| ©1990, 1995 | section list | 3: Early studies | overview | General Contents |
| Section 3.0 | 3.1 Collision avoidance subsections | Section 3.2 | ||
Collision avoidance between merchant ships at sea was originally chosen, by those who instigated the research, as an exemplar area of study, for many good reasons. Some of these reasons will be explained in this section. Because it is a good representative task, it also shows the problems of representation clearly, and these will be discussed next. Collision avoidance is described here in some detail in order to get an appreciation of the kind of problems faced when attempting to study a real-life, complex task. These considerations are a significant part of the whole work, despite the fact that there were too many problems standing in the way of research directly on the subject. These obstacles are also described here.
Collision avoidance is a good example of the kind of system, and task, described in the introduction (§1.2). Ships come into view, either visually or on radar, at unplanned times, and have to be dealt with in real-time, no matter what else is happening. Ships are expensive, and a great deal of effort is put into allocating blame for collisions, so that the cost of damages can be apportioned as fairly as possible. A nautical disaster can cost many lives. There can be a large amount of information to be dealt with, though the task can also be uneventful for long stretches. The amount of information that needs to be dealt with depends firstly on what the situation is: in the middle of the ocean, not much happens, whereas in busy shipping lanes near the coast, there are more vessels to keep a look-out for, and more work with the chart keeping a track of the ship's position. The amount of information that needs to be dealt with depends secondly on the kind of ship and the number of people on duty at once. The historical trend is for fewer people and more automation, away from the style of operation associated with navies [60], towards the `one man bridge', where the automatic systems have interfaces within the control of the `conning officer'.
Relating to the categories of §1.3, collision avoidance is clearly a dynamic control task, rather than a problem-solving task. Let us take the question of complexity firstly in terms of Woods' categories [145], §1.3.2 above. There is dynamism, though the time constants involved are of the order of minutes rather than seconds---a property shared with nuclear power plants and other process industries. The task can have strong interconnections, particularly when more than one ship presents a potential threat, but also because the different tasks that make up watchkeeping impinge on each other. There is uncertainty, in that it is never certain what actions other ships will take. And there is risk: this is not only the risk of collision (and grounding), but sometimes also the commercial risk of missing deadlines. So collision avoidance would count as fairly complex according to Woods, though perhaps not as complex as nuclear power plant control.
Collision avoidance also has a clear involvement of regulations (the collision regulations [61]), and multiple tasks. Observation of cadets in a high-fidelity night-time training simulator showed, perhaps even more clearly than observing experienced mariners would have done, how there were different elements to the task. (The author spent a week observing cadets in the ship simulator at Glasgow College of Nautical Studies.) As well as giving orders for desired heading, engine speed, and occasionally rudder angle, the watchkeeping officer has to take at least supervisory responsibility for maintenance of the chart and log; for lookout, both visually and by radar (which often involves calculations on the radar screen); for communication with other vessels, pilots and port authorities (including responding to distress calls); for looking after the cargo; and for managing the other people involved in the control and maintenance of the ship, including making sure that people are awake, doing what they should be doing, organising relief or time off vital duties, etc. This kind of human multi-tasking is common in the kind of complex tasks that we are considering in this study.
The present author's definition of complexity (§1.3.2) is in terms of the variety of possible strategies, and by implication (now that we have discussed representation) the variety of possible representations of the task. This is particularly interesting for collision avoidance, as this variety can be approached in more than one documented way.
Around 1970 a number of articles appeared in the Journal of the Royal Institute of Navigation concerned with a possible revision of the collision regulations (see, e.g., the discussion, [116]). Much of the writing focused around the question of whether the existing basis of the rules was satisfactory. The existing rules are based around the concept of right-of-way. In most situations involving the risk of collision, they say that one vessel has to give way, and the other vessel has to `stand on' (i.e., maintain course and speed), to avoid the possibility that any action taken by the stand-on vessel might counteract an action by the give-way vessel. The alternative is to have a system whereby both vessels are expected to manoeuvre, but in such a specified way that their actions add to each other's effect, rather than cancelling it. Cockcroft [25] gives the diagram of manoeuvres that was generally favoured at that time. This discussion establishes the point that opinions differ about the best strategy to adopt as a general rule, and about the concepts that would underlie that strategy.
Although Curtis [29] did not set out to show differences between individuals, his simulator experiments show a great deal of variation between the actions of different individuals presented with an identical experimental arrangement. Since his object was to determine reaction times, Curtis did not publish the reasons the mariners gave for their actions, but he reproduces in diagrammatic form the tracks followed by the 30 individuals. These are remarkably varied. Looking at the diagrams, it is difficult to believe that the mariners were all following the same strategy.
At both Liverpool Polytechnic and Plymouth Polytechnic, there was recent work on collision avoidance advice systems. In making a system capable of giving reliable advice, the task has to be given an explicit logical structure, and the obvious way to do this is on the basis of rules. To make rules, one has to have a representation language that provides the primitives in terms of which the rules will be written. Investigating some finer points of these proposed systems gives some insight into the problems with representing the collision avoidance task.
This takes input from an advanced radar system, in the form of headings and speeds of ships detected by the radar. These raw data are then interpreted into categories that are used and understandable by mariners, and of the type also used in the Collision Regulations, such as ``crossing from starboard to port, passing ahead''. In the Liverpool system, there are 32 valid combinations of this kind of descriptor, and five other descriptors dealing with other information relevant to the collision regulations and the likely inferences of an officer of the watch. 14 possible collision avoidance actions are identified, the last of which is a default category of ``emergency'' when none of the other 13 actions are appropriate. The derivation of the best appropriate collision avoidance action from the descriptors is governed by rules and procedures internal to the advice system. The rules were derived from expert mariners, who did not always agree, while the procedures to find the solution consisted largely of orderings and heuristics to guide the search for a reasonable solution, avoiding the necessity of trying out every possible manoeuvre with every target. After generating a likely action, that action is tested against all the targets, to ensure that no advice given could lead to a collision or near collision.
Liverpool's system is geared to providing advice to the officer on the bridge, and the complete calculation is reworked every 15 seconds. If advice has been given, but not taken, it may become appropriate to offer different advice. This is what is done.
The system represents consensus opinions on reasonable actions to take in the situations as described. However, a number of questions may be raised about the representation used. Firstly, the descriptors chosen were derived from the Collision Regulations, plus a consensus of mariners. If the regulations changed, this would be likely to invalidate the descriptors, not just the rules: this might be acceptable on the basis that everyone should be working within the same regulations. But what if certain mariners had other descriptors that they used, consciously or not, in their collision avoidance strategy? This would imply that the Liverpool system might give advice that was inconsistent according to some mariners' views. The research issue here would be to establish that mariner's descriptors were fully covered by the system's descriptors. Secondly, some mariners might characterise the range of actions available to them differently from the system. Again, the research called for here would be to investigate the actual range of actions that are used, and to ensure that all actions taken by mariners are given in the system. However, this would still be a problem, in that the system might give advice to a mariner to take an action that is not within that mariner's normal repertoire.
The possible use of situation descriptors other than the ones recognised by the system raises a yet more troublesome point: what if some of the descriptors used by mariners are not available to a system electronically? The lights that a target vessel shows are an obvious example. But more worrying still, how about the feeling that a watchkeeping officer gets, that the crew of a certain vessel are not going to comply with the rules?
Another problem for advice systems of this kind comes from the varying usefulness of such a system in situations where the user has different amounts of experience. Among collision avoidance situations, some occur more frequently than others. Generally, it would be reasonable to expect that in the more commonly occurring situations, there would be more knowledge and opinion available in the nautical community about good ways of responding to such situations. Equally, any particular mariner is more likely to have a worked-out strategy for dealing with these cases. These are the cases where the advice system will be at its most reliable, but also the cases where it will least be needed. On the other hand, in situations that occur only infrequently, watchkeeping officers are likely to still be at the learning stage, trying out different possible actions, and learning from experience. Following advice from the system would at least work most of the time, although this will not allow an officer to learn from different possible approaches, and develop a personal style. But it is in just the least familiar situations that the system gives up, leaving the mariner with an `emergency' that is at best ill prepared for, and even less prepared for if, due to the availability of the advice system, a personal strategy has not been developed.
Research at Plymouth has had automation more in mind, and perhaps for this reason the published paper has different priorities from Liverpool's publications, and does not describe the decision process in detail. The principles of the system design are clearly similar, with a rule-based approach being used. However, even at this relatively early stage of development, it can be seen that the representation used is not identical to that used by Liverpool. For example, they use different ways of calculating the time at which an avoidance manoeuvre should take place. This reflects debate in the Journal of Navigation about what criteria to use for modelling mariners taking avoiding action (e.g. [30]). As we consider levels of detail finer than given in the publications, it would be even more likely that differences would emerge, simply because of the difficulty of unambiguously describing a correct approach to the collision avoidance task.
An authority has suggested that ship's masters often feel the need to imprint their own personality on the job, and that all certificated officers took pride in their ability to ``interpret a situation'', and that the heuristic knowledge gained from experience ``is more valuable to them than their slavish knowledge of the Collision Regulations'' [48]. This reinforces the idea that different watchkeeping officers have different personal styles, and therefore probably different representations of the task.
There is also hearsay about the usage of modern electronic aids to navigation. It is thought that there are ships where the officers do not know enough about their radar equipment to make proper use of it. This applies particularly to the more modern equipment such as ARPA (Automatic Radar Plotting Aid), which provides the facility to predict, and display graphically, where vessels will be at a future time, assuming they hold their course and speed. In many collisions in fog, there is a suspicion that at least one of the parties was not using their equipment properly [19, p.163]. On the other hand, some channel ferry operators are thought [48] to base their (very effective) collision avoidance strategies around a modern electronic aid that shows danger areas to be avoided round other ships (the Sperry PAD system).
It would seem that strategies, and representations, are built up in the context of what information is available, and people may not be very good at adjusting their old strategy, built up over many years, on the introduction of new equipment.
Despite the wealth of interest in a study of maritime collision avoidance, there were obstacles preventing its direct study. The first of these was the inability to secure machine-readable data.
Real ships would be the ideal place to secure data on collision avoidance. However, they do not have automatic recorders, such as the `black box' devices on aircraft that are analysed after crashes, etc. To install such a device on an operational ship would be technically very complex, and it is doubtful whether ship owners would be happy having their radar equipment interfered with, and doubtful whether watchkeeping officers would be happy having all their actions recorded.
Despite the fact that nautical simulators are driven by computer, it is difficult to get machine-readable data from them. The computer architecture tends to be specialised, with little or no provision for data links to other systems conforming to any standard. Only one such link in Britain was known to the author, at the College of Maritime Studies, Warsash. This connection has been used in the study of collision avoidance behaviour [49], but the simulator is heavily used in routine training, and not readily available to outsiders for extensive experiments.
Even if the problems with data were solved, there would be still further problems in using lifelike maritime collision avoidance as an object of study.
The multi-task nature of collision avoidance has been described above, §3.1.1. In current simulator training (as observed by the author), the tasks that do not normally have a mechanical or electronic interface are simulated by having a very skilled simulator operator, who takes on the role of all the agents not immediately present, such as the engineers, pilots, port authorities, other ships, etc. In training simulators, with cadets, the other unformalised aspect of the task is the interaction of the officer of the watch with the other people on the ship's bridge. To include all this information, or to leave it out, both have problems. Including it would mean recording by hand and formalising data that it is not clear how to formalise. A realistic situation would result, but the complexity of this full realism would make the task more complex, and lengthy to learn. Lifelike collision avoidance involves long stretches of time at the task, and this too would cause problems for experimentation. It is not easy to formalise the time relationships of events which either have long-term consequences or need long-term planning (of the order of hours). On the other hand, leaving out this kind of information would make the task unrealistically easy, perhaps so easy that there would be little complexity to the task, and a logical analysis would suffice. That would mean that it would be an unsuitable object of study here. A one-man bridge simulator would be another alternative, eliminating the social side of the task, but such simulators are not widespread, and none was known that would be available.
This difficulty in simulating the collision avoidance task could be traced back to the question of whether collision avoidance actually constitutes a separate task of navigation. Clearly one can think of it as a separate aspect of the task, but perhaps it only acquires its particular character in the context of the wider task of navigation. Although it is quite easy to set up exercises on collision avoidance in ship simulators, it is notable that there are in general no such separate exercises in the use of ship simulators for routine training. If one cannot helpfully think of collision avoidance as a separate task, then analysis of it would only make sense if one analysed the task of navigation as a whole, which, as has been pointed out above (§3.1.1), has many aspects, and some of those aspects might frustrate attempts at formalisation and modelling (discussed below, §8.2.1).
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