کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
5127690 1489057 2017 12 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
A computer-aided usability testing tool for in-vehicle infotainment systems
موضوعات مرتبط
مهندسی و علوم پایه سایر رشته های مهندسی مهندسی صنعتی و تولید
پیش نمایش صفحه اول مقاله
A computer-aided usability testing tool for in-vehicle infotainment systems
چکیده انگلیسی


- A software for usability testing of in-vehicle infotainment systems was developed.
- A digital driver model was built based on Queuing Network-Model Human Processor.
- The software aims to predict the usability including eyes off road time.
- Validations show the software could provide outputs similar to the empirical data.

This paper describes the development of a computer-aided engineering (CAE) software toolkit for designers of in-vehicle infotainment systems to predict and benchmark the system usability, such as task completion time, eye glance behaviors, and mental workload. A digital driver model was developed based on the task-independent cognitive architecture of QN-MHP (Queuing Network-Model Human Processor). At the front end of the software a graphical user interface (GUI) was developed that allows designers to create digital mockups of the designs and simulate drivers performing secondary tasks while steering a vehicle. To validate the software outputs, an experiment using human drivers was conducted on a fix-based driving simulator with a radio-tuning task as a test case. Three typical in-vehicle infotainment systems that have the function of radio tuning were investigated (a touch screen, physical buttons, and a knob). The results show that the software was able to generate task completion time, total eyes-off-road time, and mental workload estimates that were similar to the empirical data. The software toolkit has the potential to be a supplemental tool for designers to explore a larger design space and address usability issues at the early design stages with lower cost in time and manpower.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Computers & Industrial Engineering - Volume 109, July 2017, Pages 313-324
نویسندگان
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