on a PSO algorithm, the method comprising the following steps:

[0071] A virtual interactive design method of a building guide sign system based on a PSO algorithm, characterized in that the method comprises the following steps:

[0072] Establish a virtual roaming scene based on research data, including establishing a three-dimensional building scene, a building guide sign design library, and a Unity virtual environment;

[0073] In the virtual reality scene, the eye movement of wayfinding is completed, the visual data and behavior trajectory of the experimenters are collected, and the objective efficiency value E of the building guide sign system is determined O ; based on the PSO particle swarm optimization algorithm, E O The first round of optimization is performed on the building guide sign design library;

[0074] In the virtual reality scene, the interactive design is completed, the subjective evaluation and design results of the experimenters on the building guide sign system are collected, and the subjective efficiency value E of the building guide sign system is calculated S ; E S The second round of optimization is performed on the building guide sign design library to generate a recommended design library;

[0075] The final design results and the recommended design library are collected, and are packaged and stored according to the identity information and experiment time of the experimenters as tags, to provide data reference for design.

[0076] The application is a virtual interactive design method of a building guide sign system based on a PSO algorithm, a virtual building space three-dimensional model is built based on research data, materials are collected and a building guide sign design library is established, and a virtual reality scene is constructed; in the virtual reality scene, a wayfinding eye movement experiment is completed, visual data of the experimenters are collected, and then the objective efficiency value E of the building guide sign is calculated O ; based on the PSO particle swarm optimization algorithm, E O One round of optimization is performed on the building guide sign design library; in the virtual reality scene, the interactive design is completed, the subjective evaluation and design results of the experimenters on the building guide sign system are collected, and the subjective efficiency value E of the building guide sign is calculated S ; E S Two rounds of optimization are performed on the building guide sign design library to generate a recommended design library; the final design results and the recommended design library are collected, and are packaged and stored according to the identity information and experiment time of the experimenters as tags, to provide data reference for subsequent related design. Specific embodiment two:

[0078] The difference between the second embodiment and the first embodiment is only that:

[0079] The step 1 is specifically:

[0080] Step 1.1: a 3D infrared scanner is used to scan the existing building, take photos of the interior environment of the building, and build a preliminary building model; through research, conventional building guide sign design materials are collected, and a building guide sign model and a building guide sign design library are built;

[0081] Step 1.2: Import the preliminary architectural model and the architectural guide sign model into Unity 3d software to edit, including creating a scene, editing a map, adding a rigid body and a physical collision;

[0082] Step 1.3: Bind the architectural guide sign model with the architectural guide sign design database to realize synchronous changes and prepare for subsequent interactive design. Specific embodiment three:

[0084] The difference between the embodiment three and the embodiment two is only that:

[0085] The step 2 is specifically:

[0086] Step 2.1: Use the Open XR toolkit and the XR interaction Toolkit resource package carried by the Unity3D software to make a virtual scene roaming function controlled by a handle; make a UI interactive interface to complete a virtual route search experiment function; write a first-person camera track code to complete behavior trajectory acquisition;

[0087] Step 2.2: Complete the route search eye movement experiment in the virtual scene, collect the visual information of the experimental personnel during virtual roaming through the eye movement tracking component; collect the behavior trajectory of the experimental personnel through the track code;

[0088] Step 2.3: Combine the visual information and the behavior trajectory to obtain the continuity, readability and saliency indicators of the architectural guide sign system; and calculate the objective efficiency value E O of the architectural guide sign system.

[0089] The calculation method of the objective efficiency value E O is as follows:

[0090] The objective efficiency value of the guide sign is the sum of the continuity indicator, the readability indicator and the saliency indicator after removing the dimension by the normalization method, which is calculated by the following formula:

[0091]

[0092] Wherein, CT(n) is the continuity indicator, min n CT(n) and max n CT(n) are the minimum value and the maximum value of the continuity indicator, RW(n) is the readability indicator, min n RW(n) and max n RW(n) are the minimum value and the maximum value of the readability indicator, CS(n) is the saliency indicator, min n CS(n) and max n CS(n) are the minimum value and the maximum value of the saliency indicator.

[0093] Step 2.4: Based on the PSO particle swarm optimization algorithm, three indicators of the building guide sign system are used to calculate E O Unfold the first round of optimization of the building guide sign design library. Specific embodiment four:

[0095] The difference between the fourth embodiment and the third embodiment of the present application is only that:

[0096] The continuity indicator of the building guide sign system is calculated based on the trajectory of the experimental personnel, and the continuity and readability indicators of the building guide sign system are calculated based on visual information separation. The calculation method is as follows:

[0097] First, calculate the shortest path D1(n) between each two continuously arranged building guide signs in the building guide sign system; call the behavior trajectory data to record the actual walking path D2(n) of the experimental personnel between each two continuously arranged building guide signs, and finally calculate the continuity indicator CT(n) of the building guide sign system by formula 1:

[0098] Specific embodiment five:

[0100] The difference between the fifth embodiment and the fourth embodiment of the present application is only that:

[0101] The first round of optimization is as follows:

[0102] Step S1, set the building guide sign design library as a particle swarm to be optimized, and each building guide sign system design corresponds to each particle to be optimized; initialize the particle swarm to take the continuity, readability and saliency indicators of the guide sign system as the position X I , and calculate the fitness value f according to X I ;

[0103] Step S2, record the individual historical optimal fitness value f p of each particle and the global historical optimal fitness value f g of the particle swarm, and take the position corresponding to each fitness value as the individual historical optimal position X and the global historical optimal position X

[0104] Step S3, calculate the particle update speed by the following formula:

[0105]

[0106] wherein, is the particle speed generated in the new round of iteration, ω is the inertia parameter; is the particle speed generated in the last round of iteration, C1 and C2 are learning parameters, is the individual historical optimal position of the particle, is the particle position generated in the last iteration, is the global historical optimal position of the particle

[0107] Step S4, updating the particle position by the following formula:

[0108]

[0109] wherein, is the particle position generated in the new iteration, is the particle position generated in the last iteration, is the particle velocity generated in the new iteration;

[0110] Step S5, re-evaluating the particle fitness value, comparing whether the fitness value of each particle is better than the individual historical optimal fitness value f p good, if yes, then replace; at the same time, re-calculate the global optimal fitness value of the particle, compare whether the global optimal fitness value of the particle is better than the global historical optimal fitness value f g good, if yes, then replace;

[0111] Step S6, repeating steps S3-S5 until the optimization requirement is met; output the global optimal value of the optimized particle and the continuity, readability and significance indicators of the design particle represented by the updated particle position in step S4 change, and the corresponding guiding sign design and guiding sign model are updated synchronously. Specific embodiment six:

[0113] The difference between the embodiment six and the embodiment five is only that:

[0114] The step 3 is specifically:

[0115] Step 3.1: making interactive design function in Unity3D software, taking the building guiding sign model as the interactive object, and realizing that the guiding sign design library can be modified;

[0116] Step 3.2: completing interactive design in the virtual scene, collecting the interactive design results of the experimenters; the experimenters fill in the experimental evaluation table, and collect the subjective evaluation of the building guiding sign system;

[0117] Step 3.3: combining the subjective evaluation of the experimenters and the interactive design results, calculating the subjective efficiency value E S of the building guiding sign system, and obtaining the score Eva(n) of each part of the guiding sign system in the experimental evaluation table, and calculating the sum according to the following formula, that is, the subjective efficiency value E S

[0118]

[0119] Wherein, Eva(i)---subjective score;

[0120] Step 3.4: using E S As a reference, the second round of optimization is performed on the building guide sign design library, and a recommended design library is generated. Specific embodiment seven:

[0122] The difference between the embodiment seven and the embodiment six is only that:

[0123] The application provides a building guide sign system virtual interactive design system based on a PSO algorithm, which comprises a roaming scene simulation module, a virtual interactive design module and a data acquisition and storage module.

[0124] The roaming scene simulation module comprises a three-dimensional building model, a building guide sign design library and a simulated route searching roaming scene.

[0125] The virtual interactive design module comprises a virtual route searching experiment, a building guide sign interactive design and a design intelligent optimization.

[0126] The data acquisition and storage module collects and stores visual information, subjective evaluation and interactive design results of the experiment personnel, and provides a reference for building guide sign optimization design. Specific embodiment eight:

[0128] The difference between the embodiment eight and the embodiment seven is only that:

[0129] The application provides a building guide sign system virtual interactive design system based on a PSO algorithm, which comprises:

[0130] A virtual scene establishment module, which establishes a virtual roaming scene based on investigation data, and comprises a three-dimensional building scene, a building guide sign design library and a Unity virtual environment.

[0131] A first round of optimization module, which completes route searching eye movement in a virtual reality scene, collects visual data and behavior trajectory of the experiment personnel, and determines an objective efficiency value E of the building guide sign system. O Based on a PSO particle swarm optimization algorithm, E O The building guide sign design library is optimized in the first round.

[0132] An interactive design module, which completes interactive design in the virtual reality scene, collects subjective evaluation and design results of the experiment personnel on the building guide sign system, and calculates a subjective efficiency value E of the building guide sign system. S E SA second round of optimization was conducted on the building wayfinding signage design library to generate a recommended design library.

[0133] The verification module collects the final design results and the recommended design library, and packages and stores them according to the experimenter's identity information and experiment time to provide data reference for the design. Specific Implementation Example Nine:

[0135] The difference between Embodiment Nine and Embodiment Eight in this application lies only in:

[0136] The present invention provides a computer-readable storage medium having a computer program stored thereon, which is executed by a processor to implement a virtual interactive design method for a building wayfinding signage system based on the PSO algorithm. Specific Implementation Example 10:

[0138] The only difference between Embodiment 10 and Embodiment 9 of this application is that:

[0139] The present invention provides a computer device, including a memory and a processor. The memory stores a computer program. When the processor runs the computer program stored in the memory, the processor executes a virtual interactive design method for a building wayfinding signage system based on the PSO algorithm.

[0140] This invention is a virtual interactive design method for a building wayfinding signage system based on the PSO algorithm. It involves constructing a 3D virtual building space model based on survey data, collecting materials and establishing a building wayfinding signage design library, and building a virtual reality scene. Within the virtual reality scene, a pathfinding eye-tracking experiment is conducted to collect visual data and behavioral trajectories of the participants, thereby calculating the objective efficiency value of the building wayfinding signage. The building wayfinding signage design library is then optimized using the PSO particle swarm optimization algorithm. Interactive design is completed within the virtual reality scene, collecting the participants' subjective evaluations and design results of the building wayfinding signage system, and calculating the subjective efficiency value of the building wayfinding signage based on both. A second round of optimization is performed on the building wayfinding signage design library to generate a recommended design library. The final design results and the recommended design library are collected, packaged and stored according to participant identity information and experiment time, providing data reference for subsequent related designs. Specific Implementation Example Eleven:

[0142] The only difference between Embodiment Eleven and Embodiment Ten of this application is that:

[0143] like Fig. 1 The virtual interactive design method for a building wayfinding signage system based on the PSO algorithm, as shown, includes the following steps:

[0144] S1: Based on the survey data, build a virtual roaming scene, which includes: establishing a 3D architectural scene, a building wayfinding sign design library, and a Unity virtual environment;

[0145] S2: Complete the wayfinding eye movement experiment within the virtual reality scene, collect the visual data and behavior trajectory of the experiment personnel, and then calculate the objective efficiency value E of the building guide sign system O ; Based on the PSO particle swarm optimization algorithm, use E O Optimize the building guide sign design library for one round:;

[0146] S3: Complete the interactive design within the virtual reality scene, collect the subjective evaluation and design results of the experiment personnel on the building guide sign system, and calculate the subjective efficiency value E of the building guide sign system based on the two; S ; Use E S Optimize the building guide sign design library for two rounds to generate a recommended design library;

[0147] S4: Collect the final design results and the recommended design library, and package and store them according to the experiment personnel's identity information and experiment time as tags for data reference for subsequent related designs.

[0148] The step S1 specifically comprises:

[0149] S11: Use a 3D infrared scanner to scan the existing building, take photos of the interior environment of the building, and build a preliminary building model; collect regular building guide sign design materials through research, build a building guide sign model and a building guide sign design library;

[0150] S12: Import the preliminary building model and the building guide sign model into Unity 3d software for editing including creating scenes, editing maps, adding rigid bodies and physical collisions;

[0151] S13: Bind the building guide sign model and the building guide sign design library data to realize synchronous changes and prepare for subsequent interactive design.

[0152] The step S2 specifically comprises:

[0153] S21: Use the Open XR toolkit and XR interaction Toolkit resource package carried by Unity3D software to make a virtual scene roaming function controlled by a handle; make a UI interactive interface to complete the virtual wayfinding experiment function; write a first-person camera tracking code to complete the behavior trajectory collection function;

[0154] S22: Complete the wayfinding eye movement experiment within the virtual scene, collect the visual information of the experiment personnel during virtual roaming through the eye movement tracking component; collect the behavior trajectory of the experiment personnel through the trajectory tracking code;

[0155] S23: combine visual information and behavior trajectory to obtain continuity, readability and salience indicators of building guide sign system; further, calculate objective efficiency value E of building guide sign system O ;

[0156] S24: based on PSO particle swarm optimization algorithm, use three indicators of building guide sign system and E O to expand one round of optimization of building guide sign design library;

[0157] In the step S23: the continuity, readability and salience indicators of building guide sign system are obtained in different ways, the continuity indicator of building guide sign system is calculated based on the behavior trajectory of experimenters, and the continuity and readability indicators of building guide sign system are obtained based on visual information separation. The calculation method is as follows:

[0158] Further, the continuity calculation method of building guide sign system is as follows: first, calculate the shortest path D1(n) between each two continuous building guide signs in the building guide sign system; call the behavior trajectory data, record the actual walking path D2(n) of experimenters between each two continuous building guide signs, and finally calculate the continuity indicator CT(n) of the building guide sign system by formula 1.

[0159]

[0160] In formula 1, CT(n) is the continuity indicator

[0161] D1(n) is the shortest path set

[0162] D2(n) is the actual walking path set

[0163] The readability of building guide sign system is related to the total gaze time of guide signs in visual information, specifically: separate the visual information of experimenters to obtain the total gaze time of each sign in the guide sign system to obtain the readability indicator RW(n) of the building guide sign system;

[0164] The salience of building guide sign system is related to the first gaze time of guide signs in visual information, specifically: separate the visual information of experimenters to obtain the first gaze time of each sign in the guide sign system to obtain the salience indicator CS(n) of the building guide sign system

[0165] In the step S23, the calculation method of objective efficiency value E O is as follows:

[0166] The objective efficiency value of guide sign is the sum of its continuity indicator, readability indicator and salience indicator after removing the dimension by normalization method, and the calculation formula is formula 2:

[0167]

[0168] E0—objective efficiency value of building guide sign system in formula 2

[0169] RW(n)—continuity index

[0170] min n CT(n), max n CT(n)—minimum value, maximum value of continuity index

[0171] RW(n)—readability index

[0172] min n RW(n), max n RW(n)—minimum value, maximum value of readability index

[0173] CS(n)—significance index

[0174] min n CS(n), max n CS(n)—minimum value, maximum value of significance index

[0175] The objective efficiency value of the building guide sign system placed in the virtual reality scene can be calculated by formula 2, and the rest of the building guide sign system designs in the design library are calculated by calculating the difference from the test system.

[0176] In the step S24, one round of optimization based on the PSO algorithm is specifically:

[0177] Step 1. Set the building guide sign design library as the particle swarm to be optimized, and each building guide sign system design corresponds to each particle to be optimized; initialize the particle swarm to take the continuity, readability and significance indexes of the guide sign system as the position X I , according to X I Performance evaluation fitness value f;;

[0178] Step 2. Record the individual historical optimal fitness value f p of each particle and the global historical optimal fitness value f g in the particle swarm, and take the positions corresponding to the fitness values as the individual historical optimal position P ibest and the global historical optimal position P best ;

[0179] Step 3. Calculate the particle update speed by formula 3;

[0180]

[0181] ω —— inertia parameter — particle velocity generated in the new round of iteration

[0182] ω —— inertia parameter

[0183] — particle velocity generated in the last round of iteration

[0184] C1, C2 —— learning parameters

[0185] — particle individual historical optimal position

[0186] — particle position generated in the last round of iteration

[0187] — particle global historical optimal position

[0188] step 4. Update the particle position by formula 4;

[0189]

[0190] ω —— inertia parameter — particle position generated in the new round of iteration

[0191] — particle position generated in the last round of iteration

[0192] — particle velocity generated in the new round of iteration

[0193] step 5. Re-evaluate the particle fitness value, compare whether the fitness value of each particle is better than the individual historical optimal fitness value f p good, then replace; at the same time, recalculate the particle global optimal fitness value, compare whether the particle global optimal fitness value is better than the global historical optimal fitness value f g good, then replace;

[0194] step 6. Repeat step 3-step 5 until the optimization requirement is met; output the optimized particle global optimal value and

[0195] The update of the particle position in step 4 represents that the continuity, readability and significance index of the designed particle change, and the corresponding guiding sign design and guiding sign model are updated synchronously;

[0196] The step S3 specifically comprises:

[0197] S31: Make interactive design functions in Unity3D software, take the guiding sign model as the interactive object, and realize that the guiding sign design library can be modified;

[0198] S32: completing the interactive design in the virtual scene, collecting the interactive design results of the experimenters; the experimenters fill in the experiment evaluation table and collect their subjective evaluation on the guiding sign system

[0199] S33: combining the subjective evaluation of the experimenters and the interactive design results, calculating the subjective efficiency value E of the guiding sign system S

[0200] S34: using E S as a reference, the guiding sign design library is optimized for two rounds, and a recommended design library is generated.

[0201] In the step S32: experiment evaluation;

[0202] In the step S33: the calculation method of the subjective efficiency value E S The calculation method of the subjective efficiency value E

[0203] Get the score Eva(n) of each part of the guiding sign system in the experiment evaluation table, and calculate the sum according to formula 5, that is, the subjective efficiency value E S

[0204]

[0205] In formula 5, E S Subjective efficiency value of building guiding sign

[0206] Eva(i) - subjective score

[0207] In the step S33: the method of two-round updating is specifically

[0208] The subjective efficiency value of the guiding sign system of the subject placed in the virtual reality scene is calculated, and the remaining design library is calculated by calculating the difference between the sign system design and the subject system; after the subjective efficiency value of various designs in the guiding sign design library is obtained, the guiding sign design library is reordered according to the subjective efficiency value from large to small, and the two-round optimization is completed; the top 10 designs of the guiding sign design library are extracted to become a recommended design library.

[0209] In addition, as Fig. 2 shown, the present application also provides a virtual interactive design system for building guiding signs, which comprises a roaming scene simulation module, a virtual interactive design module, a data acquisition and storage module;

[0210] ​The roaming scenario simulation module is used to establish a three-dimensional building scenario, a guide sign design library and a pedestrian simulation model, simulate the behavior of pedestrians in the building scenario, and restore the real roaming scenario. The virtual interactive design module is used to collect the behavior data and subjective evaluation of the experimental personnel during roaming, determine the weak links of the building guide sign design, and modify the guide sign design. The data collection and storage module is used to collect and store the data including the motion trajectory of the experimental personnel, eye movement data, audible thinking back record, subjective evaluation table and interactive design results, and store them according to the identity information and experimental time as tags.

[0211] Based on the research data, a three-dimensional model of a virtual building space is built, materials are collected and a guide sign design library is established, and a virtual reality scene is constructed. In the virtual scene, an interactive design experiment is carried out, visual data and action trajectory of the experimental personnel in the experiment are collected, and the objective efficiency value E O of the building guide sign is calculated. The subjective evaluation of the experimental personnel on the building guide sign and the interactive design results are collected, and the subjective efficiency value E S is calculated. Based on E O , the PSO particle swarm optimization algorithm is used to calculate the optimal design results of the building guide sign, and based on E S , the recommended design library is updated. Finally, the design results are collected and stored, and stored according to the identity information of the experimental personnel and the experimental time as tags, providing data reference for subsequent related design.

[0212] In the description of the specification, the description of the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" and the like means that the specific features, structures, materials or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of the present application. In the specification, the illustrative description of the above terms does not necessarily refer to the same embodiment or example. Also, the specific features, structures, materials or characteristics described can be combined in any appropriate manner in any one or N embodiments or examples. In addition, the person skilled in the art can combine and combine the different embodiments or examples described in the specification and the features of the different embodiments or examples, without contradiction. In addition, the terms "first", "second" are used for descriptive purposes only and cannot be understood as indicating or implying relative importance or implicitly indicating the number of indicated technical features. Therefore, the features limited by "first", "second" can explicitly or implicitly include at least one of the features. In the description of the present application, the meaning of "N" is at least two, for example, two, three, etc., unless otherwise specifically limited. Any process or method described in the flowchart or otherwise described herein can be understood as representing a module, fragment or part of code including one or more executable instructions for implementing custom logic functions or processes, and the scope of the preferred embodiments of the present application includes additional implementations in which the functions can be performed in the order shown or discussed, including in a substantially simultaneous manner or in reverse order according to the functions involved, which should be understood by the person skilled in the art. The embodiments of the present application. In the flowchart or otherwise described herein, logic and / or steps, for example, can be considered as a list of executable instructions for implementing logical functions, which can be embodied in any computer readable medium for use by an instruction execution system, device or apparatus, such as a computer based system, a system including a processor or other system that can fetch and execute instructions from the instruction execution system, device or apparatus. For the purpose of the present specification, "computer readable medium" can be any device that can contain, store, communicate, propagate or transport programs for use by an instruction execution system, device or apparatus or in conjunction with these instruction execution systems, devices or apparatus. More specific examples (non-exhaustive list) of computer readable medium include the following: electrical connections having one or N wires (electronic devices), portable computer diskette (magnetic devices), random access memory (RAM), read only memory (ROM), erasable programmable read only memory (EPROM or flash memory), fiber optic devices, and portable compact disc read only memory (CD ROM).Additionally, a computer readable medium can be paper or other comparable effectively medium whereupon the program is printed, since the program can be electronically retrieved, for example by optically scanning the paper or other medium, then electronically converting the scanned steps into a useable format, and then storing this information onto a computer storage medium. It is to be understood that the steps of the foregoing embodiments can be tramsformed by one skilled in the art to be implemented through hardware, software, firmware or a combination thereof depending on the particular application or in conformance with the actual desires of the inventor(s). In the foregoing embodiment, the steps of the method can be implemented in software or firmware that is stored in memory and executed by a suitable instruction execution system. As such, in some embodiments, the steps of the method can be implemented in hardware, in software stored on a machine-readable medium which is executed by a machine processor or by a combination thereof. In some embodiments, the steps of the method can be implemented in hardware using, for example, any one or a combination of the following technologies, which are all well known in the art: a discrete logic circuit(s) having logic gates for implementing logic functions upon an application of data signals; an application specific integrated circuit having appropriate combinational logic gates; a programmable gate array(s) (PGA(s)) ; a field programmable gate array(s) (FPGA(s)) ; and the like.

[0213] Those skilled in the art can understand that all or part of the steps of the foregoing method embodiments can be instructed by a program to relevant hardware, and the program can be stored in a computer readable storage medium. When the program is executed, it includes one of the steps of the method embodiments or a combination thereof. In addition, each functional unit in each embodiment of the present application can be integrated into a processing module, or each unit can exist physically independently, or two or more units can be integrated into a module. The integrated module can be realized in the form of hardware or in the form of a software function module. If the integrated module is realized in the form of a software function module and sold or used as an independent product, it can also be stored in a computer readable storage medium.

[0214] The above is only a preferred embodiment of the building guide sign system virtual interactive design method based on the PSO algorithm, and the protection scope of the building guide sign system virtual interactive design method based on the PSO algorithm is not limited to the above-mentioned embodiments. Any technical solution under the same idea belongs to the protection scope of the present application. It should be noted that for those skilled in the art, some improvements and changes without departing from the principles of the present application should also be considered as the protection scope of the present application.

Claims

1. A PSO algorithm-based virtual interaction design method for a building guide sign system, characterized by: The method comprises the following steps: Step 1: Establish a virtual roaming scene based on the research data, including establishing a three-dimensional building scene, a building guide sign design library and a Unity virtual environment; Step 2: Complete the eye movement of wayfinding in the virtual reality scene, collect the visual data and behavior trajectory of the experimenters, and determine the objective efficiency value of the building guide sign system E O ; based on the PSO particle swarm optimization algorithm, using E O Optimize the building guide sign design library for the first time Step 3: Complete the interaction design within the virtual reality scene, collect the subjective evaluation of the experimental personnel on the building guide sign system and the design results, and calculate the subjective efficiency value of the building guide sign system E S ; using E S The second round of optimization is performed on the building guide sign design library to generate a recommended design library; Step 4: Collect the final design results and the recommended design library, and package and store them according to the experimental personnel identity information and the experimental time as tags to provide data reference for the design; The first round of optimization is specifically: Step S1, set the building guide sign design library as a to-be-optimized particle group, each building guide sign system design corresponds to each to-be-optimized particle; initialize the particle group to take the continuity, readability and saliency of the guide sign system as the position X I , according to X I performance evaluation adaptive value f ; Step S2, recording individual history optimum fitness value of each particle with global history optimum fitness value in the particle swarm and taking the position corresponding to each fitness value as individual history optimum position with global history optimum position ; Step S3, calculate the particle update speed by the following formula: (3) wherein, is the particle velocity generated in the new iteration round, is the inertia parameter; is the particle velocity generated in the previous iteration round, C 1 、C 2is the learning parameter, is the particle individual history best position; is the particle position generated in the previous iteration round, is the particle global history best position Step S4, update the particle position by the following formula: (4) wherein, is the particle position generated in the new iteration round, is the particle position generated in the previous iteration round, is the particle velocity generated in the new iteration round; Step S5, re-evaluating the fitness value of the particle, comparing whether the fitness value of each particle is better than the individual historical optimal fitness value OK, if yes, replace; at the same time, re-calculate the global optimal fitness value of the particle, compare whether the global optimal fitness value of the particle is better than the global historical optimal fitness value OK, if yes, replace; Step S6, repeat steps S3-S5 until the optimization requirements are met; output the optimized particle global optimal value and the continuity, readability and significance indicators of the design particle represented by the updated particle position in step S4 change, and the guide sign design and the guide sign model are updated synchronously.

2. The method according to claim 1, wherein the method is characterized in that: The step 1 is specifically: Step 1.1: use a 3D infrared scanner to scan the existing building, take photos of the interior environment of the building, and build a preliminary building model; collect conventional building guide sign design materials through research, and build a building guide sign model and a building guide sign design library; Step 1.2: import the preliminary building model and the building guide sign model into Unity 3D software for editing, including creating scenes, editing maps, adding rigid bodies and physical collisions; Step 1.3: bind the building guide sign model and the building guide sign design library data to realize synchronous changes and prepare for subsequent interactive design.

3. The method according to claim 2, wherein the method is characterized in that: The step 2 is specifically: Step 2.1: use the Open XR toolkit and XR interaction Toolkit resource package carried by Unity3D software to make a virtual scene roaming function controlled by a handle; make a UI interactive interface to complete the virtual route finding experiment function; write a first-person camera track code to complete the behavior trajectory collection; Step 2.2: complete the route finding eye movement experiment in the virtual scene, collect the visual information of the experimental personnel during virtual roaming through the eye movement tracking component; collect the behavior trajectory of the experimental personnel through the track code; Step 2.3: Combine visual information with behavior trajectory to derive continuity, legibility and prominence indicators of the building signage system; and calculate the objective efficiency value of the building signage system E O ; Objective efficiency value E O The calculation method is: The objective efficiency value of the guide sign is the sum of the continuity index, the readability index and the significance index after removing the dimension by the normalization method, which is calculated by the following formula: (2) wherein, CT(n) is a continuity index, min n CT(n)、max n CT(n) is a minimum, maximum of a continuity index, RW (n) is a readability index, min n RW(n)、max n RW(n) is a minimum, maximum of a readability index, CS(n) is a saliency index, min n CS(n)、max n CS(n) is a minimum, maximum of a saliency index; Step 2.4: Based on PSO particle swarm optimization algorithm, use the three indicators of the building orientation sign system and E O Unfold the first round of optimization of the building orientation sign design library.

4. The virtual interactive design method of the building guide sign system based on the PSO algorithm according to claim 3, characterized in that: The continuity index of the building guide sign system is calculated based on the behavior trajectory of the experimental personnel, and the continuity and readability index of the building guide sign system is calculated based on the visual information separation, and the calculation method is specifically: Firstly, the shortest path between every two consecutive building guide signs in the building guide sign system is calculated D 1 （n） ; the actual walking path of the experimental personnel between every two consecutive building guide signs is recorded by calling the behavior trajectory data D 2 （n） , and finally the continuity index of the building guide sign system is calculated by formula 1 CT(n) : （1）。 5. The virtual interactive design method of the building guide sign system based on the PSO algorithm according to claim 4, characterized in that: The step 3 is specifically: Step 3.1: make an interactive design function in Unity3D software, take the building guide sign model as an interactive object, and realize that the guide sign design library can be modified; Step 3.2: Complete the interaction design within the virtual scene, collect the interaction design results of the experimenters; experimenters fill out the experimental evaluation form and collect subjective evaluation of the building guide sign system; Step 3.3: Combine the subjective evaluation of the experimenters with the results of the interaction design to calculate the subjective efficiency value of the building guide sign system E S ; obtain the score of each part of the guide sign system in the experimental evaluation table Eva (n) , and the sum is the subjective efficiency value according to the following formula E S （5） wherein, - subjective score; Step 3.4: Using E S As a reference, a second round of optimization is performed on the building wayfinding sign design library and a recommended design library is generated.

6. A PSO algorithm-based virtual interactive design system for building signage systems, the system being run based on the method of claim 1, characterized by: The system comprises a roaming scene simulation module, a virtual interaction design module, and a data collection and storage module. The roaming scene simulation module comprises a three-dimensional building model, a building guide sign design library, and a simulated route-finding roaming scene. The virtual interaction design module comprises a virtual route-finding experiment, building guide sign interaction design, and design intelligence optimization. The data collection and storage module collects and stores the visual information, subjective evaluation, and interaction design results of the experimenters, providing a reference for the optimization design of building guide signs.

7. A PSO algorithm-based virtual interactive design system for building signage systems, the system being run based on the method of claim 1, characterized by: The system comprises: A virtual scene establishment module that establishes a virtual roaming scene based on research data, including the establishment of a three-dimensional building scene, a building guide sign design library, and a Unity virtual environment; A first round of optimization module, the first round of optimization module completes the wayfinding eye movement in the virtual reality scene, collects the visual data and behavior trajectory of the experimental personnel, and determines the objective efficiency value of the building guide sign system E O ; based on the PSO particle swarm optimization algorithm, using E O The building guide sign design library is optimized in the first round. An interaction design module is used to complete interaction design within the virtual reality scene, collect subjective evaluation of the experimental personnel on the building guide sign system and design results, and calculate a subjective efficiency value of the building guide sign system E S ; using E S A second round of optimization is performed on the building guide sign design library to generate a recommended design library A verification module that collects the final design results and the recommended design library, and stores them according to the experimenters' identity information and experimental time as tags, providing data reference for design.

8. A computer-readable storage medium having stored thereon a computer program, characterized in that, The program is executed by a processor for implementing a virtual interaction design method for a building guide sign system based on a PSO algorithm as claimed in any one of claims 1-5.

9. A computer device, comprising: It comprises a memory and a processor, and the memory stores a computer program, when the processor runs the computer program stored in the memory, the processor executes a virtual interaction design method for a building guide sign system based on a PSO algorithm as claimed in any one of claims 1-5.

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