The study and practice of safety tacitly assumes that we know how things are done or should be done. Since humans are supposed to follow procedures, rules, and guidelines, accident investigation and risk assessment alike assume that compliance will always lead to successful outcomes. The purpose of safety analyses is consequently to understand why the outcome of an action or a series of actions (such as riding a motorcycle) was unacceptable (adverse) rather than acceptable (successful) – as in event investigation – or how that could possibly happen in the future – as in risk assessment.

In reality riding a motorcycle is never completely regular or orderly, except in very special cases. It is therefore inadvisable to assume that the riding task is as we imagine and that compliance guarantees success. Work-as-done will always be different from work-as-imagined because it is impossible to know in advance what the actual conditions experienced by a rider will be, not least what the demands and the resources will be, which means that it is impossible to provide instructions that are detailed enough to be followed ‘mechanically.’ A safety analysis must therefore begin by establishing how riding is actually done, how everyday performance takes place, and how things go right, as a prerequisite for understanding what has or could go wrong.

The reason why everyday performance nevertheless in most cases goes right is that people know or have learned to adjust what they do to match the actual conditions, resources, and constraints – for instance by trading off efficiency and thoroughness. The adjustments are ubiquitous and generally useful. But the very reasons that make them necessary also means that they will be approximate rather than precise. Approximate adjustments are the reason why things usually go right, but by the same token also the reason why things occasionally go wrong. Things do not generally go wrong because of outright failures, mistakes, or violations. They rather go wrong because the variability of everyday performance aggregates in an unexpected manner.

Whenever something is done, the intention is always to do something right and never to do something wrong. For each action, the choice of what to do is determined by many different things, including competence, understanding of the situation, experience, habit, demands, available resources, and expectations about how the situation may develop – not least about what others may do. If the expected outcome is obtained, the next action is taken, and so on. But if the outcome is unexpected, then the preceding action is re-evaluated and classified as wrong rather than right, as an error or as a mistake, using the common but fallacious post hoc ergo propter hoc argument (since event Y followed event X, event Y must have been caused by event X). With hindsight, it is pointed out what should have been done, if only people had made the necessary effort at the time. The whole argument is, however, unreasonable because the action was chosen based on the expected rather than the actual outcome. Failures and successes are equivalent in the sense that we can only say whether the preceding action was right or wrong after the outcome is known. That changes the judgement of the action, but not the action itself.

It’s surprises that count so count your surprises (you’ll be surprised how many surprises you count)!

As we all should be aware by now, the surprise tells us that we have failed to correctly predict the future state of the system and as that is the only job we actually do understanding what surprises can tell us is going to be critically important. It’s also important to know that not all surprises lead to accidents but all riders involved in accidents will have been surprised at one point or another during the process. Armed with this information it’s then possible to turn surprise to our advantage as part of an effective self-training/learning strategy.

All surprises represent an accident that would have happened were the circumstances prevailing at the time been only a tiny bit different.

In cases such as that we have clearly made a prediction error, been surprised by the resulting system state, but have then been able to make sufficient adjustments and adaptations to avoid any accident actually happening. It doesn’t always follow though that we can make sufficient post-surprise adjustments and adaptations because that’s how accidents finally happen. That doesn’t concern us at the moment though as it’s those surprises that we successfully manage that can help us to avoid having surprises we can’t manage.

A good question to regularly ask ourselves is “If I was to ride through the same section again and under the same circumstances would I do exactly the same things?” If the answer is “yes I would” then we would have learnt nothing from our first experience, but if we would have done things differently, then the original experience has taught us a valuable lesson. We would only do things differently the second time around because one or two events happened the first time that we didn’t predict and so we would change what we did in the light of the new knowledge. This is the essence of learning by experience and if we can accelerate this ability then we will start to rapidly acquire new expertise. Of course the problem we have as road riders is that once we have passed through a section we don’t often go back and have another go at it and even if we did the circumstances would usually be quite different to the first time we rode it. Rather than go back and have another go what we can do is to count the number of surprises that we actually had during a ride and that would give us a very good indication of any shortcoming in our ability to make accurate predictions of future states. More surprises indicates that our predictions need work and fewer surprises indicates that we are getting the hang of things.

In his book ‘The Upper Half of the Motorcycle’ (see reading list) Professor Bernt Spiegel dedicates a couple of pages to the use of what he calls an ‘error counter’ as a really beneficial learning aid and as errors also generate surprises then it’s perhaps something we can use. What he suggests we do is to mount a cheap tally counter somewhere near the left handlebar and click it every time we get surprised for any reason. At the end of the ride we can see at a glance how many surprises we had during the ride and that will give us an indication of how many potential accident situations we got ourselves into, but were able to manage our way out of. The idea is that the fewer surprises a rider has the better the rider is and that’s something all of us aspire to.

Professor Spiegel has made an extensive study of how the error/surprise counter works and he found that after a short period of using the counter the number of errors/surprises recorded actually increased! What he realised was that the number of registered events increased not because the user’s riding was getting worse, but that they had become more aware of the number of errors they were actually making. Before the use of the counter he found that most errors and surprises seemed to slip by almost un-noticed, but once a rider started to actively hunt for them even the tiniest error or surprise couldn’t slip through the net. Eventually of course the number of registered errors and surprises started to decrease as the rider stated to learn what it was in the system that precipitated the errors and surprises in the first place. The increased sensitivity to error and surprise resulted in a commensurate increase in the rider’s predictive capabilities and a noticeable decrease in the number of prediction failures they made.

Considering that the whole point of the Nosurprise campaign is to help riders to become better predictors then a simple device like the error/surprise counter is something that we would thoroughly recommend.

Considering mechanical failure accounts for so few accidents nowadays you would have thought that the way bikes are built and the way they are ridden wouldn’t have much of a connection. You would be wrong in this assumption however because bikes are built and bikes are ridden in what are commonly known as ‘systems’ and how systems work and sometimes fail to work is critical to our understanding of accident causation. Continue reading →

Why do riders crash in corners? After all, had they not successfully negotiated a lot of other corners before they reached the one that got them? Was there something about certain corners that made them more likely to be accident sites? Why did these riders select a particular corner entry speed that proved to be so spectacularly incorrect? What is the process that we use for judging the severity of a corner and selecting a suitable entry speed? Do we all use the same method, or are there a number of ways in which we can analyse a corner before we reach it? Continue reading →

Abstract
The ability to make control adjustments is critical to the riding task, but the range of adjustment available will always be limited. Most riders will be uncertain of where exactly those limits lie. They set personal limits which eventually become the actual limits. Continue reading →

GAPS = TRAPS

It’s the prediction that wherever there is space & time for something hazardous to occur, then there is a potential that it will actually happen. Knowing this and being prepared minimises the likelihood of being surprised in the event of it actually happening.

Whether it is a vehicle waiting at a junction, vehicles in moving or stationary traffic or vehicles moving towards you or away from you on straight roads or bends…knowing there is a gap means that gap can possibly be filled by something else. If you are aiming to occupy the same space at the same time then there has been a prediction failure and the result will be a collision. Continue reading →

As part of the ongoing engagement process I have developed an initial poll of six questions to gauge rider opinions on some riding rights & safety issues. The polls have been designed to reflect the possible opinion variance and offer balanced options to choose from.

The poll shall be ongoing for the foreseeable future with the current results being easily viewable and you will be able to measure your own responses with the rest of the response pool. Continue reading →

So often is the case, we lie in wait until a solution to a problem is discovered or more so until the solution is implemented and is working.

If we look at motorcycle safety as an overarching concern, then it is with merit to identify certain issues that do or may cause motorcycle accidents…in fact we could extend this further into general road safety or any other area of concern and apply the same principles.

There are of course certain triggers that we may perceive as being the main causes and we may even campaign to effect changes to improve our position. Continue reading →

SUMMARY

Collisions involve two road users attempting to occupy the same space on the road at the same time. Many accidents involving motorcycles are collisions with other road users, where the rider was taken by surprise but the collision was otherwise both commonplace and avoidable. The Cango?-Willgo! concept explains collisions in terms of prediction failure rather than the commonly-accepted explanation of rule-breaking or judgment failure. Cango?-Willgo! further extends the basic principle of No Surprise: No Accident. Continue reading →