A few years back, I came across an interesting experiment. And the results may well surprise you.
But first, some background. Historically, we’ve been aware that motorcycles are hard to spot – low salience in the jargon – so research has largely focused on enhancing drivers’ ability to detect motorcycles. Hence the focus on conspicuity issues, and interventions such as day riding lights, novel lighting arrangements, brightly coloured or reflective clothing, helmets and fairings.
But although research has shown that these interventions sometimes have positive effects, the fact is that drivers still “look but do not see” motorcycles.
More and more research has focused on just how we see the world around us – the topic of visual perception. As we’ve seen in articles here, we’re all subject to looking at an object in ways that change depending on context.
In one instance, researchers suggested that our prior experience changes the way we search a scene:
“When viewing a photograph or scene observers most commonly fixate on the most physically salient regions first, but if the observers have relevant content expertise (for example, a history student viewing a photograph of artefacts from the US Civil War) then they focus less on physically salient areas and more on semantically meaningful areas.” ((Humphrey & Underwood, 2009)
This aligns with studies that suggest that motorcycle license holders have that ‘relevant content expertise’, and that as a result, ‘dual-drivers’ are better at detecting motorcycles than drivers without experience riding on bikes. We pick out the ‘semantically meaningful areas’ – ie, other motorcycles – more rapidly from the other features.
This same phenomenon is seen when we look at paintings. Eye-tracking shows that rather than study the entire picture for meaning, our brain takes short-cuts to direct our attention to limited parts of a scene. And just WHICH parts we study changes depending on the question asked.
So one team of researchers suggested that an observer’s ability to detect motorcycles could be changed by making that observer more aware of motorcycles, and that they would do this by the simple expedient of showing a group of drivers a traffic scene containing more motorcycles.
Because motorcycles are hard to spot, the researchers deliberately picked two test objects for their experiment; a bike but also a bus, something which certainly isn’t low salience.
This is how the experiment worked.
The simulator was based on a vehicle cab constructed from genuine vehicle parts and standard controls together with an audio feed, to give an accurate ‘look and feel’, whilst the visual environment was provided by three 19″ screens providing a 120 degree view and what the researchers describe as ‘medium fidelity’.
The test drives were set in urban areas, with regular intersections and with a 60 kph / 37 mph speed limit. Apart from the target vehicles, everything else was four-wheeled. Vehicles appeared from right and left, as well as ahead. Traffic was moderate, with the target vehicles appearing at random.
The drivers were split into two groups, placed in the simulator and sent on a 7.5 kilometre ‘exposure’ drive. All they had to do was drive following normal road rules, but the traffic stream was different. One group encountered an unusually high number of motorcycles with no buses appearing. The other drove with an unusually high number of buses but with no motorcycles appearing.
Having completed that, both groups were sent on a second, longer 39 km drive, where they were asked to count the number of motorcycles or buses they saw, and they were told that their reaction time and accuracy were both being measured.
In this longer drive, the ‘high motorcycle prevalence’ drive contained 120 motorcycles and 6 buses. In the ‘high bus prevalence’ drive, the numbers were reversed, with just 6 motorcycles and 120 buses.
Two custom buttons on the steering wheel allowed the subjects to respond by pressing the appropriate button when they detected the targets. At the same time, their driving performance was monitored by a range of sensors including speed, lateral position, braking and acceleration.
The participants were recorded as having missed a target if they failed to respond, or responded after the target had passed them.
You’ll probably not be surprised that the drivers told to look for buses missed seeing some motorcycles. You probably WILL be surprised that when tasked with looking for motorcycles, drivers missed a greater number of buses.
That’s almost certainly not what we’d expect.
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Before you panic, most of the drivers successfully detect ALL vehicles. The detection rate was actually over 99%.
But looking at the less than 1% of cases where drivers failed to see one or the other, 68% detected all buses and 78% detected all motorcycles.
What we’re seeing here is research based on on something called the ‘prevalence effect’. The original theory grew out of research into detection issues in medical screening procedures. Highly trained staff looking through microscopes at tissue samples tend to miss the rare anomalies, even though they know what they are looking for.
In effect, motorcycles are just like those medical anomalies because we make up less than 1% of traffic on UK roads. Although drivers know they will encounter motorcycles and should “Think Bike”, the researchers wondered that if they are so rare that drivers subconsciously don’t expect to encounter any and instead focus on other parts of the scene.
Now, I must make clear again that this isn’t ‘carelessness’, it isn’t ‘not looking properly’, it isn’t ‘bad training’ and it isn’t any of the other blame-game explanations we so commonly see. What it is, is yet another example of the hidden power (and weakness) of the brain, working far below the level of our awareness.
Of course, the participants in both groups didn’t realise they hadn’t seen some of the motorcycles or some of the buses. As far as the brain’s concerned, “what we see is all there is”.
The authors’ conclusion was that the detection rates for motorcycles would be improved by the ‘simple’ expedient of putting more motorcycles on the road.
Not too surprisingly the research has been picked up by interested outfits such as FEMA and the MCIA and used as evidence that motorcycles should be promoted as a means of transport to make them safer.
In reality, we’re not about to see floods of powered two-wheelers on the roads, and drivers detection rates are not going to snowball overnight.
But don’t forget the reverse prevalence effect operates. We’re used to seeing plenty of cars – it’s easy enough for us to spot them. All we have to do is understand the Science Of Being Seen to see how drivers make ‘looked but did not see’ mistakes, then take the necessary action to avoid the collision! No Surprise? No Accident!
Can Drivers’ Expectations and Behaviour Around Motorcycles Be Influenced by Exposure?
Beanland, Lenne and Underwood
Thank you for your interesting articles which I have only just started reading.
I am new to motorcycling but have been cycling for 45 years.
On a bike another factor is at play and I am sure the same goes for motorbikes. It is not just about being seen by a car driver, it is about how a driver processes the information once they have seen you. I think that is partly based on instinctive risk perception from their point of view. Time after time I have seen drivers clock me and then pull out anyway as I pose no risk to them in their car. If they had seen me at the same distance and speed travelling towards them driving a crane they would have stayed put out of fear for their own safety.