Pettitt, Michael Andrew
Visual demand evaluation methods for in-vehicle interfaces.
PhD thesis, University of Nottingham.
Advancements in computing technology have been keenly felt in the automotive industry. Novel in-car systems have the potential to substantially improve the safety, efficiency and comfort of the driving experience. However, they must be carefully designed, so their use does not dangerously distract drivers from fundamental, safety-critical driving tasks. Distraction is a well-established causal factor in road accidents. A concern is that the introduction of new in-vehicle technology may increase exposure to distraction, and lead to an increase in distraction-related accidents. The range of systems often termed In-Vehicle Information Systems (IVIS), encompassing navigation and entertainment systems, in-car email and Internet, are the focus of this thesis, since they are commonly associated with long tasks that are not considered fundamentally relevant to driving.
A variety of Human-Computer Interaction (HCI) and Human Factors methods has been employed to assess the potential distraction of IVIS task engagement. These include on-road evaluations, driving simulator studies, and surrogate methods, such as peripheral detection tasks and static task time assessments. The occlusion technique is one such surrogate, where task performance is assessed under intermittent vision conditions. Participants complete a task with 1.5-second vision periods, followed by a period where their vision is occluded. In this way, 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's validity is presented. Sixteen participants performed two tasks on two systems under three conditions: static (full-vision), static (occlusion), and, whilst driving. Results confirmed other research, concluding that the technique is valid. However, the method's assessment through user-trials based on measures of human performance is problematic. Such trials require robust, reliable prototype systems, and can therefore only take place in later design stages. Consequently, the economic effectiveness of the technique is questionable.
The keystroke-level model (KLM), which predicts task times for error-free performance by expert users in routine tasks, provides an 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. Results demonstrate 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. In the first, predictions of occlusion metrics are compared with results from the earlier occlusion assessment. In the second, twelve participants performed three tasks on two IVIS systems under occlusion conditions. Results were subsequently compared with predicted values. Both studies conclude that the extended KLM approach produces valid predictions of occlusion methods, with error rates generally within 20% of observed values, in line with expectations for KLM predictions. Subsequently, a case study is presented, to demonstrate the technique's reliability. The results of an independent occlusion study of two IVIS tasks are compared with predictions made by a HCI expert trained in the application of the extended KLM. Error rates for this study were equally low, leading to the conclusion that the extended KLM appears reliable, though further studies are required.
It is concluded that the extended-KLM technique is a valid, reliable and economical method for assessing the visual demand of IVIS tasks. In contrast to many user-trial methods, the technique can be applied in early design stages. In addition, future work areas are identified, which could serve to further enhance the validity, reliability and economy of the technique. These include, automating the extended KLM procedure with a software tool, and, the development of new cognitive and physical operators, and new assumptions, specific to IVIS and/or occlusion conditions. For example, it will be useful to develop new cognitive operators that consider the time taken to visually reorient to complex displays following occluded periods.
Thesis (University of Nottingham only)
||Human-Computer Interaction, Occlusion, Keystroke Level Model, Human Factors, Driver Distraction
||Q Science > QA Mathematics > QA 75 Electronic computers. Computer science
||UK Campuses > Faculty of Science > School of Computer Science
||27 Mar 2008
||16 Sep 2016 11:54
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