A computer-aided usability testing tool for in-vehicle infotainment systems. (July 2017)
- Record Type:
- Journal Article
- Title:
- A computer-aided usability testing tool for in-vehicle infotainment systems. (July 2017)
- Main Title:
- A computer-aided usability testing tool for in-vehicle infotainment systems
- Authors:
- Feng, Fred
Liu, Yili
Chen, Yifan - Abstract:
- Highlights: 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. Abstract: 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 aHighlights: 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. Abstract: 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. … (more)
- Is Part Of:
- Computers & industrial engineering. Volume 109(2017)
- Journal:
- Computers & industrial engineering
- Issue:
- Volume 109(2017)
- Issue Display:
- Volume 109, Issue 2017 (2017)
- Year:
- 2017
- Volume:
- 109
- Issue:
- 2017
- Issue Sort Value:
- 2017-0109-2017-0000
- Page Start:
- 313
- Page End:
- 324
- Publication Date:
- 2017-07
- Subjects:
- Computer-aided engineering -- Human factors -- Usability testing -- Human performance modeling -- In-vehicle infotainment system -- Queuing network-model human processor
Engineering -- Data processing -- Periodicals
Industrial engineering -- Periodicals
620.00285 - Journal URLs:
- http://www.sciencedirect.com/science/journal/03608352 ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.cie.2017.05.019 ↗
- Languages:
- English
- ISSNs:
- 0360-8352
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 3394.713000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 618.xml