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How to Plays a Crucial Role in Trucking Industry

AI (Artificial intelligence) now plays the dynamic role in the trucking industry. Artificial intelligence and IoT-driven telematics produced more data or automation, but it was still difficult to see actually happening on the road. Truck accidents approximate 16,500 in damage and 57,500 for injury-related costs total 74,000, according to Yoav Banin. Banin is the chief product officer of Nauto. Nauto provides fleet performance and driver solutions.

Truckers and telematics: winning team

Considering for the other challenges facing the trucking industry, it’s essential to emphasize truck driving safety. The first priority in this matter is the nationwide shortage of truck drivers. This could lead fleet operators to hire less-experienced truck drivers or require less safety training. Truck parking is second in priority. For resulting, the third priority is driver compensation. This shortage is dependent on the safe driving records. Fleet operators managed safety risks in the past through training programs, manual coaching sessions, or driver ride-alongs.

Continuing Importance of Training Programs

Most training programs are commercial ventures by the truck driving schools throughout the US.  Truck driving schools have more popular option in the past several decades. Nevertheless, the number of truck driving schools has remained static. In few cases, it has dropped little a bit. These two factors make it difficult for many potential students to gain access for required driving programs. This limits the number of new truck drivers available for hire in recently. AI now plays a dynamic role in training programs as well.

Manual coaching sessions are becoming less common. Professional truck drivers are growing very reluctant to use of 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. The increasing state and federal restrictions on professional truck drivers and the interest in self-driving trucks, ride-alongs are becoming rarer. In additionally insurance is part of the restrictions on professional truck drivers for ride-alongs. The veteran truck driver carries the insurance.

That highlighted above three challenges are merely the tip of the iceberg. More challenges face truck drivers and employers. The bottom line is truckers must maintain an unblemished driving record. Banin stated that for all of these manual approaches did not scale well. Banin views manual data collection is hit and misses. Data collection on risky driving behaviors did not always mirror driving results.  On-camera sensors, GPS or deep learning neural networks are now crucial elements in data collecting.

They introduced telematics by using Internet of Things (IoT) sensing devices and recording devices. These Internet of Things (IoT) devices measured driving characteristics based on the 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. Internet of Things-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 for negative in any telematics system. Nevertheless, the system views it as part of defensive driving.

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

The Value of Artificial intelligence for Truckers

Artificial intelligence technology is widely used for the trucking to enable real-time road-and-driver assessments. Banin claims for the Artificial Intelligence technology can alert the driver to dangerous conditions. It can help reduce collisions by between 50 to 80 percent. Fleet managers to improve safety and reduce risk by using more sophisticated scoring models for drivers. Banin stated that it’s all of above saving money and most importantly, saving for lives. Predictive safety technology and analytics technologies have already helped fleets lower collision losses lower of their insurance premiums and prevent injuries and fatalities on the road.

Safety Measures Should be Predictive: Artificial Intelligence May Help

Analytics may be missing an ingredient. Fleet managers realized this and began to add Artificial Intelligence and computer vision to telematics, and Internet of Things. Finally, fleet managers now have the complete picture they were looking for in terms of driver safety and road conditions for Artificial Intelligence and other big data technologies such as computer vision.

Banin states to predictive safety systems can now understand driver behavior and state such as drowsiness, distractions and cell phone use. Finally, predictive safety systems provide useful insights, as well as warnings about potential collisions. All based upon the vehicle dynamics. It’s possible to give drivers extra warning time to help them ramp up of their attention and take preventative action to avoid collisions.