Implications of AI for the Trucking Industry
There are 8.7 million truck drivers worldwide, all of whom are part of the massive $800 billion industry. In the U.S. alone, where trucking is the most common job in many states, there are 3.5 million professional truck drivers and 7.8 million people employed in jobs related to trucking activity. Trucking is part of the larger transportation industry that is set to be dramatically altered by artificial intelligence (AI) technology.
Companies like Tesla, Google, Uber, and other truck manufacturers are moving full-steam ahead with AI technology and are currently testing vehicles on public roads. As these companies keep innovating, the industry will be revolutionized in many different ways. Whether it’s fuel efficiency, route optimization, drivers, or safety and accident prevention, AI will greatly impact them all.
The widespread use of self-driving trucks will be the biggest implication of AI in the trucking industry. Various states in the U.S. have passed laws allowing autonomous trucks to drive together in groups of two or more with synchronized movements. Companies like Tesla are leading the field in autonomous truck development, calling their Tesla Semi “the safest, most comfortable truck ever.”
Truck driving will likely become the first type of driving to be fully automated, long before passenger cars. This is because highways are the easiest roads for the technology to work with, and that is where most trucks operate.
The challenge with urban roads is that they are full of unexpected situations and developments, such as something running across the street. There are also many more mistakes made by drivers in these conditions. For example, a distracted driver can run straight through a red light or stop sign.
As opposed to urban roads, highways are much more predictable and constant. Vehicles normally stay in their lane, keep a safe distance from others, and travel in the same direction for long periods of time. While accidents on highways are often much worse than those on urban streets, they occur less often.
Because highways are more predictable, the software used in a self-driving truck doesn’t have to account for so many different scenarios. This also means that while self-driving trucks take over highways, there will still be the need for human drivers within cities and towns.
Accident Prevention and Safety
One of the biggest areas where AI will have an effect is in accident prevention and safety. Eventually, it is likely that there will be no human drivers in many cases. No human drivers means no human error, and one of the biggest safety issues within the industry is long hours and fatigue. Truck drivers sometimes go 11 hours straight, with each increasing hour being more hazardous, and they are not immune to the problems all drivers face like distraction from texting.
Because autonomous truck driving is going to unfold at different levels, the safety features will become even more impressive with time. At first, certain operating functions like speed and braking can be automated, the software being better than any human driver. When automated trucking reaches its peak, there will be dramatically reduced safety hazards. Stability can be improved so that trucks suffer less skidding and rollovers, and they will have faster reaction times to prevent accidents.
Fuel Efficiency and Savings
With the use of AI technology, there will be better fuel efficiency due to increased aerodynamics. Besides that, all around savings are set to reach high numbers.
Fuel is one of the top expenses for fleets, so the condition and inner workings of the truck is key. AI can be used to detect certain problems in a truck that are causing under-performance. When the industry changes to self-driving trucks, the fuel efficiency costs will lower even more. According to Plus.ai, that number will be cut by 15%.
In 2018, U.C. Berkeley Labor Center released a report that estimated there will be around $35 billion in fuel efficiency gains and a total of $168 billion saved in the industry.
Different Types of Work
With all of the big technology advancements taking place in the trucking industry, the types of jobs available will change as well. For example, there will be an increased need for remote truck drivers and many opportunities on the technological side. Governments and companies will likely implement retraining programs as well, which is true for many industries set to be impacted by AI.
It will also take time before an automated truck can operate fully without a human onboard. Even though they are very different, think of a pilot in the cockpit of an airplane. Software can control many aspects of flight navigation, with the pilot overseeing all of it. The same will be true for drivers and automated trucks.
Most of the attention surrounding AI in the trucking industry is aimed at self-driving vehicles, but there is another area that is currently undergoing automation: the back-office.
One of those jobs is freight brokerage, which is whenever middlemen are used to arrange the transportation and tracking of a load hauled by a freight carrier. In December of 2019, the trucking software company Convoy announced that they reached 100% automated brokering of loads to carriers. This came just months after they reached 100% automated load matching, meaning they have completely automated the brokering process.
Machine learning algorithms can be used to detect certain patterns that humans cannot, like which loads should go with certain drivers. This allows for more focus to be dedicated to important issues surrounding safety and other logistics.
The trucking industry will be dramatically impacted by artificial intelligence, and the extraordinary technological advancements will bring many social, economic, and environmental challenges. Governments, organizations, and industry leaders will need to come together to discuss proactive approaches involving things like retraining programs, AI regulatory policies, and ways to protect communities. By doing this, society can reap the benefits of AI while limiting any potential damage.
Author: Alex McFarland is a journalist who covers developments in AI