Driver behavior is the description of intentional and unintentional characteristics and actions a driver performs while operating a motor vehicle. There are many factors that can contribute to or alter a driver’s behavior such as age, experience, gender, attitude, emotions, fatigue, drowsiness, driving conditions, etc. These internal and external factors can change even the same driver’s ability to assess risk and make driving decisions from situation to situation. Typically, driver behaviors are characterized on a spectrum from normal to risky and aggressive.
Why is driver behavior important in fleet management?
Driver behavior is one of the most important aspects in fleet management because it affects driver safety and can heighten the risk of a collision, injury, or even fatality. Nearly 95% of serious traffic collisions are due to human error, with over 70% of commercial fleet collisions involving distracted drivers. 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 fleets are monitoring driver behavior
In addition to implementing fleet safety policies and programs, commercial fleet and safety leaders are turning to driver alert systems to monitor vehicle activities and distractions to alert drivers of imminent risks and reduce operational and insurance costs associated with collisions. The challenge is to provide drivers with the right information at the right time, without intruding on their privacy or professionalism. Improving driver behavior over time does not require surveillance or constant human monitoring of the driver if the right AI fleet safety tools are used.
Vehicle activities being monitored
- Harsh braking
- Harsh cornering
- Rapid acceleration
Distractions being monitored
- Drowsy driving
- Talking on a cell phone
- Using a tablet
- Reading paperwork
- Programming an in-vehicle infotainment system
How Nauto can improve driver behavior and fleet safety
Improving driver behavior and reducing fleet collisions requires more than safety policies, after-the fact driver training, and physics-based ADAS systems. That’s why Nauto is committed to impacting driver behavior with real-time, AI-powered solutions. AI-powered Driver Behavior Alerts and Predictive Collision Alerts continuously synthesize inputs from in and around the vehicle, including driver behavior, vehicle movement, traffic elements, and contextual data, in its multi-tasked Convolutional Neural Networks (CNN) model to determine levels of collision risk. As the detected risk intensifies, they signal the driver to take action with increasing levels of urgent alerts. This allows the driver to correct their behavior proactively, before an incident occurs instead of relying on retroactive coaching weeks after an event.
Nauto uses video and AI to detect and alert a driver whenever a driver’s eyes divert from the road or engages in other risky driving behavior—it then automatically uploads it and scores the event’s severity via a secure fleet app. The Nauto 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 an entire fleet.