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Task-Capability Interface

The most common criticisms of past models of driver behaviour include that they do not produce testable hypotheses and that they are desaiptive rather than predictive (e.g., Michon, 1989 Ranney, 1994 Rothengatter, 2002 Carsten, 2009 also Chapter 3 [Carsten]). In an attempt to correct this situation. Fuller (2000) proposed the model of task-capability interface (TCI) as a representation of the driving task... [Pg.36]

FIGURE 4.1 The task-capability interface model. (From Fuller, R. et al. 2008a. The Conditions for Inappropriate High Speed—A Review of the Research Literature from 1995 to 2006. London Department for Transport. With permission.)... [Pg.37]

Fuller, R. 2000. The task-capability interface model of the driving process. Recherche Transports Securite, 66, 47-57. [Pg.107]

Host computers. These are the most powerful computers in the system, capable of performing func tions not normally available in other units. They act as the arbitrator unit to route internodal communications. An operator interface is supported and various peripheral devices are coordinated. Computationally intensive tasks, such as optimization or advanced control strategies, are processed here. [Pg.771]

From the traditional HF/E perspective, error is seen as a consequence of a mismatch between the demands of a task and the physical and mental capabilities of an individual or an operating team. An extended version of this perspective was described in Chapter 1, Section 1.7. The basic approach of HF/E is to reduce the likelihood of error by the application of design principles and standards to match human capabilities and task demands. These encompass the physical environment (e.g., heat, lighting, vibration), and the design of the workplace together with display and control elements of the human-machine interface. Examples of the approach are given in Wilson and Corlett (1990) and Salvendy (1987). [Pg.55]

Current Development. Following success of the prototype IPU a second more comprehensive facility was commissioned. This is capable of up to four pumps of mixed peristalitic or diaphragm types, each linked to specific feed vessels on individual balances. The whole is interfaced to an IBM AT computer (see Figure 7) which in addition to Intelligent liquid additions, has the capacity to absorb modules from the work on temperature control and stirring in a full multi-tasking computer-assisted system, as mentioned above. [Pg.446]

Sensitivity and complexity represent challenges for ATR spectroscopy of catalytic solid liquid interfaces. The spectra of the solid liquid interface recorded by ATR can comprise signals from dissolved species, adsorbed species, reactants, reaction intermediates, products, and spectators. It is difficult to discriminate between the various species, and it is therefore often necessary to apply additional specialized techniques. If the system under investigation responds reversibly to a periodic stimulation such as a concentration modulation, then a PSD can be applied, which markedly enhances sensitivity. Furthermore, the method discriminates between species that are affected by the stimulation and those that are not, and it therefore introduces some selectivity. This capability is useful for discrimination between spectator species and those relevant to the catalysis. As with any vibrational spectroscopy, the task of identification of a species on the basis of its vibrational spectrum can be difficult, possibly requiring an assist from quantum chemical calculations. [Pg.280]

In this work, we have approaehed the understanding of proton transport with two tasks. In the first task, deseribed above, we have sought to identify the moleeular-level stmeture of PFSA membranes and their relevant interfaees as a funetion of water content and polymer architecture. In the second task, described in this Section, we explain our efforts to model and quantify proton transport in these membranes and interfaces and their dependence on water content and polymer architecture. As in the task I, the tool employed is molecular dynamics (MD) simulation. A non-reactive algorithm is sufficient to generate the morphology of the membrane and its interfaces. It is also capable of providing some information about transport in the system such as diffusivities of water and the vehicular component of the proton diffusivity. Moreover, analysis of the hydration of hydronium ion provides indirect information about the structural component of proton diffusion, but a direct measure of the total proton diffusivity is beyond the capabilities of a non-reactive MD simulation. Therefore, in the task II, we develop and implement a reactive molecular dynamics algorithm that will lead to direct measurement of the total proton diffusivity. As the work is an active field, we report the work to date. [Pg.172]


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