Australia’s trucking industry is no stranger to innovation.
The sector serves as a key pillar of the country’s economy – employing over 200,000 people and carrying over 234 billion tonne-kilometres each year, according to a 2023 report by the Australian Trucking Association – and as a result, is the site of frequent technological innovations designed to improve the efficiency and safety of its operations.
These solutions have come in many forms over time to address key industry challenges during certain periods, ranging from the arrival of international manufacturers like Volvo and Ford in the 1970s and subsequent competition and development, to the advent of the Electronic Work Diary, and more recently an array of alternative fuel programs that are fighting to make the industry more sustainable.
Today, concerns over driver safety and management, coupled with an ever-advancing technological space, have manifested in the implementation of Artificial Intelligence (AI), which has seemingly exploded on the scene since its introduction only a few years ago.
Since this arrival at the hands of various telematics and software companies, the applications and abilities of AI have been growing at a rapid rate, seeking to meet operators’ safety worries with state-of-the-art monitoring and alerting systems.
One of the key players in this space is Teletrac Navman, a software service company which offers electronic guidance solutions to transporters.
The developer was quick to incorporate AI into its value proposition early on in this phenomenon — a move that has seemingly paid off.
According to one of Teletrac Navman’s Safety and Compliance Solutions Specialist, Chris L’Ecluse, it is essential to be at the forefront of innovation in this space.
“As a tech company, I think being an early adopter of any technology is an imperative,” he says.
“If you’re a tech provider and you’re not ahead of the curve, you’re going to get left behind. Something we take great pride in at Teletrac Navman is the ability to understand our market and the organisations within it and create products and services that meet the needs of all parties involved.”
Teletrac Navman’s entry into the AI world came in 2020 with the release of the TN360, a large-scale software platform that collects key data on the efficiency, productivity and safety of truck drivers by measuring speed, driver behaviour behind the wheel and an assortment of other variables.
These capabilities, coupled with video cameras in the truck cab which link to this system, provide fleet managers and operators with a holistic view of any obstructions that drivers may face during their transport journeys, enabling them to create comprehensive solutions.
The reception of this technology and the sentiment surrounding AI is largely dependent on where in the workforce one lies.
Chris explains that those in the logistical supply chain are eager to bring safety and efficiency benefits to their operations, while the drivers themselves are wary of this technology in the truck cab with them.
Teletrac Navman seeks to address these concerns through the TN360’s application of corroborating drivers’ accounts of certain situations due to its recording abilities.
“Some drivers are certainly sceptical or anxious about this technology,” Chris says.
“But something that we’ve seen early adopters of our AI video telematics jump at is its ability to capture evidence of situations and events which corroborate the truck driver’s perspective. For the longest time, drivers haven’t always had the best reputation, due to their portrayal in the media mainly but I’ve come to realise that this portrayal represents an overwhelming minority of those actually on our roads.
“Members of the public and even the media tend to jump on the backs of truck drivers when things go wrong on the road, but with this AI video technology, we can see events as they play out, and support a driver’s account. This ultimately can prevent them from having to get off the road and come into an office to explain their situations.”
On that point, AI can help preserve a driver’s reputation, not to mention improve the fleet’s efficiency.
That these benefits extend beyond driver corroboration, suggest, what’s more that the surveillance capabilities and feedback systems offer new provisions for advances in coaching.
AI cameras can record audio and output this audio to drivers in real-time to warn them of potential obstructions or other hazards mid-drive.
Such functionality can serve to better inform drivers of their transgressions therefore ensuring better practice behind the wheel.
Chris is particularly excited about this application, as it offers a whole new standard for continued driver training and improvement.
“With our video telematics, drivers can be coached in real-time on a plethora of issues while driving from their speed to their following distance, to even adherence to road signs,” he says.
“All these things that the cameras capture provides essential feedback which drivers can take on to become much safer.”
Teletrac Navman’s recognition of some stigma around AI’s application, and subsequent efforts to make these applications transparent, has been echoed by other developers in the space to encourage the uptake of this technology.
Seeing Machines, another developer in the sector, has innovated in the space for over 15 years.
The company’s own AI-safety solution, Guardian, addresses similar issues pertaining to driver distraction and fatigue for fleets, and has also experienced pushback for the extent of its applications in the past.
Company CEO, Paul McGlone, notes that transparency remains a key tenet of AI development.
“One of the main challenges of implementing AI in the transport industry is the perception – sometimes misconception – around privacy and security,” he says.
“People want to know how data is being used and protected, and that’s completely understandable. Building trust with different industry stakeholders is an ongoing journey. It takes time to demonstrate the reliability and integrity of AI systems, especially in such a critical industry.”
Seeing Machines is a staunch advocate and practitioner of making the use of its data traceable and clear to alleviate concerns from the public.
In another effort to break some of these comprehension barriers of AI, Paul also refers to a list of tried-and-true technologies within the industry that have incorporated an element of AI for some time already.
“Many people don’t realise just how much AI is embedded in the products they already use,” he says.
“Cruise control, driver assistance systems, and other features have relied on AI for years, and its role is only growing. This shift in sentiment around AI, now that it’s being used in a new way, reinforces the importance of educating stakeholders and ensuring our solutions are designed with trust, security and clear benefits in mind.”
For Seeing Machines, part of this delivery of trust to consumers comes by adhering to different regulations for its AI applications, including European GDPR laws which protect data privacy, and a recent update to the EU General Safety Regulation which mandates certain AI-based safety features in vehicles.
However, these EU regulations are being consulted in lieu of any AI related mandatory guardrails.
There is no standalone law inherently created for AI regulation explicitly.
While the Australian Government has introduced the Voluntary AI Safety Standard and the AI Ethics Principles to guide technology development in this space, it seeks input on proposed legislation as calls for more targeted regulation, particularly for high-risk AI applications, increase all while widespread adoption and innovation of the technology intensifies albeit in what are considered low-risk areas.
Stephen King, Commissioner of the Australian Government’s Productivity Commission notes where potential harm exists, it must be weighed against the benefits of the technology.
“Governments need to determine whether the identified uses of the AI technology result in heightened risks of serious harm compared to the alternative,” he notes.
“The risks of AI should be judged against real-world, human-based alternatives, not a fictitious risk-free world.”
In King’s opinion, if existing regulations adequately address the identified risks, then there is no need for new regulation.
“Existing regulations may clearly cover the use of AI technology. Alternatively existing regulations may need clarification, potentially via the courts, or amendment,” he writes.
“This means that regulators must be trained and resourced to understand and respond to any risks that come from the use of AI-based technology.”
AI models are trained on massive data sets. Already in the legal profession shortcuts in legal research and document preparation have seen attorneys in a New York court submit a brief containing fake extracts and case citations.
What the lawyers didn’t know was ChatGPT, where they researched the case, can hallucinate.
The subsequent failure to check that the cases actually existed had dire consequences.
A Voluntary Standard has been put forth with ten guardrails, the first of which insists accountability for the safe and responsible deployment of AI cannot be outsourced.
These regulatory discussions and frequent innovations involving AI can greatly impact the perception of this technology for even some of the most established members of the trucking industry.
One such company, Russell Transport, has been operating in Queensland’s logistics sector for over 100 years, and has a very specific perception of the term AI and its accompanying technology.
The carrier’s third-generation family member and Director of Support Services, Julie Russell, classes the business as one intentionally not leading the pack in adoption of the technology, but rather carefully procuring the advancements that works for it.
“To us, AI includes many types of technologies that we’re using in our fleet to prevent and detect accidents in our operations, as well as support the business further,” she says.
“We are in a phase of trialling different things and seeing what works for us.”
Russell Transport is seemingly uninterested in development for development’s sake. The fleet is opting for a more pragmatic approach, incorporating this new wave of technology to serve specific purposes, where suited, namely in safety and efficiency.
This approach was established some 20 years ago, when the company was faced with a crossroads of modernisation that has seemingly defined its attitude to innovation.
“At that time, I remember we were faced with a decision between these new technology systems,” Julie says.
“One system required one dedicated computer to run its software and would provide us with information on the location of our trucks during their routes. Another brand had this same application that could sit on multiple desktops. We opted for the choice that provided us visibility on our fleet regardless of where we were. I think that choice really defined our approach to taking up technology moving forward.”
Today, Russell Transport is a dedicated user of Seeing Machines’ AI-powered Guardian solution, monitoring driver fatigue and fleet management.
Additionally, the company has been open to a wide spectrum of AI-assisted organisational applications from route planning and job planning and other fleet administration tools.
The approach, at least initially, is cautious when it comes to incorporating these assets.
“It’s a lot harder to understand how this technology works when you don’t have a clear purpose or application for it,” she says.
“We’ve focused on utilising specific innovations that can create efficiency and take our own people along for the journey so that they can harness that efficiency into their work and focus on what application of it can be most beneficial.”
In this way, Julie and Russell Transport are certainly eager for AI’s advent into the industry, as the technology will bring with it new demographics and business into the sector.
But, for the time being, a pitfall in AI’s presence actually comes from the trucking industry itself, and what Julie thinks may be a workforce which is still largely unsure of how to use it.
“I feel a lot of these new applications may not work so easily with our existing applications,” she says.
“Some of these programs may not be compatible with the ones we run, and we need to source people to bridge this gap for us. The process of scaling the learning curve can be a big bleed on a business like ours. That’s where I foresee the biggest problems with the rapid uptake of this technology in this space, particularly.”
This rapid uptake of AI technology has seemingly worked to both unite and divide members of the trucking industry – addressing sector-wide concerns of safety and fleet management with modern solutions.
While these solutions have worked to deliver enormous safety and efficiency benefits thus far, reluctance towards the technology’s widespread application persists, while its regulation and the full scope of operations are yet to be determined.
Telematics and software company Geotab is heavily invested in AI.
Sean Killen, Geotab Vice President Global Markets, views it as an advanced tool for interpreting data and making more from less.
“The math is just better than human math,” he says.
“No matter how good the compliance and scheduling person is at any of the major transport companies when their data flows through Geotab AI they’ll be able to get a better more efficient operation from it.”
The big question over the next ten years will be at what point does it jeopardise human employment. Waymo in Phoenix, Arizona has launched its self-driving taxis which are currently operational.
Sean says it does pose a question: how does eliminating that driver help society?
“I’m not sure I really see the value in eliminating that job,” he says.
“There’s value in utilising assets for fleets and being safer and wasting less fuel. If AI can do that and we know it can, then that’s great. Is it safer? You can certainly argue that it is. But I’ve also had drivers who have driven for 20 years and never had an accident.”
As some operators proceed with caution and others are quick to adopt this technology, it’s going to be a fascinating space to watch develop with perhaps no end of complexity.
