Vehicle driving space design method, device, equipment and medium
By creating human-machine and vehicle data models, combining evaluation rules and physical evaluation, the hard point parameter value of the vehicle cab is optimized, and the problems of low design efficiency and long development cycle are solved, achieving a more efficient design and verification process.
Patent Information
- Application Number
- CN202411302222.9
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-09-18
- Publication Date
- 2025-01-07
AI Technical Summary
The preliminary planning and overall plan design stage of the vehicle cab involves the design and verification of key hard point sizes in the cab, and a lot of human resources are required, resulting in a long development cycle.
By obtaining the initial hard point parameter value of the target vehicle driving space, creating a human-machine model and a vehicle data model, conducting two-wheel evaluation, combining human-machine verification rules and comfort evaluation rules, the optimized hard point parameter value is determined, and through the human-machine, the human-machine verification rules are used. The physical evaluation score of the machine physical pedestal is combined with the development score threshold to optimize the hard point parameter value.
Quickly determine the key human-machine hard point parameter values, organically combine theoretical design with user verification, improve design efficiency, shorten development cycle, and ensure the accuracy of design results.
Smart Images
Figure CN119272408A_ABST
Abstract
Description
Technical Field
[0001] The present invention relates to the technical field of vehicle body layout design, and in particular to a vehicle driving space design method, device, equipment and medium. Background Art
[0002] At present, the design and verification of key hard point dimensions (i.e. hard point parameter values) in the cab are very labor intensive and require a lot of human resources, and the development cycle is generally long. However, the competition in the vehicle market is becoming increasingly fierce. In order to improve product development efficiency and shorten product development cycle, it is particularly important to improve the efficiency of key hard point dimension design in the vehicle cab during the product planning stage. Summary of the invention
[0003] The present invention provides a vehicle driving space design method, device, equipment and medium to solve the current problems of low design efficiency and long development cycle of hard point parameter values of a vehicle cab.
[0004] According to one aspect of the present invention, a vehicle driving space design method is provided, comprising:
[0005] Obtaining initial hard point parameter values of the target vehicle's driving space, and creating a human-machine model and a vehicle data model based on the initial hard point parameter values;
[0006] According to the human-machine model, vehicle data model, human-machine verification rules, and human-machine comfort evaluation rules, two rounds of evaluation are performed on the initial hard point parameter values to obtain the actual hard point parameter values to be verified;
[0007] Obtain the physical evaluation score of the human-machine physical test bench built with the actual hard point parameter value to be verified, and determine the hard point parameter value for driving space optimization based on the physical evaluation score and the development scoring threshold.
[0008] According to another aspect of the present invention, there is provided a vehicle driving space design device, comprising:
[0009] The data acquisition and modeling module is used to obtain the initial hard point parameter values of the target vehicle's driving space and create a human-machine model and a vehicle data model based on the initial hard point parameter values;
[0010] A data evaluation module is used to perform two rounds of evaluation on the initial hard point parameter values according to the human-machine model, the vehicle data model, the human-machine verification rules, and the human-machine comfort evaluation rules to obtain the actual hard point parameter values to be verified;
[0011] The space optimization parameter value determination module is used to obtain the physical evaluation score of the human-machine physical test bench built with the actual hard point parameter value to be verified, and determine the driving space optimization hard point parameter value based on the physical evaluation score and the development scoring threshold.
[0012] According to another aspect of the present invention, an electronic device is provided, the electronic device comprising:
[0013] at least one processor; and
[0014] a memory communicatively connected to the at least one processor; wherein,
[0015] The memory stores a computer program that can be executed by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the vehicle driving space design method described in any embodiment of the present invention.
[0016] According to another aspect of the present invention, a computer-readable storage medium is provided, wherein the computer-readable storage medium stores computer instructions, and the computer instructions are used to implement the vehicle driving space design method described in any embodiment of the present invention when executed by a processor.
[0017] According to another aspect of the present invention, a computer program product is provided, the computer program product comprising a computer program, and the computer program, when executed by a processor, implements the vehicle driving space design method described in any embodiment of the present invention.
[0018] The technical solution of the embodiment of the present invention obtains the initial hard point parameter values of the target vehicle driving space, and creates a human-machine model and a vehicle data model based on the initial hard point parameter values, thereby performing two rounds of evaluation on the initial hard point parameter values according to the human-machine model, the vehicle data model, the human-machine verification rules, and the human-machine comfort evaluation rules, and obtains the actual hard point parameter values to be verified, and then obtains the physical evaluation score of the human-machine physical bench built with the actual hard point parameter values to be verified, and determines the optimized hard point parameter values of the driving space according to the physical evaluation score and the development score threshold. This solution can quickly determine the key human-machine hard point parameter values, organically combine theoretical design, evaluation, and human-machine physical bench verification suitable for user groups, effectively ensure the accuracy of the design results, solve the current problems of low design efficiency and long development cycle of hard point parameter values of vehicle cabs, and can improve the design efficiency of hard point parameter values, thereby reducing the vehicle development cycle.
[0019] It should be understood that the contents described in this section are not intended to identify the key or important features of the embodiments of the present invention, nor are they intended to limit the scope of the present invention. Other features of the present invention will become easily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS
[0020] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.
[0021] Figure 1 A flow chart of a vehicle driving space design method provided in Embodiment 1 of the present invention;
[0022] Figure 2 A two-dimensional side view of a driving space simulation provided by the first embodiment of the present invention;
[0023] Figure 3 A three-dimensional human-machine model provided in the first embodiment of the present invention;
[0024] Figure 4 A flow chart of a vehicle driving space design method provided in Embodiment 2 of the present invention;
[0025] Figure 5 A schematic diagram of the structure of a vehicle driving space design device provided in Embodiment 3 of the present invention;
[0026] Figure 6 A schematic diagram of the structure of an electronic device that can be used to implement an embodiment of the present invention is shown. DETAILED DESCRIPTION
[0027] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.
[0028] It should be noted that the terms "initial", "target", etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.
[0029] Embodiment 1
[0030] Figure 1 This is a flow chart of a vehicle driving space design method provided in the first embodiment of the present invention. This embodiment is applicable to the case of efficiently developing a vehicle cab space design. The method can be executed by a vehicle driving space design device. The vehicle driving space design device can be implemented in the form of hardware and / or software. The vehicle driving space design device can be configured in an electronic device. Figure 1 As shown, the method includes:
[0031] Step 110: Obtain initial hard point parameter values of the target vehicle driving space, and create a human-machine model and a whole vehicle data model based on the initial hard point parameter values.
[0032] Among them, the target vehicle can be a vehicle for driving space design. Based on the energy type, the target vehicle can be divided into pure electric vehicles, hybrid vehicles and oil vehicles, etc. The application scenarios of the target vehicle can include commercial and / or personal use. The initial hard point parameter value can be a hard point parameter value configured for the driving space of the target vehicle. The man-machine model can be used to simulate three-dimensional human postures. The whole vehicle data model can be a three-dimensional model of the whole vehicle. Exemplarily, the whole vehicle data model includes but is not limited to the body coordinate system, wheels, ground, cab main frame, the outline of the cab main frame and the seat R point, etc. The cab main frame includes the key characteristic lines and curved surfaces of the cab. The man-machine model includes but is not limited to the clock point, the steering wheel center and adjustment range, the H point position line and travel, the eye ellipse, the head envelope, the stomach envelope, the knee envelope, and the hand extension and interface, etc.
[0033] In an embodiment of the present invention, the initial hard point parameter values configured during the design of the target vehicle driving space can be first obtained, and then based on the initial hard point parameter values and drawing software, a human-machine model and a whole vehicle data model can be drawn in a software environment.
[0034] Optionally, the vehicle drawing related data associated with the initial hard point parameter values can be determined, so that the initial hard point parameter values and the vehicle drawing related data can be input into the drawing software to generate a vehicle data model, and further obtain the relevant data of the three-dimensional human body model that simulates various driving postures in the vehicle data model to draw the human-machine model.
[0035] For example, the simulated two-dimensional side view of the vehicle data model and the human-machine model can be found in Figure 2 , the three-dimensional human-machine model can be found in Figure 3 .
[0036] Step 120: Perform two rounds of evaluation on the initial hard point parameter values according to the human-machine model, the vehicle data model, the human-machine verification rules, and the human-machine comfort evaluation rules to obtain the actual hard point parameter values to be verified.
[0037] Among them, the human-machine verification rules can be used to verify the feasibility of the driver and passenger using the vehicle functional parts, which must meet the requirements of relevant regulations and product competitiveness. The human-machine comfort evaluation rules can be used to evaluate the driver and passenger satisfaction with vehicle comfort. The actual hard point parameter value to be verified can be the hard point parameter value determined after evaluating the initial hard point parameter value based on the human-machine verification rules and the human-machine comfort evaluation rules.
[0038] In an embodiment of the present invention, the initial hard point parameter values can be evaluated for the first time based on the human-machine model, the whole vehicle data model and the human-machine verification rules, and the initial hard point parameter values can be evaluated again based on the human-machine model, the whole vehicle data model and the human-machine comfort evaluation rules, and the hard point parameter values that pass the evaluation are used as the actual hard point parameter values to be verified.
[0039] Step 130: Obtain the physical evaluation score of the human-machine physical test bench built with the actual hard point parameter value to be verified, and determine the driving space optimization hard point parameter value based on the physical evaluation score and the development score threshold.
[0040] The human-machine physical test bench may be a test bench that simulates the actual vehicle use environment of the target vehicle. The human-machine physical test bench may include, but is not limited to, a simulated cab aluminum frame with windshield adjustment, an interior white model with adjustable interior space of the cab, a steering wheel, three pedals, and an adjustable seat. The physical evaluation score may be a physical evaluation value obtained based on the human-machine physical test bench simulating the actual vehicle use environment. The development scoring threshold may be a pre-set score that represents the satisfaction of the product goal.
[0041] In an embodiment of the present invention, the actual hard point parameter values to be verified can be applied to the construction of a man-machine physical test bench, and the man-machine physical test bench can be used to simulate the actual vehicle usage environment, so that the evaluation team can conduct a physical evaluation of the man-machine physical test bench to obtain a physical evaluation score, and then compare the physical evaluation score with the development scoring threshold. When the physical evaluation score is not less than the development scoring threshold, the actual hard point parameter values to be verified are evaluated again based on the physical evaluation score and the evaluation data corresponding to the actual hard point parameter values to be verified, so as to determine the driving space optimization hard point parameter values that meet the product goals.
[0042] In this scheme, the hard point parameter values for driving space optimization are determined based on the actual evaluation scores and the development scoring thresholds. This can avoid the problem of large sensory differences among different people when determining the hard point parameter values for driving space optimization based only on the actual evaluation scores, and can also avoid the problem of no real scenario verification and evaluation when determining the hard point parameter values for driving space optimization based only on the development scoring thresholds.
[0043] The technical solution of the embodiment of the present invention obtains the initial hard point parameter values of the target vehicle driving space, and creates a human-machine model and a vehicle data model based on the initial hard point parameter values, thereby performing two rounds of evaluation on the initial hard point parameter values according to the human-machine model, the vehicle data model, the human-machine verification rules, and the human-machine comfort evaluation rules, and obtains the actual hard point parameter values to be verified, and then obtains the physical evaluation score of the human-machine physical bench built with the actual hard point parameter values to be verified, and determines the optimized hard point parameter values of the driving space according to the physical evaluation score and the development score threshold. This solution can quickly determine the key human-machine hard point parameter values, organically combine theoretical design, evaluation, and human-machine physical bench verification suitable for user groups, effectively ensure the accuracy of the design results, solve the current problems of low design efficiency and long development cycle of hard point parameter values of vehicle cabs, and can improve the design efficiency of hard point parameter values, thereby reducing the vehicle development cycle.
[0044] Embodiment 2
[0045] Figure 4 This is a flow chart of a vehicle driving space design method provided in the second embodiment of the present invention. This embodiment is specific based on the above embodiment and provides a specific optional implementation method for performing two rounds of evaluation on the initial hard point parameter values according to the human-machine model, the vehicle data model, the human-machine verification rules and the human-machine comfort evaluation rules to obtain the actual hard point parameter values to be verified. Figure 4 As shown, the method includes:
[0046] Step 210: Obtain initial hard point parameter values of the target vehicle driving space, and create a human-machine model and a whole vehicle data model based on the initial hard point parameter values.
[0047] In an optional embodiment of the present invention, obtaining the initial hard point parameter values of the target vehicle driving space may include: obtaining the benchmark hard point parameter values of the benchmark vehicle driving space based on the human-machine verification of the key hard point parameters; and determining the initial hard point parameter values according to the benchmark hard point parameter values and the preconfigured hard point experience parameter values.
[0048] Among them, the key hard point parameters of human-machine verification can be the key hard point parameters of the target vehicle cab formulated by the evaluator. The benchmark vehicle can be a publicly sold vehicle with the same product positioning as the target vehicle. The benchmark hard point parameter value can be the hard point parameter value set when performing human-machine simulation on the driving space of the benchmark vehicle. The pre-configured hard point experience parameter value can be the corresponding parameter value pre-configured for the key hard point parameters of human-machine verification.
[0049] In an embodiment of the present invention, a human-machine evaluation team can be assembled to define the user group of the target vehicle, unify the evaluation method, and enable the evaluators to perform unified prescribed actions during the evaluation process. The evaluation results of the evaluation team can be recorded and analyzed, thereby setting key hard point parameters for human-machine verification based on the evaluation results and the development goals of the target vehicle, and determining a benchmark vehicle for the target vehicle, so that the parameter values corresponding to the key hard point parameters for human-machine verification of the benchmark vehicle's driving space are used as the benchmark hard point parameter values. Furthermore, the initial hard point parameter values that meet the design of the target vehicle's driving space can be screened out from the benchmark hard point parameter values and the pre-configured hard point experience parameter values.
[0050] Optionally, initial hard point parameter values that meet the target vehicle driving space design can be screened out from the benchmark hard point parameter values and pre-configured hard point experience parameter values based on manual or preset data screening rules.
[0051] For example, the key hard point parameters and associated data of human-machine verification can refer to the following table:
[0052] Table 1 Human-machine verification key hard point parameter query table
[0053]
[0054] In an optional embodiment of the present invention, creating a human-machine model and a whole vehicle data model based on the initial hard point parameter values may include: creating a human-machine model and a whole vehicle data model based on a hybrid modeling technique and the initial hard point parameter values. The target vehicle driving space may include a driving space of a light pure electric commercial vehicle.
[0055] Among them, the hybrid modeling technology can be CATIA.
[0056] In an embodiment of the present invention, the target vehicle may be a light electric commercial vehicle, and thus a human-machine model and a whole vehicle data model are created using hybrid modeling technology based on the initial hard point parameter values configured for the driving space of the light electric commercial vehicle.
[0057] Exemplarily, the target vehicle may be a light-duty pure electric commercial vehicle that is not a low-entry model, and the created vehicle data model focuses on meeting the needs of light-duty commercial vehicle users for standing activities in the cab.
[0058] Step 220: Perform a first round of evaluation and verification on the initial hard point parameter values according to the human-machine model, the vehicle data model and the human-machine verification rules to determine the initial verification hard point parameter values.
[0059] Among them, the initial inspection hard point parameter value can be a hard point parameter value that complies with human-machine verification rules.
[0060] In an embodiment of the present invention, a human-machine model and a vehicle data model can be used to simulate various human postures of the driver and passengers in the driving space of the target vehicle, and the feasibility of the application of vehicle functional parts under various simulated human postures can be verified through human-machine verification rules, that is, the initial hard point parameter values are evaluated and verified for the first round, and the verified initial hard point parameter values are used as the initial verification hard point parameter values.
[0061] In an optional embodiment of the present invention, a first round of evaluation and verification is performed on the initial hard point parameter values according to the human-machine model, the whole vehicle data model and the human-machine verification rules to determine the initial hard point parameter values, which may include: verifying the driver's operating behavior simulated by the human-machine model and the whole vehicle data model according to the human-machine verification rules; when the verification is successful, the initial hard point parameter values are used as the initial hard point parameter values, and when the verification fails, the initial hard point parameter values are updated, and the operation of creating the human-machine model and the whole vehicle data model based on the initial hard point parameter values is returned.
[0062] In the embodiment of the present invention, the initial hard point parameter value is evaluated and verified according to the human-machine verification rules for the driver's operation behavior simulated by the human-machine model and the whole vehicle data model. If the verification is successful, it means that the driver can operate the vehicle function parts normally, so the initial hard point parameter value is used as the initial verification hard point parameter value. If the verification fails, it means that the driver cannot operate the vehicle function parts normally, and the initial hard point parameter value can be manually updated, and the operation of creating the human-machine model and the whole vehicle data model based on the initial hard point parameter value is returned until the initial verification hard point parameter value is successfully verified.
[0063] Step 230: Perform a second round of evaluation and verification on the initial hard point parameter values according to the human-machine model, the vehicle data model and the human-machine comfort evaluation rules to determine the actual hard point parameter values to be verified.
[0064] In an embodiment of the present invention, a human-machine model and a vehicle data model are used to simulate various human postures of the driver and passengers in the driving space of the target vehicle, so that the user's comfort under various simulated human postures is evaluated according to the human-machine comfort evaluation rules, that is, a second round of evaluation and verification is performed on the initial hard point parameter values, and the verified initial hard point parameter values are used as the actual hard point parameter values to be verified.
[0065] In an optional embodiment of the present invention, a second round of evaluation and verification is performed on the initial hard point parameter values according to the human-machine model, the vehicle data model and the human-machine comfort evaluation rules to determine the actual hard point parameter values to be verified, which may include: evaluating the driver's operating behavior simulated by the human-machine model and the vehicle data model according to the human-machine comfort evaluation rules; when the evaluation passes, using the initial hard point parameter values as the actual hard point parameter values to be verified, and when the evaluation fails, updating the initial hard point parameter values, and returning to execute the operation of creating the human-machine model and the vehicle data model based on the initial hard point parameter values.
[0066] In the embodiment of the present invention, the initial hard point parameter value is evaluated and verified according to the human-machine comfort evaluation rule for the driver's operation behavior simulated by the human-machine model and the whole vehicle data model. If the evaluation is passed, it indicates that the cab space configuration using the initial hard point parameter value can meet the driver's comfort needs, and then the initial hard point parameter value is used as the actual hard point parameter value to be verified. If the evaluation fails, it indicates that the cab space configuration using the initial hard point parameter value cannot meet the driver's comfort needs, so the initial hard point parameter value is manually updated, and the operation of creating the human-machine model and the whole vehicle data model based on the initial hard point parameter value is returned to execute until the second round of evaluation and verification passes.
[0067] Optionally, the vehicle data model can be used to simulate various postures of personnel during vehicle use based on RAMSIS (automotive ergonomics software). That is, in the RAMSIS software environment, the human-machine model that best suits the users of the product can be customized, including gender, nationality, age, era, body shape and percentile, and ultimately output a human-machine comfort evaluation to complete the second round of evaluation and verification.
[0068] Step 240: Obtain the physical evaluation score of the human-machine physical test bench built with the actual hard point parameter value to be verified, and determine the driving space optimization hard point parameter value based on the physical evaluation score and the development score threshold.
[0069] For example, the evaluation team can formulate a unified evaluation standard, and the actual evaluation scores can be divided into several levels, such as very dissatisfied, somewhat dissatisfied, relatively satisfied, very satisfied, and impeccable. The corresponding scores can be set in a specific and granular manner for each level.
[0070] In an optional embodiment of the present invention, determining the hard point parameter value for optimizing the driving space based on the physical evaluation score and the development score threshold may include: when the physical evaluation score is greater than or equal to the development score threshold, calculating the target comprehensive evaluation score based on the physical evaluation score and the comfort score data; when the target comprehensive evaluation score is greater than or equal to the development score threshold, using the actual hard point parameter value to be verified as the hard point parameter value for optimizing the driving space.
[0071] The comfort rating data may be a user comfort rating given to the hard point parameter value during the second round of evaluation and verification. The target comprehensive evaluation score may be a score determined by combining the physical evaluation score and the comfort rating data.
[0072] In an embodiment of the present invention, the physical evaluation score can be compared with the development scoring threshold. If the physical evaluation score is greater than or equal to the development scoring threshold, the mean of the physical evaluation score and the comfort scoring data, or the sum under different weights, can be calculated, and the calculation result can be used as the target comprehensive evaluation score. The target comprehensive evaluation score is further compared with the development scoring threshold. If the target comprehensive evaluation score is greater than or equal to the development scoring threshold, the actual hard point parameter value to be verified is used as the hard point parameter value for driving space optimization.
[0073] In an optional embodiment of the present invention, the vehicle driving space design method may further include: when the physical evaluation score is less than the development score threshold, updating the initial hard point parameter value, and returning to execute the operation of creating a human-machine model and a whole vehicle data model based on the initial hard point parameter value, until the determined physical evaluation score is greater than or equal to the development score threshold.
[0074] In the embodiment of the present invention, when the physical evaluation score is less than the development scoring threshold, the initial hard point parameter value can be manually updated, and the operation of creating a human-machine model and a vehicle data model based on the initial hard point parameter value is returned until the physical evaluation score is determined to be greater than or equal to the development scoring threshold, and then the target comprehensive evaluation score is calculated based on the physical evaluation score and the comfort score data. When the target comprehensive evaluation score is greater than or equal to the development scoring threshold, the actual hard point parameter value to be verified is used as the hard point parameter value for driving space optimization.
[0075] Based on this solution, the optimized design and verification results of the driving cabin space that meet the needs of users can be achieved efficiently and accurately, which can effectively avoid the risk of not meeting the product development goals in the later actual vehicle verification stage, and significantly improve the efficiency of light electric commercial vehicle product development. Considering the changing needs of users in the future light commercial vehicle market, the increasing and differentiated comfort needs, the driving space design method of this solution can be improved or replaced in the later stage based on product and technology changes and production level development.
[0076] The technical solution of the embodiment of the present invention obtains the initial hard point parameter values of the target vehicle's driving space, and creates a man-machine model and a whole vehicle data model based on the initial hard point parameter values, thereby performing a first round of evaluation and verification on the initial hard point parameter values according to the man-machine model, the whole vehicle data model and the man-machine verification rules to determine the initial hard point parameter values, and further performing a second round of evaluation and verification on the initial hard point parameter values according to the man-machine model, the whole vehicle data model and the man-machine comfort evaluation rules to determine the actual hard point parameter values to be verified, thereby obtaining the physical evaluation score of the man-machine physical bench built with the actual hard point parameter values to be verified, and determining the driving space optimization hard point parameter values according to the physical evaluation score and the development scoring threshold. In this solution, the theoretical design verification is completed based on the human-machine model and the vehicle data model, and the human-machine physical test bench is used to simulate the actual vehicle usage environment. The hard point parameters are evaluated and verified for different usage conditions. The accuracy of the key hard point parameter values is guaranteed by the mutual driving of the evaluation results and the theoretical design values. The perception evaluation of different target user groups can be quickly realized, and the output results are accurate and efficient, which effectively improves the product development efficiency. It solves the current problems of low design efficiency and long development cycle of hard point parameter values of vehicle cabs, and can improve the design efficiency of hard point parameter values, thereby reducing the vehicle development cycle.
[0077] Embodiment 3
[0078] Figure 5 This is a schematic diagram of the structure of a vehicle driving space design device provided by Embodiment 3 of the present invention. Figure 5 As shown, the device comprises:
[0079] The data acquisition and modeling module 310 is used to acquire the initial hard point parameter values of the target vehicle driving space and create a human-machine model and a whole vehicle data model based on the initial hard point parameter values;
[0080] The data evaluation module 320 is used to perform two rounds of evaluation on the initial hard point parameter values according to the human-machine model, the vehicle data model, the human-machine verification rules and the human-machine comfort evaluation rules to obtain the actual hard point parameter values to be verified;
[0081] The space optimization parameter value determination module 330 is used to obtain the physical evaluation score of the human-machine physical test bench built with the actual hard point parameter value to be verified, and determine the driving space optimization hard point parameter value based on the physical evaluation score and the development score threshold.
[0082] The technical solution of the embodiment of the present invention obtains the initial hard point parameter values of the target vehicle driving space, and creates a human-machine model and a vehicle data model based on the initial hard point parameter values, thereby performing two rounds of evaluation on the initial hard point parameter values according to the human-machine model, the vehicle data model, the human-machine verification rules, and the human-machine comfort evaluation rules, and obtains the actual hard point parameter values to be verified, and then obtains the physical evaluation score of the human-machine physical bench built with the actual hard point parameter values to be verified, and determines the optimized hard point parameter values of the driving space according to the physical evaluation score and the development score threshold. This solution can quickly determine the key human-machine hard point parameter values, organically combine theoretical design, evaluation, and human-machine physical bench verification suitable for user groups, effectively ensure the accuracy of the design results, solve the current problems of low design efficiency and long development cycle of hard point parameter values of vehicle cabs, and can improve the design efficiency of hard point parameter values, thereby reducing the vehicle development cycle.
[0083] Optionally, the data acquisition and modeling module 310 includes a data acquisition unit and a modeling unit. The data acquisition unit is used to acquire the benchmark hard point parameter value of the benchmark vehicle driving space based on the human-machine verification key hard point parameter; and determine the initial hard point parameter value according to the benchmark hard point parameter value and the pre-configured hard point experience parameter value.
[0084] Optionally, a modeling unit is used to create the human-machine model and the vehicle data model based on a hybrid modeling technology and the initial hard point parameter value. The target vehicle driving space includes a driving space of a light pure electric commercial vehicle.
[0085] Optionally, the data evaluation module 320 includes a first evaluation verification unit and a second evaluation verification unit. The first evaluation verification unit is used to perform a first round of evaluation verification on the initial hard point parameter value according to the human-machine model, the whole vehicle data model and the human-machine verification rules to determine the initial hard point parameter value. The second evaluation verification unit is used to perform a second round of evaluation verification on the initial hard point parameter value according to the human-machine model, the whole vehicle data model and the human-machine comfort evaluation rules to determine the actual hard point parameter value to be verified.
[0086] Optionally, the first evaluation and verification unit is specifically used to verify the driver's operating behavior simulated by using the human-machine model and the whole vehicle data model in accordance with the human-machine verification rules; when the verification is successful, the initial hard point parameter value is used as the initial verification hard point parameter value, and when the verification fails, the initial hard point parameter value is updated, and the operation of creating the human-machine model and the whole vehicle data model based on the initial hard point parameter value is returned.
[0087] Optionally, a second evaluation and verification unit is specifically used to evaluate the driver's operating behavior simulated by using the human-machine model and the whole vehicle data model according to the human-machine comfort evaluation rules; when the evaluation passes, the initial hard point parameter value is used as the actual hard point parameter value to be verified, and when the evaluation fails, the initial hard point parameter value is updated, and the operation of creating the human-machine model and the whole vehicle data model based on the initial hard point parameter value is returned.
[0088] Optionally, the space optimization parameter value determination module 330 is specifically used to calculate the target comprehensive evaluation score based on the physical evaluation score and the comfort score data when the physical evaluation score is greater than or equal to the development score threshold; when the target comprehensive evaluation score is greater than or equal to the development score threshold, use the actual hard point parameter value to be verified as the driving space optimization hard point parameter value.
[0089] Optionally, the space optimization parameter value determination module 330 is specifically used to update the initial hard point parameter value when the physical evaluation score is less than the development score threshold, and return to execute the operation of creating a human-machine model and a whole vehicle data model based on the initial hard point parameter value until the determined physical evaluation score is greater than or equal to the development score threshold.
[0090] The vehicle driving space design device provided in the embodiment of the present invention can execute the vehicle driving space design method provided in any embodiment of the present invention, and has the corresponding functional modules and beneficial effects of the execution method.
[0091] Embodiment 4
[0092] Figure 6 A schematic diagram of an electronic device that can be used to implement an embodiment of the present invention is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device may also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices (such as helmets, glasses, watches, etc.) and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present invention described and / or required herein.
[0093] like Figure 6As shown, the electronic device 10 includes at least one processor 11, and a memory connected to the at least one processor 11, such as a read-only memory (ROM) 12, a random access memory (RAM) 13, etc., wherein the memory stores a computer program that can be executed by at least one processor, and the processor 11 can perform various appropriate actions and processes according to the computer program stored in the read-only memory (ROM) 12 or the computer program loaded from the storage unit 18 to the random access memory (RAM) 13. In the RAM 13, various programs and data required for the operation of the electronic device 10 can also be stored. The processor 11, the ROM 12, and the RAM 13 are connected to each other through a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.
[0094] A number of components in the electronic device 10 are connected to the I / O interface 15, including: an input unit 16, such as a keyboard, a mouse, etc.; an output unit 17, such as various types of displays, speakers, etc.; a storage unit 18, such as a disk, an optical disk, etc.; and a communication unit 19, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 19 allows the electronic device 10 to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks.
[0095] The processor 11 may be a variety of general and / or special processing components with processing and computing capabilities. Some examples of the processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various dedicated 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 11 executes the various methods and processes described above, such as a vehicle driving space design method.
[0096] In some embodiments, the vehicle driving space design method may be implemented as a computer program, which is tangibly contained in a computer-readable storage medium, such as a storage unit 18. In some embodiments, part or all of the computer program may be loaded and / or installed on the electronic device 10 via the ROM 12 and / or the communication unit 19. When the computer program is loaded into the RAM 13 and executed by the processor 11, one or more steps of the vehicle driving space design method described above may be performed. Alternatively, in other embodiments, the processor 11 may be configured to execute the vehicle driving space design method in any other appropriate manner (e.g., by means of firmware). In some embodiments, a computer program product including the aforementioned computer program may be released for user use and technology promotion.
[0097] Various implementations of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various implementations can include: being implemented in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which can be a special purpose or general purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.
[0098] Computer programs for implementing the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, so that when the computer program is executed by the processor, the functions / operations specified in the flow chart and / or block diagram are implemented. The computer program may be executed entirely on the machine, partially on the machine, partially on the machine and partially on a remote machine as a stand-alone software package, or entirely on a remote machine or server.
[0099] In the context of the present invention, a computer-readable storage medium may be a tangible medium that may contain or store a computer program for use by or in combination with an instruction execution system, device or equipment. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices or equipment, or any suitable combination of the foregoing. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. A more specific example of a machine-readable storage medium may include an electrical connection based on one or more lines, a portable computer disk, 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 disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.
[0100] To provide interaction with a user, the systems and techniques described herein may 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 trackball) through which the user can provide input to the electronic device. Other types of devices may also be used to provide interaction with the user; for example, the feedback provided to the user may be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form (including acoustic input, voice input, or tactile input).
[0101] The systems and techniques described herein may be implemented in a computing system that includes backend components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes frontend components (e.g., a user computer with a graphical user interface or a web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such backend components, middleware components, or frontend components. The components of the system may 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.
[0102] A computing system may include a client and a server. The client and the server are generally remote from each other and usually interact through a communication network. The client and server relationship is generated by computer programs running on the corresponding computers and having a client-server relationship with each other. The server may 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 difficult management and weak business scalability in traditional physical hosts and VPS services.
[0103] It should be understood that the various forms of processes shown above can be used to reorder, add or delete steps. For example, the steps described in the present invention can be executed in parallel, sequentially or in different orders, as long as the desired results of the technical solution of the present invention can be achieved, and this document does not limit this.
[0104] The above specific implementations do not constitute a limitation on the protection scope of the present invention. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions can be made according to design requirements and other factors. Any modification, equivalent substitution and improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims
1. A vehicle driving space design method, characterized in that: include: Acquire initial hard point parameter values of the target vehicle driving space, and create a human-machine model and a whole vehicle data model based on the initial hard point parameter values; According to the human-machine model, the vehicle data model, the human-machine verification rules and the human-machine comfort evaluation rules, two rounds of evaluation are performed on the initial hard point parameter values to obtain actual hard point parameter values to be verified; Obtain a physical evaluation score of a human-machine physical test bench built with the actual hard point parameter value to be verified, and determine the driving space optimization hard point parameter value based on the physical evaluation score and a development scoring threshold.
2. The method according to claim 1, characterized in that The step of obtaining the initial hard point parameter value of the target vehicle driving space includes: Based on the key hard point parameters verified by human-machine, obtain the benchmark hard point parameter values of the benchmark vehicle driving space; The initial hard point parameter value is determined according to the benchmark hard point parameter value and the preconfigured hard point experience parameter value.
3. The method according to claim 1, characterized in that The step of creating a human-machine model and a vehicle data model based on the initial hard point parameter values includes: Based on the hybrid modeling technology and the initial hard point parameter values, creating the human-machine model and the whole vehicle data model; The target vehicle driving space includes a driving space of a light pure electric commercial vehicle.
4. The method according to claim 1, characterized in that: The step of performing two rounds of evaluation on the initial hard point parameter values according to the human-machine model, the vehicle data model, the human-machine verification rules, and the human-machine comfort evaluation rules to obtain the actual hard point parameter values to be verified includes: According to the human-machine model, the vehicle data model and the human-machine verification rules, a first round of evaluation and verification is performed on the initial hard point parameter values to determine the initial verification hard point parameter values; According to the human-machine model, the whole vehicle data model and the human-machine comfort evaluation rule, a second round of evaluation and verification is performed on the initially verified hard point parameter values to determine the actual hard point parameter values to be verified.
5. The method according to claim 4, characterized in that The first round of evaluation and verification of the initial hard point parameter values is performed according to the human-machine model, the vehicle data model and the human-machine verification rules to determine the initial verification hard point parameter values, including: Verifying the driver's operating behavior simulated by using the human-machine model and the whole vehicle data model according to the human-machine verification rules; When the verification is successful, the initial hard point parameter value is used as the initial verification hard point parameter value, and when the verification fails, the initial hard point parameter value is updated, and the operation of creating a human-machine model and a whole vehicle data model based on the initial hard point parameter value is returned.
6. The method according to claim 4, characterized in that The performing a second round of evaluation and verification on the initially verified hard point parameter values according to the human-machine model, the vehicle data model and the human-machine comfort evaluation rule to determine the actual hard point parameter values to be verified includes: Evaluating the driver's operating behavior simulated by the human-machine model and the whole vehicle data model according to the human-machine comfort evaluation rule; When the evaluation passes, the initial hard point parameter value is used as the actual hard point parameter value to be verified, and when the evaluation fails, the initial hard point parameter value is updated, and the operation of creating a human-machine model and a whole vehicle data model based on the initial hard point parameter value is returned.
7. The method according to claim 1, characterized in that Determining the driving space optimization hard point parameter value according to the physical evaluation score and the development scoring threshold includes: When the physical object evaluation score is greater than or equal to the development scoring threshold, a target comprehensive evaluation score is calculated according to the physical object evaluation score and the comfort scoring data; When the target comprehensive evaluation score is greater than or equal to the development score threshold, the actual hard point parameter value to be verified is used as the driving space optimization hard point parameter value.
8. The method according to claim 7, characterized in that Also includes: When the physical evaluation score is less than the development score threshold, the initial hard point parameter value is updated, and the operation of creating a human-machine model and a whole vehicle data model based on the initial hard point parameter value is returned to be executed until the determined physical evaluation score is greater than or equal to the development score threshold.
9. A vehicle driving space design device, characterized in that: include: A data acquisition and modeling module, used to acquire initial hard point parameter values of the target vehicle driving space, and create a human-machine model and a whole vehicle data model based on the initial hard point parameter values; A data evaluation module, configured to perform two rounds of evaluation on the initial hard point parameter values according to the human-machine model, the vehicle data model, the human-machine verification rules, and the human-machine comfort evaluation rules, to obtain actual hard point parameter values to be verified; The space optimization parameter value determination module is used to obtain the physical evaluation score of the human-machine physical test bench built with the actual hard point parameter value to be verified, and determine the driving space optimization hard point parameter value according to the physical evaluation score and the development scoring threshold.
10. An electronic device, characterized in that: The electronic device comprises: at least one processor; and a memory communicatively connected to the at least one processor; 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 so that the at least one processor can execute the vehicle driving space design method according to any one of claims 1 to 8.
11. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer instructions, and the computer instructions are used to implement the vehicle driving space design method according to any one of claims 1 to 8 when executed by a processor.
12. A computer program product, characterized in that The computer program product comprises a computer program, which, when executed by a processor, implements the vehicle driving space design method according to any one of claims 1 to 8.