Artificial Intelligence (AI) is emerging as a game-changer in various sectors, and the trucking industry will be no exception.
AI has the potential to revolutionise vehicle design, including that of heavy vehicles, as well as transform the way trucks operate on our roads.
In my column this month I will explore some of the ways in which AI might be used across the trucking industry by exploring the benefits it could bring, the challenges it has the potential to address and the future possibilities it may unlock.
Starting with vehicle design: from the basic exterior shape of a truck that plays a major factor in the vehicle’s aerodynamics and its physical appearance; the layout of key components and systems that effect performance and weight distribution; to the ergonomic layout of the driving cabin environment and the driver’s eye view of their internal and external surroundings; these features can not only be designed by AI, but enhanced by multiple iterations of concepts and designs, far more than was ever previously possible.
All leading to new, innovative solutions, never before thought possible.
With the fundamental vehicle layout complete, AI can use simulations to test features and functions, refining design elements and system functionality.
AI can test software systems and AI can be embedded into vehicle software via machine learning algorithms, allowing systems to understand driver preferences, learn to navigate complex environments, react to unexpected obstacles, and make decisions in real-time.
AI is helping to develop and push the boundaries of truck design. While humans remain at the core of the project, AI enables manufacturers to create and develop trucks with unique and innovative concepts and features.
In the manufacturing process, AI helps streamline supply chain routes, predict supply disruptions and optimise inventory management.
This enhances the manufacturing process, reduces production delays and costs, resulting in a more efficient assembly. Meanwhile AI computer vision systems provide unparalleled precision in inspecting vehicles for defects during the production process.
Once complete and delivered to the customer, AI can be used to intelligently plan and optimise routes for the truck’s daily operations.
AI driven route planning algorithms consider real-time traffic data, weather conditions, minimise empty truck kilometres, improve load consolidation and other variables to optimise truck routes.
By analysing historical and current data, AI systems can identify the most efficient routes, reducing travel time and fuel consumption.
These intelligent systems can adapt to dynamic situations, providing drivers with real-time updates and alternative routes to avoid traffic congestion or road closures. Intelligent route planning and optimisation not only improve efficiency but also enhances customer satisfaction by ensuring timely deliveries.
Of ever-increasing importance to transport operators, AI can play a crucial role in improving fuel efficiency and reducing operational costs in the trucking industry.
Advanced AI algorithms analyse various factors such as load weight, road conditions, and driving behaviour to optimise fuel consumption. AI systems can provide real-time feedback to drivers, promoting fuel-efficient driving techniques.
Additionally, AI-powered predictive analytics can identify patterns and anomalies in fuel usage, enabling companies to implement strategies, such as driver training to reduce fuel waste. AI powered driver assistance features are improving safety in the trucking industry.
These features include collision avoidance systems, adaptive cruise control, and lane departure warnings.
Utilising sensors and AI algorithms, these systems can detect potential hazards, provide driver alerts and/or take corrective actions.
We are witnessing the power of AI-enabled video analytics systems that analyse, in real-time, video camera footage in trucks to identify risky driving behaviours such as tailgating, aggressive manoeuvres, distracted or fatigued driving.
By detecting these behaviours, AI algorithms can provide valuable insights for driver training and behaviour modification.
Additionally, these systems can potentially assist in accident investigations by providing accurate data and visual evidence. Fatigue and distractions pose significant risks to truck drivers and other road users.
AI powered fatigue and distraction monitoring systems utilise advanced technologies such as facial recognition and eye tracking to detect signs of fatigue or distraction as they occur.
These systems issue alerts to drivers, reminding them to refocus their attention and take breaks.
While continued transgressions could depower the truck, or send alerts to operational managers, allowing for external interventions, thus preventing crashes.
The future possibilities of AI in the trucking industry are vast, exciting and potentially endless. I have only touched upon a few possibilities here.
There is no doubt that these new trucks will provide better road safety outcomes for all road users and become, yet again, another reason why the industry as a whole should join as one to champion TIC’s call for the modernisation of the Australian Truck Fleet.
Tony McMullan CEO,
Truck Industry Council
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