Artificial intelligence now plays a dynamic role in the trucking industry. AI and IoT-driven telematics produced more data and automation, but it was still difficult to see what was actually happening on the road. A truck accident results in $16,500 in damage and $57,500 for injury-related costs totaling $74,000, according to Yoav Banin. Banin is the chief product officer of Nauto. Nauto provides fleet performance and driver solutions.

Truckers are the backbone of the American supply chain.

Truckers and telematics; a winning team

Considering other challenges facing the trucking industry, it is essential to emphasize truck driving safety.

The first priority in this matter is a nationwide shortage of truck drivers. This could lead fleet operators to hire less-experienced truck drivers and require less safety training. Truck parking is second in priority. Finally, a third priority is driver compensation.

This shortage is dependent on safe driving records.

Fleet operators managed safety risks in the past through training programs, manual coaching sessions, and driver ride-alongs.

Continuing Importance of Training Programs

Most training programs are commercial ventures by truck driving schools throughout the United States.  Truck driving schools have been a popular option in the past several decades. However, the number of truck driving schools has remained static.

In some cases, it has dropped quite a bit. These two factors make it difficult for many potential students to gain access to the required driving programs. This limits the number of new truck drivers available for hire today. Artificial intelligence now plays a dynamic role in training programs as well.

Manual coaching sessions are becoming less common. Professional truck drivers are growing more and more reluctant to use their time in low-paying manual coaching.  Truckers make more money driving solo. And veteran drivers who seem most willing to do manual coaching often have the worst driving records.

Due to the increasing state and federal restrictions on professional truck drivers, and the interest in self-driving trucks, ride-alongs are becoming rarer. Additional insurance is part of the restrictions on professional truck drivers for ride-alongs. The company or the veteran truck driver carries the insurance.

The above three challenges are merely the tip of the iceberg. Many more challenges face truck drivers and their employers. The bottom line is truckers must maintain an unblemished driving record.

What Trucking Experts Say

Banin stated that all of these manual approaches didn’t scale well. Banin views manual data collection as very hit-or-miss. Data collection on risky driving behaviors did not always mirror driving results.  On-camera sensors, GPS, and deep learning neural networks are now crucial elements in data collecting.

In the early 2000s, fleet managers began to look for even better methods. They introduced telematics using Internet of Things sensing devices and recording devices. As a result, these IoT devices measured driving characteristics based on vehicle motion. Acceleration, speed, and braking are crucial to accurate telematics. The devices reported the data to central databases and applications at the corporate office.

IoT-driven telematics produced more data and automation, but it was still difficult to see what was actually happening on the road.

Banin used the example of hard-braking, which is usually a negative in any telematics system. However, the system views it as part of defensive driving.

Banin states that defensive driving is key to avoiding accidents. Telematics and IoT are excellent at understanding vehicle condition, fuel consumption, and identifying potential maintenance issues that could pose a risk. But, they can’t tell us the top causes of accidents, because preventing accidents is where the focus needs to be.

Safety Measures Should be Predictive – Artificial Intelligence May Help

Analytics may be missing an ingredient. Fleet managers realized this and began to add AI and computer vision to telematics, and IoT. As a result, fleet managers now have the complete picture they were looking for in terms of driver safety and road conditions thanks to AI and other big data technologies like computer vision.

Banin states that predictive safety systems can now understand driver behavior and state, including distractions, drowsiness, and cell phone use. As a result, predictive safety systems provide useful insights, as well as warnings about potential collisions. All based upon vehicle dynamics. Because of this, it is possible to give drivers extra warning time to help them ramp up their attention and take preventative action to avoid collisions.

The Value of AI for Truckers

Artificial intelligence technology is widely used in trucking to enable real-time road-and-driver assessments. Banin claims that AI technology can alert the driver to dangerous conditions. And as stated above, this can help reduce collisions by between 50 and 80%.

Fleet managers can improve safety and reduce risk by using more sophisticated scoring models for drivers.

Banin stated, “At the end of the day, it’s all about saving money and, most importantly, saving lives.” “Predictive safety technology and analytics technologies have already helped fleets lower collision losses, lower their insurance premiums, and prevent injuries and fatalities on the road.” This is how Artificial intelligence now plays a dynamic role in the trucking industry.

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Brad Anderson

Editor In Chief at ReadWrite

Brad is the editor overseeing contributed content at He previously worked as an editor at PayPal and Crunchbase. You can reach him at brad at