AI Applications in the Trucking Industry
The transportation industry is ever-changing. We’ve come a long way since the early inventions of steamboats and railway carriages. With the recent torrent of technological innovation and the development of Artificial Intelligence (AI) technology, the transportation industry — with emphasis on trucking and delivery — has seen a wide-scale transformation.
While predictive maintenance, semi-autonomous trucks, and precision mapping technologies have already been widely adopted in the industry, ideas of fully autonomous trucks, as well as truck platooning, are not far off from being fully realized. Here we will explore some of the present and future applications of AI in the trucking sector:
The Game Has Changed
With AI having already changed the status quo of so many other industries, a ripple effect has been created. Interrelated industries are being affected by such changes and forced to follow suit. Consider e-commerce giant Amazon’s recent foray into the healthcare sector, which has direct ramifications for the trucking industry. Some hospitals today are able to use Amazon’s “Dash” buttons to order medical supplies like syringes and gloves — a capability that has reduced supply chain labor costs by 80%. It stands to reason that this development would also affect fleet managers in their operations. By integrating AI technology into its healthcare operations, which in turn impacts shipping; Amazon is a prime example of how AI and digitization are changing all sorts of industries, with cascading effects. The trucking industry is not exempt from these changes.
Other, non-AI-related changes in the trucking industry require solutions. For instance, it’s predicted that there will be a shortage of almost 200,000 truck drivers by 2026, due to old age and complicated driving requirements. With fewer drivers available but more drivers required, solutions are needed urgently.
Thus, AI and machine learning technologies are required to help solve problems like traffic congestion, the management of larger fleets and the shortage of drivers. The development and implementation of new technologies are already on track in the trucking industry; and with new technological developments every day, innovation in this sector isn’t likely to stop.
Improved Fleet Management and Driver Safety
Currently, AI is already making the jobs of fleet managers much easier and more effective. As trucks have been using telematics, vehicle sensors and IoT technology to track processes; this data can then be used by machine learning technologies to improve safety, productivity and cost-efficiency. Machine learning technology achieves these goals by improving routes to lessen miles driven, reducing unwanted driving behaviors and predicting when vehicles require maintenance.
Furthermore, trucking companies are using onboard video to give context to driving events as well as to monitor their drivers. Verizon’s ‘Connect’ Integrated Video uses AI technology to automatically sift through hours of footage for the fleet manager, assisting to identify harsh or unsafe driving footage as well as gain insight into operations. These insights act to improve future driver performance as well as mitigate risk.
Finally, Advanced Driver Assistance Systems (ADAS) powered by AI technology are being installed into many trucks to ensure easier and safer trips for truck drivers. The capabilities of this technology include adaptive cruise control, lane departure warning system, park assist, lane keep assist, automatic emergency braking and driver monitoring system.
Autonomous Trucks and Truck Platooning
Truck platooning and autonomous trucks are the future of AI in the trucking industry. In an article on FleetOwner, Michael Roeth, executive director of the North American Council for Freight Efficiency (NACFE), explains that “at about a 50- or 60-ft. following distance, two-truck platooning could deliver a fuel savings of 10% for the second truck in the platoon and between 4-5% for the lead truck.” However, for platooning technology to become more mainstream, industry-wide challenges like public acceptance and regulatory policies need to be overcome. Considering Roeth’s statement that platooning is “a natural step in truck automation since it builds on the technology that is already being purchased on trucks,” the future is likely to see this development become more commonplace.
Similarly, the idea of self-driving vehicles and the implementation of steps toward making these a reality has been a top tech trend for a while now. Both platooning and the ability to integrate driverless trucks on the road, it will solve many of the aforementioned problems while also introducing a new level of efficiency to the trucking industry.
Current trials have proven that delivery time can be reduced by utilizing self-driving trucks. Start-up self-driving truck company TuSimple recently completed a trial with the US Postal Service to deliver letters from Phoenix to Dallas in 22 hours, a route which usually takes a truck driver 48. Thus, autonomous trucks will seamlessly be able to fill the gap resulting from a future shortage of truck drivers, while greatly reducing costs. In fact, an article by McKinsey and Company states that “operating costs would decline by about 45%, saving the US for-hiring trucking industry between $85 billion and $125 billion”.
Conclusion
AI technology has already begun to change the trucking industry as we know it. With new machine deep learning technologies as well as more and more data being collected and stored, the possibilities for new innovations are endless. Both today and in the future, AI is predicted to continue revolutionizing the trucking industry for the better.
