Presentation by Kevin Williams MSc of Survival Skills Rider Training to the National Motorcycle Safety Seminar, Tuesday 16 November
Some years ago, I was waiting for a candidate to come back from the old-style Driving Standards Agency (DSA) motorcycle test when the examiner turned up early minus the trainee. That’s normally a sign the trainee’s lost the examiner (it happens), the bike’s broken down (occasionally) or the bike’s been dropped and is too damaged to ride (not uncommon if it happens during the on-road U turn – the brake or clutch levers can snap off). In this case, he told me that she’d dropped the bike.
Naturally, I asked what had happened and if she was ok. He told me that she’d just been passing a parked car when a car had pulled out from a side turning just ahead of her, crossed close in front of her and accelerated away at high speed. She’d been forced to brake, and in doing so she’d locked the front wheel on the wet road and fallen off. Fortunately, he continued, she was only bruised and the bike had only suffered a few additional dents and scrapes, but needed a new brake lever to be rideable.
“She was a bit surprised when the car pulled out but the odd thing is,” he continued, “we’d just done the emergency stop a couple of minutes earlier, and she did a perfect one”.
Unfortunately, it wasn’t that much of a surprise to me. Nor is it much of a surprise to the people who look at accident reconstructions – ineffective or overbraking errors are often reported in this kind of incident.
Now it might be understandable if the accident had involved a rider who had taken their test thirty years ago. There was little training back then.
But the emergency stop has been a feature of the bike test for decades, and training courses mean riders have been trained to make emergency stops for at least thirty years. OK, there’s an explanation here too – few riders practice emergency techniques as much as we should. I didn’t practice much myself until I started instructing and realised how rusty my own skills were.
But when a rider who’s been freshly trained in emergency stops and can demonstrate that she could actually do them well – as the examiner had noticed – and yet still falls off in a real-life emergency, then we need to ask a searching question:
“Why couldn’t she use the skills she’d been trained to use when she REALLY needed them?”
Before I say anything else, let’s define ‘accident’. It’s a word that’s gone out of favour with the emergency services, but it’s used throughout research into road safety. So an accident can be defined as an unplanned event, generally associated with negative consequences such as fatalities, injuries, or physical damage to vehicles. Run a quick search on Google and you’ll find factual statements like “motorcyclists are 20 or 30 times more likely to be killed on two wheels”. Some figures suggest 40 times more likely to be killed.
Often the bare bones of facts are backloaded with a subjective, uninformed, emotive and ultimately prejudicial judgment: “they know the risk of riding a motorcycle, but they still choose to ride rather than use a a much safer car”. For example, agony aunt Claire Rayner, in her review of Melissa Holbrook Pierson’s motorcycling book ‘The Perfect Vehicle’, admits her prejudice that nothing Pierson writes could change her attitude about motorcycling because, “I used to be hospital casualty nurse and spent so much time dealing with bikers who were scraped off the road like so much raspberry jam after accidents that I became an implacable hater of the machine… The danger to which bikers constantly put themselves, however well-wrapped in their urban armour of studded leather, and however horrendously helmeted, seems to me a reason for banning the infernal machines. …a smell of blood and smashed muscle and bone mixed with engine oil. That is what motor cycle means to me. And, I’m afraid, always will.”
What makes bikers tick is a question that’s exercised a lot of minds inside the biker community. For example, on the www.bikesafer.com website they asked “very accomplished riders and trainers… the same question about biker psychology and its relationship to safety”.
They went on to identify:
- risk takers
- rule breakers
- riders with a victim mentality
- biker ‘Fashion Victims’
- ‘death wish’ bikers
But sometimes the same view of motorcyclists as thrill-seekers, gamblers and risk-takers is the result of objective research into rider behaviour. The Transport Research Laboratory carried out a formal study into the same question. It’s called ‘Passion, performance, practicality: motorcyclists’ motivations and attitudes to safety – motorcycle safety research project’. They attempted to answer the same question with “an original way to categorise riders based on their motivations to ride”.
Riders rated what was important to them about riding a powered two wheeler on a scale ranging from ‘not important at all’ to ‘very important’. The seven categories they came up with were:
- Look-at-me enthusiasts
- Car aspirants
- Performance disciples
- Car rejecters
- Performance hobbyists
- Riding disciples
- Riding hobbyists
“Look-at-me enthusiasts” had the highest accident propensity and “Riding hobbyists” the lowest.
The same sort of study has been tried elsewhere. An Australian study from 2007, “Psychological and social factors influencing motorcycle rider intentions and behaviour” claimed to have identified “…key aspects of rider behaviour considered to influence safety: motorcycle handling skills; rider awareness; riding while impaired or not; and the tendency to bend road rules, push limits, and ride at extreme speeds or perform stunts”. A second study examined the psychological and social factors influencing these behaviours, and they found riders classed psychologically as ‘sensation seeking’ and ‘aggressive’ turned out to be good predictors for riders who chose risk-taking behaviours.
But how does knowing all this fit into a safety framework? Are these behavioural labels even valid? Are any of them really relevant to my trainee who fell off?
Let’s go back in time. The scientific study of accidents started about one hundred years ago, has continued apace and has created dozens of complimentary and competing theories. So we’ll just sketch out some of the broader ideas.
One of the first theories considered accidents to be random events, when Bortkiewicz studied the frequence of deaths from horse kicks in the Prussian army, and found that the distribution of deaths in the army units was almost perfectly random, something he wrote about in his book ‘The Law of Small Numbers’, published in 1898. As a result, the idea that gained favour was that accidents were events over which humans had no control.
However, Greenwood and Yule (1920) discovered that accidents in munitions factories during the First World War involved just a few workers, far fewer than explained by randomness. Their conclusion was that some people were more prone to accidents than others. That belief grew into the Domino Theory that stated that heredity and environment cause people to act in a faulty way which in turn leads to unsafe acts and ultimately to an accident. Coinciding with a surge of interest in psychoanalysis and the writings of Sigmund Freud, the belief took hold that psychological testing could identify people with the personality disorders that made them particularly prone to accidents and be used to deny them access to the activities were they were likely to cause one.
In 1939, the idea that just a few people are accident-prone was undermined by Thomas Forbes. He found that most car accidents were caused by ordinary drivers. By looking at accidents across two time frames, he found although 1% of drivers were involved in 23% of all accidents during the 1931-33 period, that same 1% of drivers were only involved in 4% of accidents in the 1934-36 period. In other words, the majority of of accidents in the second period were not caused by those drivers who might have been considered ‘accident-prone’ by looking at the first study period. This is a demonstration of a phenomenum known as regression to the mean.
With the post-war growth of motoring, the ‘causal accident theory’ argued that only by finding the real causes of accidents would successful prevention become possible, and that the real causes of accidents can only be found by studying each accident in detail, looking at the events leading to it and the circumstances surrounding it. This was related to research into the causes of disease by identifying the microorganisms and mechanisms triggering infections. The conclusion was that accidents typically have more than one cause, that one cause is rarely significantly more decisive than others, and that most accidents were a chain of events ultimately caused by human error. Many in-depth studies thus attributed road accidents to the initial errors made by road users. As a result, by the 1950s emphasis was on modifying human behaviour as the only effective measure in preventing accidents.
It soon became apparent these efforts were only modestly successful. ‘Systems Theory’ emerged in the 1950s as a result and became popular in the 1960 and 70s. This theory states that accidents should be looked at in terms of a system with three components: the person, the machine, and the environment. Accidents are the result of maladjustments in the interaction between these components of the system. To answer the question “why do humans err?”, the answer proposed by systems theory is that errors are made because the system design is inadequate and does not match human capability. The solution was seen as modification to the system itself. In road safety that meant improvements to vehicle design (seat belts, ABS for example) and via traffic management and highway engineering. The result has been significant improvements in reducing the accident rate.
Road safety today employs what is largely a mix of the ‘causal accident theory’ focusing on modifying human behaviour laced with ‘systems theory’ focusing on road engineering, traffic control systems and safer vehicles.
We’ll leave aside engineering solutions and focus on one of the many studies of accidents involving motorcyclists which have focused on identifying risk-taking behaviour.
The paper ‘Risk and Motorcyclists in Scotland’, written in 2006 by workers at the TRL and Napier University in New Zealand, used a questionnaire to obtain “measures of behaviour, attitudes and self-reported rider style together with demographic information”.
They found that most riders in this study said they were aware of, or willing to believe, objective estimates of motorcycling risk. Furthermore, they were willing to accept these levels of risk and few would consider giving up motorcycling because of them.
The authors concluded “It does not appear that, as a group, motorcyclists base their behaviour on grossly under-estimating the risks of motorcycling as an activity” although they went on to qualify statement by saying “there were also indications that a substantial proportion of respondents (42%) felt that this statistical risk for riders like themselves did not actually apply to them because they were good riders”.
They identified three rider groups, and suggested ‘remedial action’.
“Risk Deniers” might be tackled with information on the real risks of motorcycling provided it is presented in a convincing way to show that they themselves are not immune from risk.
“Realistic Accepters” already self-assess their own risk at a higher level than the other groups, worry more about the risks and are more aware that their own skills do not protect them from this risk. They were thought to be the group most susceptible to educational and training interventions.
“Optimistic Accepters” might be influenced by educational campaigns designed to bring home to them the true impact of motorcycle accidents on victims and their families and measures designed to improve awareness of personal limitations and to reduce the belief that skill provides immunity from risk.”
Here’s the kind of interventions that were suggested:
- promotion of ‘safe’ goals for motorcycling – smoothness and safety rather than speed and ‘progress’
- making available and promoting pre- and post-test training and educational measures to improve riders’ safe-riding skills, influence attitudes and behaviour, improve self-evaluation skills and awareness of risk-increasing factors
- developing an increased skill level without a corresponding increase in risk –possibly by using highly-respected expert riders so that riders aspire to ride as well as these experts
- encouraging good perception & planning skills
- suggesting the goal of completing all rides with no ‘surprises’ and making the point that ‘being a good rider is not enough’ or, rather, redefining what is seen as a good rider
As you can see, it’s a classic example of how ‘behaviour-based safety’ is proposed to work by changing values via a machine-like input / output mechanism; give people a REASON to change their behaviour, they WILL change their behaviour.
The ‘Risk and Motorcyclists in Scotland’ paper went to say that: “It may also be the case that, for some riders at least, it is unrealistic to expect educational and training measures to be very effective in reducing risk; and that if the government wishes to reduce their risk substantially, attention will also need to be given to engineering and enforcement-based measures”.
Zero Tolerance Safety argues that people think according to rules and make conscious choices when breaking them, that behaviour that breaches the rules cannot be tolerated and compliance be enforced by creating an authority and control culture which punishes those tempted not to conform.
Just how important do we see punishment as a strategy? In a recent study of motorcycle fatalities in London for Transport for London entitled ‘Analysis of Police collision files for motorcyclist fatalities in London, 2006-09’, the authors suggested a series of countermeasures that could have prevented the fatal collisions including:-
- Additional motorcyclist training to improve riding skill
- Improved braking systems for motorcycles
- Additional training to improve drivers’ awareness of motorcycles.”
- Speed warning systems
- Speed enforcement to increase speed limit compliance
The proposed intervention for 51% of the cases was ‘enforcement’. It would appear that the stick is very definitely considered mightier than the carrot.
PUBLISHED PROJECT REPORT PPR621
Analysis of Police collision files for motorcyclist fatalities in
L Smith, J Knowles and R Cuerden
But how effective is enforcement with the threat of punishment? Gerald Wilde of ‘risk homeostatis’ fame says:
“Although enforcement of punitive law is one of society’s traditional attempts at motivating people towards safety, the evidence for its effectiveness has not been forthcoming. It suffers from several other problems as well…
“First is the “self-fulfilling prophecy” effect of attribution. For example, labeling people with undesirable characteristics may stimulate individuals to behave as if they had these characteristics. Treat people as if they were irresponsible and eventually some will behave as if they were.
“Second, the emphasis is on process controls; ie, on specific behaviours such as using a piece of safety equipment or obeying the speed limit, instead of focusing on the end result, which is safety. Process controls are cumbersome to design and implement, and they can never totally encompass all undesirable specific behaviours of all people at all times.
“Third, punishment brings negative side-effects. Punishment creates a dysfunctional organizational climate, marked by resentment, uncooperativeness, antagonism and even sabotage. As a result, the very behaviour that was to be prevented may in fact be stimulated.”
It’s also been observed that punishment often results in road users developing strategies to avoid the punishment by not being caught rather than adjusting their behaviour in the way that was intended.
A worrying consequence of the belief that that in a perfect world no-one should make mistakes and should be punished if they do, is the creation of the belief that whilst we ride the ‘Perfect Ride’, it’s others making mistakes putting us at risk. Lacking tolerance of human fallibility in others only creates a victim mentality that then devolves responsibility for safety onto others. Motorcyclists are fully aware that accidents on built-up roads are more likely to the the fault of the motorist rather than the motorcyclist and sixty years of campaigns to prevent ‘looked but did not see’ collisions has only succeeded in creating a culture were many riders firmly adhere to the ‘Old View’ of rider safety, arguing that these collisions are the result of mistakes by ‘bad-apple’ road users whose behaviour puts us at risk. Even in 2014 rider groups are still campaigning along these very lines, and arguing that those drivers should be educated and punished into “taking more care” or “looking harder for bikes” rather than encouraging riders to look out for their own safety.
By contrast, Wilde sees encouragement and: “countermeasures…that reward people for accident-free performance seem to be the most effective.”
Maybe insurance companies reward people for accident-free performance, but unless you count the very nebulous goals like persuading motorcyclists they should be “riding for pleasure as a goal” or “aspiring to ride as well as the experts”, reward for good performance is not a characteristic of road safety generally.
Let’s introduce another radical thinker into safety. Sidney Dekker is professor of Human Factors and Flight Safety at Griffith University in Brisbane, Australia, where he founded the Safety Science Innovation Lab. He’s also a part-time Boeing 737 pilot, and author of the highly influential ‘The Field Guide to Understanding Human Error’ as well as a short paper called the ‘Re-invention of Human Error’, where he wrote:
“When faced with a ‘human error’ problem, you may be tempted to ask ‘Why didn’t these people watch out better?’ Or, ‘How can I get my people more engaged in safety?’ You might think you can solve your safety problems by telling your people to be more careful, by reprimanding the miscreants, by issuing a new rule or procedure and demanding compliance. These are all expressions of ‘The Bad Apple Theory’ where you believe your system is basically safe if it were not for those few unreliable people in it.”
“It is counterproductive to say what people failed to do or should have done, since none of that explains why people did what they did…” Statements such as “poor decisions”, “failures to adhere to brief”, “failures to prioritize attention”, “improper procedure”… are not explanations, and could not even lead to explanations of performance.” Labels like this are after-the-fact judgments, made with hindsight, which “make unrealistic assumptions of virtual omniscience and unlimited computational power on part of people inside the situation”.
And of course, that “20 / 30 / 40 times more likely to be killed on a bike” headline figure seems to suggest that motorcyclists as a group are bad-apples.
But if we factor in the skewed distribution of fatalities that finds that a significant proportion of riders who are killed are either unqualified or disqualified, or drunk or drugged (the real ‘bad-apples’) then what about the rest?
Does that headline figure mean riders generally are accident-prone?
To find that out we need to know not “how many motorcyclists are killed per mile” but “how many motorcyclists crash per mile”. And guess what? That figure is remarkably difficult to find in the literature. There’s plenty of research into the injury rate per mile, but I couldn’t find a single reference to research into crash rate per mile. In fact, the best I could find was some work carried out in the USA by the National Highway Traffic Safety Administration.
The 100-Car Naturalistic Driving Study was set up to collect large-scale naturalistic driving data. In the course of two million vehicle miles and over 12 to 13 months monitoring of each vehicle, they collected almost 43,000 hours of data involving 241 primary and secondary drivers, with data collected by instrumentation system including five channels of video and vehicle kinematics. 78 out of the 100 vehicles were ‘own cars’ rather than fleet vehicles.
From the data, an “event” database was created. crashes,near crashes and other “incidents.” Data was classified by pre-event manoeuvre, precipitating factor, event type, contributing factors, and the avoidance manoeuvre exhibited. Parameters such as vehicle speed, vehicle headway, time-to-collision,and driver reaction time are also recorded.
The authors concluded: “There is every indication that the drivers rapidly disregarded the presence of the instrumentation, as is indicated by the resulting database containing many extreme cases of driving behaviour and performance including: severe fatigue, impairment, judgment error, risk taking, willingness to engage, aggressive driving, and traffic violations.”
So maybe there are a lot of bad-apples driving around in the USA? That would seem to be the case, from that previous damning statement.
At least, it seems to be the case right up to the point you discover that in the two million miles of the study period, there were 15 police-reported and 82 total crashes, including minor collisions. Assume an annual mileage for an average driver of 10,000 miles and that’s one accident per driver every 20 years.
Are motorcyclists in the UK significantly different? Without figures we can only speculate but it seems unlikely. With an actively riding population of around one million, the vast majority of motorcyclists are not killed and injured.
And this is why Dekker says we should stop trying to put peoples’ actions in simple categories like error, risk-taking or recklessness. “Wherever you got that idea, get rid of it,” he says.
“It is not to say what people failed to do. It is to understand why they did what they did…” It’s certainly a question we need to ask about my trainee and her crash.
Why do we do what we do? That’s the field of cognitive science. As we ride we build a mental model of the environment and the events that are occurring around us. The model provides a meaningful interpretation of the here-and-now reality and points to potential outcomes, and we use it to behave in a way that makes sense at the time.
But that mental model is subject to faults.
Back to my trainee who fell off. If she had been riding unsupervised, it might have been tempting to conclude she was riding “too fast for the conditions”, or maybe “reacted too late”. As she was undergoing training, an alternative conclusion was that she hadn’t been properly taught – or hadn’t mastered – hard braking. But as the examiner observed, “we’d just done the emergency stop a couple of minutes earlier, and she did a perfect one”.
Those conclusions are examples of the hindsight-based ‘Old View’ of accidents.
By the time my candidate got to the test, she had probably performed between forty and fifty practice emergency stops, building skill to the point where her stops were positive and controlled, in wet and dry conditions. The skills learned and practised to a high level allowed her to perform a test-standard emergency stop in front of the examiner. So, in theory she should have been able to stop safely when the car pulled out.
But all through her training, she’d been repeated trained to react to stop when a person standing off to one side raised a hand. She hadn’t actually been trained to react to a real emergency. Just like anyone else who takes the bike test, she had been taught the right technique, but trained to react to the wrong ‘trigger’ stimulus.
Thus her skillful brake use in front of the examiner failed to guarantee a skillful reaction when the car pulled out. She panicked and crashed.
Let’s just remind ourselves of what Dekker said: “It is not to say what people failed to do. It is to understand why they did what they did…”
She had the skills. But her brain let her down. Her mental model of the environment didn’t include a car pulling out in front of her because we’d never exposed her to that particular situation.
So it might seem that the answer is more training to build more patterns of skilled behaviour to allow us to perform most actions without conscious attention? That’s certainly one of the strategies identified by that paper ‘Risk and Motorcyclists in Scotland’.
A quick lesson on how our brain is put together is in order. Our brain is sometimes referred to as the triune brain because it consists of three sections that, in very simplistic terms, mirror our development from primitive vertebrate to modern human being.
Go back 450 million years and the first fish with a backbone appeared, with a very small and simple brain but still capable of handling the basic body functions such as breathing and heart beat, taste and vision and balance and co-ordination.
About 150 million years later, reptiles evolved with slightly more sophisticated brains hard-wired for reflex actions, such as the basic instincts necessary for survival and the preservation of genes. ‘React or Die’ was the original design brief. Part of that reflex is to guard space around the animal, by fighting off rivals that threaten to intrude or by running away.
Around 200 million years ago, the first mammals appeared and inherited the basic functioning of the reptilian brain. The most primitive part of the human brain is sometimes called the Lizard or Reptilian brain, because we share it with those crocodiles and it still controls many of the basic body functions.
In addition it controls basic, instinctive and unconscious responses to stimuli as well as being on constant guard for danger. It’s able to perform ‘ritualistic’ tasks that have proven to be safe in the past and is blisteringly quick in responding, around ten to twenty times faster than the Neo-cortex – handy if a crocodile attempts to bite our leg off. But it isn’t smart. It can’t think ahead or understand the consequences of the actions that it tells us to take. It only chooses between what it knows by experience works, and with no experience to call on, it defaults to the most basic fight or flight responses that suited our remote ancestors.
Mammalian brains also came with two new areas hard-wired to it:
- The Mid-brain, where the Reticular Activating System works with the Limbic System to filter incoming data like vision and sound. It picks out important pieces of information and brings them to conscious attention. A good example of it functioning is when we hear someone mention our name in a noisy room. It also controls emotions, immune system, sleeping, governs our sexuality, and is the site for long term memory. The limbic system validates new knowledge and routes information to where it is processed in the neo-cortex as well as dealing with our sense of identity and values. It holds all three parts of the brain in balance, and links long-term memory with emotion.
- The left and right hemispheres together make up the Neo-Cortex. This is the ‘thinking cap’ and the largest part of the human brain. It’s where conscious thinking and reasoning skills is centered, where we indulge in creative thinking, learning from new experiences and problem solving. It’s able to discern relationships between objects and construct patterns of meaning.
Grabbing the front brake and falling off was clearly a fight-or-flight instinctive reaction to threat. Despite her training, my trainee’s reptilian brain took over in a genuine emergency.
So, let’s put our brain to work riding our bike. We use all three parts in a complex interchange of roles as the situation in front of us changes.
We’re taught that we need to ‘think’ and ‘concentrate’ as we ride and drive. Unfortunately, that’s not how our brain works. The neo-cortex certainly can function to solve problems in real time but it’s time-consuming and exhausting. That’s why learning – including learning to ride – is so difficult and tiring. It’s also far too slow and attempting to use the thinking part of the brain for rapid decision-making in complex situations would fail because the huge number of tasks we perform as we ride would simply overwhelm it – at any moment we can only hold a few pieces of information in our conscious mind.
So in fact the brain works in a very different way. Wherever possible, the mid-brain processes incoming information subconsciously to match it to a previous experience that had a successful outcome. It’s fast and linear and uses trigger events. For example, if I say: “The cat sat on the…”, you’ll have no difficulty filling in the missing word. We learn the same patterns of association when riding. Once out of the beginner stage we don’t think about changing gear nor consciously work out what a red traffic light means and how to stop for it – we learn by previous experience.
The mid-brain can also throw up an alert about incoming information that matches an experience that did NOT have a successful outcome – sending an alert to our real-time brain along with a sense of unease; what some people call ‘Spidy Sense’ after the tingle that Spiderman gets when there are villains around. Hopefully, the heightened awareness allows us to spot the problem and deal with it before it becomes a threat to personal safety.
This autopilot is our ‘default’ state as we ride; using pre-learned ‘skill-based’ riding to carry out the necessary tasks automatically, where much of the data processing carried out entirely subconsciously. Many people doubt this concept of ‘riding on autopilot’ and blame ‘lack of concentration’ for accidents, but this really is the way our brain works to allow us to ride for and most of the time it works very well.
But there are also ‘failure modes’ when we are taken by surprise and these are often mistaken for ‘lack of concentration’.
Our brain lets us down in novel situations. If there is no matching pattern for the mid-brain to find in the database, it may prevent us from even realising a hazard exists. In the case of my trainee, it was the first car that had ever pulled out in front of her – the chances are she failed to registered a threat until it was about to block her path.
Even if we recognise the hazard, if we have no plan for dealing with the developing situation then the problem is handed to our real-time, slow-thinking neo-cortex. Unfortunately, it’s likely to be too slow in working out the solution to deal with the emergency. Even if my trainee had seen the emerging car, the chances of her associating the learned emergency stop routine in time were almost non-existent.
With no action taken our last line of defence, the ‘fight or flight’ reptilian brain steps in with a last-ditch attempt to avoid personal harm. Unfortunately, crocodiles never learned to ride motorcycles and its built-in routines are nearly always wrong – so she grabbed the brakes and fell off. This incidentally, is the source of what Keith Code calls ‘Survival Reactions’.
So an accident can happen to a rider with good skills, if there’s a lack of prior data in the database about where that particular skill needs to be applied. It’s practical learning which builds this database, not theoretical knowledge. This is what makes riding so dangerous for new riders – and to a lesser extent to returning riders who’ve forgotten what they knew. We quickly build the most fundamental knowledge about hazards and how to deal with them effectively – but only if we survive our first encounters with those hazards.
The black swan theory was developed by statistician and risk analyst Professor Nassim Nicholas Taleb to explain an event that comes as a surprise, has a major effect, and lies so far outside the realm of common experience that nothing we’ve seen or heard would help us predict one.
But if black swans are incredibly rare and unpredictable, all the other things that go wrong must be more common and also much more predictable – just like seeing a white swan. Errors are not novel or random but are a constant feature of all human behaviour. Very few crashes are ‘black swan’ events and within the population of motorcyclists accidents aren’t uncommon.
A key observation is that sixty years of safety campaigns based on the various different theories of accident prevention have failed to prevent the same type of collisions. Accident rates have dropped but motorcyclists are still crashing in the same ways and in the same places they’ve always done – they’re still making the same mistakes. The vast majority of motorcycle crashes happen because the rider didn’t predict one possible future from his actions, yet crashes and collisions happen with a statistically predictable frequency within the population of riders and they happen in non-random situations. Duncan MacKillop places these ‘standard accidents’ as Crashes on rural bends, Sorry Mate I Didn’t See You collisions at junctions, Nightmare Overtakes that go wrong, Shunts in traffic and Loss of Control incidents. Within the motorcycling population there are vanishingly small numbers of truly unpredictable black swan events.
If we’re approaching a junction, what’s the worst case scenario? A car pulling out on us has to be pretty high on the list. Yet it’s the most common collision there is. We’ve seen how a novice rider could be caught out but how come so many skilled and experienced riders end up failing to predict the obvious?
Nobel Prize Winner and psychologist Daniel Kahneman, PhD, has spent decades investigating human thought processes. Kahneman has described how what he calls our ‘System 1’ – our automatic, intuitive, very quick mind – usually lets us navigate the world easily and successfully. System 1 should be checked by ‘System 2’ – our deliberative, analytical and very slow mind – but when we begin to think we’re experts at what we’re doing, System 2 gets lazy and mostly just endorses the decisions reached by System 1 because using System 2 is both slow and tiring.
And this is where things begin to break down. System 1 leads us to make regular, predictable errors in judgment. Even if cars do pull out in front of us, if it last happened a long time ago and it’s a rare occurrence, our fast, intuitive System 1 mind may say “and it won’t happen this time either”. Our slow, analytic System 2 mind may know that cars pull out in front of bikes at junctions and that it really should act as a double-check on System 1’s decision to race through the junction. But the emergency occurs rarely enough that a lazy System 2 may fail to check our behaviour. The false “the car won’t pull out” predictions seemed true enough to System 1 as we approached the junction because prior experience was that “nothing ever pulled out of that junction before”. Usually nothing pulls out which reinforces our reliance on our faulty System 1. But when the car does pull out, it’s a total surprise and the reptilian brain takes charge and deploys its battery of wrong answers to the emergency.
If we accept Kahneman’s theories, we should see straight away that advice given to riders to consider “what you can reasonably expect to happen” is just asking for our judgment to be a product of our intuitive, lazy and fallible System 1. It’s not the reasonable event that kills us, it’s the entirely unexpected, unreasonable event.
Kahneman has also pointed out that we don’t spend much time asking what we don’t know, but that we make do with what we do know. Kahneman refers to this as ‘What You See Is All There Is’. Yet from that very limited mental model, we behave as though we know all there is to know. Even though we know that a hedge could hide a car at a junction, we behave as though nothing is there. We might even miss seeing the junction. Our decision is likely to be biased in any case – our natural tendency is to look for evidence supporting what we want to do rather than seek reasons we shouldn’t do something.
If something looks like a good idea, that’s likely our System 1 talking and we need to train ourselves to take a moment to to let our System 2 take a shot at analysing the data and ask if it’s really so great – we need to perform a ‘pre-mortem’ and look for the worst case scenario, not the best. It may take a little longer to get the desired result and we may miss a few ‘opportunities’. But we’ll avoid a lot of nasty surprises.
Resilience in the face of a threat of personal harm is not a property of a system, it is a capability of the individual within it to recognize the boundaries of safe operations, a capability to steer back from the boundaries in a controlled manner, a capability to recover from a loss of control if it does occur. Yet unlike pilots, riders are not systematically taught to understand, predict and recover from errors, whether their own or other road users’. They are rarely taught anything other than ‘best practice’ in the hope this will result in them avoid making their own errors. With limited understanding of human fallibility, our ability to make reliable decisions involving error – ours or someone else’s – is severely compromised. Faulty, incomplete, or imprecise data can only ever lead to ‘garbage in – garbage out’. It’s just as true when it comes to accident avoidance.
Bikers aren’t bad people. As we’ve seen, too much road safety is retrospective. “What should have been done” is a judgment, made from an after-the-fact position that often makes unrealistic assumptions about the ability of people to conform to a rule-bound, normative ‘ideal driving’ model based firmly on hindsight.
Individuals within the road safety industry question the effectiveness of existing interventions too. In his report on education in road safety for the RAC Foundation, Dr Frank McKenna (Professor of Psychology and a director of Perception and Performance) noted that:
“Educational interventions often are not sophisticated and are not based on any theory or on a formal body of knowledge. Designing an educational intervention with no guiding theory is like designing a medical intervention with no understanding of physiology.”
The newly-formed ‘No Surprise: No Accident’ group of which I’m part believes that if significant inroads are to be made into motorcycle casualties, two things need to happen to allow a ‘New View’:
- The road safety industry needs a single, robust, unifying, easily stated theory that fits with scientific principles and incorporates fundamental knowledge from the fields of human factors, neuroscience, psychology and perception as well from established practice in the aviation industry.In the midst of all the suggestions regarding behaviour modification and better skills training, the paper ‘Risk and Motorcyclists in Scotland’ came up with the same answer by suggesting:“the goal of completing all rides with no ‘surprises’ and making the point that ‘being a good rider is not enough’ or, rather, redefining what is seen as a good rider”.We are in full agreement with that statement because it’s surprises that precipitate unplanned and ultimately faulty responses that lead to accidents. We believe by redefining the definition of a good rider as one who avoids surprises and by promoting the goal of riding in such a way that the rider avoids surprises can form the central plank of an effective motorcycle safety strategy that avoids accidents.
- The main thrust of Sidney Dekker’s argument is that from INSIDE the decision-making bubble, behaviour is rational and thus to produce meaningful interventions the road safety industry needs accept that road users’ assessments and actions made sense at the time, given the circumstances that surrounded them. Accepting that the vast majority of riders are not ‘bad-apples’, just ordinary riders doing ordinary things in the moments before an accident, we can also see that the idea that ‘better’ riding skills or deterrence as strategy for behaviour change are flawed. If I don’t think I’m doing anything wrong in the moments before an accident, WHAT should I change, even if I WANT to change?
And so to find out about human error, knowing where people went wrong is far less important than finding out why their assessments and actions made sense to them at the time. Pilot error might be the final act that actually crashes the plane. But the pilot did not deliberately set out to crash the plane – his intent was to perform his job correctly. So just WHAT was the preceding decision that led to the faulty choice and just WHY did the chain of events LEAD to pilot error? Even risky behaviour must have made some kind of sense just before the crash.
We believe the single unifying theory of ‘No Surprise: No Accident’ can increase the likelihood of a rider using predictive riding and identifying for themselves the predictable circumstances which are likely to result in human error by themselves or another road user. Reduce the chance the motorcyclists will be surprised, and we increase they chance that they will be able to take avoiding or evasive action.
We see two key strategies:
- We need to discover ways of helping riders to a genuine, long-lasting understanding of what are TO THE INDIVIDUAL RIDER more-or-less theoretical hazards. Safety is not an intellectual exercise and education needs to focus on training motorcyclists to learn how ‘reverse engineer’ common crashes so that they really, truly, deeply understand them so the rider makes an emotional connection with the hazard – this is particularly important for new riders. We need riders who genuinely understand how they make the mistakes that lead to single vehicle crashes. The paradox of common accidents is that to each and every individual rider, the number of genuinely life-threatening situations that rider will experience is also vanishingly small. In the case of the young rider critically injured by an accident, it may be the only one in their motorcycling career. We need riders who genuinely understand “two to tangle” collision dynamics so that they can avoid being caught up in ‘the other fellow’s’ mistake. As they we gain skills, we need to teach them to avoid complacency and use those skills to widen margins for error, not exploit them for gain, progress, smoothness or polish. Mostly we need all motorcyclists to see riding as on-going disaster management – after all, a disaster really is just a simple slip-up away.
- Secondly, motorcyclists’ expectations need to be shifted away from the idea that “we’ll be safe if ‘THEY’ do the right things”, whether that’s other road users, highway designers or even the courts. If anything, the ‘Perfect Ride’ idea that no-one should make mistakes also means motorcyclists have even less tolerance of fallibility in others. Many riders firmly adhere to the ‘Old View’ of rider safety, arguing that many collisions are the result of mistakes by ‘bad-apple’ road users whose behaviour puts us at risk. Even in 2014 rider groups are still campaigning along these very lines, and arguing that those drivers should be educated and punished into “taking more care” or “looking harder for bikes” rather than encouraging riders to look out for their own safety. There’s no reason that interventions cannot be aimed at drivers but as motorcyclists we need to stop thinking that the system of roads and our interactions with other users should be be ‘fixed’ for us.
Riders aren’t bad people, far less bad-apples. But they are not making the best of their talents and abilities because they are not getting the best advice or knowledge. Fundamentally, we need to produce riders who can accept the road is not a perfect environment and that other road users are fallible, then harness the power of predictive riding to avoid being surprised by events they could and should have foreseen. This means we must find ways of equipping motorcyclists with the capability to recognise, and recover from, situations that could lead to a loss of control over the situation, and resultant personal harm.
We may seem to be stating the same old things – anticipation, playing the “What if…?” game, etc, aren’t exactly new. But we believe that making this fundamental reversal of perspective away from ‘bad-apples’ leads to a different kind of safety thinking where we cease to see motorcyclists as the source of risk that undermines an otherwise safe system but rather as the source of diversity, insight, creativity, and wisdom about safety. Accepting “being a good rider is not enough” and promoting “the goal of completing all rides with no ‘surprises'” should be the overarching principle which riders should aspire to, whilst at the same time offering a robust and logical hook on which to hang that eminently achievable goal – now it’s up to us to find ways of achieving it.
No Surprise: No Accident. A ‘New View’ of rider safety