How Can AI Be Implemented in the Trucking Industry?

The transportation industry has seen exponential growth over the last decade, and much of this growth can be credited to the introduction and application of web and software solutions. However, despite these advancements, the industry is still prone to accidents and maintenance issues, causing delays which can be prevented. The solution may lie in the introduction of artificial intelligence. Trucking companies can use AI to improve their fleets’ safety, increase fuel efficiency and cut down on costs. Here are some ways that AI can be implemented in the trucking industry:

Automated Driving

The trucking industry is seeing a shift towards automated driving. This can be done through driverless trucks or self-driving trucks, which will likely be more common in the near future.

Driverless trucks are already being tested on public roads in some states across the U.S., including Florida and California. The technology behind driverless vehicles is still in its infancy so don’t expect to see them taking over roadways anytime soon, but it’s certainly something worth keeping an eye on as it develops. 

Highway Pilot is  an example of automated driving technology that has been implemented into many semi-trucks across Europe (and soon North America). It allows drivers to switch between manual and fully automated modes so they can rest while their vehicle drives itself down highways at speeds up to 70 mph (112 km/h).  When using this feature, there must always be a driver present inside the cab, but they aren’t required to manually steer or control any other functions besides acceleration/deceleration. This feature has proven quite popular among drivers who often have long commutes every day between cities where there might not always be designated rest stops along their routes.

Predictive Maintenance

Predictive maintenance is a software solution that allows you to predict when a truck needs maintenance. It uses data from the truck’s sensors, OBD2, GPS and other systems to determine when maintenance is needed.

With predictive maintenance, you can schedule repairs before your trucks start breaking down. This saves time and money because if there’s an issue with a truck, it will not be on the road delivering goods or picking up loads – so predictive maintenance means fewer delays in getting goods delivered or picked up.

It also means less downtime for your drivers who won’t have to wait around while their trucks are repaired (or worse still – replaced).

Truck Platooning

Truck platooning is the process of connecting two or more trucks together in a line, so that they can travel at a faster speed than they would without being connected. The lead truck controls the speed of the platoon, and all following trucks follow in a row behind it. 

This method has been shown to increase fuel efficiency by as much as 10%, due to the fact that following vehicles do not need to waste energy accelerating or decelerating.

Technically speaking, truck platooning can occur either wirelessly or via a cable. Wireless connections are based on Wifi technology and have been successfully tested on public roads in Europe and Japan since 2016; however, there remains debate over whether they should be allowed in North America due to safety concerns stemming from inconsistent wireless coverage across countries (which could potentially lead drivers into dangerous situations). 

Cable connections have also been successful; however, they require extra work when setting up because cables must be installed between individual trucks instead of one long cable stretching between multiple vehicles like with wireless connections.

AI can be implemented in the trucking industry in many ways to increase safety and efficiency.

AI can be implemented in the trucking industry in many ways to increase safety and efficiency. For example, AI could be used to determine whether a driver is fatigued based on video footage of them driving. 

The system would recognize certain cues such as erratic steering, blinking eyes or yawning that indicate when someone may need to take a break before they get too tired.

Vehicle-to-vehicle communication systems are also being developed that would allow trucks to communicate with each other and share data about road conditions or dangerous drivers ahead of them on the road.  This type of communication could prevent crashes by warning drivers about potential hazards ahead or giving them alternate routes around areas where traffic is slowing down due to accidents or construction zones.

The trucking industry has great potential with the implementation of AI.

Truck drivers are under increased pressure, and at the same time, there is an increasing shortage of qualified drivers. This means that it should be easier than ever before to integrate automated driving into fleets. Thanks to advances in technology, there are now more options for fleet owners who want to implement AI applications like predictive maintenance or platooning into their business practices.

 

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