Assessing the Human Factor in Truck Driving

Human factors assessment techniques are commonly applied to a variety of workplaces to examine the nature of operations and how key functions are controlled operationally; however, these tools appear to overlook key aspects of truck driving, particularly the driver’s relationship to the driving experience. The fundamental issue is with the ability to completely decompose truck driving and accurately document the truck drivers working environment will be problematic. Therefore, to demonstrate how a truck driver moves between each series of sub-tasks will require a purpose-built assessment tool that that is both practical and relevant to truck driving

Experimental user interface design toolkit for interaction research (IDTR).

The research reported and discussed in this thesis represents a novel approach to User Interface evaluation and optimisation through cognitive modelling. This is achieved through the development and testing of a toolkit or platform titled Toolkit for Optimisation of Interface System Evolution (TOISE). The research is conducted in two main phases. In phase 1, the Adaptive Control of Thought Rational (ACT-R) cognitive architecture is used to design Simulated Users (SU) models. This allows models of user interaction to be tested on a specific User Interface (UI). In phase 2, an evolutionary algorithm is added and used to evolve and test an optimised solution to User Interface layout based on the original interface design. The thesis presents a technical background, followed by an overview of some applications in their respective fields. The core concepts behind TOISE are introduced through a discussion of the Adaptive Control of Thought “ Rational (ACT-R) architecture with a focus on the ACT-R models that are used to simulate users. The notion of adding a Genetic Algorithm optimiser is introduced and discussed in terms of the feasibility of using simulated users as the basis for automated evaluation to optimise usability. The design and implementation of TOISE is presented and discussed followed by a series of experiments that evaluate the TOISE system. While the research had to address and solve a large number of technical problems the resulting system does demonstrate potential as a platform for automated evaluation and optimisation of user interface layouts. The limitations of the system and the approach are discussed and further work is presented. It is concluded that the research is novel and shows considerable promise in terms of feasibility and potential for optimising layout for enhanced usability

Attentional capture by meaning: A multi-level modelling study

We present a computational study of attentional capture by meaning, based on Barnard et al's key-distractor attentional blink task. We highlight a sequence of models, from an abstract black-box to a structurally detailed white-box model. Each of these models reproduces the major findings from the key-distractor blink task. We argue that such multi-level modelling gives greater confidence in the theoretical position encapsulated by these models