Impact of human-computer interaction tasks in smart cockpit on user experience satisfaction
Open Access
Article
Conference Proceedings
Authors: Tianxiong Wang, Yuanyuan Wang, Mengmeng Xu, Long Liu, Jing Chen
Abstract: In order to help automotive interior and exterior decoration and human-computer interaction interface designers effectively avoid the risk of poor interface usability and further enhance the user experience, we quantify the complexity of human-computer interaction behaviors in smart cars, and explore the specific task indicators and weight distributions affecting the complexity of human-computer interaction inside the smart cockpit, as well as propose a methodology for measuring the complexity of human-computer interaction tasks in smart cars. First of all, by adopting the method of questionnaire survey, an index system consisting of eight evaluation indexes, namely, the complexity of logical structure, the complexity of interface design elements, the complexity of information channel transmission method, the number of actions, the complexity of management interface information, the complexity of human-computer interaction inputs, the level of knowledge and cognitive volume required for human-computer interaction, and the complexity of the layout of human-computer interaction digital interfaces, has been established. Secondly, we use the weight calculation method that combines Fuzzy Analytic Hierarchy Process (FAHP) and Entropy Weight Method(EWM) to determine the factors that have the most influence on the complexity of human-computer interaction behaviors of the smart cockpit. Finally, human-computer interaction behaviors with high complexity are calculated and design optimization recommendations are made. The evaluation results show that the complexity of the human-computer interaction digital interface layout in the cockpit (X8), the complexity of the logical structure (X1), and the level of knowledge and cognition required for human-computer interaction (X7) have a greater impact on the complexity of human-computer interaction tasks in the vehicle. Meanwhile, navigation operation, video and audio playback and music selection switching are human-computer interaction tasks with higher complexity and also need to be explored by designers focusing on them. The method can help designers avoid the risk of excessive design complexity and high user learning costs, and can assist designers to intervene in advance of design problems related to the above indicators.
Keywords: Cmplexity test, Human-computer interaction, Entropy Weight Method, Smart cockpit
DOI: 10.54941/ahfe1005434
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