Cab posture comfort evaluation method, device and equipment and storage medium

Abstract

The invention discloses a cab attitude comfort evaluation method, device and equipment and a storage medium. According to the method, at least one built cab environment model is determined, each cab environment model corresponds to one driving use area in a cab, and the driving use areas are obtained by dividing the cab area according to the driving use frequency; obtaining the constructed human body model, and determining a constraint relationship between the human body model and each cab environment model in a driving state; according to each constraint relationship, determining a region evaluation result of the corresponding driving use region in the driving state; and determining a posture comfort evaluation result of the cab in the driving state according to the evaluation result of each region. By means of the method, the actual driving use area replaces the theoretical use area to construct the cab environment model to restrain the human body model, more accurate evaluation results of all the areas are obtained, and then the accuracy and objectivity of the posture comfort evaluation result of the cab are improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of vehicle evaluation, and in particular to a cab posture comfort evaluation method, device, equipment and storage medium. BACKGROUND

[0002] In the design and development process of an automobile, especially for commercial vehicles, the operation comfort of a driver is closely related to driving safety, and the layout scheme of a cab is one of the core factors affecting the posture comfort of the driver.

[0003] When evaluating the posture comfort of a cab in a layout scheme of an automobile cab, the method commonly used in the industry is to evaluate through the personal feelings and feedback of a driver. However, this method based on subjective feelings cannot guarantee the objectivity and consistency of the evaluation results, and lacks standardized quantitative indicators, so that accurate comparative analysis and optimization improvement cannot be performed.

[0004] In order to make up for the shortcomings of the existing evaluation method, the existing research proposes to introduce theoretical objective factors for evaluation. However, due to the possible large deviation between theory and practice, the posture comfort evaluation relying only on theoretical objective factors will result in low accuracy of the evaluation results, and cannot truly reflect the comfort performance of the cab layout scheme in actual use. SUMMARY

[0005] The present application provides a cab posture comfort evaluation method, device, equipment and storage medium, to solve the problem of low accuracy of the evaluation results of the existing evaluation method, and the inability to truly reflect the comfort performance of the cab layout scheme in actual use.

[0006] In a first aspect, the present application embodiment provides a cab posture comfort evaluation method, which comprises:

[0007] determining at least one cab environment model constructed, each cab environment model corresponding to a driving use area in the cab, and each driving use area dividing the cab area according to the driving use frequency;

[0008] obtaining a human body model, and determining the constraint relationship between the human body model and each cab environment model in a driving state;

[0009] determining the area evaluation result of the corresponding driving use area in the driving state according to each constraint relationship;

[0010] determining the posture comfort evaluation result of the cab in the driving state according to each area evaluation result.

[0011] In a second aspect, the present application embodiment provides a cab posture comfort evaluation device, which comprises:

[0012] an environment model determining module configured to determine at least one cab environment model constructed, each cab environment model corresponding to a driving usage area in the cab, each driving usage area being obtained by dividing the cab area according to driving usage frequency;

[0013] a constraint relationship determining module configured to obtain a human body model and determine constraint relationships between the human body model and each cab environment model in a driving state;

[0014] a first result determining module configured to determine area evaluation results of the corresponding driving usage areas in the driving state according to each constraint relationship;

[0015] a second result determining module configured to determine a posture comfort evaluation result of the cab in the driving state according to each area evaluation result.

[0016] In a third aspect, an electronic device is provided, and the electronic device comprises:

[0017] at least one processor;

[0018] and a memory in communication connection with the at least one processor;

[0019] wherein the memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor to enable the at least one processor to execute the cab posture comfort evaluation method according to any one of the embodiments of the present application.

[0020] In a fourth aspect, a computer readable storage medium is provided, and the computer readable storage medium stores computer instructions for enabling a processor to implement the cab posture comfort evaluation method according to any one of the embodiments of the present application.

[0021] The technical scheme of the embodiment of the present application is to determine at least one cab environment model, each cab environment model corresponding to a driving use area in the cab, the driving use areas being divided according to driving use frequencies to obtain the cab areas; obtain a human body model and determine constraint relationships between the human body model and the cab environment models in a driving state; determine area evaluation results of the corresponding driving use areas in the driving state according to the constraint relationships; and determine a posture comfort evaluation result of the cab in the driving state according to the area evaluation results. With this method, the actual driving use areas are obtained by dividing the cab areas according to the actual driving use frequencies, the actual driving use areas are used to replace the theoretical use areas to construct the cab environment model, the human body model is constrained, and thus more accurate area evaluation results are obtained. The posture comfort evaluation result of the cab in the driving state is determined according to the area evaluation results, and the accuracy and objectivity of the posture comfort evaluation result of the cab are improved.

[0022] It should be understood that the content described in this part is not intended to identify key or important features of the embodiments of the present application, nor is it used to limit the scope of the present application. Other features of the present application will become apparent from the following description. BRIEF DESCRIPTION OF DRAWINGS

[0023] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings needed in the embodiment description will be briefly introduced. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creative effort.

[0024] Figure 1 A flowchart of a cab posture comfort evaluation method provided by the embodiment of the present application;

[0025] Figure 2 An interface schematic diagram of a cab posture comfort evaluation method provided by the embodiment of the present application, which displays evaluation index values of driving use areas relative to each posture evaluation index;

[0026] Figure 3 A structural schematic diagram of a cab posture comfort evaluation device provided by the embodiment of the present application;

[0027] Figure 4 A structural schematic diagram of an electronic device that can be used to implement the embodiment of the present application is shown. DETAILED DESCRIPTION

[0028] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0029] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0030] It should be noted that when evaluating the driver's cab posture comfort of different cab layout schemes, existing research has proposed introducing some objective factors, such as the ideal driver posture, to compensate for the shortcomings of subjective evaluation methods. However, due to the significant discrepancy between the ideal and real-world conditions, relying solely on the ideal posture for evaluation will result in low accuracy and fail to truly reflect the comfort performance of the cab layout scheme in actual use.

[0031] Based on this, embodiments of the present invention provide a method for evaluating cab posture comfort. Figure 1 This is a flowchart of a method for evaluating driver's posture comfort according to an embodiment of the present invention. The embodiment of the present invention can be applied to scenarios that evaluate the posture comfort of the driver under a driver's cab layout scheme. The method can be executed by a driver's posture comfort evaluation device, which can be implemented in the form of software and / or hardware. Optionally, it can be implemented by an electronic device, preferably a mobile terminal, desktop computer, laptop computer, or server.

[0032] like Figure 1 As shown, the cab posture comfort evaluation method provided in this embodiment of the invention may specifically include:

[0033] S101, determine the constructed at least one cab environment model, each cab environment model corresponds to a driving use area in the cab, and each driving use area is obtained by dividing the cab area according to the driving use frequency.

[0034] The cab environment model can be understood as a digital and virtual representation of the environment in the cab, which is used to describe and analyze the environmental characteristics and use functions in the cab. The cab environment model can include the main driving components in the cab that are manipulated or used by the driver, and the layout positions of the driving components, which can include a steering wheel, a driver's seat, an accelerator, a brake pedal, and a driving floor, etc.

[0035] It can be understood that in order to evaluate the comfort of the driver's posture when actually using or manipulating the driving components in the driving area, one or more cab environment models can be determined, each cab environment model corresponding to a driving use area. The driving use area can be understood as a joint area used by the driver in the actual driving process, which is composed of driving manipulation areas on each driving component. The driving manipulation area can be understood as the area on the driving component that is actually in contact with the human body during driving. The driving use frequency can be considered as the ratio of the number of drivers using each driving manipulation area to the total number of drivers within a set statistical time, or the ratio of the use frequency of each driving manipulation area to the total use frequency of the corresponding driving component within a set statistical time.

[0036] In this embodiment, each driving use area can be obtained by dividing the cab area according to the driving use frequency. An exemplary optional way to determine each driving use area can be: determining vehicles consistent with the driving components and their layout positions in the cab environment model, and equipping each vehicle with a sensing device; collecting the driving manipulation areas used by the driver during driving based on the sensing device within a set statistical time, and counting the number of drivers using each driving manipulation area; determining the driving use frequency of each driving manipulation area, and determining the driving manipulation areas falling into different frequency level intervals according to each driving use frequency and a pre-set frequency level interval (such as a high frequency level interval, a medium frequency level interval, and a low frequency level interval); and determining the driving manipulation areas contained in different frequency level intervals as driving use areas corresponding to different driving use frequencies, respectively.

[0037] In this embodiment, key driving components related to the comfort of the driving posture can be determined in advance, such as the accelerator pedal, the brake pedal, the floor, the seat, and the steering wheel, etc., and the cab environment model corresponding to different driving use areas can be constructed by a pre-set algorithm or general software in combination with each driving use area divided.

[0038] S102, acquire the constructed human body model, and determine constraint relationship of the human body model and each cab environment model in the driving state.

[0039] It can be understood that the human body size customized by the driver, such as height, weight, sitting height, waist circumference, arm length and leg length, can be acquired in advance, and the human body model of the driver is constructed based on the human body size.

[0040] In the embodiment, for each cab environment model, the constraint relationship of the human body model and the cab environment model in the driving state is determined respectively. An optional mode can be that: first, the H point on the human body model is constrained in the plane surrounded by the seat stroke frame, in the case that the sitting posture of the driver is kept upright, the H point on the human body model is constrained in the stroke of the vehicle seat in the driving use area of the cab environment model, the left heel point is constrained on the heel point of the clutch pedal in the driving use area, the left foot pedal point is constrained in the clutch pedal use area in the driving use area, the right heel point is constrained on the heel point of the accelerator pedal in the driving use area, the right foot pedal point is constrained in the accelerator pedal use area in the driving use area, the torso angle is set as the seat backrest inclination angle, the hands are constrained with the use area of the steering wheel in the driving use area, and the human body sight line is set as 6 degrees below the front to complete the constraint setting.

[0041] S103, determine the area evaluation result of the corresponding driving use area in the driving state according to the constraint relationship.

[0042] The area evaluation result can be understood as the comfort evaluation result of the driver using a driving use area in the driving state.

[0043] In the embodiment, different driving postures of the driver can be simulated according to the constraint relationship respectively, and the corresponding area evaluation result of the driver in the driving posture of each driving use area is determined through a preset rule.

[0044] S104, determine the posture comfort evaluation result of the cab in the driving state according to the area evaluation result.

[0045] The posture comfort evaluation result can be considered as the posture comfort evaluation result of the driver in the driving state under the cab arrangement scheme.

[0046] In the embodiment, the posture comfort evaluation result of the cab is determined by summarizing the area evaluation result. In an optional embodiment, different weights can be given to the area evaluation result according to the driving use frequency when summarizing.

[0047] The technical scheme of the embodiment is characterized in that at least one cab environment model is determined, each cab environment model corresponds to a driving use area in the cab, each driving use area is divided according to a driving use frequency to obtain a cab area, a human body model is obtained, and a constraint relationship between the human body model and each cab environment model in a driving state is determined; according to the constraint relationship, a region evaluation result of the corresponding driving use area in the driving state is determined; and according to the region evaluation result, a posture comfort evaluation result of the cab in the driving state is determined. The method is characterized in that the actual driving use area is obtained by dividing the cab area according to the actual driving use frequency, the actual driving use area is used to replace the theoretical use area to construct the cab environment model, the human body model is constrained, and a more accurate region evaluation result is obtained. According to the region evaluation result, the posture comfort evaluation result of the cab in the driving state is determined, and the accuracy and objectivity of the posture comfort evaluation result of the cab are improved.

[0048] As a first optional embodiment of the embodiment of the application, each driving component of the vehicle cab is provided with a mechanical sensor.

[0049] Accordingly, the determination of each driving use area can be embodied as:

[0050] a1) obtaining sensor data collected by each mechanical sensor on the corresponding driving component.

[0051] In the embodiment, the mechanical sensors can be arranged on each driving component of the actual vehicle in advance.

[0052] Optionally, a ring-shaped pressure sensor array can be arranged on a steering wheel included in the driving component, the ring-shaped pressure sensor array is used to detect a holding pressure distribution and a contact duration; a piezoresistive sensor can be arranged on a driver seat included in the driving component in a grid manner according to a set size, covering a seat cushion and a backrest of the driver seat, the piezoresistive sensor is used to detect a pressure center offset trajectory; and a strain gauge type force sensor can be arranged on a throttle pedal, a brake pedal and a driving floor included in the driving component, respectively, and is used to detect a foot force distribution.

[0053] For example, the ring-shaped pressure sensor array can be 6 groups of piezoelectric film sensors arranged along the circumference of the steering wheel, covering an operating area with a diameter of 300 mm; the pressure distribution system can adopt a 4*4 grid piezoresistive sensor (resolution 10*10 cm 2 ); and the range of the strain gauge type force sensor can be selected as 0 to 500 Newton.

[0054] b1) determining a driving manipulation area of each driving component according to the arrangement position of each mechanical sensor and the corresponding sensor data.

[0055] In the embodiment, the actual driving operation area of each driving component (such as the steering wheel, the pedal and the seat) of the driver can be determined according to the arrangement position of each force sensor and the corresponding sensor data.

[0056] c1) obtaining a pre-constructed driver actual operation area data set corresponding to the cab, and determining each driving use area according to the driver actual operation area data set and the driving operation area, wherein the driver actual operation area data set comprises data summary of the actual operation area involved in the actual driving operation of a set number of drivers.

[0057] In the embodiment, the actual operation area involved in the actual driving operation of a set number of drivers, such as the steering wheel area, the pedal area, the floor area and the seat area, can be captured in advance by a capturing device installed in the actual vehicle, such as a camera, a sensor and the like. The data summary of the actual operation area forms a driver actual operation area data set, which is used to provide data support for determining the driving use area.

[0058] Based on the pre-constructed driver actual operation area data set, the driving operation area is compared with the driver actual operation area data set, so as to accurately determine the driving use area.

[0059] The technical solution of the embodiment determines the driving operation area of each driving component according to the arrangement position of each force sensor and the corresponding sensor data, and determines each driving use area according to the driver actual operation area data set and the driving operation area, so as to accurately determine the driving use area actually used by the driver in the actual driving state, and provide strong support for accurately and objectively determining the posture comfort evaluation result of the cab.

[0060] As one of the implementation manners, the determination of each driving use area according to the driver actual operation area data set and the driving operation area can be further specified as follows:

[0061] c11) comparing the actual operation area in the driver actual operation area data set with each driving operation area.

[0062] In the embodiment, each driving operation area can be superimposed on the actual operation area in the driver actual operation area data set, and the comparison result can be determined according to the overlapping area.

[0063] c12) counting the use frequency of each driving operation area according to the comparison result, and obtaining the driving use frequency of each driving operation area.

[0064] In the embodiment, the driving manipulation regions with consistent comparison results can be accumulated to count the usage frequency of each driving manipulation region, such as the first driving manipulation region of the steering wheel is used 500 times, and the second driving manipulation region is used 50 times; or the third driving manipulation region of the steering wheel is used by 950 drivers, the fourth driving manipulation region is used by 500 drivers, and the fifth driving manipulation region is used by 50 drivers. According to the usage frequency, the driving usage frequency of each driving manipulation region can be obtained. According to the above example, if the total usage frequency is 1000 times, the driving usage frequency of the first driving manipulation region is 50%, and the driving usage frequency of the second driving manipulation region is 5%. If the total number of drivers is 1000, the driving usage frequency of the third driving manipulation region is 95%, the driving usage frequency of the fourth driving manipulation region is 50%, and the driving usage frequency of the fifth driving manipulation region is 5%.

[0065] c13) According to the driving usage frequency and the preset frequency level interval, the driving manipulation region falling into each different frequency level interval is determined, and the driving manipulation region contained in the different frequency level interval is determined as the driving usage region corresponding to the different driving usage frequency.

[0066] For example, the frequency level interval can be preset based on experience or actual needs, such as setting the driving usage frequency greater than or equal to 95% as a high frequency level interval, the driving usage frequency greater than or equal to 50% and less than 95% as a medium frequency level interval, and the driving usage frequency greater than or equal to 5% and less than 50% as a low frequency level interval.

[0067] In the embodiment, the driving manipulation region can be divided according to the frequency level interval to which the driving usage frequency falls, the driving manipulation region falling into each different frequency level interval is determined, and the driving manipulation region contained in the different frequency level interval is determined as the different driving usage region, so as to obtain the driving usage region classified according to the driving usage frequency. For example, the driving manipulation region contained in the high frequency level interval is the steering wheel A region, the seat B region and the accelerator pedal C region, and the driving usage region corresponding to each driving usage frequency falling into the high frequency level interval is the joint region of the steering wheel A region, the seat B region and the accelerator pedal C region.

[0068] The technical solution of the embodiment is characterized in that the driving frequency of each driving manipulation area is obtained by counting the use frequency of each driving manipulation area, and each driving use area is determined according to the driving frequency of each driving manipulation area and a preset frequency level interval, so that the driving use area classified according to the driving frequency is obtained, the driving use area with different driving frequencies can be evaluated in the subsequent targeted evaluation, and the driving use area with high driving frequency can be considered more in the comprehensive evaluation, thereby providing strong support.

[0069] As a second optional embodiment of the embodiment of the application, the step of determining the area evaluation result of the corresponding driving use area in the driving state according to each constraint relationship can be specifically optimized as follows:

[0070] a2) For each constraint relationship, the evaluation index value of the driving use area relative to each attitude evaluation index is determined according to the constraint relationship and the corresponding driving use area, and in combination with a set attitude evaluation index, by using a given attitude evaluation model.

[0071] For example, Figure 2 In the attitude comfort evaluation method provided by the embodiment of the application, an interface schematic diagram for displaying the evaluation index value of the driving use area relative to each attitude evaluation index is shown. Figure 2 As shown in the figure, the attitude evaluation index can include overall discomfort, such as fatigue and discomfort, and the attitude evaluation index can also include body part discomfort and health index. Alternatively, the current value can be determined as the evaluation index value, and the current value can be understood as the actual value of each attitude evaluation index determined by the attitude evaluation model based on the constraint relationship and the corresponding driving use area; or the current value and the difference value can be determined as the evaluation index value, and the difference value is the difference between the current value and the reference value.

[0072] b2) The area evaluation value when driving in the driving posture of the driving use area is determined according to each evaluation index value, and the area evaluation value is determined as the area evaluation result.

[0073] In the embodiment, the area evaluation value when driving in the driving posture of the driving use area can be determined according to each evaluation index value based on a preset algorithm.

[0074] The technical solution of the embodiment is characterized in that the evaluation index value relative to each attitude evaluation index under each constraint relationship is determined by using a given attitude evaluation model, and the area evaluation value when driving in the driving posture of the driving use area is determined based on each evaluation index value, so that the corresponding area evaluation result of the driving use area with different driving frequencies is determined in a targeted manner, thereby providing data support for determining the attitude comfort evaluation result of the cab.

[0075] As a third optional embodiment of the embodiment of the present application, the posture comfort evaluation result of the driver's cabin in the driving state determined according to the evaluation result of each region can be embodied as the following steps:

[0076] a3) determining the evaluation weight corresponding to each driving use region, and extracting the region evaluation value of the corresponding driving use region from the evaluation result of each region.

[0077] As one of the implementation manners, the evaluation weight corresponding to each driving use region is determined by the corresponding driving use frequency.

[0078] For example, the higher the frequency represented by the frequency level interval corresponding to the driving use frequency, the higher the evaluation weight of the driving use region corresponding to the driving use frequency can be set.

[0079] The above technical solution of the embodiment makes it possible to consider more the comfort of the driving use region that the driver is more used to in actual driving when making a comprehensive evaluation, thereby improving the accuracy of the posture comfort evaluation result.

[0080] As another implementation manner, the evaluation weight corresponding to each driving use region can be set based on experience value or actual needs.

[0081] b3) weighting each region evaluation value by using each evaluation weight, and determining the weighting result as the posture comfort evaluation result.

[0082] In the embodiment, the posture comfort evaluation result of the driver under the current driver's cabin arrangement scheme is obtained by weighting each region evaluation value by using each evaluation weight. For example, if the frequency level interval is set as a high frequency level interval, a medium frequency level interval and a low frequency level interval, the posture comfort evaluation result W can be determined as:

[0083] W = w A X + w B Y + w C Z;

[0084] wherein X is the region evaluation value corresponding to the driving use region of the driving use frequency in the high frequency level interval; Y is the region evaluation value corresponding to the driving use region of the driving use frequency in the medium frequency level interval; Z is the region evaluation value corresponding to the driving use region of the driving use frequency in the low frequency level interval; w A is the evaluation weight corresponding to X; W B is the evaluation weight corresponding to Y; w C is the evaluation weight corresponding to Z; preferably, W A > W B > wC .

[0085] The technical scheme of the embodiment determines the evaluation weight corresponding to each driving use area, extracts the area evaluation value of the corresponding driving use area from the area evaluation result, and performs weighted processing on the area evaluation value by using the evaluation weight, so that an objective, accurate and comprehensive posture comfort evaluation result is obtained.

[0086] Figure 3 A structural schematic diagram of a cab posture comfort evaluation device provided by the embodiment of the application is shown in FIG. 1. Figure 3 As shown in the figure, the device comprises an environment model determination module 31, a constraint relationship determination module 32, a first result determination module 33 and a second result determination module 34, wherein,

[0087] The environment model determination module 31 is configured to determine at least one cab environment model constructed, each cab environment model corresponding to a driving use area in the cab, and each driving use area being obtained by dividing the cab area according to the driving use frequency;

[0088] The constraint relationship determination module 32 is configured to obtain a human body model and determine the constraint relationship between the human body model and each cab environment model in the driving state;

[0089] The first result determination module 33 is configured to determine the area evaluation result of the corresponding driving use area in the driving state according to each constraint relationship;

[0090] The second result determination module 34 is configured to determine the posture comfort evaluation result of the cab in the driving state according to each area evaluation result.

[0091] The technical scheme of the embodiment determines the driving use frequency of each driving manipulation area by counting the use frequency of each driving manipulation area, determines each driving use area according to the driving use frequency of each driving manipulation area and the pre-set frequency level interval, and obtains the driving use area classified according to the driving use frequency, so that the subsequent driving use areas with different driving use frequencies can be evaluated in a targeted manner, and the driving use area with high driving use frequency can be considered more in the comprehensive evaluation.

[0092] Further, the mechanical sensors are arranged on each driving component of the vehicle cab, respectively; correspondingly, the device further comprises a use area determination module, which specifically can comprise:

[0093] The data acquisition unit is configured to acquire the sensor data collected by each arranged mechanical sensor on the corresponding driving component;

[0094] The manipulation region determination unit is configured to determine a driving manipulation region of each driving component according to the arrangement position of each force sensor and the corresponding sensor data;

[0095] The driving use region determination unit is configured to obtain a pre-constructed driver actual operation region data set corresponding to the cab, and determine each driving use region according to the driver actual operation region data set and the driving manipulation region. The driver actual operation region data set includes data aggregation of actual operation regions involved in actual driving operation of a set number of drivers.

[0096] Further, the driving use region determination unit can be specifically configured to:

[0097] compare the actual operation regions in the driver actual operation region data set with each driving manipulation region;

[0098] count the use frequency of each driving manipulation region according to the comparison result, and obtain a driving use frequency of each driving manipulation region;

[0099] determine the driving manipulation regions falling into each different frequency level interval according to each driving use frequency and a pre-set frequency level interval, and determine the driving manipulation regions contained in the different frequency level intervals as the driving use regions corresponding to different driving use frequencies, respectively.

[0100] Further, a ring-shaped pressure sensor array is arranged on a steering wheel included in the driving component, and is configured to detect the grip pressure distribution and the contact duration; a pressure resistance sensor is arranged on a driver seat included in the driving component in a grid manner according to a set size, and covers the cushion and backrest of the driver seat, and the pressure resistance sensor is configured to detect the pressure center offset trajectory; a strain gauge type force sensor is arranged on an accelerator pedal, a brake pedal and a driving floor included in the driving component, respectively, and is configured to detect the foot force distribution.

[0101] Further, the first result determination module 33 can be specifically configured to:

[0102] for each constraint relationship, according to the constraint relationship and the corresponding driving use region, and in combination with a set attitude evaluation index, determine an evaluation index value of the driving use region relative to each attitude evaluation index through a given attitude evaluation model;

[0103] determine a region evaluation value when driving in the driving attitude of the driving use region according to each evaluation index value, and determine the region evaluation value as the region evaluation result.

[0104] Further, the second result determination module 34 can be specifically configured to:

[0105] Determine the evaluation weight corresponding to each driving use area, and extract the area evaluation value of the corresponding driving use area from the area evaluation result of each driving use area.

[0106] Each evaluation weight is used to weight each area evaluation value, and the weighting result is determined as the posture comfort evaluation result.

[0107] Further, the evaluation weight corresponding to each driving use area is determined by the corresponding driving use frequency.

[0108] The cab posture comfort evaluation device provided by the embodiment of the present application can perform the cab posture comfort evaluation method provided by any embodiment of the present application, and has the corresponding function modules and beneficial effects of the execution method.

[0109] Figure 4 A structural schematic diagram of an electronic device 40 that can be used to implement embodiments of the present application is shown. The electronic device is intended to represent various forms of digital computers, such as laptops, desktops, tablets, personal digital assistants, servers, blade servers, mainframes, and other appropriate computers. The electronic device can also represent various forms of mobile devices, such as personal digital processors, cellular telephones, smart phones, wearable devices (e.g., headsets, glasses, watches, etc.), and other similar computing devices. The components shown here, their connections and relationships, and their functions, are meant to be examples only, and are not intended to limit the implementations of the present application described and / or claimed in this document.

[0110] As shown in Figure 4 The electronic device 40 includes at least one processor 41, and a memory, such as a read-only memory (ROM) 42, a random access memory (RAM) 43, etc., which is communicatively connected to the at least one processor 41, wherein the memory stores a computer program that can be executed by the at least one processor, and the processor 41 can perform various appropriate actions and processes according to the computer program stored in the read-only memory (ROM) 42 or loaded from the storage unit 48 into the random access memory (RAM) 43. In the RAM 43, various programs and data required for the operation of the electronic device 40 can also be stored. The processor 41, the ROM 42, and the RAM 43 are connected to each other through a bus 44. An input / output (I / O) interface 45 is also connected to the bus 44.

[0111] A plurality of components in the electronic device 40 are connected to the I / O interface 45, including: an input unit 46, such as a keyboard, a mouse, etc.; an output unit 47, such as various types of displays, speakers, etc.; a storage unit 48, such as a magnetic disk, an optical disk, etc.; and a communication unit 49, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 49 allows the electronic device 40 to exchange information / data with other devices through a computer network, such as the Internet, and / or various telecommunication networks.

[0112] The processor 41 can be various general and / or special purpose processing components with processing and computing capabilities. Some examples of the processor 41 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special-purpose artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any appropriate processor, controller, microcontroller, etc. The processor 41 performs various methods and processes described above, such as the cab posture comfort evaluation method.

[0113] In some embodiments, the cab posture comfort evaluation method can be implemented as a computer program tangibly embodied in a computer readable storage medium, such as the storage unit 48. In some embodiments, part or all of the computer program can be loaded and / or installed onto the electronic device 40 via the ROM 42 and / or the communication unit 49. When the computer program is loaded onto the RAM 43 and executed by the processor 41, one or more steps of the cab posture comfort evaluation method described above can be performed. Alternatively, in other embodiments, the processor 41 can be configured to perform the cab posture comfort evaluation method by any other appropriate means, such as by means of firmware.

[0114] Various implementations of the systems and techniques described above can be realized in digital electronic circuitry, integrated circuitry, a field programmable gate array (FPGA), an application specific integrated circuit (ASIC), a system on a chip (SOC), a programmable logic device (PLD), a computer hardware, firmware, software, and / or combinations thereof. These various implementations can include implementation in one or more computer programs that are executable and / or interpretable on a programmable system including at least one programmable processor, which can be special or general purpose, coupled to receive data and instructions from, and to transmit data and instructions to, a storage system, at least one input device, and at least one output device.

[0115] Computer programs for implementing the methods of the present application can be written in any combination of one or more programming languages. These computer programs can be provided to a processor of a general purpose computer, special purpose computer, or other programmable data processing apparatus, such that the computer program, when executed, enables the functions / acts specified in the flowcharts and / or block diagrams to be implemented. The computer program can be executed entirely on a machine, partially on a machine, partially on a machine as a standalone software package and partially on a remote machine or entirely on a remote machine or server.

[0116] In the context of the present application, a computer-readable storage medium can be a tangible medium that can contain or store a computer program for use by or in connection with an instruction execution system, apparatus, or device. A computer-readable storage medium can include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. Alternatively, a computer-readable storage medium can be a machine-readable signal medium. More specific examples of a machine-readable storage medium will include one or more lines of electrical connections, a portable computer diskette, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or Flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0117] To provide for interaction with a user, the systems and techniques described here can be implemented on an electronic device having a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user and a keyboard and a pointing device (e.g., a mouse or a trackball) by which the user can provide input to the electronic device. Other kinds of devices can be used to provide for interaction with a user as well; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form, including acoustic, speech, or tactile input.

[0118] The systems and techniques described herein can be implemented in a computing system that includes a back end component, e.g., as a data server, or that includes a middleware component, e.g., an application server, or that includes a front end component, e.g., a user computer having a graphical user interface or a Web browser through which a user can interact with an implementation of the systems and techniques described herein, or any combination of such back end, middleware, or front end components. The components of the system can be interconnected by any form or medium of digital data communication, e.g., a communication network. Examples of communication networks include a local area network (LAN), a wide area network (WAN), a blockchain network, and the Internet.

[0119] The computing system can include clients and servers. A client and server are generally remote from each other and typically interact through a communication network. The relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other. A server can be a cloud server, also known as a cloud computing server or cloud host, which is a host product in the cloud computing service system, to solve the defects of large management difficulty and weak business scalability in traditional physical host and VPS service.

[0120] It should be understood that the various forms of flow shown above can be re-ordered, added to, or deleted from without departing from the scope of the present disclosure. For example, the steps recited in the present disclosure can be executed in parallel, executed in sequence, or executed in different orders, as long as the desired results of the technical solutions of the present disclosure can be achieved, and the present disclosure is not limited herein.

[0121] The above detailed description does not constitute a limitation on the protection scope of the present application. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent replacements, and improvements made within the spirit and principles of the present application shall be included in the protection scope of the present application.

Claims

1. A method for evaluating driver's cab posture comfort, characterized in that, include: Determine at least one cab environment model to be constructed. Each cab environment model corresponds to a driving use area in the cab. The cab area is divided according to the driving use frequency. Obtain the constructed human body model and determine the constraint relationship between the human body model and each of the cab environment models under driving conditions; Based on the constraints described, determine the area evaluation results of the corresponding driving use area under driving conditions; The evaluation results of the cab's posture comfort under driving conditions are determined based on the evaluation results of each of the aforementioned areas.

2. The method according to claim 1, characterized in that, Each driving component in the vehicle's cab is equipped with a force sensor; Accordingly, the steps for determining each of the aforementioned driving use areas include: Acquire sensor data collected by each deployed mechanical sensor on the corresponding driving component; Based on the placement of each mechanical sensor and the corresponding sensor data, the driving control area of ​​each driving component is determined. Obtain a pre-constructed driver operation area dataset corresponding to the cab, and determine each driving use area based on the driver operation area dataset and the driving operation area. The driver operation area dataset includes a summary of data on the operation areas involved in actual driving operations by a set number of drivers.

3. The method according to claim 2, characterized in that, The step of determining each driving usage area based on the driver's actual operation area dataset and driving operation area includes: Compare the actual operation areas in the driver's actual operation area dataset with each of the driving operation areas; Based on the comparison results, the frequency of use of each driving control area is statistically analyzed to obtain the driving usage frequency of each driving control area; Based on the driving frequency and the preset frequency level range, the driving operation area falling into each different frequency level range is determined, and the driving operation area included in the different frequency level range is respectively determined as the driving use area corresponding to the different driving frequency.

4. The method according to claim 2 or 3, characterized in that, The steering wheel, included in the driving components, is equipped with a ring-shaped pressure sensor array, which is used to detect the grip pressure distribution and contact duration. The driving components include a driver's seat with a grid of piezoresistive sensors arranged according to a set size, covering the seat cushion and backrest of the driver's seat. The piezoresistive sensors are used to detect the offset trajectory of the pressure center. The driving components, including the accelerator pedal, brake pedal, and driving floor, are equipped with strain gauge force sensors to detect the force distribution applied by the feet.

5. The method according to claim 1, characterized in that, The step of determining the area evaluation result of the corresponding driving use area under driving conditions based on each of the aforementioned constraints includes: For each constraint, using a given attitude evaluation model, based on the constraint and the corresponding driving use area, and combined with the set attitude evaluation indicators, the evaluation index value of the driving use area relative to each attitude evaluation index is determined. Based on the values ​​of each evaluation index, a regional evaluation value is determined when driving in the driving posture of the driving area, and the regional evaluation value is determined as the regional evaluation result.

6. The method according to claim 1, characterized in that, The step of determining the cab posture comfort evaluation result under driving conditions based on the evaluation results of each of the aforementioned regions includes: Determine the evaluation weight corresponding to each of the driving use areas, and extract the area evaluation value of the corresponding driving use area from the evaluation results of each area; The evaluation values ​​of each region are weighted using the evaluation weights, and the weighted result is determined as the posture comfort evaluation result.

7. The method according to claim 6, characterized in that, The evaluation weights for each driving use area are determined by the corresponding driving use frequency.

8. A device for evaluating driver's cab posture comfort, characterized in that, include: The environment model determination module is used to determine at least one cab environment model. Each cab environment model corresponds to a driving use area in the cab. The cab area is divided according to the driving use frequency. The constraint relationship determination module is used to acquire the constructed human body model and determine the constraint relationship between the human body model and each of the cab environment models in the driving state. The first result determination module is used to determine the area evaluation result of the corresponding driving use area under driving conditions based on the constraints mentioned above. The second result determination module is used to determine the posture comfort evaluation result of the cab under driving conditions based on the evaluation results of each of the aforementioned regions.

9. An electronic device, characterized in that, The electronic device includes: At least one processor; and a memory communicatively connected to the at least one processor; The memory stores a computer program that can be executed by the at least one processor, which is then executed by the at least one processor to enable the at least one processor to perform the cab posture comfort evaluation method according to any one of claims 1-7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions that cause a processor to execute the cab posture comfort evaluation method according to any one of claims 1-7.

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