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Research On Design Of Task-centric In-vehicle Adaptive Human-Computer Interface

Posted on:2018-04-18Degree:DoctorType:Dissertation
Country:ChinaCandidate:X HanFull Text:PDF
GTID:1362330623954318Subject:Mechanical engineering
Abstract/Summary:PDF Full Text Request
To take participate in IT based warfare,modern military armed vehicles are usually required to deal with large amount of information related to environment and battle tasks.These information is needed to be transformed into battle decision by operators as per humancomputer interface,which not only increase pressure on operators,but also lead to a decision delay.To improve decision efficiency,military in-vehicle human-computer interface is required to reduce useless information depends on operators' interactive requirements,and provides as much decision support as possible to facilitate operators' decision.As a hot research topic,Adaptive Human-Computer Interface(AHCI)is seen as a viable option and had been widely applied in individualization service.Although it had been applied in civil in-vehicle interface,how to utilize it in military interface still remains much problems.Considering the characteristics of “task-centric” contained in military in-vehicle humancomputer interface,it is required to combine “task-centric” and design principle of “operatororiented” when adding adaptive behavior to the interface to achieve win-win for human and battle task.Since the key point of design is when and how to present an adaptive interface,this thesis specially focus on requirement of military human-computer interaction task,performing research for AHCI design based on characteristics of task-centric.Contents of this thesis include forming of conceptual architecture,studying task and operators based dual trigger factors,providing decision support function,analyzing information availability based on decision making thought,and forming visualized design prototype based on the aforementioned theories.An experiment is finally performed to validate the proposed method.The main purposes of this thesis are reducing operators' cognitive load,increasing task performance,realizing dual adaptation for both task variation and operator's individual difference,and facilitating the application of the proposed method in such similar in-vehicle human-computer interfaces.The detailed content can be concluded as:(1)Research on conceptual architecture of in-vehicle AHCI based on the principle of task-centric.To solve the current problem related to how to complete a specific complex task with AHCI,with a military in-vehicle human-computer interface,this thesis firstly clarifies its display,functional and task requirements,then propose task centralization based in-vehicle AHCI conceptual architecture.The key point of this architecture is when treating task performance as the core target,taking operators' individual characteristics and task context into consideration to satisfy requirements on interface display.The theoretical architecture also provide the foundation for upcoming researches.(2)Research on displays of assistant decision-making task information.To reduce the amount of brain work caused by fundamental information,this thesis study the data processing in a special battle situation that object is undertaking threatens from both ground and air.Fuzzy optimum selection is firstly performed to evaluate threat degree.Rough set method is then adopted for plan selection,and assistant task information is finally provided to save operator from large amount of task-related information.The main purpose of this study is to provide a foundation for AHCI decision-making support function.(3)Research for user categorization based on decision-making characteritics analysis.Since decision-making tasks are always involved into task-centric human-computer interaction,and different operators characteristics may lead to various decisions,previous AHCI design may lead to maladjustment or over adjustment and even confusion due to lack of researching for operators' decision characteristics.This thesis combines general decisionmaking style(GDMS)and subjective evaluation in risk preference to perform research for individual decision-making characteristics in battle decision environment,and the relationship between GDMS and risk performance is also studied to categorize operators based on a war-simulation human-computer interaction experiment in LabVIEW.The purpose of this study is to provide a foundation for AHCI adaptive trigger mechanism.(4)Research on information availability for various task context and user categories.It is well admitted that redundancy information may interfere decision,but current AHCI seldom consider availability of information presented in the interface toward individual operator,which will directly affect decision results.To achieve adaptive information presentation based on individual operator's characteristics,by combining subjective evaluation of information availability in a simulated experiment,this thesis firstly discuss the task information requirements of operators for different situations of various decision-making characteristics,then the necessary task information displayed in interface is determined to be provided adaptively.Finally,experimental validation is performed to prove the positive contribution of this method,to provide a foundation for adaptive task information display in AHCI.(5)Research on visualization design and prototype construction of task-centric in-vehicle AHCI.Based on aforementioned researches,this thesis performs visualization design for military AHCI,including working manner of adaptive interface morphing,coding designing of interface elements.What's more,based on human-computer interaction task flow chart of commander,Axure RP is adopted to design commander AHCI prototype,and according to the results obtained in this prototype to provide response for operators under various task circumstances.The purpose is to provide a foundation for similar AHCI development and application.
Keywords/Search Tags:Task-centric, In-vehicle adaptive human-computer interface, Decision-making style, Risk preference, Information availability
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