How Hazard Perception Can Identify Risk in Professional Drivers

The eyes have it! Can you spot the safe from less safe driver?

Take a look at this video below, it shows the eye-movements of two Fire and Rescue Service drivers who watched one of our hazard clips filmed from a fire appliance on a blue light run.

 

In the video you can see lines and circles appearing over the scene. The lines show how the drivers’ eyes move around the road. When the eyes pause on something, a circle grows. These pauses are called fixations. The larger the circle, the longer the driver looks at that location.

 

These fixations show what the driver is paying attention to, giving us insight into their hazard perception and how they read the road.

Two drivers are shown in the video. One set of eye movements is blue, and the other is orange. One driver is considered low risk, with very few crashes while driving for the fire service. The other driver is high risk and has been involved in significantly more crashes.

The question is : Can you tell which driver is the high risk driver — orange or blue?

 You should have noticed that the fire appliance is passing a bus on its right when a car almost emerges from a side road behind the bus into the path of the emergency vehicle. This is our hazard. The car ultimately decides not to pull out, but it is still important that drivers detect this hazard as early as possible.

 

If you looked closely, you will have seen that our orange driver looks at the hazard first. The blue driver also looks at the hazard, but slightly later. The difference in timing may appear small, but even half a second’s earlier detection can be the difference between avoiding a crash and not.

Graphic comparing a low risk driver and a high risk driver

As you might expect, the orange driver is our low risk driver, while the blue driver is classed as high risk based on their previous collisions.

 

If we were always able to tell where drivers were looking, perhaps we would have a good chance of identifying those drivers who are more likely to have a collision in the future. While eye tracking technology has improved incredibly over the years, it remains somewhat specialist and expensive equipment. 

Fortunately, there is a cheaper and easier way to assess how good drivers are at reading the road…

In two of our recent blogs, we explored some of the benefits of hazard perception assessment and training for both learner and fleet
drivers.

 

Over 50 years of research shows that hazard perception skill is consistently linked to collision risk and that the test can distinguish safer from less safe drivers. In addition, the benefits of the test are significant, with estimates suggesting:

Damage only collisions icon
8,535 fewer damage only collisions
Injury collisions icon
1,076 fewer injury collisions
Financial savings icon
£89.5 million saved

 

These benefits are estimated to result from the introduction of the test.

How hazard perception tests identify driver risk

Essentially, hazard perception tests are doing the same thing as our eye tracking study – separating safer from less safe drivers on the basis of whether they look at hazards.


With eye tracking equipment we can definitively tell if and when a driver looks at a hazard. With a hazard perception test however we record drivers’ response times to seeing a hazard. These response times should relate directly to when they first spotted the hazard, but are much cheaper to measure than using complex eye tracking equipment.

Key Idea

Hazard perception tests and eye tracking studies measure the same underlying skill: whether drivers detect hazards early enough.

 

Eye tracking shows exactly where a driver looks. Hazard perception tests measure how quickly drivers respond when they detect a developing hazard, providing a practical and cost effective way of assessing the same ability.

Why traditional hazard perception tests fall short for fleets

Despite these successes, the approach has yet to gain traction in the fleet training and assessment industry for identifying risk in fleet drivers. The reasons for this are without doubt multifaceted, and we alluded to some of these in our previous blogs.

Key limitations of traditional hazard perception tests

Despite these successes, the approach has yet to gain traction in the fleet training and assessment industry for identifying risk in fleet drivers. The reasons for this are without doubt multifaceted, and we alluded to some of these in our previous blogs.

Hazard warning symbol indicating potential danger.

Ambiguous scoring windows

Professional drivers often report pressing before the scoring window opens because they predict the hazard very early. As a result, correct anticipation may not be rewarded.

Lack of a measure of accuracy

Traditional hazard perception tests record response times, but we have no way of knowing exactly what drivers are pressing for. This means we cannot always be certain that the response reflects the true hazard.

Target and checklist icon representing accuracy and correct hazard identification.
Heavy goods vehicle icon representing HGV drivers.

Lack of a vehicle specific content

Many professional drivers complete hazard perception tests designed for learner drivers. For example, HGV drivers may complete a test filmed from a car driver’s perspective, which does not reflect the hazards they encounter in their day to day work.

 Fortunately, there are variations of the hazard perception test that can avoid these issues whilst being able to identify driver risk, even better than the traditional test!

The Hazard Prediction Test

Several alternative tests have been developed to overcome the ambiguity of the button response, with some tests requiring users to click on the area of the scene where the hazard appears (yet still within a time window). Other variations remove the need for a scoring window altogether. Instead of pressing a button as quickly as possible when a hazard is detected, the video stops just as the hazard begins, and the screen is occluded. The driver is simply asked, “What happens next?” and must choose from one of the four options on the screen. 

Hazard prediction test screen showing multiple choice options asking what happens next in a driving scenario

If the driver has read the road appropriately, they should be able to identify the correct answer, thus a measure of accuracy is provided. This test is known as the ‘Hazard Prediction Test’, and we have published evidence to show this test is better suited to professional fleet drivers than the traditional DVSA button-response test when you need to identify risk within your fleet.

How is the Hazard Prediction Test Relevant for Professional Drivers?

In a research project conducted at Nottingham Trent University, we developed both a hazard perception and a prediction test for professional fire service drivers. The aim of the study was to develop a test that could identify safe from less-safe drivers to better target training needs within the fire service. With assistance from Nottinghamshire Fire and Rescue Service (NFRS), the project began by filming from fire appliances on blue-light training runs around Nottinghamshire for two weeks. A multi-camera system was used to capture footage from the forward view of the cabin and the 6 views that the driver can see through the mirrors (see below).

An image of a schematic representation of where cameras are attached to a fire appliance to develop a hazard test for fire appliance drivers

Once all the footage was collected, the footage was edited into a graphical overlay that had been designed to represent the interior cabin of a fire appliance.

 

The footage was then reviewed by a team of transport psychologists and fire service personnel to identify content of interest. A selection clips were chosen on the basis that they provided at least one hazard of sufficient concern. These clips were then developed into both a hazard perception and a hazard prediction test.

 

For the hazard perception test, hazard windows were set using an onset (earliest point hazard could be detected) and offset time (latest point a driver could make a correct response to the hazard). For the prediction test, the clips were edited to finish just as the hazard became visible. At this point the screen was occluded, and we asked drivers ‘What happens next?’, with four possible options displayed onscreen (only one was the correct answer, and was indeed what happened next!).

How can we know that the tests work?

With the tests developed, we then wanted to determine whether either test was able to identify risk in professional fire service drivers. You might wonder just how researchers know that their tests work? How can we be sure that a test can identify those risker drivers who are more likely to have a collision in the future?

Comparison graphic showing safe versus less safe decision making with green check shield and red warning shield

To answer these questions, researchers typically evaluate tests using safe and less-safe drivers (defined objectively by their collision history), or they use novice and experienced drivers (as we know that novice drivers are far more likely to have a collision than experienced drivers). If a hazard test is to be deemed valid, it must show a statistically significant difference between the scores of these two groups of drivers. If this is the case, we can be more confident that the test is truly measuring our targeted driver safety skill.

Testing Drivers!

To validate our fire appliance hazard prediction and perception tests, we tested both assessments on four different driver groups:

 

  • 🚒 Novice fire appliance drivers (in training)
  • 🚒 Experienced fire appliance drivers
    • ⚠️ High risk drivers (based on collision history)
    • ✔️ Lower risk drivers (based on collision history)
  • 🚗 Matched car driver control group (non fire service drivers with similar age and driving experience)

All drivers completed both the hazard prediction test and the traditional hazard perception test, and their eye movements were recorded.

What did we find?

For the hazard perception test, we found that all fire service drivers (regardless of experience) were faster at detecting the hazards than the car drivers. Whilst this suggests the fire service are better than the average car driver (which is good news!) this result was not particularly helpful to the fire service. They really wanted to use the test to identify which of their drivers might have a crash in the future.

Interestingly, their eye-movements showed that the experienced fire service drivers spotted more hazards and looked at them faster and for longer than the novice fire service drivers. Yet, even though the experienced drivers were spotting the hazards faster, this wasn’t reflected in their response times.


“But I thought you said response times should directly relate to how quickly one looks at a hazard?”

 

Theoretically, yes. But there is evidence that the relationship between looking at a hazard and pressing a button is more complex than we might think.

Unfortunately, pressing the button does not just measure the time it takes to spot a hazard. It also includes the time that drivers take to decide that it really is a hazard. When drivers judge whether something is hazardous or not, they compare it to events they have witnessed during their years of driving. As highly experienced and trained drivers are more likely to avoided a range of hazards over the years, they may spot a hazard quickly, but may then let the hazard develop before they consider it to be a hazard to themselves.

 

Psychologists call this criterion bias, and this could explain why some may allow a hazard to develop more before making a response. Regardless of the reason, short of putting eye-trackers on all fire service drivers, our fire appliance FA hazard perception test was not that useful to the fire service for identifying which of their drivers are most at risk of a collision.

Criterion bias concept illustrated with bold text highlighting bias in decision making

For the hazard prediction test, we observed again that our control group of car drivers were worse at predicting the upcoming hazard (remember, this test uses a measure of accuracy, not a response time). However, we also found that the low-risk FA drivers were now significantly better at predicting the upcoming hazard than the high-risk drivers! Finally we had a test that could be used to identify which fire service drivers are at greater risk of collision (without having to rollout expensive eye tracking equipment in every fire station!).

Overall Conclusion

Whilst both the hazard perception and hazard prediction tests could identify a difference between normal car drivers and fire service drivers, only the hazard prediction test was able to discriminate between safe and less-safe fire service drivers. Following this, Nottinghamshire Fire and Rescue Service rolled out the use of our hazard prediction test with their drivers in both acquisition and refresher training.

This research focused on one type of professional drivers – fire appliance drivers – but as discussed in our previous blog, different driving roles encounter different hazards. We believe that any hazard assessment or training should match both the type of driving and vehicle that a driver does in real life. To that end, we have been developing different hazard tests for these different roles and we now assessments and training available for HGVs, cars, vans and even cars on emergency response drives.

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