WU Xiaoli ,WEI Wentao ,CALDWELL Sabrina ,XUE Chengqi ,and WANG Linlin

1.School of Design Art &Media,Nanjing University of Science &Technology,Nanjing 210094,China;2.School of Mechanical Engineering,Southeast University,Nanjing 211189,China;3.College of Mechanical and Electrical Engineering,Hohai University,Changzhou 211100,China;4.School of Computer Science,Australian National University,Canberra 2600,Australia

Abstract: With the rapid development of digital and intelligent information systems,display of radar situation interface has become an important challenge in the field of human-computer interaction.We propose a method for the optimization of radar situation interface from error-cognition through the mapping of information characteristics.A mapping method of matrix description is adopted to analyze the association properties between error-cognition sets and design information sets.Based on the mapping relationship between the domain of error-cognition and the domain of design information,a cross-correlational analysis is carried out between error-cognition and design information.We obtain the relationship matrix between the error-cognition of correlation between design information and the degree of importance among design information.Taking the task interface of a warfare navigation display as an example,error factors and the features of design information are extracted.Based on the results,we also propose an optimization design scheme for the radar situation interface.

Keywords: radar situation interface,error-cognition,information feature mapping,visual information display.

1.Introduction

The human-computer interaction industry has long been exploring reasonable and feasible design methods to improve the information presentation problem faced by current digital,intelligent radar situation interface.Especially in the field of complex information systems,researchers both at home and abroad have devoted time and effort to seek reasonable methods for information display through research on information coding and layouts.For instance,in the Human Measures and Performance Project,NASA specifically studied the problems of color security and availability of the design of various complex graph display interfaces in the aviation field [1].Yeh et al.carried out experiments to investigate how to best exhibit relevant electronic information on battlefield maps [2].Montgomery et al.performed an experimental study on the effect of luminance on an observer’s degree of reliability in identifying information in a visual display [3].Tullis [4] and Schum [5] investigated the efficiency of identifying digital and graphical information coding.Monnier applied the experimental paradigm of visual delay in search tasks to study the relationship between colors and locations [6].Parsons et al.summarized ten attributes of interactive visual displays (including importance,relations,and adjustability of interactions) [7].In 1984,at an early stage of the aviation industry in our country,Liang analyzed and investigated the usage of circular scale instruments in different types of domestic airplane pilot seats to propose suggestions to improve their instrumental scales,pointers,digital display,benchmark of flight attitude,instrumental size,and layout [8].Neyedli et al.performed research on the information representation of auto-battle recognition system [9].Wu et al.performed physiological research on the information representation and interface design of humanmachine interfaces of complex systems [10-14].All these works indicate the importance of information presentation in the process of monitoring task execution.They conclude that icons,symbols,and colors are critical styles of expression for information presentation.

With the rapid development of computer graphics and user interface technologies,the study of human errors has also been applied to the field of interface design to improve interface effectiveness.Nielsen et al.[15] and Shryane et al.[16] proposed methods for reducing the error rates to improve interface efficiency.Li proposed a system for the error classification of human-computer interfaces [17].He proposed that inattention and overattention can both be regarded as key ideas which need to be taken into consideration in the research on human errors.Hassnert et al.concluded that it is not possible to have a uniform standard for error classification [18].It is stated that the corresponding types of human errors should be identified through experimental methods.Inductive classification is conducted towards user errors by means of user interface tests of the software [18].Maxion et al.investigated the use of the external subgoal support method to enhance the reliability of user interfaces by reducing errors [19].Roco et al.used a driver behavior questionnaire to analyze the reasons caused by attention errors (driving errors,traffic violations,and excessive behaviors) and found the key factors causing operational errors [20].Shappell et al.analyzed aircraft accidents data in 2013 and also identified attention,comprehension and other related factors corresponding to skills and decision-making [21].Anokhin et al.analyzed the ergonomics of control panel design of the main control room in a nuclear power station,concluding that the most typical design error is incompatibility between irregular layout and equipment [22].Shen et al.established the theory and method of the human error cognition model [23].Wang et al.established an operator behavior model from the perspective of human factors engineering and decision-making behavior [24].Li established an evaluation model and a reliability evaluation method of nuclear power plant digital control system based on operator situation cognition [25].

In the research field of design methodology,the design process is regarded as a system that transforms a model from a concept-function to structural mapping.This has been studied in depth since the end of the 20th century,and has been applied to the fields of machinery and product design.Direct mapping from a function to a structure was proposed by Pahl et al.in 1992 as a typical representation in the field [26].In 2000,Suh proposed an alternate reciprocating mapping in terms of functionstructure mapping and structure-subfunction mapping[27].Based on [26],in 1996,Gero proposed a multi-level mixed mapping method which introduced a behavioral domain between the functional and structural domains[1].In the above-mentioned studies,the process of design solution is formed by mapping methods such as matrix description and genetic algorithms.This process opens up an effective method for the design of mechanical structures that can be widely applied to the innovative design of products.In the human-computer interaction field,for the optimization of design methods for complex information interfaces,we must discuss the feasibility of the designs from the perspective of error-cognition to design mapping.It needs to be seen whether this is able to open up a solution process for interface design while learning from error factors.

This paper proposes a framework called the “error-cognition-design”,based on our study of the association between error factors,visual cognition and design information.This framework offers a technique that can map the mechanism of error-cognition into the design factors of radar situation interface,to perform optimization for the design of complex radar situation interface.

2.Optimized method of information interaction interface

In this paper,we study the possible mapping among error,cognition,and design.The transition from the mapping of error and cognitive domains to the mapping of a design domain enables the process of optimizing interface efficiency.The design solution process of a complex radar situation interface can be developed by importing error factors and combining them with the visual cognition behavior of the information interface.

The optimization method of a radar situation interface from error-cognition to information feature mapping could provide a reliable analytical solution.This procedure is summarized as shown Fig.1.

Fig.1 Procedure of the optimization method

(i) Given an error-cognition domain,we can determine the degree of relative importance of the error-cognition from the cross correlation between domain factors,and then the association properties of error-cognition can be solved.

(ii) We can establish a design information domain from analyzing design factors of information features.By the same method of error-cognition,the association properties of the design information feature can be solved.

(iii) We can establish the design solution process from error-cognition to information feature mapping.We also need to determine the objective constraints of design information features.

(iv) In the case of task interface design of typical display systems,we can extract error factors based on the monitoring interface tasks and then obtain the solution process from error-cognition to information feature mapping from extracted error factors.

3.Error-cognition factors and design information factors

3.1 Error factors of information interaction interface

In radar situation interface,for example,an aviation information display,there are several possible tasks to be executed,such as monitoring status data,querying task information,monitoring threat,security state information,and so on.Display interfaces of complex information system display navigation,situation pictures,status data,and other information.The monitoring task is likely to be performed,including plan creating,state monitoring,and burst scheduling.We can classify the monitoring interfacial task either by abrupt events and common tasks,or by the order in which tasks are performed.Thus,as shown in Table 1,we list the monitoring interface tasks and corresponding error factors to extract the error characterization of a monitoring interface of a complex system.

Table 1 Characterization of error factor of monitoring interface task [10]

3.2 Information features of radar situation interface

As analysis object of design information characteristic,monitoring task interface of some kind of navigation war is divided into four parts based on different tasks: radar situation interface,weapon mounting interface,multi-sensor interface,and flight data display interface,including navigation,situation charts,state data,alarm reminder,and other information display.There are four processes in monitoring tasks which may be performed such as monitoring/detection,state query,response planning,and response execution.The information content displayed in the different monitoring task interfaces will be regarded as the content of main information in searching,reading,recognition,judging selection,and decision making.The radar situation interface mainly displays the information of the aircraft radar area including the appearance of the target,the database calling,the different aircraft symbols in the range,the attacked target display,the driving route,and other information.The weapon mounting interface mainly displays the selection of weapons,the display,the launch selection,the current state of selection,the weapon programming,etc.The multisensor display interface mainly displays radar setting and selection,satellite map information,radar proportional rendering,and other information.The flight data display interface mainly displays the machmeter,the forecast speed,the attack angle,the height,the horizontal meter calibration,fuel and other indicators.

4.Solution process from error-cognition to information feature mapping

4.1 Analysis on the association properties of error-cognition

First,we need to analyze the association properties of the error-cognition domain.LetRE0={re1,re2,···,rem1} be the screened error-cognition set,whererei(i=1,2,···,m1)denotes the error factor.Let us assume thatrei,rej∈RE0.

Since the corresponding processes of cognitive information are different from one another,the same error factors do not have corresponding inclusion and crossing relations.For instance,take the case of misreading caused by visual restrictions or unreasonable matching of information.These two conditions do not have the properties of inclusiveness or intersection [28].They belong to error factors from different perspectives,and can be explained as errors resulting from different internal reasons.Therefore,the relationsreiandrejare both considered to be independent of each other.Therefore,if the error factors included inreiare not related to the error factors included inrej,we make sure thatreiandrejare independent from each other.

With respect to the existing correlation between error and cognition,when further screening the factors in the error-cognition domain,selections must be made among error-cognition factors with mutual exclusion [29].The choice for the appropriate factors must be made based on the sequence of the degrees of importance of the factors.

After screening,the error-cognition set can be denoted as={re1,re2,···,rep},whererei(i=1,2,···,p) represents the error-cognition factor.They can be refined with a new sorting process based on their degrees of importance and some unimportant ones will be deleted at the same time.

In this paper,the method of analytic network process(ANP) is employed to determine the degree of importance between error and cognition [30].This procedure of using ANP is summarized as follows:

Step 1Without considering the correlation between error and cognition,the weights of error-cognition are determined.A numerical sequence of 1 to 9 is adopted for notation,and a normalization is conducted to obtain the error-cognition weight vectorwr=(w1,w2,···,wp)T,where

Step 2Determine the cross correlation between the error and cognition.A matrixEis used to describe such cross correlation.1-3-9 is employed to express the weak,the intermediate,and the strong cooperative relations between error and cognition,respectively;(-1)-(-3)-(-9)is adopted to denote the weak,the intermediate,and the strong conflict relations between error and cognition.0 denotes the irrelevance of error-cognition,whereeij=eji，eii=9.

The correlation information for each involved errorcognition factor can be calculated by analyzing the crosscorrelation matrixE.Take the error-cognition factorreias an example.

(i) Positive correlation numberRpidenotes the number of error-cognition factors positively related torei.

(ii) Negative correlation numberRnidenotes the number of error-cognition factors negatively related torei.

(iii) Degree of positive correlationRspidenotes the total sum of the correlation degrees of error-cognition factors that are positively related torei.

(iv) Degree of negative correlationRsnidenotes the total sum of the correlation degrees of error-cognition factors that are negatively related torei.

(v) Average degree of correlationdenotes the average value of the correlation degrees of error-cognition factors that are related torei.is represented by

The information above is fundamental to determining the degree of relative importance of the error-cognition.It is also used to select the values of error-cognition that have the same degree of importance.The method to identify values of error-cognition with identical degrees of importance is as follows:

(i) First,find out the subset of error-cognition forRni=0 (i=1,2,···,p).Then sort the values of the errorcognitionRspiin each set in a descending order and make selections.

(ii) If the result of the last step does not yield the desired values,increase the value ofRniby 1.Find out the corresponding subset of error-cognition,and select the error-cognition factor which has a large value forRpiand a large value for.The value of error-cognition should also have a negative correlation with,indicating a low degree of importance of error-cognition.

(iii) If the result of the last step does not satisfy all of the requirements,then return to the previous step and repeat till the requirements are satisfied.

Step 3Determine the relationship among the degrees of importance of the error-cognition.The matrixWris used to describe this relationship among the degrees of importance of the error-cognition.Takereias an example.Based on the consideration that there is a correlation betweenreiand error-cognition,the degrees of relative importance of the other error-cognition factors with respect toreiare determined to obtain a matrixWi.

Step 4Determine the degree of importance for the error-cognition.Vectoris used to denote the degree of importance for the error-cognition as

Step 5Determine the final error-cognition.According to the sequence of the degree of importance of the error-cognition,unimportant factors of error-cognition are removed.When the difference in the degree of importance of the error-cognition is not outstanding,the decision method in (2) is employed to make decisions.Then calculate the final error-cognition represented byRE={re1,re2,···,rem};and the vector denoting the degree of importance of error factors aswE=(w1,w1,···,wm)T,which corresponds to the normalized error-cognition set.

4.2 Analysis of the mutual correlation properties of design information features

Operators can divide the monitoring tasks (Taski) into four processes.They are surveillance/discovery,status inquiry,response planning,and response execution.Each process executes different tasks such as information search,information recognition and reading,information identification,and information selection and judgment.Each of these tasks is associated with the relevant design information steps from 1 ton: Design (i1'),Design(i2'),…,Design(in').LetCQ0={cq1,cq2,···,} be the error-cognition set,wherecqi(i=1,2,···,n1) represents the error factor,then for eachcqi,we havecqj∈CQ0(j=1,2,···,n1).

An interface for monitoring complex information systems displays numerous complicated information items.Such a display may sometimes not be systematic and may even contain a certain level of redundancy.Thus,it may become necessary to arrange,filter,and analyze the designed information features.There are three kinds of relations which exist betweencqiandcqj.They are inclusion,intersection,and independence.The design information set after screening is denoted as={cq1,cq2,···,cqp},where each elementcqi(i=1,2,···,p) is an information feature.During the design process,after removing redundancies,these features may contain relations such as mutual exclusion,irrelevance,mutual conflict,and mutual collaboration.

The ANP method is next adopted to determine the degree of importance of the features for information design.First,we determine the weight of the information features,as well as the mutual relations among them to obtain the mutual correlation matrixQ:

The correlation information of each relevant feature can be obtained by analyzing the mutual correlation matrixQ.Identical to the method used in the error-cognition set,taking the information featurecqias an example,the positive correlation numberCpi,the negative correlation numberCni,the positive correlation degreeCspi,the negative correlation degreeCsni,and the average correlation degreecan be obtained.

In this way,we can determine the importance of the degree of relationships ofWcfrom the information features.Take the information featurecqias an example.The ANP method is employed to obtain the vector of the relative degree of importance of the information features.This is represented bywi=(w1i,w2i,···,wii,···,wpi)T,in whichWe can use this to solve the relation matrixWcto determine the degree of importance of the information features:

Finally,from (5) the degree of importance of the design informationw′q=Wc×wc=(wq1,wq2,···,wqp)Tcan be determined.The eventual design informationCQ={cq1,cq2,···,cqn} and the corresponding vector for the degree of importance of the design information (after normalization) can be written aswQ=(w1,w2,···,wn)T.

4.3 Mapping from error-cognition to design information

The relationship between the degrees of importance of the error-cognition and the design information is denoted byWqe.When determining this relationship,we suppose that each design information is irrelevant from one another,with respect to every item of the error factors.Then we compare the design information with each other,and the relationship matrix to obtain the relevant error factor.Subsequently the AHP method is used to find solutions to the vector of the degree of importance for each design information for that error factor.This is represented aswqe=(w1i,w2i,…,wii,…,wpi)T.Regarding the vector of the degree of importance for each design information of each error factor,the relation matrixWqeof the error-cognition and the design information is constructed as follows:

From the matricesWqeandWq,we obtain the relationship matrix between the error-cognition and the design information,while considering the correlation among the design information as follows:

Comprehensively,considering the influence of degree of importance of error-cognition on design information,the vector of the degree of importance of design information is obtained as follows:

4.4 Objective constraints of interface layout

When optimizing the contents of information presentation,in addition to considering the degrees of importance of the features of design information,it is also necessary to consider the rationality of information features in the interface layout.The interaction interface includes all kinds of information fragments,such as symbols,indicators,line symbols,and characters,which are assembled to become an information set from the information flow.Demir et al.stated information structure is the form of information assembled [31].Thus,in this paper,from the point of information instruction,combined with 10 attributes of interacting visual display from [7],we can define information blocks,functional divisions,task divisions and visual flows as design information features of interface layout.According to the objective programming approach,we establish a mathematical model for the optimization and decision-making for the design information features in the interface layout [32].We determine the objective constraints of design information features from several aspects as follows:

(i) Information capacity inside the interface area.The information units related graphics could be assembled as an information block.For example,different tactical models,such as attacking,defense,and expansive,could be combined as one closely arranged information unit.In the monitoring task interface,this information block could be combined as Unit A={x1,x2,···,xn}.There are BlockA1,BlockA2,···,BlockAn,which could be formed into an information (Info) unit,that is Info={A1,A2,···,An}.According to the characteristics of information interaction systems,it is known that as the complication and size of information increases,so does the difficulty of the information layout.Hence,the quantity of information inside the interface,namely the information capacity,is a factor to be considered for design optimization.The amount of information can be quantified by a bit [33].With respect to the probability that the information occurs in the interface area,the capacity of different interface areas can be computed as follows:

To serve as a constraint,we set the probability of events that can possibly happen during the corresponding execution of a task for all kinds of information features.Then we calculate the average information quantity of these information features.

(ii) Visual flow of interface information.The visual behavior of operators forms a certain visual flow in the interface.This is the second imortant factor for design optimization.According to visual behavior rules and eye tracking,the visual flow mainly includes sensitivity of stimulus,guidance of physical location,edge effect and the gaze-saccade process [34].

(iii) The degree of relevance of information functions.With respect to the difference between functions,an internal graph-element relation has been formed among the information.This will form information blocks that are relatively concentrated in the interface.This is the third factor for design optimization.Based on information blocks,we need to consider the functional correlation among information blocks.For examples,the speed controlling area is comprised of airspeed,height,heading,etc.The weapons mounting selective area is comprised of class,selection marking,etc.The function division area could be designated as Unit B={y1,y2,…,yn}.There are AreaB1,AreaB2,···,AreaAn,which could be formed as function area (Func) unit,that is Func={B1,B2,···,Bn}.

(iv) Tasks partitioned according to their degrees of importance.It is also necessary to consider the degrees of importance of the tasks in the interface layout.For different combinations of tasks,different task partitions are required.Hence,the task level is the most crucial factor in the interface layout.Based on the function division,we also need to consider the operator’s monitoring task.The monitoring task could be divided into different areas according to different processing of monitoring/detection,state query,response planning and response execution.There is a direct connection between the task division and the function division,including fuel gage searching,indication radar setting and selection,weapon plan and bomb mode selection.Therefore,the task division area could be indicated as Unit C={P1,P2,···,Pn}.

4.5 Mathematical model and modeling procedures of objective programming

Combining the aforementioned analysis,we identify four constraints: information capacity,visual flow,graph-element relations,and task level.They are categorized into quantitative constraints (information capacity) and qualitative constraints (visual flow,graph-element relations,and task level).The weighted multi-objective programming method is adopted to obtain the optimal information feature set for design optimization.The general mathematical model of objective programming can be written as follows:

where ωi(i=1,2,···,m) stands for the weight of an objective,represents the negative deviation to theith objective,represents the positive deviation to theith objective,xjis a 0-1 variable meaning thejth (j=1,2,···,n)feature of the design information,wDjstands for the degree of importance for thejth feature of the design information,rijrepresents thejth feature of the design information that uses theith quantitative constraint,Ristands for theith quantitative constraint,andwijrepresents thejth feature of the design information with respect to the weight of theith qualitative constraint objective.

5.Case of task interface design of typical avionics display systems

5.1 Error factor and extraction of information features of a typical avionics display interface

In order to verify the reasonability of our design method for mapping from error-cognition to design information,we intend to take the surveillance task interface of a complex information system as an example.This paper takes information features of the surveillance task interface of an avionics display system for analysis (as depicted in Fig.2),in which the error factors are extracted based on the monitoring interface tasks and corresponding error factors (see Table 1) as follows:

Fig.2 Monitoring tasks

(i) Visual restriction– omission (re1);

(ii) Visual mistake– misreading/misjudgment (re2);

(iii) Visual interference– ignorance (re3);

(iv) Attention shifting and distraction– miss (re4);

(v) Cognitive deviation– misunderstanding (re5);

(vi) Unreasonable matching– confusion (re6).

With respect to six items of error factors,the designers target the monitoring tasks executed by the operators,and combine them with features from design information to determine seven items from the design information features as follows:

(i) Location of an information feature (cq1);

(ii) Visible range of an information feature (cq2);

(iii) Spacing of information features (cq3);

(iv) Intensity of visual attention of an information symbol (cq4);

(v) Recognition of an information icon (cq5);

(vi) Degree of conciseness of an information icon (cq6);

(vii) Differences between information icons (cq7).

In the following we focus on six items of error factors from these typical error-cognition sets and seven items of design information features extracted by surveillance tasks executed by operators.The analysis will be conducted one by one with respect to the reaction chain.The optimizations of the intensity of visual attention are performed mainly with respect to the line symbol,the character symbol,and a combination of the line and character symbols.We also consider the significance,such as the allocation of colors and line frame symbols which affect the intensity of the visual attention.The optimization of the recognition and the distinction of information graphic symbols are mainly from the points of understanding,degree of cognition,and similarity of graphic symbols.The relevant symbols of design information are shown in Fig.3.

Fig.3 Information symbols

With respect to the characterization methods of design factors for interface layout,the information structure of the interface can be extracted via abstract layouts [35].As a result,a layout analysis of the original interface results in the output of the layout abstracts of each sub-interface as depicted in Fig.4.

Fig.4 Information layout of a monitoring task interface

It can be seen from the information structure of the interface that this layout can be partitioned into four visual districts,and these districts are divided equally in such a way that they lack concern for visual searching behaviors.Those to be considered for the factors of information layouts are the locations of information features(cq1),the visible ranges of information features (cq2),and the intervals of the information features (cq3).

5.2 Mapping from error-cognition to design information

With respect to the mapping method from error-cognition to the features of design information,the procedure to obtain the optimized design information is set as follows:

Step 1Determine the relative weights of the error factors for the error-cognition.Suppose the error factors denoted by the numerical sequence of 1 to 9 are irrelevant.Then compare five items of error factors to get the solution such that (re1,re2,re3,re4,re5,re6)=(3,7,5,3,9,1).After normalization,we obtain the relative weighted vector of error factorwr,wherewr=[0.107,0.250,0.179,0.107,0.321,0.036]T.

Step 2DetermineWr,the relationship matrix of the degrees of importance of the error factors:

Step 3Determine the relationship matrix of the degrees of importance between the error factors and the features of design information:

Step 4Determine the relationship matrix of the degrees of importance of the features of design information:

Step 5Calculate the weight of an error factorwE:

Step 6CalculatewQ,the vector of the degrees of importance for the features of design information:

Step 7Consider the quantitative objective constraints.For information features,information capacity is regarded as the quantitative constraint.Generally,in multi-dimensional comprehensive conditions,the transmission rate can be enhanced.However,they will always be below 10 bit/s.This is the limit of the human information transmission rate,that is,information transmitted above this rate cannot be fully comprehended.In a complex information interface,the transmission rate of information is influenced by multiple factors such as the size of graphical symbols,color,position,and connecting line symbols.These factors are called stimulus dimensions[36].Thus,the information transmission rate which is optimal for operators to comprehend is not a constant.It changes with the features and the dimensions of the different graphical information symbols and the complexity of the task to be executed.

Hence,for different tasks to be executed by operators,the visual cognition processes from monitoring/discovery,status inquiry,and response planning to response execution can take 30 s to 180 s.This may sometimes lead to situations where it is possible to miss the optimal time for task execution.As a result,we can say that the information capacity to simultaneously perform information processing in an information interface should be within 300 bits to 1 800 bits.If this capacity is exceeded,it becomes hard for operators to execute an information task.In this case,seven information features correspond to the task processes that need to be executed;they arecq1,cq2,cq3,cq4,cq5,cq6,andcq7respectively (see Table 2).With respect to the computational formula for the average quantity of informationthe computation can be performed as shown in Table 3.

Table 2 Probabilities of occurrence pi of possible executed tasks corresponding to the information features

Table 3 Probabilities of occurrence of possible executed tasks corresponding to the information features

The numerical value ofcq1is calculated as

The size of the information capacity as displayed in Table 3 does not take into consideration factors such as the quantity of information features of the same category.The quantity of different information features in the monitoring task interface is approximately from 1 to 100.For instance,the number of characters is between 20 and 80,and the number of graphical symbols is generally between 3 and 15.Therefore,the information from each of the seven categories of information features is below 200 bits and the total information capacity of all the categories is between 300 bits and 1 800 bits.

Taking the correlation between the information features into consideration,the capacity of information featuresvcan be expressed as follows:

Step 8Consider the qualitative objective constraints.We consider three objective constraints of information features.When carrying out interface layouts for design information,these constraints are considered from the point of the visual flow,the graph-element relations,and the task.For sufficient consideration of the optimization of design information with respect to the interface layouts,it is necessary to quantify the qualitative objectives.The method of “pairwise comparison” is used to compare seven items of information features.Next we obtain the weighted vector of each design information feature for the information capacity,visual flow,graph-element relations,and task level considered in the interface layouts.They are denoted bywQ,wR,andwT,respectively.

Step 9Determine the relative weights of the objective constraints.Results calculated by “pairwise comparison”are shown in Table 4,where “RMC” represents the objective mapping from error-cognition to the design information.

Table 4 Relative weight of various objective constraints

Step 10The weighted multi-objective programming model is established by using the results of the abovementioned nine steps.The specific planning model is presented as follows:

With respect to the solution process of planning by Lingo,the solutions tocq1,cq2,···,cq7can be obtained as follows:cq1=0.214 0,cq2=3.182 0,cq3=0,cq4=0.625 3,cq5=2.166 7,cq6=0,cq7=0.

With respect to the results of multiple objective planning,four major information features,cq1(the location of information feature),cq2(the visible range of information feature),cq4(the intensity of visual attention of information symbols feature),andcq5(the recognition property of information graphic symbols feature) are regarded as the main objects of design optimization for this monitoring task interface.

5.3 Information display and interface design according to results of multi-objective planning

According to visual behavioral characteristics and visual searching model [34,36]，vision is directed from left to right,from up to down,and from the upper left,the upper right,the lower left to the lower right.The distribution of interface layouts is shown in Fig.5,including the main task execution area (optimal visual zone),task execution reserve (secondary visual zone) and task execution reserve (third visual zone).The layout should maximize the task execution area and hide non-execution areas.It can adjust different information block displays in respect to position and visual range.

Fig.5 Information optimized layout of monitoring task interface

According to extraction of the error factors,analysis of visual behavior,the reaction chain of error factors and information features,and the results of multiple objectives planning,the avionics interface display can be optimized via the information symbols design and the information block layout.Optimized mode interface display is shown in Fig.6.

Fig.6 Optimized mode interface display

6.Conclusions

This paper innovatively establishes the correlations among error factors,visual cognition,and design information.We propose that the interface design of complex information systems can directly benefit from the information derived from the sources of task failures.It also opens up a new shortcut towards the study of the design method of complex information interfaces,and builds up this design method from error-cognition to the mapping of information features.

With respect to the design method of complex information interfaces,we explore a use-case for the design of a typical naval warfare display system.Error factors such as omission,misreading/misjudgment,and ignorance,are extracted along with the description of the relevant information features of tasks for the operators.Through the solution process of mapping,we identify four significant areas of information display design that can be improved in the monitoring task interface.These results verify the validity of the design method for information interfaces based on the mechanism of error-cognition.

The features of design information,such as locations of information characteristics,visual range,separation distance,and visual attention intensity of symbols,are determined in accordance with the reaction chain of error factor-information characteristics.We find a solution to this problem by mapping from error-cognition to the information features.Based on the results,we also propose an optimization design scheme for the monitoring task interface.