Distracted driving is anything that inhibits a driver from paying full attention to the task of driving, or inhibits them from being fully engaged to adequately respond to changes in the driving environment. According to the National Highway Traffic Safety Administration, distractions typically fall into three categories:
What are common distracted driving behaviors?
Distracted driving comes in a variety of forms. These behaviors include instances when a driver is looking down or away from the road ahead for a period of time long enough to lose situational awareness of the forward driving scene like:
- Drowsy driving
- Talking on a cell phone
- Texting
- Eating
- Smoking
- Using a tablet
- Reading paperwork
- Programming an in-vehicle infotainment system
Why is distracted driving a problem?
A driver may be engaging in one or more distracted driving behaviors at any given time. The result is the same: heightened risk of a collision, injury, or even fatality. There’s little argument that distracted driving is one of the fastest growing threats to safe driving today and cause of collisions in the United States. Nearly 95% of serious traffic collisions are due to human error,¹ with over 70% of commercial fleet collisions involving distracted drivers.² The National Safety Council reports on a typical day, more than 700 people are injured in distracted driving crashes. These statistics are true indicators of how safely drivers are using the roadways and why keeping commercial fleet drivers and bystanders safe on the road is becoming a bigger and more costly challenge for many fleet managers and safety leaders.
Why do video telematics and dashcam solutions fall short when it comes to distracted driving?
To detect driver distraction, most video telematics and dashcam solutions today require driver video to be uploaded to the cloud for analysis (i.e. human review) before any distraction determination is made. There are significant shortcomings to this approach:
- The time lag, or latency, resulting from data transmission from the vehicle to the cloud and back again prevents real-time alerting. This means the driver doesn’t get a chance to act in time to prevent the incident, and worse, the supervisor knows something has happened even before the driver does (since many systems on the market don’t even let the driver know data was captured).
- Drivers fear in-vehicle video will be used against them, and will find ways to block the system from working as intended. When this occurs, they’re missing out on a chance to be exonerated from the collisions that are not their fault, as well as a chance to learn. This would be possible if the driver was notified of the risk first, in real-time, while they still had an opportunity to change their behavior or avoid the risk.
How Nauto helps prevent distracted driving
Reducing distracted driving and fleet collisions requires more than safety policies, traditional driver training, and physics-based ADAS (Advanced Driver Assistance) systems. That’s why Nauto is committed to ending distracting driving with AI-powered solutions. AI-powered Driver Behavior Alerts technology is a proven way fleets can combat distracted driving by audibly alerting drivers as soon as they’ve become distracted for an extended period of time. This allows the driver to correct their behavior proactively, instead of relying on retroactive coaching weeks after an event. By analyzing billions of data points from over one billion AI-analyzed video miles, Nauto’s machine learning algorithms continuously improve and help to impact driver behavior before events happen, not after.
Nauto uses video and artificial intelligence to detect and alert a driver whenever a driver’s eyes divert from the road or engage in other distracted behavior—it then automatically uploads it and scores the event’s severity via a secure fleet app. Nauto’s scoring system, called VERA (Vision Enhanced Risk Assessment) includes a risk rating for the frequency and severity of distraction events (for example, a distraction event while stopped at a red light would not generate the same high risk score as a distraction event that occurred at 65 mph on a freeway). These automatic uploads of significant events and insights delivered in real time help fleet managers improve overall driver performance and enhance the safety and efficiency of the entire fleet.
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¹ National Highway Traffic Safety Administration (2016).
² Nauto and Atlas Financial Holdings. Driver Safety Study (2018).
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