A comprehensive evaluation method for bus passenger cabin experience

Abstract

A comprehensive evaluation method for passenger cabin experience on buses includes: 1. establishing a control tool framework for a comprehensive evaluation system for passenger cabin experience on buses; 2. performing parameterized and comprehensive construction of data structures for system data, evaluation algorithm data streams, and environmental feedback data; 3. topologically integrating parameters at all levels of the passenger cabin experience system using a formula, specifically by multiplying subjective parameters of human-computer interaction by objective values ​​of their respective comfort experience algorithms and then cumulatively adding them; constructing a topological structure for parameters at all levels; and iterating the dynamic system of the topological structure relationships of each element sphere in a linked manner; 4. comprehensively evaluating the cabin experience by calculating Overall_comfort of the optimized system parameter formula; and 5. iterating the genetic algorithm of the genes for the excellent parameter formula. The present invention implements functional linkage between various parameter elements, can collect customer comfort requirements in different scenarios, and help customers understand their own comprehensive comfort experience formula.

Description

Technical Field

[0001] The present invention relates to the technical field of automobile cockpits, and more specifically to a comprehensive evaluation method for passenger cockpit experience of buses. Background Art

[0002] The comprehensive passenger experience services offered by existing smart buses are rapidly evolving. With the "multiple screens per vehicle" trend, passengers' increasingly diverse entertainment needs have become a hotspot for major automakers to showcase their intelligence. Many new smart cockpit concepts have emerged, such as gaming cockpits, music cockpits, and movie cockpits. Against this backdrop, the integration of streaming platforms, improvements to cockpit entertainment hardware, and the development of XR technology have enabled KTV, cinemas, shopping, and other entertainment and comfort features to be seamlessly integrated into bus cockpits, transforming them into "super entertainment spaces." This has led to the following technical requirements:

[0003] 1. The intelligent passenger cockpit of new buses breaks through the technical limitations of space and sensory perception, providing greater satisfaction for passengers' comfort. Through more intelligent seats, climate control systems, fragrance systems, and entertainment systems, passengers can feel more comfortable and enjoyable while driving. The richness of future bus entertainment and the diversification of cockpit experience dimensions require appropriate fusion technology to integrate various comfort quantitative evaluation systems to adapt to new cockpit experience scenarios.

[0004] 2. With the increasing in-car integration of internet applications, the central control screen in the intelligent driver's cockpit has become a new internet terminal device in addition to its vehicle control functions. To facilitate the driver's use of the central control screen to provide passengers with a suitable integrated riding experience, new experience evaluation technologies are needed to integrate the various adjustable parameters of the vehicle's central control and the passenger compartment.

[0005] 3. Technological development has reduced bus passengers' tolerance for boring rides. Providing games and entertainment services related to the ride experience through tools such as seatback PADs while passengers are riding can alleviate the boredom of the ride. Summary of the Invention

[0006] The present invention provides a comprehensive evaluation method for passenger cabin experience of a bus, which provides passengers with a suitable comprehensive riding experience and makes the passengers feel more comfortable and enjoyable during the ride.

[0007] The present invention adopts the following technical solutions:

[0008] A comprehensive evaluation method for passenger cabin experience of a bus includes the following steps:

[0009] Step 1: Establish a control tool framework for the comprehensive evaluation system of passenger cabin experience in buses;

[0010] Step 2: Perform parameterized comprehensive construction of the data structure of the bus passenger cabin experience comprehensive evaluation system based on the system data, evaluation algorithm data flow, and environmental feedback data;

[0011] Step 3. Use the formula to perform topological fusion on the parameters of each level of the passenger cabin experience system; specifically, 3.1. Use the following fusion formula to calculate the overall comfort: Overall_comfort = Temperature_comfort*Temperature_k+Humidity_comfort*Humidity_k+Seat_posture_comfort*Seat_posture_k+Internet_speed_comfort*Internet_speed_k+Calculator_performance_comfort*Calculator_performance_k+Air_quality_comfort*Air_quality_k+Odor_environment_comfort*Odor_environment_k+Light_intensity_comfort*L ight_intensity_k+Illumination_range_comfort*Illumination_range_k+Lighting_color_comfort*Lighting_color_k+Noise_comfort*Noise_k+Music_repertoire_comfort*Music_repertoire_k+Frequency_excitation_comfort*Frequency_excitation_k+Volume_comfort*Volume_k; 3.2. Construct the topological structure of parameters at each level; 3.3. Conduct linkage iteration on the dynamic system of the topological structure relationship of each element ball;

[0012] Step 4: Evaluate the overall cabin experience by calculating Overall_comfort for the optimized system parameter formula;

[0013] Step 5: Genetic algorithm iteration of excellent parameter formula genes.

[0014] The control tool framework of step 1 includes a main control unit and an enabling device module. The main control unit includes an intelligent host. The intelligent host interacts with the enabling device module through a router. The enabling device module includes AI sensors, lighting, air conditioning and fresh air systems, magnetically controlled skylights, intelligent audio systems, fragrance systems, game entertainment systems, and smart door locks.

[0015] The second step specifically includes: 2.1. Parameter aggregation, including seat system human posture comfort parameters, entertainment system comfort parameters, natural light comfort parameters, fragrance comfort parameters, and subjective input parameters of human-computer interaction; 2.2. Parameter structuring and streamlining of the parameter system. Through the two dimensions of scenarios and human sensory organs, the elements of the PLC hardware-enabled control in the vehicle form the parameter structure of the passenger cabin experience system through connection functions, and further, through specific theme scenarios, the parameter information is aggregated into an information flow that can be fused and solved using relevant formulas.

[0016] The human posture comfort parameter of the seat system in step 2.1 is obtained by the following formula to obtain the current human comfort evaluation score: Where: Kn is the weighted importance of each angle to the overall comfort, and αn is the limb angle.

[0017] The specific method for obtaining the entertainment system comfort parameters in step 2.1 is as follows: the adaptation of the audio music to the theme Theme_adaptation_music is obtained by table lookup method, the adaptation of the video to the theme Theme_adaptation_video is obtained by table lookup method, and the adaptation of the game to the theme Theme_adaptation_game is obtained by table lookup method.

[0018] The specific method for obtaining the natural light comfort parameters in step 2.1 is as follows: based on the latitude and longitude provided by the vehicle navigation system, the vehicle's heading angle information, and the time and weather information obtained by the vehicle communication system, the vehicle's light transmission system calculates the natural light parameters of each space in the vehicle, and quantitatively evaluates the lighting conditions in the specific space, and then obtains the natural light comfort parameters of the specific space in the specific scene through a table lookup method.

[0019] The specific method for obtaining the ambient temperature comfort parameters in step 2.1 is as follows: the interior space is layered according to height, and each layer of space is further subdivided; a simple finite element calculation can be used to determine the predicted temperature value of each numbered space under steady-state airflow conditions, combined with the weather and light intensity used in lighting calculations, the human body's position in the interior space, the air conditioning wind speed, and the ambient temperature measured by the interior temperature sensor; Temperature_comfort is obtained by looking up a statistical table of big data on human temperature comfort.

[0020] The specific method for obtaining the fragrance comfort parameter in step 2.1 is to quantify the concentration index of the fragrance particles in the air and the adaptability parameter of the fragrance and the theme through the function: Fragrance_average_comfort = Fragrance_average_comfort * Fragrance_color_adaptation.

[0021] The specific method for obtaining the subjective input parameters of the human-computer interaction in step 2.1 is as follows: a. During human-computer interaction, the subjective parameters are controlled by controlling the radius of the element ball by opening and closing two fingers on the control touch screen; b. During human-computer interaction, the relationship between the two elements is defined by sliding a finger from the center of one element ball to another element ball, and these relationship lines constitute the topological structure of this parameter system; c. After the interaction between the above-mentioned two points a and b is defined, these small balls will present a rich parameter setting formula under the influence of the relationship defined by b, and the system obtains an overall evaluation score by calculating the evaluation function of the entire parameter system.

[0022] The step 3.2 is to use the synchronous iterative algorithm of the repulsion-attraction dynamic system in electronic games to achieve the effect of rapid sorting and optimization of its topological relationship, which is as follows: ① Sort out the functional relationship between the main factors; ② Calculate whether the relationship between the two element balls in the topological relationship is attraction or repulsion, as well as the magnitude of the attraction and repulsion forces through function linkage.

[0023] For passengers or drivers who choose to actively modify the relationship network of each element in the subjective input parameters of human-computer interaction, the system uses the relationship matrix of each relationship element to define a relationship function for it.

[0024] The specific approach of step 3.3 is: through the hierarchical transmission mechanism of function-influenced parameters, the element ball is allowed to freely move and iterate its parameter state in the relational topological space under the drive of the function force until the parameter state of the entire system is stable.

[0025] The step five specifically includes: 5.1. Calculating the main optimization target of the genetic algorithm, that is, demand satisfaction = Overall_comfort / 1400; using the length of the relationship line between each ball in the topological space relative to the size of the demand satisfaction to measure the resource coordination: resource coordination = relationship line length / Overall_comfort; 5.2. Based on the iteration of the genetic algorithm, continuously optimizing various parameters of the cabin experience in different scenarios; 5.3. Through the human-computer interaction method provided by the system, collecting customers' comfort requirements in different scenarios and making the requirements what you see is what you get, helping customers understand their own comprehensive comfort experience formula.

[0026] It can be seen from the above description of the present invention that, compared with the prior art, the present invention has the following advantages:

[0027] 1. This invention uses a suitable fusion algorithm to quantify and algorithmically integrate multi-dimensional passenger cabin experience parameters, including music and sound systems, fragrance, seating, and lighting. By structuring the resulting comfort parameter system, the various parameter element modules achieve functional linkage. This element sphere topology system captures customer comfort requirements across diverse scenarios and enables WYSIWYG solutions, helping customers understand their own comprehensive comfort experience formula.

[0028] 2. The present invention optimizes various algorithm parameters of the comprehensive evaluation system for passenger cabin experience in buses. The system can generate customized adaptation plans that match specific passengers or passenger groups through the algorithm. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] Figure 1 This is a control tool framework diagram of the comprehensive evaluation system for passenger cabin experience in buses of the present invention.

[0030] Figure 2 The overall block diagram of the parameterized comprehensive construction of the present invention.

[0031] Figure 3 Schematic diagram of human posture comfort parameters of the seat system of the present invention.

[0032] Figure 4 This is a schematic diagram of the dynamic description of the music frequency of the present invention.

[0033] Figure 5 Schematic diagram of the vehicle floor space divided into a plurality of small squares according to the present invention.

[0034] Figure 6 Schematic diagram of the interior space of a vehicle divided by height according to the present invention.

[0035] Figure 7 Schematic diagram of temperature prediction for each numbered space in a vehicle according to the present invention.

[0036] Figure 8 Schematic diagram of fragrance release in a car according to the present invention.

[0037] Figure 9 This is a topological diagram of the spheres required for human-computer interaction according to the present invention.

[0038] Figure 10 This is a schematic diagram of how various elements are formed into a parameter structure through scenes and people's own sensory organs.

[0039] Figure 11 Schematic diagram of the network related to the fragrance types and music tracks of the present invention.

[0040] Figure 12 Schematic diagram of the resource coordination degree of the genetic algorithm of the present invention.

[0041] Figure 13 This is a schematic diagram of sample No. 8 in the 34th generation of the genetic algorithm.

[0042] Figure 14 Schematic diagram of sample No. 2 and sample No. 4 of the 41st generation of the genetic algorithm.

[0043] Figure 15 This is a schematic diagram of sample No. 5 in the 42nd generation of the genetic algorithm.

[0044] Figure 16 This is a schematic diagram of sample No. 10 in the 46th generation of the genetic algorithm.

[0045] Figure 17 Schematic diagram of sample No. 12 and sample No. 13 of the 48th generation of the genetic algorithm.

[0046] Figure 18 This is a schematic diagram of sample No. 14 in the 48th generation of the genetic algorithm.

[0047] Figure 19 Schematic diagram of sample No. 8 and sample No. 9 of the 49th generation of the genetic algorithm. DETAILED DESCRIPTION

[0048] The following describes specific embodiments of the present invention with reference to the accompanying drawings. Numerous details are provided below to provide a comprehensive understanding of the present invention, but those skilled in the art will appreciate that the present invention can be practiced without these details. Well-known components, methods, and processes are not described in detail below.

[0049] A comprehensive evaluation method for passenger cabin experience of a bus includes the following steps:

[0050] Step 1: Establish a control tool framework for the comprehensive evaluation system of bus passenger cabin experience.

[0051] Reference Figure 1 The control tool framework mainly includes a main control unit and an enabling device module. The main control unit can coordinate the enabling control of all passenger cabin and comfort-related equipment (i.e., enabling device modules).

[0052] The main control unit includes the intelligent host, intelligent central control and intelligent panel. The intelligent host exchanges information with the enabling device modules in the car through the router. The main interactive contents are described in the following table:

[0053]

[0054] Table 1. Perception and execution modules of the comprehensive evaluation system for passenger cabin experience in buses

[0055] Step 2: Parameterize and comprehensively construct the data structure of the comprehensive evaluation system for passenger cabin experience, including system data, evaluation algorithm data flow, and environmental feedback data. The overall structure is as follows: Figure 2 shown.

[0056] in:

[0057] 2.1 Parameter Collection and Parameter Structuring

[0058] 2.1.1. Seat system human posture comfort parameters: Posture_comfort - posture comfort (100-point scale), αn - limb angle.

[0059] In this embodiment, the 15 main joint angles α0 to α14 that can be affected by the seat system are defined. AI can identify them with the help of the in-car camera and adjust the angles of the seat back, footrest, armrest, headrest, etc. to match the human body to achieve the most comfortable angle defined below. Figure 3 .

[0060] ① Figure 3 The mid-neck angle is α0;

[0061] ②α1-α14, 7 pairs of data that are symmetrical on both sides, respectively describing a series of angles from the upper arm extension angle to the angle between the footrest and the tibia;

[0062] ③ According to the ergonomic comfort statistics of various body parts and angles, score each angle from the most uncomfortable 0 points to the most comfortable 100 points, such as Figure 3 As shown on the right, the angle of 110° between the thigh and abdomen is the most comfortable, and the comfort scores at other angles are normally distributed;

[0063] ④ The current human comfort evaluation score can be obtained by taking the average of all angles α0-α14: Note: 1. Kn is the weighted importance of each angle to overall comfort. 2. Passengers may sacrifice comfort to achieve the highest score when engaging in activities such as office work and gaming.

[0064] 2.1.2 Entertainment system comfort parameters: Theme_adaptation - theme adaptability (100 points).

[0065] ① Theme_adaptation_music (100 points):

[0066] Theme_adaptation_music is obtained by table lookup method, see Table 2;

[0067]

[0068]

[0069] Table 2. The suitability of music to a certain theme

[0070] Note: The degree of adaptation of the parameters in Table 2 to the theme mainly comes from the relationship between the frequency structure of the music and the theme, see Figure 4 . Figure 4 By performing clustering operations on the dynamic changes in the frequency points of the music, a quantitative description of the dynamic frequency of the music can be obtained. For example, the color of the frequency points of the polyphonic canon in the first row shows periodic changes, and the regularity of the different melodic systems of Bach's music in the fifth row corresponds to each other. This embodiment only uses the frequency characteristic calibration values ​​of the music in the above table for quantitative calculation. Figure 4 Demonstrate the rationality of this calibration.

[0071] ② Theme_adaptation_video (100-point scale): Use the table lookup method to obtain the parameters, the same as above.

[0072] ③ Theme_adaptation_game (100-point scale): Use the table lookup method to obtain parameters, the same as above.

[0073] 2.1.3. Natural light comfort parameter: Natural_light_comfort (100-point scale)

[0074] Based on the latitude and longitude provided by the vehicle navigation system, the vehicle's heading angle information, the time and weather information obtained by the vehicle communication system, and the vehicle's light transmission system (glass with electronically adjustable light transmittance), the natural light exposure parameters of each space in the vehicle are calculated. Figure 5 The figure divides the floor space inside the car into several small squares. By calculating the light exposure parameters of the small square space where the passengers are located, the light conditions of the specific space can be quantitatively evaluated, and then the natural light comfort parameters of the specific space under specific scenes can be obtained through the table lookup method.

[0075] 2.1.4. Ambient temperature comfort parameter: Temperature_comfort (100 points)

[0076] ① Divide the interior space into layers according to height, and further subdivide each layer of space, such as Figure 6 As shown, the bottom-most space No. 271 is numbered 0_271.

[0077] ② Because the interior space of the vehicle is a relatively closed air system, a simple finite element calculation can be used to determine the predicted temperature value of each numbered space under steady-state airflow conditions, combined with the weather and light intensity used in the illumination calculation in 2.1.3, the air conditioning wind speed, and the ambient temperature measured by the in-vehicle temperature sensor. Figure 7 As shown in the figure, in this scenario prediction, the temperature near the roof air conditioner is lower, while the temperature near the front and rear windows where sunlight is shining is higher.

[0078] ③ Through the statistical table of big data on human body’s temperature comfort, Temperature_comfort is obtained by looking up the table.

[0079] 2.1.5 Fragrance comfort parameter: Fragrance_comfort (100-point scale)

[0080] The effects of fragrance on human physiology and psychology are:

[0081] Physiology: Aromatic substances enter the lungs through the nasal cavity and pass through the capillaries to complete their physiological effects on the body;

[0082] Psychology: The aromatic information carried by the smell is transmitted to the limbic system of the brain through nasal stimulation, producing psychological effects of emotion and memory.

[0083] Similar to the comfort parameters for entertainment, the impact of fragrance on comfort varies from person to person and from scene to scene. Therefore, the concentration index of aromatic particles in the air and the adaptability parameters between the fragrance and the scene need to be combined and quantified through the function: Fragrance_average_comfort = Fragrance_average_comfort * Fragrance_color_adaptation.

[0084] ①Fragrance_concentrati on :See Figure 8 The spatial concentration prediction value can be obtained by combining the aroma release dose of the aroma machine with the finite element calculation in the figure. The unit is mg / m 3 ;

[0085] ② Fragrance_average_comfort (100-point scale): The average comfort value under the concentration is found from the comfort table obtained through the concentration comfort experiment;

[0086] ③ Fragrance color adaptation: Because there are relatively few fragrance types that can be used in a car's cabin, this example sets a strong correlation with the interior theme lighting color. For ease of calculation, fragrance types and colors are mapped one-to-one. The corresponding color adaptation is 1, and the non-corresponding color adaptation is 0 (see Table 3).

[0087]

[0088]

[0089] Table 3. Correspondence between aroma types and colors

[0090] 2.1.5 Subjective input parameters of human-computer interaction;

[0091] In this embodiment, the passenger or driver can input the vehicle system's emphasis on the following 14 comfort-related factors that are controllable by the intelligent passenger cabin system. This will influence the final parameter system formed when evaluating the system operation (out of 100 points), as shown in Table 4:

[0092] Comfort-related factor names Subjective parameters temperature Temperature_k humidity Humidity_k Seat posture Seat_posture_k Internet speed Internet_speed_k Calculator performance Calculator_performance_k Air quality Air_quality_k Smell environment Odor_environment_k Light intensity Light_intensity_k Light range Illumination_range_k Light color Lighting_color_k noise Noise_k Music Tracks Music_repertoire_k Frequency Excitation Frequency_exci tation_k volume Volume_k

[0093] Table 4. Subjective parameters of human-computer interaction

[0094] a. Human-computer interaction can be controlled on the control touch screen. Figure 9 In the game, you can control the size of the element sphere radius by pinching your fingers to control the subjective parameters in the table above.

[0095] b. During human-computer interaction, you can swipe your finger from the center of one element sphere to another to define the relationship between two elements. These relationship lines constitute the topological structure of this parameter system;

[0096] c. By defining the interaction between points a and b, these balls will present a rich set of parameter settings under the influence of the relationship defined by b. The system then calculates an overall evaluation score by applying an evaluation function (described later) to the entire parameter system. This score, along with feedback from the entire system, such as changes in seat angle, music played, fragrance, glass transmittance, and system theme, stimulates passengers' curiosity. This simple game allows us to collect sufficient customer preference data, providing reference data for subsequent optimization of the entire parameter system.

[0097] 2.2. Parameter structuring and parameter system streamlining;

[0098] Reference Figure 10 Through the two dimensions of scene and human sensory organs, the interior of the car is Figure 1The PLC hardware-enabled control elements described in the paper form the parameter structure of the passenger cabin experience system through connection functions, and further aggregate the parameter information into an information flow that can be integrated and solved using relevant formulas through specific theme scenarios.

[0099] 2.2.1. Active connection mechanism of functional modules for information flow processing

[0100] by Figure 10 Taking the middle horizontal axis scene as an example, the selection path is: Entertainment Scene → Music & Video Appreciation → Music Appreciation;

[0101] Related functional modules actively connect:

[0102]

[0103] It is assumed that the environmental parameters available in the scene are: ride time 17:30, longitude: 118.082481, latitude: 24.497745, weather: cloudy.

[0104] Calculate the following according to the method described in 2.1.3: Figure 4 The natural light exposure conditions shown are then used to calculate Natural_light_comfort.

[0105] Calculate the following according to the method described in 2.1.4: Figure 5 The ambient temperature conditions shown are then used to calculate Temperature_comfort.

[0106] Assume that on a cloudy evening, a passenger wants to listen to a lullaby and takes a nap, and selects the theme "Quiet Night". The system calculates the entertainment system comfort parameter according to the formula in step 2.1.2:

[0107] Theme_adaptation = Theme_adaptation_music + Theme_adaptation_video (scene selection value is not, the value is 0 at this time) + Theme_adaptation_game (scene selection value is not, the value is 0 at this time)

[0108] Theme_adaptation_music optimization algorithm is activated, according to Figure 4 In the audio analysis method, the functional tune Mozart-Lullaby has a monotonous audio dynamic, and the highest matching degree with the current theme is 95 in Table 2, so the track can be selected based on the evaluation parameters.

[0109] 2.2.2 Passive connection mechanism of functional modules for information flow processing

[0110] like Figure 10The connection lines between the various functional modules show the influence of passive drive or enabling parameters between the functional modules.

[0111] ① In this embodiment, the above-mentioned selected functional modules can be further optimized through the selection of music: frequency excitation (high, medium and low frequencies) in music performance, suppression of high and low frequencies, and reduction of volume.

[0112] ②The volume control is linked to the noise control in the sound environment, activating the Active Noise Control function;

[0113] ③ The selection of the music track is also linked to the parameter selection of the interior lighting color, see Table 5

[0114]

[0115]

[0116] Table 5, Track and Light Color Matching Table

[0117] ④ The calculation method for the relationship between the interior ambient light color formula and the fragrance comfort parameters described in 2.1.5 can drive the selection of the type of in-car fragrance.

[0118] Step 3: Use the formula to perform topological fusion on the parameters of each level of the passenger cabin experience system.

[0119] 3.1. According to the algorithm requirements, all data will eventually be integrated and calculated into an overall indicator: 0verall_comfort overall comfort.

[0120] according to Figure 10 In the fusion formula of the overall comfort of the cabin experience, the human dimension's comfort evaluation (because 0verall_comfort needs to be fed back to the feeling subject through the human-computer interaction interface) is as follows:

[0121] Overall_comfort=Temperature_comfort*Temperature_k+Humidity_comfort*Humidity_k+Seat_posture_comfort*Seat_posture_k+Internet_speed_comfort*Int ernet_speed_k+Calculator_performance_comfort*Calculator_performance_k+Air_quality_comfort*Air_quality_k+Odor_environment_comfort*Odor_enviro nment_k+Light_intensity_comfort*Light_intensity_k+Illumination_range_comfort*I1lumination_range_k+Lighting_color_comfort*Lighting_color_k+No ise_comfort*Noise_k+Music_repertoire_comfort*Music_repertoire_k+Frequency_excitation_comfort*Frequency_excitation_k+Volume_comfort*Volume_k.

[0122] That is, objectively take the values ​​of the subjective parameters of human-computer interaction in Table 4*their respective comfort experience algorithms, and then add up all 14 factors.

[0123]

[0124]

[0125] Table 6. Evaluation factor value calculation function table

[0126] Note: The final calculated value in Table 6 needs to be obtained after the parameters in the function "()" are input, and the algorithm involved is not included in the present invention.

[0127] 3.2. Constructing the topological structure of parameters at each level

[0128] like Figure 9 As shown, there is a very complex functional connection between the values ​​of various comfort influencing factors. The topological relationship needs to be reorganized and planned by some method. The present invention draws on the synchronous iterative algorithm of the repulsion-attraction dynamic system in electronic games to achieve the effect of rapid arrangement and optimization of its topological relationship, as follows:

[0129] ① As described in 3.1, sort out the functional relationship between the main factors (this embodiment is built for the convenience of example Figure 9 For example, the functional relationship between volume and noise is: a, volume = k 音噪比 * Noise, unit: decibel, volume increases with noise; b. Calculate the impact of volume and noise on Volume_comfort, and the impact of volume and noise on Noise_comfort; c. Use a function to express the relationship between the different values ​​of Volume_comfort() and Noise_comfort() through the common variable changes:

[0130] Volume_comfort(Noise_comfort());

[0131] N0ise_comfort(Volume_comfort()).

[0132] ② Use function linkage to calculate whether the topological relationship between two element spheres is attractive or repulsive, as well as the magnitude of the attractive and repulsive forces. For example, in a Karaoke scene, the noisy variable environment makes Noise_comfort() very small, but because the scene is Karaoke, Volume_comfort() is relatively large. Therefore, in the topological dynamic system, the radius of the Volume_comfort sphere increases, squeezing the radius of the Noise_comfort sphere very small.

[0133] ③ For passengers or drivers who choose to actively modify the relationship network of each element as described in 2.1.5, Subjective Input Parameters of Human-Computer Interaction, the system uses the relationship matrix of each relationship element (some are virtual matrices, for example: Internet speed and temperature factors have basically no relationship, but the system background has a comparison relationship k between the average value of the data collected through big data) 虚拟 ) defines a relational function for it.

[0134] 3.3. Conduct linkage iteration on the dynamic system of the topological structure relationship of each element sphere.

[0135] Through Figure 9 The hierarchical transmission mechanism of the function-influenced parameters shown on the right allows the element balls to freely move and iterate their parameter states in the relational topological space under the drive of the function force until the parameter state of the entire system stabilizes. Referring to the computing power of existing ordinary vehicle systems, one iteration is 0.01 seconds, and the number of iterations is generally 2000 to complete the topology optimization. The specific description is as follows:

[0136] In this embodiment, temperature comfort has the most direct impact on comfort. The function influence starts from temperature. The system has built-in functions related to illumination and light. In a cool environment, passengers define their own music tracks, such as lullabies, which in turn affect a series of factors in the second, third, and fourth layers. Similarly, the factor balls push each other out or attract each other under the influence of each function, and then affect their respective radius in the next iteration (the radius value is ) and relationship forces, users can also specify that the radius of certain elements of particular interest remain unchanged for iterative calculations, which are intuitively displayed in the topological system as bouncing between element balls;

[0137] Furthermore, after a sufficiently large amount of human-computer interaction data is iterated through the function relationship network, the numerical relationship of some abstract data will be obtained. Figure 11 ,like Figure 11 The established correlation data between fragrance types and music tracks (the longer the rectangle, the greater the correlation) creates data conditions for the optimal formula selection in step six.

[0138] Step 4: Evaluate the overall cabin experience by calculating the Overall 1comfort of the optimized system parameter formula;

[0139] Step 5: Genetic algorithm iteration of excellent parameter formula genes, see Figures 12 to 19 ;

[0140] By making extensive use of the data generated by this system, parameter formulas for various comfort requirements can be calculated. These parameter formulas can be used as parameter genes for system modulation. By utilizing the iterative optimization function of genetic algorithms, gene strips can be generated under different scenarios and requirements.

[0141] 5.1. The main optimization targets of genetic algorithms;

[0142] Degree of demand satisfaction: Based on a 100-point scale, if all 14 factors mentioned above are fully met, Overall_comfort = 1400. Therefore, demand satisfaction = Overall_comfort / 1400.

[0143] Resource coordination: Figure 12 shown.

[0144] For the 48th generation, sample No. 14, during the iterative optimization of a scenario requirement formula, the system failed to converge due to the weak function definition of the parameter relationship network and the lack of appropriate constraints between the elements. Even though the requirement satisfaction was as high as 0.935, it was impossible to coordinate such a comfort effect in reality. Therefore, the parameter resource coordination degree is needed to characterize the coordination effectiveness of the function relationship network on the system. Figure 18In the topological form of sample No. 14 of the 48th generation, the relationship line is pulled very long by the element ball, and the repulsive force is much greater than the attractive force. Therefore, the resource coordination degree is measured by the length of the relationship line between each ball in the topological space relative to the size of the demand satisfaction: resource coordination degree = relationship line length / Overall l_comfort.

[0145] Since the length of the relationship line may be 0 in extreme cases, it is not suitable to be the numerator of the above formula. The greater the resource coordination degree, the less reliable the parameter formula. Therefore, after the 14th sample of the 48th generation appears, such a gene situation will no longer appear in the subsequent iterations of the genetic algorithm.

[0146] 5.2. Continuously optimize various cockpit experience parameters in different scenarios through the iteration of genetic algorithms;

[0147] 5.3. Through the human-computer interaction method provided by the system, the comfort requirements of customers in different scenarios are collected, and the requirements can be met, helping customers understand their own comprehensive comfort experience formula.

[0148] The above is only a specific implementation of the present invention, but the design concept of the present invention is not limited to this. Any non-substantial changes to the present invention using this concept shall be deemed as an infringement of the protection scope of the present invention.

Claims

1. A comprehensive evaluation method for passenger cabin experience of a bus, characterized by: The following steps are involved: Step 1: Establish a control tool framework for the comprehensive evaluation system of passenger cabin experience on buses. The control tool framework in Step 1 includes a main control unit and an enabling device module. The main control unit includes an intelligent host, which exchanges information with the enabling device module via a router. The enabling device module includes AI sensors, lighting, air conditioning and fresh air systems, magnetically controlled sunroof windows, intelligent audio systems, fragrance systems, gaming and entertainment systems, and smart door locks. Step 2: Perform parameterized comprehensive construction of the data structure of the bus passenger cabin experience comprehensive evaluation system based on the system data, evaluation algorithm data flow, and environmental feedback data; Step 3: Use the formula to perform topological fusion on the parameters of each level of the passenger cabin experience system; specifically: 3.

1. Calculate the overall comfort using the following fusion formula: Overall_comfort=Temperature_comfort Temperature_k+Humidity_comfort Humidity_k+Seat_posture_comfort Seat_posture_k+Internet_speed_comfort Internet_speed_k+Calculator_performance_comfort Calculator_performance_k+Air_quality_comfort Air_quality_k+Odor_environment_comfort Odor_environment_k+Light_intensity_comfort Light_intensity_k+Illumination_range_comfort Illumination_range_k+Lighting_color_comfort Lighting_color_k+Noise_comfort Noise_k+Music_repertoire_comfort Music_repertoire_k+Frequency_excitation_comfort Frequency_excitation_k+Volume_comfort Volume_k; 3.

2. Construct the topological structure of the parameters at each level; Step 3.2 is to use the synchronous iterative algorithm of the repulsion-attraction dynamic system in electronic games to achieve the effect of rapid sorting and optimization of its topological relationship, specifically as follows: ① Sort out the functional relationship between the main factors; ② Calculate whether the relationship between two element balls in the topological relationship is attraction or repulsion, as well as the magnitude of the attraction and repulsion forces through functional linkage; 3.

3. Linkage iterate the topological structure relationship dynamic system of each element ball; Step 4: Evaluate the overall cabin experience by calculating Overall_comfort for the optimized system parameter formula; Step 5: Genetic algorithm iteration of the excellent parameter formula gene; specifically, including: 5.

1. Calculating the optimization target of the genetic algorithm, that is, demand satisfaction = Overall_comfort / 1400; using the length of the relationship line between each element sphere in the topological space relative to the size of the demand satisfaction to measure resource coordination: resource coordination = relationship line length / Overall_comfort; 5.

2. Based on the iteration of the genetic algorithm, continuously optimize the various parameters of the cabin experience in different scenarios; 5.

3. Through the human-computer interaction method provided by the system, collect customers' comfort requirements in different scenarios to help customers understand their own comprehensive comfort experience formula.

2. The comprehensive evaluation method for passenger cabin experience of a bus according to claim 1, characterized in that: The second step specifically includes: 2.

1. Parameter aggregation, including seat system human posture comfort parameters, entertainment system comfort parameters, natural light comfort parameters, fragrance comfort parameters, and subjective input parameters of human-computer interaction; 2.

2. Parameter structuring and streamlining of the parameter system. Through the two dimensions of scenes and human sensory organs, the elements of the PLC hardware-enabled control in the vehicle form the parameter structure of the passenger cabin experience system through connection functions, and the parameter information is aggregated into an information flow that is fused and solved using formulas through thematic scenes.

3. The comprehensive evaluation method for passenger cabin experience of a bus according to claim 2, characterized in that: The human posture comfort parameter of the seat system in step 2.1 is obtained by using the following formula to obtain the current human comfort evaluation score: Seat_posture_comfort= / n, where: Kn is the weighted importance of each angle to the overall comfort, and αn is the limb angle.

4. The comprehensive evaluation method for passenger cabin experience of a bus according to claim 2, characterized in that: The specific method for obtaining the entertainment system comfort parameters in step 2.1 is as follows: the adaptation of the audio music to the theme Theme_adaptation_music is obtained by table lookup method, the adaptation of the video to the theme Theme_adaptation_video is obtained by table lookup method, and the adaptation of the game to the theme Theme_adaptation_game is obtained by table lookup method.

5. The comprehensive evaluation method for passenger cabin experience of a bus according to claim 2, characterized in that: The specific method for obtaining the natural light comfort parameters in step 2.1 is as follows: based on the latitude and longitude provided by the vehicle navigation system, the vehicle's heading angle information, and the time and weather information obtained by the vehicle communication system, the vehicle's light transmission system calculates the natural light parameters of each space in the vehicle, and quantitatively evaluates the lighting conditions in the space, and then obtains the natural light comfort parameters of the space under the above scenario through a table lookup method.

6. The comprehensive evaluation method for passenger cabin experience of a bus according to claim 2, characterized in that: The specific method for obtaining the ambient temperature comfort parameter in step 2.1 is as follows: the interior space is layered according to height, and each layer is further subdivided; finite element calculation is performed to obtain the predicted temperature value of each numbered space under the condition of steady airflow, combined with the weather and light intensity used in the lighting calculation, and then combined with the position of the human body in the interior space, the air conditioning wind speed, and the ambient temperature measured by the interior temperature sensor; Temperature_comfort is obtained by looking up the statistical table of big data on human body's temperature comfort.

7. The comprehensive evaluation method for passenger cabin experience of a bus according to claim 2, characterized in that: The specific method of obtaining the fragrance comfort parameter in step 2.1 is to quantify the concentration index of the fragrance particles in the air and the adaptability parameter of the fragrance and the theme through the function: Fragrance_comfort=Fragrance_average_comfort Fragrance_color_adaptation; the concentration of fragrance particles Fragrance_concentration, the average fragrance comfort value Fragrance_average_comfort, and the color adaptation of the fragrance type Fragrance_color_adaptation.

8. The comprehensive evaluation method for passenger cabin experience of a bus as claimed in claim 2, characterized in that: The specific method for obtaining the subjective input parameters of the human-computer interaction in step 2.1 is as follows: a. During human-computer interaction, the subjective parameters are controlled by controlling the radius of the element ball by opening and closing two fingers on the control touch screen; b. During human-computer interaction, the relationship between the two elements is defined by sliding a finger from the center of one element ball to another element ball. These relationship lines constitute the topological structure of the subjective parameter system; c. After the interactive definition of the above two steps a and b, these small balls will present a rich parameter setting formula under the influence of the relationship defined in step b, and the system obtains an overall evaluation score by calculating the evaluation function of the entire subjective parameter system.

9. The comprehensive evaluation method for passenger cabin experience of a bus according to claim 8, characterized in that: For passengers or drivers who choose to actively modify the relationship network of each element in the subjective input parameters of human-computer interaction, the system uses the relationship matrix of each relationship element to define a relationship function for the subjective input parameters.

10. The comprehensive evaluation method for passenger cabin experience of a bus according to claim 1, characterized in that: The specific approach of step 3.3 is: through the hierarchical transmission mechanism of function-influenced parameters, the element ball is allowed to freely move and iterate its parameter state in the relational topological space under the drive of the function force until the parameter state of the entire system is stable.

Images