| ©1990, 1995 | section list | 4: The Simple Unstable Vehicle | overview | General Contents |
| Section 4.3 | 4.4 Discussion subsections | Section 5.1 | ||
The first major doubt to raise in respect of the SUV experiment concerns the extent to which it looked likely to achieve its aims at all. One of the ideas was that humans would be able to relate to the task, because it was to some extent familiar; and that this might lead to a transfer of skill from actual bicycle-riding. The fact that no-one managed to ride the SUV at full speed suggests that, for whatever reason, no extensive transfer of skill had taken place. To anyone who had the experience of controlling the SUV simulation, it was apparent that it did not feel like a bicycle. This may have been due to some unrecognised defect in the model itself, or due to the lack of provision of suitable information and feedback for the subject. There were many channels of information and control in real bicycle-riding that were absent from the simulation. These included:
Given that humans could not use their unconscious bicycle-riding skill, the task was likely to involve much learning. The simulation allowed the possibility of concentrating on this knowledge-based kind of performance (in Rasmussen's terminology again) by slowing the simulation down sufficiently to allow time for problem-solving, or conscious thought; but if this was going to be the kind of approach used, there was little point in basing the task on a motor skill. There would be much more obvious ways of studying knowledge-based information processing, if that was what was wanted. But, as discussed in § 1.3, the aim of this study was not to explore the knowledge-based area. Alternatively, it might be more fruitful to study pole-balancing skill, since that relates more closely to work already done, and it seems that pole-balancing would have no disadvantage over the SUV simulation as a human control task for study.
But a greater problem, effectively ruling out pole-balancing along with the SUV control task, is the importance of the psycho-motor level of analysis to these actions. Looking at the last section (§ 4.3), human control of the SUV seems to have much that is difficult to account for with a straightforward cognitive model of control. A full analysis of the SUV control data would have not only to take account of the imperfections in the measurement of human actions, but also to account for the `noise' inherent in the human manual control. A possible approach would be to create a predictive model of the human control actions as a whole, within the tolerances of this noise, along the lines of ones developed in the context of (manual) ship manoeuvring, based on engineering-style approaches (e.g. [136, 139]).
However ship control is not generally considered to be a skill in which fractions of a second are very important. In Sutton & Towill's paper [136], the frequencies of the power spectrum of wheel demands (human and model, compared) lie below 0.15Hz, which is an order of magnitude away from the predominant frequency in our ``DANGLE'' data, which appears to be around 1--2Hz.
If one wanted to take account of response times, a much more complex model would have to be constructed, where the action effected at a particular moment was dependent on the information available at a slightly earlier time. One of the most interesting features of the data from the SUV experiment is that they show little or no average delay between ROLL and ANGLE, and between DROLL and DANGLE. This would point towards a model of control actions as based on predictive quantities, not just the most obvious current quantities. In other words, the rules governing a detailed predictive model of human control would probably not be based on exactly the same quantities as those underlying the hand-crafted rules for SUV control.
As well as the unfathomed complexity of the finer details of the psycho-motor mechanisms by which actions are effected, there is also the problem of relating these actions to intentions which could be present at a conscious level. We can clearly imagine a conscious intention to place the handlebars at a certain angle, or to move them for a certain period of time at a certain rate. But the pace of actions in such a task is too fast for a verbal report of intentions at this level, and it seems unlikely that any conscious monitoring of actions would reveal reliably what was being done.
If there are rules governing the control actions, then there must be a way of representing those actions in harmony with the way actions are represented in those rules. If we cannot reliably infer that representation from verbal reports, then we would have to infer the representation from the records of actions alone. It is unclear how this could be done, given the presumable complexity of the psycho-motor processes, which mediate intentions to physical actions, in this kind of task.
The possibility of writing fairly simple control rules suggests that there may be simple control processes at a higher level, which are masked by the contortions of lower-level processes which attempt to make up for psycho-motor limitations. We may infer from this that modelling a manual task is likely to involve modelling at the psycho-motor level: perhaps involving both mechanisms of perception and mechanisms of effecting actions. Although this is an important area of study in its own right, it does not have great implications for the kind of real-life task that we have in mind throughout this study.
Worse, the involvement of an important psycho-motor aspect will tend to obscure the other, more cognitive aspect of performance. This may happen from the point of view of the operator, for whom a task can demand much motor-skill learning while being relatively straightforward at higher levels; and from the point of view of the researcher, who would have to unravel the motor-skills before gaining a clear impression of the cognitive skill.
The main conclusion must be that in this type of task, it is unclear how to represent human actions, and this blocks a deeper analysis of the human skill. Thus, we need to study a non-manual task where the complexity would have a more cognitive character.
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