Seeing Machines leveraged its unparalleled, naturalistic driving data from Guardian, its real-time driver fatigue and distraction solution for fleets, to pinpoint and address the trends surrounding risky driving habits. Designed to provide a deeper understanding of driver and fleet behaviour, the 2022-23 Guardian Insights Report delves into deidentified data from 25,202 vehicles across 2,585 fleets in Australia and New Zealand, for the 12-month period to 30 September 2023.

Learn more and download the Guardian Insights Report

Click to listen to the full interview below or scroll down to read the full transcript.

0:00 Leon Delaney
You may have heard of a company called Seeing Machines, which is a locally based Canberra business that has attracted quite a lot of attention in recent years because of the nature of the technology that they have created. And they’ve released their first distraction report on heavy vehicle drivers. And the report found that heavy vehicle drivers experience, would you believe, around 60 fatigue and distraction events every hour? I mean, that’s alarming. Sinian. Sorry. Senior Human Factor Scientists. Scientists at Seeing Machines, Dr Kyle Wilson. Good afternoon.

0:40 Kyle Wilson
Afternoon. How you doing?

0:41 Leon Delaney
Not too bad. Thanks very much for joining us today. First of all, what exactly is your technology and how does it work?

0:47 Kyle Wilson
Yeah, so our technology, it’s a safety system which heavy vehicle operators use to protect their drivers from distraction but, but also importantly fatigue risk. So, this is an, a piece of hardware that sits in the cab of a, of a truck. It’s pointed towards the driver and it’s looking for key indicators of behaviours, but behaviours and movements that are indicative of fatigue and distraction. When, when it picks these behaviours up, it will alert the driver in real time to prevent a crash. Essentially. As well as that, there is a, a snippet of video that’s actually sent to some trained Seeing Machines analysts who will review the footage, verify you know whether it’s a, it’s a genuine fatigue event, and then they can actually contact the, the customer to provide further intervention.

1:47 Leon Delaney
So, if in the event of a driver for example nodding off to sleep, can the machine sound an alarm that’s significant enough to actually wake the driver up.

1:59 Kyle Wilson
Yeah absolutely. So, so what you’re talking about there, you know, you know we, we term a microsleep. It’s a very common thing especially in heavy vehicle drivers. Our, the technology that we have is trained on, on a, a really significant amount of data. Where we have lots of those microsleep events in the datasets and we, we’ve become very, very good at detecting these events. So, for a driver that does close their eyes in a way that, that you know appears to be a microsleep, immediately the, the system will vibrate the driver’s seat, it will sound an audio alarm and yeah this is just super effective. You know it does save drivers lives. So, it’s important.

2:52 Leon Delaney
It certainly is and the lives of other road users as well because a distracted, or a, or a driver that is fatigued could well collide with somebody else and cause serious harm or worse to innocent bystanders. So, this particular report, the distraction report, how was it compiled, how much, how did you collect all the data and what does it show?

3:17 Kyle Wilson
Yeah. So, you know, we have a really unique lense into this problem given that we have our technology and so many vehicles and, and we have, we have you know, we have this problem occurring in, in, in real time. So, we, we’ve taken over 23,000, data from over 23,000 vehicles in Australia and New Zealand over the last 12 months. This consists of over two and a half thousand fleets and all of the events that we’re reporting on here, have been verified. So, they’ve been looked at by a trained analyst who has confirmed that you know, yes that is a, a genuine event and, and it’s, it’s given a really interesting and important insight into the times of days, the days of the week that are, that are most common for distraction and fatigue events.

4:15 Leon Delaney
Is there a particular time and a particular day where the danger is greater?

4:20 Kyle Wilson
Yeah, yeah there is, and it differs for fatigue and distraction. So, for fatigue, drivers between the hours of 4:00 to 5:00 AM that, that’s a really high-risk time. So, and our data, this is the most common time for a driver to have a fatigue event. The day of the week was Saturday and this all, it all really makes sense when you consider that, you know as humans, we’re not in control of our circadian rhythm. It doesn’t matter if you’ve woken up at 3:00 AM and you’ve, you’re only one or two hours into your journey. At 4:00 AM, your body is telling you that it’s time to sleep. So, it really makes sense what, what we’re seeing here.

5:09 Leon Delaney
OK. And the distraction events occurred at a totally different time of day.

5:14 Kyle Wilson
Yeah, that’s right. So, it was early in the morning or later in the morning. It was 8:00 to 9:00 AM when drivers were most likely to be distracted. And the day of the week was Sunday. So yeah, I mean, I guess that’s probably indicative of, of people, you know, being tempted to, to use their phone, maybe they’re being contacted by others at that time. But yeah, a little bit different to the, the time that we saw for fatigue.

5:42 Leon Delaney
Yeah. What can we do with this data to make our roads safer?

5:47 Kyle Wilson
Well, yeah, I mean for a start it’s a, it’s an important tool that heavy vehicle operators can use to, you know recognise what are those really high-risk days of the week, times of the day that our operators are likely to be grappling with, with these problems with. It’s, you know, these are, these are really important trends and if you don’t have this technology installed already there, there’s just really no way of, of being able to tell, to be able to recognise these trends in, in your own fleet. So, I think it’s an important tool for them in that way.

6:24 Leon Delaney
Indeed. Thanks very much for your time today.

6:26 Kyle Wilson
No worries. Thank you.

6:27 Leon Delaney
Thank you. Dr Kyle Wilson, Senior Human Factors Scientist at Seeing Machines. News is next on 2CC.