SUMMARY: The ‘old view’ of crashes holds that road users who crash must be lacking in skill or failing to conform to the rules. The ‘new view’ understands the opposite to be a significant factor – that it is only in specific sets of circumstances that where road users are confronted with an unexpected development – prediction failures – that their skills and responses break down. This article offers a primer into the concepts underpinning No Surprise: No Accident.
The ‘Old View’
For a long time, it’s been assumed that if you teach people to a suitable level of skill and then ensure they conform to a set of rules, they won’t crash.
From that perspective, it’s easy to assume that those people who do crash therefore either have inadequate skills or broke the rules.
Typical descriptions of crashes use phrases like “lost control” or “too fast for the conditions”.
A problem of logic
But a moment’s thinking shows there’s a problem with this description of the event. The rider clearly was “in control” and “wasn’t too fast for the conditions” a mile up the road or they would have crashed there. The same logic applies half a mile away… or 100 metres away… or even just 20 metres from the point things went awry. Many road users have a long history of crash-free riding or driving, and they were only ‘out of control’ or ‘too fast’ at just one point – the precise location they crashed. And of course many more riders experience near-misses.
So what changed at that exact point?
What do we already know?
To answer this question, let’s look at what we do know already.
We know where motorcyclists crash – the majority of crashes involving motorcycles happen in the same places over and over. Just think about the two most common crashes; the collision with a turning car and the rider who crashes on a bend.
We know why people crash – an inappropriate response at the important moment, whether’s that’s changing speed or changing direction in the wrong way, or failing to make an input when one was needed.
We also know what those inappropriate responses are – Keith Code got a big chunk of the answer with his ‘Survival Reactions’ that he wrote about in ‘Twist of the Wrist 2’, where he talked about inappropriate reactions like target fixation, freezing on the steering, grabbing a big handful of brake.
For years, it’s been suggested that the riders who crash need “more skills”, except we also know that many people who crash as a result of making those inappropriate responses were actually trained to make the right inputs – at the most basic level emergency stops have been part of rider training for decades and for the last couple of years riders have been trained to swerve too.
What goes wrong with what riders do?
So why don’t riders deploy their crash avoidance skills when they need them?
That’s the question that’s been forgotten and the logical step forward that ‘No Surprise’ has made is to identify that the trigger for these inappropriate reactions all revolves around just how the rider perceives the developing situation in the last few and crucial seconds; in fact, right where the right input would prevent a crash.
The key factor preventing the correct response turns out to be that our expectation of how the situation will develop, which is based on a subconscious comparison with situations we’ve dealt with in the past, turns out to be a mismatch with the current situation. What begins to happen isn’t what we were expecting. The result is surprise. And surprise derails our training.
A matter of brains
An important point to understand is that we do not ride a motorcycle by ‘thinking’ or ‘concentrating’. The area of the brain that allows us to make reasoned decisions is the neo-cortex, and it is far too slow and would be overwhelmed by the huge amount of data requiring processing from our senses. The brain is a complex organ with many systems that work side-by-side to process the information that comes in to our brain in real-time as we ride. Although we hear, feel and smell as we ride, the dominant sense is what we see, and we rely on the mid-brain to filter the incoming data stream to reduce it to manageable proportions.
The mid-brain is fast, speedily processes the data and acts as a kind of switchboard.
If the data the mid-brain processes match scenarios that have already been learned and successfully negotiated, then the mid-brain does the human equivalent of automating the task. It runs the program that is the best fit for what it sees, a program that it’s learned by experience has worked in similar situations in the past.
Remember learning to catch? We can see both parts of the brain working together. In the very earliest stages, we had to work out just how to judge the flight of the ball and time our own movement to intercept it, and we weren’t very good – this is the slow neo-cortex doing the hard data-crunching work to compute flight and coordinate movement. As we got better, not only were we able to catch the ball much more easily as the mid-brain began to process the data and control our muscles without conscious input. Based on repeated experience, a cricket slip fielder will unconsciously use the flight of the ball as the bowler delivers it combined with the movements of the batsman to judge the likely flight of the ball towards them.
This is exactly how we learn to process routine tasks as we ride the bike, and even how we become expert riders. We know that a corner that tightens up or a car that cuts across our path at a junction are threats, so we can learn to scan a bend for clues it’s about to tighten up and to watch for junctions where a car could cut across our path. Our responses are learned and handled by the part of our brain we can train to perform these tasks without conscious thinking, Even swerving and braking can become routine – that’s exactly what riding practice is for.
And then something happens that doesn’t fit the programs.
Should the mid-brain detect anything novel in the incoming data, it will re-root that particular chunk to the real-time neo-cortex for processing – we experience this as a sudden heightened awareness. We start thinking about what we’re seeing, and how we’re going to deal with it.
For example, if someone shouts “catch”, and we look round to see someone about to toss a brick at us, we integrate what we know about catching a ball and what we know about the characteristics of a brick (it’s heavier and an awkward shape) and we make our best guess as to how we can make a controlled catch. With a bit of luck we’ll get it right, but we could equally drop it on our toes.
This is not a learned response, but a reasoned, real-time decision and once again it parallels how we deal with new situations we haven’t encountered when riding. We can attempt to solve the problem by analogy with what we do know. Just like dropping a brick, we don’t always get it right. Hard braking into a tightening bend is rarely the best solution.
And there’s one further problem. This real-time thinking is slow. And time is often a luxury we don’t have on two wheels.
Think what we do if we detect the threat from a ball unexpectedly travelling straight at our head – we duck or put a hand up to deflect it and protect our face without conscious thought. If there’s an immediate threat of personal harm, and EVEN THOUGH WE KNOW HOW TO CATCH, this automatic defence kicks in. This is the third component of the brain in action, the ancient ‘reptilian brain’ that controls our fight and flight reactions.
Experience, habit and prediction failure
Even experienced riders get caught out by common errors. Few crashes are one-offs and by and large, motorcyclists have been having the same crashes since Gottlieb Daimler first stuck a engine in a bicycle frame.
What we’ve termed ‘prediction failures’ indicate a discrepancy between what we expected to happen and could therefore deal with, and how the last few seconds actually developed in a way that we couldn’t cope with.
The problem is we’re creatures of habit. The more something happens (or doesn’t happen) the more our brain will rely on that prior experience and and our habits tend to narrow down to “what worked yesterday will work today”.
Paradoxically, it’s likely that the longer we ride and the longer nothing happens – that is, the longer the intervals between prediction failures – the more we come to trust our ‘anticipation’ skills and the less we actively contemplate just what could go wrong. That means it’s very difficult to stay focused on staying out of trouble. This isn’t complacency or over-confidence but a basic function of the way our brain processes experience and it can happen despite the best intentions of the rider to try to stay alert. We go mentally stale – even good cricketers drop balls after hours of nothing to do.
Skills? Or Expectations?
It’s no good just learning how to catch the ball; if we don’t EXPECT to have to catch it, we won’t catch it. Although the cricket fielder knows that the ball might never come their way in a five day test match, they are prepared to catch each and every ball. As the bowler runs in, for just those few moments they’ll be highly focused and expecting to have to catch that ball. And the next one. And the one after that.
We can – MUST – do exactly the same as we ride. It’s no good knowing developing high order riding skills or even knowing that a corner could theoretically tightens up or that cars cutting across our path at a junction are major threats, we have to EXPECT each and every bend to tighten out of sight and to EXPECT every car at every junction to cut across our path.
The bigger the gulf between the scenario we were mentally prepared for and the way real life developed, the less chance we have of prevent our reptilian brain taking control in an emergency. Only by expecting the ‘worst case scenario’ are we equipping ourselves to deal with it.
Staying on task
As stated earlier, it’s important to understand is that we do not ride a motorcycle by ‘thinking’ or ‘concentrating’. Real-time processing of data is not only slow but requires a lot of energy so it flattens our ‘batteries’ quickly. This is why learning to ride when we have to think about what we’re doing is so extremely tiring. With experience, we power down our real-time brain and rely increasingly on the energy-efficient mid-brain to automate riding, so we can ride further and for longer without getting exhausted.
The problem is finding a balance between the energy-efficient autopilot and the energy-intensive focus.
Let’s return to our cricketing analogy. Field in the slips is a highly specialised, highly focused task and quite exhausting for someone not used to playing there. So experienced players only raise their awareness at the important moment, when the ball’s actually being bowled. At the important moment, they are ‘on task’, yet between deliveries their attention will drop away to near-zero, only to heighten as the bowler runs in again.
A motorcyclist also needs to react to cues with heightened attention in the locations we know to be particularly hazardous. To prevent riders being surprised, we need simple reminders of what can go wrong to keep them mentally fresh. At a junction, rather than thinking ‘the driver could go, but should wait’, we need to mentally re-program for the worst case scenario: “Cango? Willgo!” alerts the rider to the possibility that if the road is not physically blocked, the driver could turn into the path of the bike. “Gaps = Traps” programs the rider to look for empty spaces, which would be important passing parked cars, when filtering and overtaking.
And of course, “No Surprise: No Accident!” which sums up the concept; we’ll only catch the ball, if we know it’s coming and that it’s the unexpected surprises that catch many riders out in circumstances that were both predictable and avoidable. No Surprise helps riders stay ‘on task’ and use the skills they already have.
Conclusions – the ‘New View’
What we’ve termed ‘prediction failures’ indicate a discrepancy between what we expected to happen and could have dealt with, and how the situation actually developed in last few seconds before the crash or near miss. This is the key to ‘No Surprise’; understanding that it’s the event what we DIDN’T predict that is the issue, because once surprised, even though we have training in collision avoidance techniques, we’re at risk of having our reptilian brain take over.
We believe that motorcyclists have to switch to seeing the worst case scenario in every situation but this is not to simply re-inventing ‘anticipation’. If anticipation is a passive guessing what could happen next, prediction is proactively having a plan and expecting to have to use it, reducing the risk of our reptilian brain taking over with inappropriate ‘survival reactions’.
We believe one way to approach the issue is via these simple mnemonics which we consider to be effective because they cue an awareness of the need to focus on the outcome that has negative implications for the rider. We also believe they will be effective because they avoid laying blame on anyone; they judge neither the rider, nor other road users, nor even the environment, because they are factual, simple predictions based on observations of the road ahead.
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