Subway station way-finding method and system based on sound scene guidance

Abstract

The invention belongs to the technical field of man-machine interaction, and particularly relates to a subway station way-finding method and system based on sound scene guidance. Determining sound scene elements which may influence visual search and path-finding efficiency of the passenger; establishing a VR virtual scene model containing environment information; based on the constructed VR virtual scene model, multiple groups of contrast experiments are carried out by changing parameters of sound scene elements, a subject wears VR equipment to carry out subway station way-finding simulation in a 3D scene, way-finding efficiency under different sound scene setting conditions is recorded, and data are collected; and performing analysis based on the combination of the collected experimental data and the actual environment condition or design condition of the target subway station, and formulating an optimal sound scene guiding scheme so as to realize implementation and application in the target subway station. The method is used for solving the problems that an effective sound scene guiding method is difficult to design and related methods cannot be flexibly applied to real and non-real scenes due to lack of a quantitative control method for acoustic parameters related to path-finding efficiency in the prior art.

Description

Technical Field

[0001] The present invention belongs to the technical field of human-computer interaction, and particularly relates to a subway station wayfinding method and system based on soundscape guidance. Background Art

[0002] In transportation hubs such as subway stations, it is particularly important for passengers to quickly and effectively identify environmental information and reach their destinations. Therefore, an accurate and efficient wayfinding system is needed to guide passengers in terms of direction. The existing wayfinding in subway stations mainly relies on visual search guidance systems such as guiding signs and station maps. Due to the existence of attention competition, this system is usually easily affected by other environments, or due to improper arrangement of visual signs or inconspicuous setting positions, resulting in chaotic and inefficient wayfinding within the station. In addition, the single visual wayfinding guidance ignores the wayfinding needs of visually impaired people, causing difficulties for visually impaired people to find their way and affecting their travel safety and efficiency.

[0003] To solve the above problems, the present invention proposes an innovative subway station guiding wayfinding method combined with soundscape design. This method uses VR technology to construct a highly restored subway station environment model to achieve precise control of environmental parameters. At the same time, through controlled acoustic parameter simulations and comparative experiments, the wayfinding efficiency and accuracy of subjects in different soundscape environments are compared and analyzed, which can effectively quantify the impact of different acoustic parameters on passengers' wayfinding efficiency and path search, and can provide refined guidance for the optimization of soundscape settings in specific subway stations and the design of future subway station barrier-free wayfinding systems. Summary of the Invention

[0004] The present invention provides a subway station wayfinding method based on soundscape guidance to solve the problem in the prior art that due to the lack of a quantitative control method for acoustic parameters related to wayfinding efficiency, it is difficult to design an effective soundscape guidance method, and at the same time, it is also impossible to flexibly apply related methods to real and non-real scenarios.

[0005] The present invention provides a subway station wayfinding system based on soundscape guidance to implement a subway station wayfinding method based on soundscape guidance.

[0006] The present invention is realized through the following technical solutions:

[0007] A subway station wayfinding method based on soundscape guidance, the method comprising the following steps:

[0008] Step 1, determining soundscape elements that may affect passengers' visual search and wayfinding efficiency, including sound source position, number of sound sources, loudness, pitch, sound pressure level, and / or sound content;

[0009] Step 2, based on the soundscape elements in Step 1, establishing a VR virtual scene model containing environmental information according to the actual environmental conditions or design conditions of the target subway station;

[0010] Step 3: Based on the VR virtual scene model constructed in Step 2, conduct multiple groups of comparative experiments by changing the parameters of the soundscape elements determined in Step 1. The subjects wear VR devices to perform subway station wayfinding simulations in the 3D scene, record the wayfinding efficiency under different soundscape settings, and collect data.

[0011] Step 4: Analyze the experimental data collected in Step 3 in combination with the actual environmental conditions or design conditions of the target subway station, and formulate the best soundscape guidance plan for implementation and application at the target station.

[0012] Furthermore, Step 1 specifically includes the following steps:

[0013] Step 1.1: Use literature reviews, passenger interviews, or expert consultations to determine the key soundscape elements that may affect passenger wayfinding efficiency, including sound source location, number of sound sources, loudness, pitch, sound pressure level, and sound content.

[0014] Step 1.2: Based on the typical characteristics of the soundscape elements, preliminarily judge the direction of the influence of each element on wayfinding efficiency, and use the expert scoring method to determine the importance weights of each element.

[0015] Furthermore, Step 2 specifically includes the following steps:

[0016] Step 2.1: Extract the physical information of the target subway station scene, record the environmental information, measure and record the physical information of the sound environment of the target subway station, and record the on-site audio.

[0017] Step 2.2: Divide the target station into five functional zones according to the spatial form, namely the subway entrance, the entrance passage, the concourse of the ticket hall, the platform passage, and the platform level.

[0018] Step 2.3: Combine the physical information recorded in Step 2.1 and the functional zones in Step 2.2, use 3D modeling software to build a 3D model of the target subway station, import the 3D model into Unity software for rendering, and import the pre-recorded on-site audio into the Audio Sourse component of Unity software according to the measured values to create 3D spatial audio and restore the virtual subway station scene.

[0019] Furthermore, or Step 2.1: Extract the physical design information of the target subway station scene, record the environmental information in the design scheme, refer to and record the physical information of the real sound environment conditions of the target subway station, and record the on-site audio.

[0020] Furthermore, Step 3 specifically includes the following steps:

[0021] Step 3.1: Randomly select multiple subjects to participate in the experiment. First, the subjects wear VR devices and complete the benchmark in-station wayfinding behavior according to the specified destinations in the basic subway station scene constructed in Step 2, and record their average time used and accuracy rate.

[0022] Step 3.2: After completing the benchmark in-station wayfinding behavior, quantitatively change the soundscape elements determined in Step 1, and import the adjusted 3D spatial audio into the subway station virtual scene to conduct multiple groups of comparative experiments again. The subjects continuously repeat Step 3.1, record the soundscape element parameters, time used, and accuracy of all groups, and observe the influence of each group of parameters on the wayfinding efficiency of the subjects.

[0023] Step 3.3: After each scene experience, the subjects remove the VR devices and rest for no less than 5 minutes to ensure the accuracy of subsequent experiments.

[0024] Step 3.4: After completing all scene experiences, the users remove the VR devices.

[0025] Further, Step 4 specifically includes the following steps:

[0026] Step 4.1: Conduct multiple linear regression analysis on the recorded soundscape element parameter information and duration.

[0027] Step 4.2: Compare and screen the optimal solution with the basic simulation results, and determine a series of soundscape guiding element parameters that can significantly improve the wayfinding efficiency in the optimal solution set.

[0028] Step 4.3: Combine the specific optimization situations of different subway stations, such as funds, optimization intentions, etc., to select a suitable soundscape setting plan.

[0029] Further, Step 4.1 is specifically: Determine that the y to be predicted is the wayfinding time of the subject, and a group of D-dimensional vectors X, denoted as vector w.

[0030] Thus, a certain y i is expressed as where x i，d represents the d-th eigenvalue of the i-th sample vector Xi;

[0031]

[0032] Use b = w D+1 to represent b in the parameters, expand the D-dimensional features to D + 1 dimensions, and obtain

[0033]

[0034] where the vector w represents the weights of each soundscape element, and the data formed can be expressed as

[0035]

[0036] From this, through calculation, linear programming can obtain an optimal solution, and these optimal solutions yield an optimal hyperplane.

[0037] A subway station wayfinding system based on soundscape guidance, the system uses the subway station wayfinding method based on soundscape guidance as described above, and the system includes:

[0038] A soundscape element determination module that determines soundscape elements that may affect passengers' visual search and wayfinding efficiency, including sound source position, number of sound sources, loudness, pitch, sound pressure level, and / or sound content;

[0039] A VR virtual scene model establishment module that, based on the soundscape elements of the soundscape element determination module, establishes a VR virtual scene model containing environmental information according to the actual environmental conditions or design conditions of the target subway station;

[0040] A data collection module that, based on the VR virtual scene model constructed by the VR virtual scene model establishment module, conducts multiple groups of comparative experiments by changing the parameters of the soundscape elements determined by the soundscape element determination module. The subjects wear VR devices to simulate subway station wayfinding in a 3D scene, record the wayfinding efficiency under different soundscape settings, and collect data;

[0041] An analysis module that analyzes by combining the experimental data collected by the data collection module with the actual environmental conditions or design conditions of the target subway station, and formulates an optimal soundscape guidance plan for implementation and application at the target station.

[0042] A computer device includes a memory, a processor, and a computer program stored on the memory and executable on the processor. When the processor executes the computer program, the above-mentioned method is implemented.

[0043] A computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the above-mentioned method is implemented.

[0044] The beneficial effects of the present invention are:

[0045] The present invention constructs an in-station environment of a subway station simulated by VR, combines different acoustic parameters to simulate the wayfinding environment of the subway station after soundscape design, clarifies the influence of soundscape design on the wayfinding efficiency of passengers in the station, thereby quantitatively analyzing the in-station soundscape wayfinding system, determining the optimal soundscape guidance wayfinding method for the target subway station, which helps to improve the passing efficiency of the crowd in the subway station and improve the traffic convenience and journey experience of passengers (especially visually impaired people).

[0046] The present invention combines a high-fidelity VR environment model and conducts simulation and comparison experiments by controlling acoustic parameters to clarify the quantitative control of acoustic parameters related to wayfinding efficiency in a subway station, thereby realizing the design of an acoustic scene guidance system in the subway station and providing a scientific basis and design guidance for the optimization and improvement of the wayfinding guidance system in the subway station. The method is applicable to both the existing real in-station environment and the non-real scenarios in the scheme design stage.

[0047] The present invention proposes an innovative wayfinding method for subway stations that combines soundscape design, which can integrate the visual wayfinding guidance system and acoustic guidance in the subway station, improve the in-station path search efficiency, ensure the travel convenience of visually impaired people, and optimize the travel experience of subway passengers. Under the framework of this wayfinding method, for the general population (without visual impairment and hearing impairment), it is expected that their wayfinding efficiency can be generally increased by more than 25%; for visually impaired people, it is expected that their wayfinding efficiency can be increased by more than 35%. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] Figure 1 is a flowchart of the method of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0049] In the following description, specific details such as specific system structures and technologies are presented for the purpose of illustration rather than limitation, so as to thoroughly understand the embodiments of the present application. However, those skilled in the art should clearly understand that the present application can also be implemented in other embodiments without these specific details. In other cases, detailed descriptions of well-known systems, devices, circuits, and methods are omitted to avoid unnecessary details from interfering with the description of the present application.

[0050] It should be understood that when used in this specification and the appended claims, the term "comprising" indicates the presence of the described features, wholes, steps, operations, elements, and / or components, but does not exclude the presence or addition of one or more other features, wholes, steps, operations, elements, components, and / or their combinations.

[0051] It should also be understood that the terms used in the specification of the present application are only for the purpose of describing specific embodiments and are not intended to limit the present application. As used in the specification of the present application and the appended claims, unless the context clearly indicates otherwise, the singular forms "a", "an", and "the" are intended to include the plural forms.

[0052] The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings of the present application specification. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all of the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments in the present application without creative efforts shall fall within the scope of protection of the present application.

[0053] In the following description, many specific details are set forth in order to provide a thorough understanding of the present application. However, the present application may also be implemented in other ways different from those described herein. Those skilled in the art may make similar extensions without departing from the connotation of the present application. Therefore, the present application is not limited by the specific embodiments disclosed below.

[0054] Embodiment 1

[0055] As shown in Figure 1 the following, a subway station wayfinding method based on soundscape guidance is provided. The method includes the following steps:

[0056] Step 1: Determine the soundscape elements that may affect the visual search and wayfinding efficiency of passengers, including but not limited to the sound source location, the number of sound sources, loudness, pitch, sound pressure level, or / and sound content, etc.;

[0057] Step 2: Based on the soundscape elements in Step 1, establish a VR virtual scene model containing environmental information according to the actual environmental conditions of the target subway station or (if the subway station is in the design stage, according to the design conditions) design conditions;

[0058] Step 3: Based on the VR virtual scene model constructed in Step 2, conduct multiple groups of comparative experiments by changing the parameters of the soundscape elements determined in Step 1. The subjects wear VR devices to simulate subway station wayfinding in a 3D scene, record the wayfinding efficiency under different soundscape settings, and collect data;

[0059] Step 4: Analyze the experimental data collected in Step 3 in combination with the actual environmental conditions or design conditions of the target subway station, and formulate an optimal soundscape guidance plan for implementation and application at the target station.

[0060] Further, Step 1 specifically includes the following steps:

[0061] Step 1.1: Use literature review, passenger interviews, or expert consultation methods to determine the key soundscape elements that may affect the wayfinding efficiency of passengers, including sound source location, the number of sound sources, loudness, pitch, sound pressure level, and sound content, etc.

[0062] Step 1.2: According to the typical characteristics of the soundscape elements, preliminarily judge the influence direction (positive feedback, negative feedback, magnitude of influence, etc.) of each element on the wayfinding efficiency, and use the expert scoring method to determine the importance weight of each element (for example, the sound pressure level element has been proven to be related to visual search and has a relatively large influence in scientific experiments, so the expert scoring weight will be greater than the sound content element with less research data)

[0063] Further, Step 2 specifically includes the following steps:

[0064] Step 2.1: Extract the physical information of the target subway station scenario, record the environmental information such as moving objects, signs, walls, columns, etc., measure and record the physical information of the sound environment of the target subway station, and record the on-site audio;

[0065] Step 2.2: Divide the target station into five functional zones according to the spatial form, namely the subway entrance, the entrance passage, the concourse of the ticket hall, the platform passage, and the platform level;

[0066] Step 2.3: Combine the physical information recorded in Step 2.1 and the functional zones in Step 2.2, use 3D modeling software such as Sketchup, Rhino, Unity to construct a 3D model of the target subway station, import the 3D model into the Unity software for rendering, and import the pre-recorded on-site audio into the Audio Sourse component of the Unity software according to the measured values to create 3D spatial audio, and restore the virtual subway station scene.

[0067] Further, or in Step 2.1: Extract the physical design information of the target subway station scenario, record the environmental information such as moving objects, signs, walls, columns, etc. in the design scheme, refer to and record the physical information of the similar real sound environment conditions of the target subway station, and record the on-site audio.

[0068] Further, Step 3 specifically includes the following steps:

[0069] Step 3.1: Randomly select multiple subjects (including visually impaired people) to participate in the experiment. The subjects first wear VR devices and complete the benchmark in-station wayfinding behavior in the basic subway station scene constructed in Step 2 according to the specified destination, and record their average time and accuracy rate;

[0070] Step 3.2: After completing the benchmark in-station wayfinding behavior, quantitatively change the soundscape elements determined in Step 1 (for example, change the sound pressure level in decibels per unit; change the sound source position according to the subway entrance, the entrance passage, the ticket hall, etc., and so on), and import the adjusted 3D spatial audio into the virtual subway station scene for multiple groups of comparative experiments. The subjects continuously repeat Step 3.1, record the soundscape element parameters, time, and accuracy of all groups, and observe the impact of each group of parameters on the subjects' wayfinding efficiency;

[0071] Step 3.3: After each scene experience, the subjects remove the VR devices and rest for at least 5 minutes to ensure the accuracy of subsequent experiments;

[0072] Step 3.4: After completing all scene experiences, the user removes the VR device.

[0073] Further, Step 4 specifically includes the following steps:

[0074] Step 4.1: Perform multiple linear regression analysis on the recorded parameter information and duration of each soundscape element;

[0075] Step 4.2: Compare and screen the optimal solutions with the basic simulation results, and determine a series of soundscape guiding element parameters in the optimal solution set that can significantly improve the wayfinding efficiency;

[0076] Step 4.3: Select a suitable soundscape setting plan in combination with the specific optimization situations of different subway stations, such as funds and optimization intentions.

[0077] Further, the specific content of Step 4.1 is as follows: Determine that the y to be predicted is the wayfinding time of the subject, and a set of D-dimensional vectors X (D is the number of soundscape elements related to wayfinding efficiency determined in Step 1.2), denoted as vector w;

[0078] Thus, a certain y i is expressed as where x i，d represents the d-dimensional eigenvalue in the i-th sample vector Xi;

[0079]

[0080]

[0081] Use b = w D+1 to represent b in the parameters, expand the D-dimensional features to D + 1 dimensions, and obtain

[0082]

[0083] where the vector w represents the weights of each soundscape element, and the data formed can be expressed as

[0084]

[0085] In the formula, non-bold represents a scalar, and bold represents a scalar.

[0086] Thus, through calculation (applicable to machine learning), linear programming can obtain an optimal solution, and these optimal solutions obtain an optimal hyperplane (a series of optimal soundscape element parameter sets).

[0087] The present invention innovatively combines subway station wayfinding guidance with soundscape design. By quantitatively controlling relevant soundscape parameters, it realizes in-station sound-assisted path guidance, effectively improves the travel efficiency of subway passengers and the public travel convenience and satisfaction of visually impaired people, and provides a new perspective and tool for the subway station wayfinding system.

[0088] Based on VR simulation technology, the present invention establishes a basic process for testing wayfinding efficiency and regulating related parameters through virtual simulation means, and can quantitatively analyze and judge the soundscape parameters that can effectively improve wayfinding efficiency. This quantitative simulation experimental method provides a scientific basis for the impact of the sound environment in the subway station on the wayfinding guidance efficiency, and helps to accurately implement measures for optimizing the subway traffic environment.

[0089] The present invention classifies the wayfinding efficiency problem in the subway station as a multiple linear regression problem, which can be analyzed using a linear programming model, making it more suitable for machine learning and meeting the processing requirements of today's multi-variable big data problems, providing the possibility of new tool operations for the research of related problems.

[0090] The method proposed by the present invention can cover multiple soundscape design elements, ensuring the comprehensiveness and integrity of the design optimization of the in-station soundscape wayfinding environment.

[0091] Compared with traditional wayfinding methods, the method proposed by the present invention has a wide range of applications, being applicable to both existing scenarios and non-realistic scenarios at the concept stage of the plan, and can provide scientific support for evidence-based design and optimization improvement of the building environment in the subway station.

[0092] Embodiment 2

[0093] This embodiment provides a subway station wayfinding system based on soundscape guidance. The system uses the subway station wayfinding method based on soundscape guidance described in Embodiment 1. The system includes:

[0094] A soundscape element determination module that determines the soundscape elements that may affect passengers' visual search and wayfinding efficiency, including sound source position, number of sound sources, loudness, pitch, sound pressure level, and / or sound content;

[0095] A VR virtual scene model establishment module that, based on the soundscape elements of the soundscape element determination module, establishes a VR virtual scene model containing environmental information according to the actual environmental conditions or design conditions of the target subway station;

[0096] A data collection module that, based on the VR virtual scene model constructed by the VR virtual scene model establishment module, conducts multiple groups of comparative experiments by changing the parameters of the soundscape elements determined by the soundscape element determination module. The subjects wear VR devices to simulate subway station wayfinding in the 3D scene, record and collect data on the wayfinding efficiency under different soundscape settings;

[0097] An analysis module that analyzes by combining the experimental data collected by the data collection module with the actual environmental conditions or design conditions of the target subway station, and formulates an optimal soundscape guidance plan for implementation and application at the target station.

[0098] Based on VR simulation technology, the present invention establishes a basic process for testing pathfinding efficiency and regulating related parameters through virtual simulation means, and can quantitatively analyze and judge the soundscape parameters that can effectively improve pathfinding efficiency. This quantitative simulation experimental method provides a scientific basis for the influence of the sound environment in the subway station on the pathfinding guidance efficiency, and helps to accurately implement measures for optimizing the subway station traffic environment.

[0099] The present invention classifies the pathfinding efficiency problem in the subway station as a multiple linear regression problem, which can be analyzed using a linear programming model, making it more suitable for machine learning and meeting the processing requirements of today's multi-variable big data problems, providing the possibility of new tool operations for the research of related problems.

[0100] Embodiment 3

[0101] The embodiment of the present invention provides an electronic device, which includes a memory, a processor, and a computer program stored in the memory and executable on the processor. Among them, the memory is used to store software programs and modules, and the processor executes various functional applications and data processing by running the software programs and modules stored in the memory. The memory and the processor are connected by a bus. Specifically, when the processor runs the above computer program stored in the memory, any step in the first embodiment is implemented.

[0102] It should be understood that in the embodiment of the present invention, the so-called processor may be a central processing unit (CPU), and the processor may also be other general-purpose processors, digital signal processors (DSPs), application specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or the processor may also be any conventional processor, etc.

[0103] The memory may include a read-only memory, a flash memory, and a random access memory, and provide instructions and data to the processor. A part or all of the memory may also include a non-volatile random access memory.

[0104] ]As can be seen from the above, the electronic device provided by the embodiment of the present invention can implement the subway station wayfinding method based on soundscape guidance as described in Embodiment 1 by running a computer program. By combining a high-fidelity VR environment model and conducting simulation comparison experiments by controlling acoustic parameters, the quantitative control of acoustic parameters related to wayfinding efficiency in the subway station is clarified, so as to realize the design of the soundscape guidance system in the subway station, and provide a scientific basis and design guidance for the optimization and improvement of the wayfinding guidance system in the subway station. The method is applicable to both the existing real in-station environment and the non-real scenarios in the scheme design stage.

[0105] It should be understood that if the above integrated module / unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, to implement all or part of the processes in the above method embodiments of the present invention, it can also be completed by a computer program instructing relevant hardware. The above computer program can be stored in a computer-readable storage medium. When the computer program is executed by a processor, the steps of the above method embodiments can be implemented. Among them, the above computer program includes computer program code, and the above computer program code can be in the form of source code, object code, executable file or some intermediate form, etc. The above computer-readable medium can include: any entity or device capable of carrying the above computer program code, recording medium, USB flash drive, mobile hard disk, magnetic disk, optical disc, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signal, telecommunication signal, and software distribution medium, etc. It should be noted that the content included in the above computer-readable storage medium can be appropriately increased or decreased according to the requirements of legislation and patent practice in the jurisdiction.

[0106] The above description of the disclosed embodiments enables those skilled in the art to implement or use the present invention. Various modifications to these embodiments will be obvious to those skilled in the art, and the general principles defined herein can be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention will not be limited to these embodiments shown herein, but will be accorded the widest scope consistent with the principles and novel features disclosed herein.

[0107] Those skilled in the art can clearly understand that, for the convenience and brevity of description, only the above-mentioned division of each functional unit and module is used as an example. In actual applications, the above-mentioned functions can be allocated to different functional units and modules according to needs, that is, the internal structure of the above-mentioned device can be divided into different functional units or modules to complete all or part of the functions described above. Each functional unit and module in the embodiments can be integrated into a processing unit, or each unit can exist physically alone, or two or more units can be integrated into one unit. The above-mentioned integrated unit can be implemented in the form of hardware or in the form of a software functional unit. In addition, the specific names of each functional unit and module are only for the convenience of mutual distinction and do not limit the protection scope of the present invention. The specific working processes of the units and modules in the above-mentioned system can refer to the corresponding processes in the foregoing method embodiments and will not be elaborated herein.

[0108] It should be noted that the methods and their detailed examples provided in the above embodiments can be combined with the devices and equipment provided in the embodiments for mutual reference and will not be elaborated herein.

[0109] Those of ordinary skill in the art can realize that the units and algorithm steps of each example described in combination with the embodiments disclosed herein can be implemented by electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are executed in a hardware or software manner depends on the specific application and design constraints of the technical solution. Professional technicians can use different methods to implement the described functions for each specific application, but such implementation should not be considered to exceed the scope of the present invention.

[0110] In the embodiments provided by the present invention, it should be understood that the disclosed device / terminal device and method can be implemented in other ways. For example, the device / equipment embodiments described above are only illustrative. For example, the above-mentioned division of modules or units is only a logical function division. In actual implementation, there can be other division methods. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed.

[0111] The above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit them. Although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions described in the foregoing embodiments, or perform equivalent replacements for some of the technical features. These modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention and should all be included in the protection scope of the present invention.

Claims

1. A subway station wayfinding method based on soundscape guidance, characterized in that, The method includes the following steps: Step 1: Determine the soundscape elements that may affect passengers' visual search and wayfinding efficiency, including sound source location, number of sound sources, loudness, pitch, sound pressure level, and / or sound content; Step 2: Based on the soundscape elements in Step 1, establish a VR virtual scene model containing environmental information according to the actual environmental conditions or design conditions of the target subway station; Step 3: Based on the VR virtual scene model constructed in Step 2, conduct multiple groups of comparative experiments by changing the parameters of the soundscape elements determined in Step 1. The subjects wear VR devices to simulate subway station wayfinding in the 3D scene, record the wayfinding efficiency under different soundscape settings, and collect data; Step 4: Analyze the experimental data collected in Step 3 in combination with the actual environmental conditions or design conditions of the target subway station, and formulate the best soundscape guidance plan for implementation and application at the target station.

2. The method according to claim 1, wherein The specific content of Step 1 includes the following steps: Step 1.1: Use literature review, passenger interviews, or expert consultation methods to determine the key soundscape elements that may affect passengers' wayfinding efficiency, including sound source location, number of sound sources, loudness, pitch, sound pressure level, and sound content. Step 1.2: According to the typical characteristics of the soundscape elements, preliminarily judge the influence direction of each element on wayfinding efficiency, and use the expert scoring method to determine the importance weight of each element.

3. The method according to claim 1, characterized in that, The specific content of Step 2 includes the following steps: Step 2.1: Extract the physical information of the target subway station scene, record the environmental information, measure and record the physical information of the sound environment of the target subway station, and record the on-site audio; Step 2.2: Divide the target station into five functional zones according to the spatial form, namely the subway entrance, the entrance passage, the ticket hall concourse, the platform passage, and the platform level; Step 2.3: Combine the physical information recorded in Step 2.1 and the functional zones in Step 2.2, use 3D modeling software to construct a 3D model of the target subway station, import the 3D model into Unity software for rendering, and import the pre-recorded on-site audio into the Audio Sourse component of Unity software according to the measured values to create 3D spatial audio and restore the virtual subway station scene.

4. The method according to claim 3, wherein Or Step 2.1: Extract the physical design information of the target subway station scene, record the environmental information in the design plan, refer to and record the physical information of the real sound environment conditions of the target subway station, and record the on-site audio.

5. The method according to claim 1, wherein The specific content of Step 3 includes the following steps: Step 3.1: Randomly select multiple subjects to participate in the experiment. The subjects first wear VR devices to complete the benchmark in-station wayfinding behavior according to the specified destination in the basic subway station scene constructed in Step 2, and record their average time and accuracy rate; Step 3.2: After completing the benchmark in-station wayfinding behavior, quantitatively change the soundscape elements determined in Step 1, and import the adjusted 3D spatial audio into the subway station virtual scene to conduct multiple groups of comparative experiments again. The subjects continuously repeat Step 3.1, record the soundscape element parameters, time, and accuracy of all groups, and observe the influence of each group of parameters on the subjects' wayfinding efficiency; Step 3.3: After each scenario experience, the subject removes the VR device and takes a rest for at least 5 minutes to ensure the accuracy of subsequent experiments. Step 3.4: After all scenario experiences are completed, the user removes the VR device.

6. The method according to claim 4, wherein The specific steps of Step 4 are as follows: Step 4.1: Perform multiple linear regression analysis on the recorded parameter information and duration of each soundscape element. Step 4.2: Compare and screen the optimal solutions with the basic simulation results, and determine a series of soundscape guiding element parameters in the optimal solution set that can significantly improve the wayfinding efficiency. Step 4.3: Select a suitable soundscape setting plan in combination with the specific optimization conditions of different subway stations, such as funds and optimization intentions.

7. The method according to claim 6, wherein Specifically, Step 4.1 is: Determine that the y to be predicted is the wayfinding time of the subject, and a set of D-dimensional vectors X, denoted as vector w. Thus, a certain y i is represented as where x i，d represents the d-th eigenvalue in the i-th sample vector Xi; Use b = w D+1 to represent b in the parameters, expand the D-dimensional features to D+1 dimensions, and obtain Among them, vector w represents the weights of each soundscape element, and the data formed can be expressed as Thus, through calculation, linear programming can obtain an optimal solution, and these optimal solutions obtain an optimal hyperplane.

8. A subway station wayfinding system based on soundscape guidance, characterized in that, The system uses the soundscape-guided subway station wayfinding method as described in any one of claims 1-7. The system includes: A soundscape element determination module that determines soundscape elements that may affect passengers' visual search and wayfinding efficiency, including sound source position, number of sound sources, loudness, pitch, sound pressure level, and / or sound content. A VR virtual scene model establishment module that, based on the soundscape elements of the soundscape element determination module, establishes a VR virtual scene model containing environmental information according to the actual environmental conditions or design conditions of the target subway station. A data collection module that, based on the VR virtual scene model established by the VR virtual scene model establishment module, conducts multiple sets of comparative experiments by changing the parameters of the soundscape elements determined by the soundscape element determination module. The subject wears the VR device to simulate subway station wayfinding in the 3D scene, records the wayfinding efficiency under different soundscape setting conditions, and collects data. An analysis module that analyzes the experimental data collected by the data collection module in combination with the actual environmental conditions or design conditions of the target subway station, and formulates the best soundscape guiding plan for implementation and application at the target station.

9. A computer device, characterized in that, It includes a memory, a processor, and a computer program stored on the memory and executable on the processor. When the processor executes the computer program, it implements the method as described in any one of claims 1-7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program, and when the computer program is executed by the processor, it implements the method as described in any one of claims 1-7.

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