Genetic Optimization Design And Evaluation Of Excavator Information Interface Based On User Need

With the continuous development of information technology and artificial intelligence,the interactive interface of excavators has gradually evolved from traditional button-based types to touch screen-based ones.By adopting a touch-based information interface,excavator drivers can better meet their cognitive and operational needs for intelligence,precision,and efficiency.However,due to the constant upgrading of excavator systems and changes in user requirements,the excavator interface needs to integrate increasingly more functions and information.Currently,the problem of redundant and disordered information in excavator interface urgently needs to be solved.This study aims to focus on user needs and carry out research on interface optimization methods and evaluation systems to address the sore points of the existing excavator information interface.Firstly,through questionnaire surveys,user interviews,and user experience map analysis of target user characteristics,user needs were obtained and the importance degree of user needs was analyzed using the KANO model.Then,by establishing a mapping relationship between user needs and design requirements,a QFD quality house model was constructed to determine the priority of design requirements and establish the optimization design objectives of the excavator information interface.Secondly,the main functions of the information interface were extracted based on interface function analysis,and reasonable classification was conducted.On this basis,the design genes of the interface were extracted.The fitness function was improved based on the weight of design requirements,and an optimization model based on interactive genetic algorithm was established to generate the optimal design gene combination.At the same time,combining common interface layout forms,multiple different interface layout schemes were generated,and eye movement experiments were conducted.The entropy weight method and grey correlation analysis method were used to rank the optimization of each layout scheme to obtain the optimal interface layout scheme.Finally,based on the design objectives,this study further optimized the design scheme of the excavator information interface.Through task performance evaluation,physiological experiments evaluation,and subjective evaluation of NASA-TLX cognitive load,the original and optimized design schemes were comprehensively evaluated to verify the effectiveness of the optimization design scheme and the feasibility of the genetic optimization design method.This study proposes reasonable optimization design objectives based on KANO-QFD excavator information interface design research.Meanwhile,the optimization design method based on interactive genetic algorithm and eye tracking technology improves the quality and efficiency of the optimization design,providing a reference value for the information interface design research of engineering vehicles such as excavators.