Mapping accurate fatigue black spots

Imagine driving your journey to work today with no road signs or road markings.

You could possibly be driving an unfamiliar road with no recommendations or advice on speed limits or safe braking distances or warnings of steep descents or hairpin bends.

This may sound implausible, but when it comes to drowsiness and fatigue, we currently drive without any real warnings about the dangers we could be facing.

That driver approaching you from the opposite direction on a dual carriageway could be dangerously fatigued. A fatigued driver is a hazardous driver and as they become drowsy, they enter a state where they are unable to react quickly enough and are at risk of falling asleep at the wheel.

Although we all think we can stop ourselves from falling asleep, it is a scientific fact we cannot, and often we are unaware or unable to read the signs indicating we have entered the state of drowsiness.

Black spot

We have all heard the term ‘black spot’ – a black spot, or sometimes called a ‘driver fatigue crash zone’ on a public road is a place where over time numerous accidents have occurred. Authorities often use this accident data to make whatever changes they can: they might decrease the speed limit, add a crash barrier or introduce other measures.

The problem with all of these is often it is too little too late. How many times have we heard the phrase “the accident occurred at a known black spot”? If it was a known black spot, and accidents continue occurring there then surely the countermeasures in place have not been entirely successful.

It is time for a new approach

What if we could predict locations where accidents were more likely to occur? If we assume roads are designed to be as safe as possible, then we must turn our attention to individual vehicles and drivers.

Over the years, Optalert has been gathering massive volumes of data from drivers protected by our fatigue detection technology. Recently we overlaid our millions of driver fatigue scores over satellite roadmap images and this data identified specific ‘at risk’ locations. These locations have proven over time to have recorded consistent high risk warnings for our drivers which means they can be objectively identified as driver fatigue black spots.

Fig 1 – historical fatigue information creates a fatigue hot spot ‘heat map’

Optalert’s ability to identify driver fatigue black spots with accuracy is a significant step toward reducing fatigue-related accidents.

In the future, this information could be used to significantly increase the safety of the general driving population. Truck rest stops could be located a little more scientifically – aligned with these calculated fatigue black spots. Current fatigue warning signs could be located at actual danger areas. Road construction could be changed. Ripple strips already effective to denote a change of conditions, such as an intersection after a long straight, could be deployed around areas known to be driver fatigue black spots.

Authorities around the world have been looking at fatigue black spots and have taken action in various forms to address the problem. Unfortunately, it is often based on assumptions and interpretation of accident data, as to date, there has been no data for drivers who have had unreported near misses or micro sleeps.

We now have the data, let’s save some lives.