阅读说明：本技术 一种人机功能分配方法 (Man-machine function distribution method ) 是由 李珍 王奇涛 赵所 王海涛 殷毅 张勇 郝云飞 隋劼 徐刚 石星辰 于 2021-05-25 设计创作，主要内容包括：本申请属于飞机设计领域,特别涉及一种人机功能分配方法。包括：步骤一、将运行场景划分为多个阶段,并获取各个阶段的运行场景信息；步骤二、获取多维度的人机能力特征对比信息；步骤三、构建所述运行场景各个阶段的人机交互信息流模型；步骤四、识别所述人机交互信息流模型中的关键任务,并对所述关键任务进行功能分配权衡,获得关键任务中操作动作的功能分配结果。本申请的人机功能分配方法,基于运行场景分析,通过人机能力特征对比和建立人机交互信息流模型,识别关键任务,对比关键任务中同一活动人机分别执行的利弊实现功能分配的优化,解决人机分工优化互补设计的问题。(The application belongs to the field of airplane design, and particularly relates to a man-machine function distribution method. The method comprises the following steps: dividing an operation scene into a plurality of stages, and acquiring operation scene information of each stage; step two, obtaining multi-dimensional human-computer capability characteristic comparison information; thirdly, constructing a man-machine interaction information flow model of each stage of the operation scene; and fourthly, identifying the key tasks in the human-computer interaction information flow model, and carrying out function distribution balancing on the key tasks to obtain a function distribution result of the operation actions in the key tasks. The man-machine function allocation method is based on operation scene analysis, key tasks are identified through man-machine capability characteristic comparison and man-machine interaction information flow model establishment, optimization of function allocation is achieved through comparison of advantages and disadvantages which are respectively executed by the same active man machine in the key tasks, and the problem of man-machine labor division optimization complementary design is solved.)

1. A human-machine function allocation method, comprising:

dividing an operation scene into a plurality of stages, and acquiring operation scene information of each stage;

step two, obtaining multi-dimensional human-computer capability characteristic comparison information;

thirdly, constructing a man-machine interaction information flow model of each stage of the operation scene;

and fourthly, identifying the key tasks in the human-computer interaction information flow model, and carrying out function distribution balancing on the key tasks to obtain a function distribution result of the operation actions in the key tasks.

2. The human-machine function allocation method according to claim 1, wherein in the step one, the operation scene is divided into 9 stages of takeoff, climbing, cruising out of impact, entering a target area, fighting, exiting the target area, return voyage, descending and landing.

3. The human-machine function allocation method according to claim 2, wherein in step one, the operation scenario information includes an operation purpose, an operation time, a location, an actor, an operation scenario trigger condition, and an operation flow.

4. The method according to claim 1, wherein in step two, the step of obtaining the multi-dimensional human-machine capability feature comparison information comprises obtaining four-dimensional human-machine capability feature comparison information of information receiving, information storage, information processing, information and efficiency output.

5. The human-machine function allocation method according to claim 1, wherein in step three, the human-machine interaction information flow model comprises a behavior operation action unit, an action operation object unit, an information flow delivery unit and a decision determination unit.

6. The human-machine function allocation method according to claim 5, wherein the human-machine interaction information flow model is divided into a plurality of sub-modules according to behavior clustering.

7. The human-machine function allocation method according to claim 1, wherein in step four, the identifying key tasks in the human-machine interaction information flow model and performing function allocation weighing on the key tasks, and the obtaining a function allocation result of an operation action in a key task includes:

s401, identifying a key task in the human-computer interaction information flow model, determining the dimension to which an operation action in the key task belongs, acquiring human-computer capability feature comparison information corresponding to the dimension, and determining an evaluation index of an information processing capability feature;

s402, determining a system comprehensive evaluation index influencing the comprehensive efficiency of the system scheme;

s403, determining the weight of each evaluation index, and establishing a function distribution balance evaluation matrix;

s404, scoring the effect of the corresponding operation action executed by the human machine, and judging the actor of the operation action according to the weighted total score.

8. The method according to claim 7, wherein in S402, the system comprehensive evaluation index includes space resource, weight, cost, and security.

Technical Field

The application belongs to the field of airplane design, and particularly relates to a man-machine function distribution method.

Background

The function distribution is an important content in the design process of a complex man-machine intelligent system, and needs an analysis method of an application system to reasonably distribute tasks of people and machines and scientifically design functions of the people and the machines. With the development of computer and artificial intelligence technology, the information environment in the use scene of the fighter is more complex, the human-computer system is gradually developed into a complex human-computer intelligent system with human-computer multi-mode interaction, and the roles of the fighter in different stages of task execution of the fighter are gradually penetrated into the assisting people to undertake different degrees of assistant decision making and automatic control through traditional single and immobilization. Therefore, the man-machine interaction of the fighter gradually changes from pure information transmission to three levels of information coupling of perception, decision and execution. The high integration of the information environment and system functions of a fighter, in the actual fighter design and research work, needs to meet the actual combat requirements and needs an engineered function allocation method.

The existing function distribution method has poor universality, single distribution standard and insufficient combination of the function distribution process and the design process, and is difficult to adapt to the complex use scene of the fighter and the interaction requirement of the complex man-machine intelligent system of the fighter brought by the rapid development of the technology. The situation of the battlefield environment is changed instantly, so that the function allocation of the fighter is necessarily a dynamic optimization iteration process related to the operational use information, and the fixed method cannot be applied to a scene with high cooperation between the fighter and the man-machine.

Accordingly, a technical solution is desired to overcome or at least alleviate at least one of the above-mentioned drawbacks of the prior art.

Disclosure of Invention

The present application is directed to a method for assigning human-machine functions, which solves at least one problem of the prior art.

The technical scheme of the application is as follows:

a man-machine function allocation method includes:

dividing an operation scene into a plurality of stages, and acquiring operation scene information of each stage;

step two, obtaining multi-dimensional human-computer capability characteristic comparison information;

thirdly, constructing a man-machine interaction information flow model of each stage of the operation scene;

and fourthly, identifying the key tasks in the human-computer interaction information flow model, and carrying out function distribution balancing on the key tasks to obtain a function distribution result of the operation actions in the key tasks.

Optionally, in the first step, the operation scene is divided into 9 stages of takeoff, climbing, cruising and striking, entering a target area, fighting, exiting the target area, returning, descending and landing.

Optionally, in the first step, the operation scenario information includes an operation purpose, an operation time, a location, an actor, an operation scenario trigger condition, and an operation flow.

Optionally, in the second step, the obtaining of the multidimensional human-machine capability feature comparison information includes obtaining four-dimensional human-machine capability feature comparison information of information receiving, information storage, information processing, information and efficiency output.

Optionally, in step three, the man-machine interaction information flow model includes a behavior operation action unit, an action operation object unit, an information flow delivery unit, and a decision determination unit.

Optionally, the human-computer interaction information flow model is divided into a plurality of sub-modules according to behavior clustering.

Optionally, in the fourth step, the identifying a key task in the human-computer interaction information flow model, and performing function allocation balancing on the key task, and obtaining a function allocation result of an operation action in the key task includes:

s401, identifying a key task in the human-computer interaction information flow model, determining the dimension to which an operation action in the key task belongs, acquiring human-computer capability feature comparison information corresponding to the dimension, and determining an evaluation index of an information processing capability feature;

s402, determining a system comprehensive evaluation index influencing the comprehensive efficiency of the system scheme;

s403, determining the weight of each evaluation index, and establishing a function distribution balance evaluation matrix;

s404, scoring the effect of the corresponding operation action executed by the human machine, and judging the actor of the operation action according to the weighted total score.

Optionally, in S402, the system comprehensive evaluation index includes space resource, weight, cost, and security.

The invention has at least the following beneficial technical effects:

the man-machine function allocation method is based on operation scene analysis, key tasks are identified through man-machine capability characteristic comparison and man-machine interaction information flow model establishment, optimization of function allocation is achieved through comparison of advantages and disadvantages which are respectively executed by the same active man machine in the key tasks, and the problem of man-machine labor division optimization complementary design is solved.

Drawings

FIG. 1 is a flow chart of a human-machine function assignment method according to an embodiment of the present application;

FIG. 2 is a cross-sectional view of an operation scenario of a man-machine function assignment method according to an embodiment of the present application;

FIG. 3 is a schematic diagram of a human-computer interaction information flow model of a human-computer function assignment method according to an embodiment of the present application;

FIG. 4 is a human-machine function assignment trade-off evaluation matrix of the human-machine function assignment method according to an embodiment of the present application;

FIG. 5 is a single person/multi person function assignment weighted evaluation matrix of a human-machine function assignment method according to an embodiment of the present application

Fig. 6 is a function assignment balance evaluation matrix scoring table of the man-machine function assignment method according to an embodiment of the present application.

Detailed Description

In order to make the implementation objects, technical solutions and advantages of the present application clearer, the technical solutions in the embodiments of the present application will be described in more detail below with reference to the drawings in the embodiments of the present application. In the drawings, the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The described embodiments are a subset of the embodiments in the present application and not all embodiments in the present application. The embodiments described below with reference to the drawings are exemplary and intended to be used for explaining the present application and should not be construed as limiting the present application. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application. Embodiments of the present application will be described in detail below with reference to the accompanying drawings.

In the description of the present application, it is to be understood that the terms "center", "longitudinal", "lateral", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", and the like indicate orientations or positional relationships based on those shown in the drawings, and are used merely for convenience in describing the present application and for simplifying the description, and do not indicate or imply that the referenced device or element must have a particular orientation, be constructed in a particular orientation, and be operated, and therefore should not be construed as limiting the scope of the present application.

The present application is described in further detail below with reference to fig. 1 to 6.

The application provides a man-machine function distribution method, which comprises the following steps:

dividing an operation scene into a plurality of stages, and acquiring operation scene information of each stage;

step two, obtaining multi-dimensional human-computer capability characteristic comparison information;

thirdly, constructing a man-machine interaction information flow model of each stage of the operation scene;

and fourthly, identifying the key tasks in the human-computer interaction information flow model, and carrying out function distribution balancing on the key tasks to obtain a function distribution result of the operation actions in the key tasks.

According to the man-machine function distribution method, operation scene analysis is firstly carried out, and the operation scene of the airplane is analyzed according to a typical use process.

In the preferred embodiment of the application, the use phases of the fighter are summarized as 9 phases of takeoff, climbing, cruising out of a hit, entering a target area, fighting, exiting the target area, returning, descending and landing. After the conditions and the switching time of the operation scene are defined, the operation scene information of each stage, including the operation purpose, the operation time, the location, the actor, the operation scene trigger condition and the operation flow, is taken, and an operation scene section diagram is drawn, as shown in fig. 2, so that a designer is helped to make the relationship among the operation scenes of the airplane, the switching flow of the operation scenes and the window condition more clear.

According to the man-machine function distribution method, the man-machine capability feature comparison information is obtained from multiple dimensions.

In the preferred embodiment of the application, the capability characteristics of the human-computer are compared in four dimensions of information receiving, information storage, information processing and information and efficiency output. In this embodiment, the human-machine capability characteristic analysis indexes are divided based on the Fitts law, and the capability characteristics of the pilot and the airplane are compared by combining the pilot population characteristics, such as training, strong physical function, excellent perception, knowledge diversification and pressure resistance, and limited adaptability of technical development and equipment installation, as shown in table 1.

TABLE 1 human-machine capability characteristic comparison information table

The man-machine function distribution method of the application is based on the operation scene, and a man-machine interaction information flow model of each stage of the operation scene is constructed, as shown in fig. 3. In this embodiment, the man-machine interaction information flow model includes a behavior operation action unit, an action operation object unit, an information flow delivery unit, and a decision determination unit, and may also be divided into a plurality of sub-modules according to behavior clustering. The main functions of human-computer interaction are decomposed, the system combs detailed activity flows in each behavior, actors, participants, activities and decisions of the activities are defined according to experience, functions, decision conditions, conversion logic and sequences required by the activities in the model are identified, and operation actions, operation objects, information flow transmission, decision branch and judgment, parallel/serial relation or selection and the like are expressed in a graphic form.

In the fourth step, identifying key tasks in the human-computer interaction information flow model, and performing function distribution balancing on the key tasks, and obtaining a function distribution result of operation actions in the key tasks includes:

s401, identifying a key task in a human-computer interaction information flow model, determining the dimension to which an operation action in the key task belongs, acquiring human-computer capability feature comparison information corresponding to the dimension, and determining an evaluation index of an information processing capability feature;

s402, determining a system comprehensive evaluation index influencing the comprehensive efficiency of the system scheme;

s403, determining the weight of each evaluation index, and establishing a function distribution balance evaluation matrix;

s404, scoring the effect of the corresponding operation action executed by the human machine, and judging the actor of the operation action according to the weighted total score.

In the preferred embodiment of the application, by reviewing the human-computer interaction information flow model, integrating and concluding the scenes and environments of human-computer operation/action, input and output, information, decision and the like in the model, activities or links with potential risks, which are dense in activities, influence task completion and are defined as key tasks, in the system operation flow are estimated and identified, the key tasks are balanced and optimized in function allocation, the function allocation of the optimized key tasks is checked, and the potential risks in the function allocation in the key tasks are concerned.

It can be understood that in the embodiment, the balance of the function distribution of the key tasks is that each function in the task is executed by a person/machine and the benefit and the disadvantage of the system operation are executed by a single person/multiple persons according to the requirement. And establishing a human/machine function distribution weighing evaluation matrix (as shown in figure 4) or a single/multi-human function distribution weighing evaluation matrix (as shown in figure 5), taking the function distribution scheme as a row, and taking the evaluation index as a column. From the engineering perspective, the evaluation index comprises two aspects of human and functional characteristics and system comprehensive balance.

It can be understood that, in this embodiment, after determining the key task, it is determined whether each operation action in the corresponding key task belongs to information reception, information storage, information processing, or information and performance output, and corresponding human-computer capability feature comparison information is found, and an evaluation index of the human-computer capability feature is determined by combining specific contents of the operation action; the system comprehensive evaluation index is an index which affects the comprehensive efficiency of the system scheme except the four dimensions of information processing, such as space resources, weight, cost, safety and the like, and is determined by combining project characteristics in actual evaluation.

Further, the weight of the evaluation index is given by combining the actual situation of the platform scheme, after a function distribution weighing evaluation matrix is established, expert scoring is adopted for evaluation, a weighing evaluation matrix scoring table (shown in fig. 6) is distributed for each function, weighting summation is carried out by comparing different function distribution schemes, the scheme with the total score is the final opinion of the expert, and finally the opinion of all the experts is considered comprehensively to determine the result of function distribution optimization.

According to the man-machine function distribution method, when the total scores of the distribution schemes in the function distribution balance evaluation matrix are close to each other (the difference is about 10% of the total score), the two schemes can be used. The specific items in each grading table can be observed in a focused manner, the matching of the man-machine labor division and the user capacity characteristics is balanced by combining the detailed judgment of the score of each item, partial auxiliary decision can be provided for a human by combining the actual requirement of a task in engineering design, or the activity can be completed by combining the man-machine dynamic complementation, so that the system scheme is reasonable and feasible, and the comprehensive efficiency of the man-machine system is optimal. Wherein, activities with large difference of human and functional characteristics and system comprehensive balance index score represent that the activities can complete the role transformation along with the subsequent technical development. In subsequent designs, staged implementations may be considered in conjunction with actual project development cycles.

The man-machine function distribution method can combine qualitative analysis and quantitative evaluation, obtains man-machine capability characteristic comparison information and establishes a man-machine interaction information flow model based on operation scene analysis, and is closely combined with operational use requirements. By identifying key tasks, a function distribution balance evaluation matrix is established, and advantages and disadvantages of different functional schemes are comprehensively compared from the perspective of human-computer capability characteristics and system comprehensive balance, so that dynamic optimization iteration is realized, and function decomposition and function distribution (optimization balance) in engineering design are organically combined. Through engineering practice verification, the method fully utilizes the principle of determining function distribution by utilizing human-machine capability characteristics, realizes dynamic human-machine function distribution and balance optimization, can effectively solve the problem of human-machine equipment adaptation in engineering design, improves human-machine work efficiency, realizes adjustment and adaptivity of tasks completed by human-machine cooperation, achieves optimization and complementation of human-machine capability, and improves the operational efficiency of weapon equipment.

The above description is only for the specific embodiments of the present application, but the scope of the present application is not limited thereto, and any changes or substitutions that can be easily conceived by those skilled in the art within the technical scope of the present application should be covered within the scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.