When people start talking about artificial intelligence (AI), it’s easy to get bogged down in terms like neural nets, algorithms, machine learning and more. But you don’t really need to understand all that to take advantage of AI.
In essence, artificial intelligence is simply the capability of a machine to imitate intelligent human behavior.
Artificial intelligence “is really a set of capabilities that allow a computer to do something that would have required human intelligence in the past — or something that would have taken far too long for a human to do,” said Brian Stuelpner, vice president of strategy, planning and architecture for Schneider. “Things like conducting analysis or making very complicated decisions in a fraction of the time. We use it a lot to take over mundane and repetitive tasks, so that people can move on to something of higher value.”
Michael Phillippi, vice president of technology at Lytx, described AI as “acting as a kind of purpose-built brain, designed to learn and conduct particular tasks. Just like people learn over time, and get better at certain jobs, AI also gets better over time by integrating data from multiple sources. In the context of AI, we refer to that as machine learning.”
However, AI is not some sort of magic silver bullet.
“AI isn’t a panacea,” said Ray Ghanbari, chief technology officer for SmartDrive. “How well it works is really driven by the quality of the training data that it has been built around,” just as a human student’s learning will be affected by the teaching materials provided.
Stuelpner said there’s a misconception that humans are removed from the picture in artificial intelligence.
“With the AI that we’ve deployed, there’s a lot of training that goes into trying to bring the human knowledge that we have and digitize it so the computer can understand what we do. So it’s not taking the person out. It’s actually just reshaping the role of the person.”
With those caveats in mind, here are five ways AI can be used in trucking and logistics.
1. Make Customer Interactions More Meaningful
One way Schneider is using AI is handling customer email requests.
“We get millions of emails a year from our customers, many of them asking fairly simple questions like, ‘Where’s my freight?’” Stuelpner said. “What we’ve been able to do is utilize artificial intelligence to understand the intent of the question that’s coming in, and in near real time, go to the systems that know the answer, and return an accurate answer to that request in three to five seconds.”
That has not only improved the customer experience, he notes, but also improved the associate experience by eliminating a lot of mundane, repetitive work.
Kingsgate Logistics is using AI in several ways, Tom Curee, senior vice president of strategy and innovation. One of those ways is determining the best time of day to call a prospect, using data such as social media activity, when prospects opened your email, when they have visited the website, etc.
Another example is analyzing recorded calls to determine what the company’s most successful sales reps do and coach less-successful reps.
2. Make Logistics More Efficient
Many believe AI offers vast potential to make the way loads are matched up with trucks far more efficient. Over the past several years, companies such as Convoy, Loadsmart and Uber have developed automated load-matching apps that use machine learning (a subset of AI) to help their algorithms get “smarter” with each load matched. Earlier this year, large carriers started piloting a “Book Now” option for DAT Load Board users, which looks to automatically match carriers with freight.
Schneider has a sizeable logistics business and is using AI and machine learning to provide better recommended loads to its third-party carriers.
At third-party logistics provider Transplace, chief executive Frank McGuigan offered a couple of examples of how the company uses AI to speed logistics:
- Processing thousands of traffic patterns helps AI algorithms predict where there are exceptions, alerting dispatchers early to help them reschedule loads around the delay.
- Its Dynamic Continuous Moves program uses AI to identify millions of potential pairings for tendering loads in pairs as continuous moves versus a single load.
3. Make Predictive Maintenance a Reality
“There’s an awful lot of work that’s going on with predictive maintenance right now,” said SmartDrive’s Ghanbari. By feeding an AI algorithm data about what eventually leads to a maintenance event, you can train the data to look into the future and, based on data from that particular vehicle, predict the likelihood that it’s going to need a particular type of maintenance in the future, he said.
The power of AI-driven predictive maintenance will only increase, Ghanbari predicted, as the increasing numbers of sensors on today’s trucks relay more and more data to the learning algorithms. Right now, he says, predictive maintenance tells you when the truck is going to break down. AI will tell you why the truck is going to break down.
4. Improve Safety
In-cab camera systems have opened up vast possibilities for the use of artificial intelligence.
“Smart video uses AI and machine learning to intelligently capture and automatically classify that video data the dashcam is capturing,” said Kevin Aries, head of global product success for Verizon Connect.
Ghanbari said this is one of the areas where AI excels: detection or classification. This is done through computer vision, or machine vision. These algorithms allow for automatic detection or identification of objects and behaviors from visual data such as images or video.
“Machine vision acts as a smart set of eyes to give an AI system more information about what is going on,” said Lytx’s Phillippi. This also helps remove the potential for human error or bias, as well as the time-consuming processes associated with manually reviewing video.
5. Improve Driver Productivity
If one searches the internet using terms Google “AI’’ and “truck drivers,’’ most of the results deal with autonomous trucks. But many of the AI technologies that are being used to develop autonomous trucks are also being used today in advanced truck driver assistance systems. AI is helping to power automated on-board systems such as lane-keeping assistance, adaptive cruise control, collision mitigation, and so on.
Less sexy but no less important, however, are ways AI can work to cut out some of the tedious tasks truck drivers face and help reduce wasted time in their schedules.
For instance, Schneider uses AI for more accurate estimated times of arrival, through something it calls ETAI. This helps both customers and truck drivers.
Looking ahead, Stuelpner said, “we’re really moving towards the spot where each and every truck driver is going to almost have an assistant with them, allowing them to focus on driving, focus on being profitable.”
In fact, AI will continue to allow trucking “to make better decisions at a speed that we couldn’t really comprehend in the past. And I think that’s really the promise of AI in the trucking industry. It’s going to drive a whole lot of efficiency,’’ he said.