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How to Help Your Fleet Drivers Avoid Distractions

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Your fleet drivers face an ever-growing number of distractions on the roads, and those distractions are causing severe consequences: the total number of distraction-affected collisions, total collisions, and motor vehicle deaths all soared between 2011 and 2019

Distracted driving happens when a driver is not paying full attention to the task of driving safely. Instead, the driver’s attention is divided between safely operating a vehicle and anything else, such as eating, reviewing paperwork, or feeling drowsy. 

Technology can play a key role in reducing distracted driving and help keep your drivers — and pedestrians, cyclists, and other drivers in your community — safe. But to achieve the safety improvements you’re looking for, you need technology that genuinely helps your drivers. 

Overall, collisions are on the rise, and so are collisions that involve distractions. Data from (1) the National Highway Traffic Safety administration for 2011 and 2019 and from (2) the National Safety Council.

Learn how you can address these trends today with ideas from a panel of industry experts, including our Chief Product Officer. View the Fleet Safety Conference session now.

Distracted driving solutions: what works for fleets

New tools, which might look like a camera, can detect signs of distracted driving and sound an alert to remind drivers to focus on the road. The alerts act as a friendly in-cabin coach to automatically encourage safer behavior. But not all of these systems are equally helpful. 

To prevent a collision, a distracted driver needs both an alert and time to respond. Consider a driver who’s looking at a cell phone. The alert sounds. Then, the driver needs to put down the phone, refocus on the road, and finally take action. Fleet drivers, who often handle large, heavy vehicles that take time to stop, need alerts that give them sufficient warning, meaning their alert system needs to be able to predict what’s about to happen. With just a moment or two of warning, the driver won’t have enough time to respond effectively.

To qualify as predictive, an alert system also needs to account for the wide range of distractions facing drivers, from phones to paperwork to snacks and even drowsiness. Yet most distracted driving alert systems can only detect and warn drivers about a few behaviors.

So how can an in-cabin alert system predict what’s about to happen and give drivers sufficient warning? That requires artificial intelligence that can understand driving behavior the way a human coach would — that is, the AI can detect an extensive range of potentially risky behaviors — and work for drivers with different appearances, attire, eyewear, and even in-cabin lighting.

For AI to understand distracted driving and provide predictive alerts, it can’t look only at the driver’s behavior. It also needs to watch the road ahead because distracted driving takes place in context. 

A driver is adjusting the stereo system — that’s the distraction. Then, a car pulls in front of the truck, and suddenly a collision is imminent. That’s the context. The best distracted driving solutions will detect both these risks and give the driver an early warning to help prevent that collision or, at a minimum, mitigate its severity.

Here, the right AI can outperform a human coach: it can watch the road and the driver simultaneously, assessing the distraction and the context to help prevent collisions. A human coach would have to switch from looking at the driver to the road and back again and wouldn’t be able to process all the information rapidly enough to provide an early warning.

Avoiding false alerts and alert fatigue

Let’s imagine a different scenario. Again the driver is adjusting the stereo system, but there’s no external threat such as a car pulling in front of the truck. Here, the ideal solution will sound progressive alerts that become more severe the longer the distracted behavior continues because the longer the driver’s eyes are off the road, the more likely a collision becomes. On a wide open road, a collision and the alert sounds may not become imminent. 

Sounding an early warning in this scenario might seem like a good idea, but constant early warnings cause alert fatigue and annoy drivers. Drivers may then ignore the alerts or even tamper with or obstruct the device that’s meant to help them. 

Alerts that go off when the driver isn’t distracted are another key cause of alert fatigue. 

At first, drivers using a system prone to false alerts will quickly learn to ignore the alerts. Over time, though, they’ll experience more frustrations. Too many false alarms could unfairly affect their performance reviews, and they may seek jobs elsewhere. 

On the other hand, if the system is not sensitive enough, it won’t help drivers avoid collisions. You won’t see the safety gains you want, and you won’t see a return on your investment.   

For distracted-driving alerts to work, they must matter. They must give drivers consistently useful feedback that helps them avoid collisions. In other words, the best distracted driving solution is highly accurate. As drivers spend time with a highly accurate system, they learn from experience that the technology is a valuable assistant, not a distraction or irritation

Alerts that matter also don’t add to the cognitive load drivers already bear every day, especially when they’re operating sophisticated vehicles with multiple systems, like trucks used by utility maintenance workers. 

To find a solution that produces highly accurate, predictive alerts and accounts for driving behavior and context, look for one with AI that: 

  • Detects external risks, such as whether your driver’s vehicle is about to be rear-ended, even in less-than-ideal conditions: at night, at unusual intersections, or when there’s a combination of risk factors. 
  • Detects internal risks, such as a driver eating or looking at a cell phone, and does so even if the driver is wearing sunglasses. 
  • Fuses this information to provide genuinely helpful real-time alerts. 

Fusion must happen quickly, so look for a distracted driving solution where the AI processing takes place in the vehicle — sometimes called “on the edge” — rather than in the cloud. You’ll then have a solution that works almost instantly because data doesn’t have to travel from the vehicle to the cloud and back again, and one that works even when the vehicle can’t connect to the cloud. 

Learn more about the importance of alert accuracy from a panel of experts, including our Chief Product Officer, by watching an insightful session from the Fleet Safety Conference.

What are the best distracted driving solutions for fleets?

In addition to being powered by predictive-AI, accounting for context, and being highly accurate, here are five more key criteria the best distracted driving solutions meet. 

The alerts are audible only so they don’t add more visual distractions for a driver. If a light flashes as a visual alert, the first thing a driver will typically do is look at the light, meaning that alert has actually delayed the driver’s ability to focus on the road. Audible-only alerts allow drivers to immediately return their eyes to where they need to be. 

They work in real-world driving conditions. Your drivers are on the road at night, when it’s raining, and when it’s snowing. They encounter peculiar intersections and unusual combinations of risk factors. Distracted driving in these situations is especially risky, so a distracted driving solution must perform accurately and effectively in them, or it won’t help drivers.

They enable you to reduce manual coaching time yet still improve safety. Distracted driving alerts provide in-the-moment feedback and guidance to your drivers to help them improve performance. But the alerts are just one part of an effective distracted driving solution. 

In many instances, initial installation of an alert device will yield quick improvements, but human coaching is essential to ensuring those gains endure. Many managers with coaching responsibilities are pressed for time, and they have limited insight into which drivers most need coaching and on which behaviors. It’s difficult to know how to create the biggest positive impact on safety in the time available. 

An ideal distraction alert system guides your coaching efforts. You see, at a glance, which drivers aren’t responding to the in-cab alerts or are engaging in other risky driving behavior, including not only the ABCs (acceleration, harsh braking, cornering) but also a broad range of additional behaviors that research shows influence risk, such as a history of past collisions or near-collisions

The best systems also automatically tag critical, high-severity events and upload relevant video and additional data — such as location, vehicle speed, and road conditions — rather than recording everything. This way, you can see what happened in the video, understand the context, and pay attention to the most important events. Advanced AI makes this feature possible by acting as the incident review and data analysis team you wish you could hire. 

As you target your coaching at drivers who need the most support, be sure to also recognize your safest drivers. To make the most of your time and improve driver retention, look for a distracted driving solution that helps you quickly identify your top performers so you can reward them. 

When your distracted driving solution includes all these elements, you have the power to make the most effective, highest impact coaching decisions every day.

They respect driver privacy. Automatically tagging and uploading only relevant video and data enables efficient coaching. It also helps protect driver privacy. When drivers know they’re not always being recorded and that their managers will only see pertinent performance issues on video, they’re more likely to embrace the technology. 

Some systems offer managers the option to do a surprise drop-in and suddenly start watching a driver, which often feels intrusive or even creepy to drivers. The right technology, one that has highly accurate AI at its core, makes drop-ins unnecessary and gives drivers the privacy they want.

They’re part of a comprehensive vehicle safety solution. Reducing distracted driving is a critical component of fleet safety, but it’s not the only one. 

When searching for a distracted driving solution, look for one that’s part of a holistic safety solution that helps drivers reduce multiple risks in real time and helps you improve fleet safety over time.

There’s much more to explore when it comes to helping your drivers reduce distracted driving. Learn what you can do today by watching an informative and engaging session from the recent Fleet Safety Conference. Our Chief Product Officer, Yoav Benin, joins a panel of industry experts and covers:

  • How some fleets are able to reduce their rate of severe distractions to zero and maintain that level for months.
  • How technology can help clear drivers when they’re not at fault and help reduce claims costs.
  • Why it’s essential to take a holistic approach to reducing distracted driving.  

Watch the session today. 

Author bio: The Nauto Story Scout is always on the lookout for ways to help you improve driver safety, prevent collisions, and make our roads safer for all. The Story Scout learned many of its skills from the Nauto predictive-AI, which is always on the lookout for risks and distractions to help your drivers stay safe. 

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