Development of an extended keystroke level model for predicting the visual demand of in-vehicle interfaces - thesis submitted to the University of Nottingham for the degree of Doctor of Philosophy

A variety of human-computer interaction and human factors methods have been employed to assess the potential distraction of IVIS task engagement. The occlusion technique is one such surrogate, where task performance is assessed under intermittent vision conditions. The technique evaluates how visually demanding a task is, mimicking the behaviour of glancing to and from the forward road scene when driving and performing IVIS tasks. An evaluation of the technique confirmed its validity, but assessment of the method through user-trials based on measures of human performance is problematic. The keystroke-level model (KLM), which predicts task times for error-free performance by expert users in routine tasks, provides and alternative quantitative assessment method to user-trials. Tasks are decomposed into their most primitive actions, termed operators, which are associated with empirically assessed time values. These values are then summed to predict performance times. An evaluation of the technique in a vehicle environment is presented: twelve participants performed eleven tasks on two in-car entertainment systems, and task times were compared with KLM predictions. Theresults demonstrated that the technique remains valid beyond its original, desktop computing-based context. However the traditional KLM predicts static task time only, and an extended procedure is required to consider occluded task performance. Two studies are presented, seeking to extend the KLM in order to model task performance under the interrupted vision conditions of occlusion trials. Both studies showed that the extended KLM approach provides valid predictions of occlusion methods, with error rates generally within 20% of observed values. Subsequently, a case study is presentedto demonstrate the reliability of the technique.

• Corporate Authors:

  UNIVERSITY OF NOTTINGHAM

  UNIVERSITY PARK
  NOTTINGHAM,   United Kingdom  NG7 2RD
• Authors:
  • PETTITT, M
• Publication Date: 2007

Language

• English

Media Info

• Pagination: unpaginated

Subject/Index Terms

• TRT Terms: Attention; Distraction; Driver information systems; Ergonomics; Hazards; Human factors; Intelligent transportation systems; Interfaces; Internet; Methodology; Obstructions (Navigation); Prevention; Prototypes; Route guidance; Technology; Theses; Vehicle compartments; Vehicle interiors; Vision
• Uncontrolled Terms: Infotainment
• Subject Areas: Operations and Traffic Management; I83: Accidents and the Human Factor; I91: Vehicle Design and Safety;

Filing Info

• Accession Number: 01166032
• Record Type: Publication
• Source Agency: TRL
• Files: ITRD
• Created Date: Aug 26 2010 8:39AM