The different industries are at different stages when it comes to data-driven transformation. One of the industries that’s taken the data and AI revolution further than many others is the trucking industry. The first thing that comes to mind is self-driving trucks, obviously, but there are many other aspects of the industry that have evolved tremendously over the past few years.
Trucking is responsible for moving 70% of all deliveries in the world, and 80% of our communities depend on trucks for the distribution of everyday goods, spanning from raw materials, medicine, groceries, and everything in between. There are about 3 million truck drivers in Europe driving a total of about 1,700 billion kilometers of European roads. In 2020 the size of the European road transport industry was 324.5 billion euros, a dip frome the year before due to Covid, but is estimated to bounce back and reach 340 billion euros in 2021. The market has been steadily growing and will reach a staggering 23% increase in 2023 compared to 2010. There are primarily two factors behind the rapid adoption in advanced analytics and AI solutions within the industry. Primarily, it’s security, as fatigue has been a particular problem for professional truckers. During long-haul transportation, it’s not uncommon for drivers to work 12 hours a day and reach 70 hours a week with little or poor sleep. Unsurprisingly, 20% of all crashes and fatalities involving long-haul trucking, take place between midnight and 6am, the peak period of driver fatigue. Secondly, there’s a major shortage of truck drivers. In the US, the industry is already short 61.000 drivers and the gap is expected to widen to a shortage of 160.000 drivers by 2028. Europe is already dealing with an enormous shortage of drivers and road transport firms are racing towards a driver shortage crisis of 150,000 unfilled jobs.
These two factors have contributed to the major advancements in self-driving trucks and other AI-driven solutions. At the same time, the continuous growth of e-commerce demands speed, visibility, and agility. Over the last few years, the industry has also shown tremendous change in tracing and tracking, creating a whole new supply chain transparency. Looking forward, we see four areas where AI and advanced analytics will continue to transform the evolving trucking industry and enable smart transportation.
The tracking system can help in communicating with vehicles constantly, gathering data about how long a vehicle has been on a road, where it is headed, and which route would be the most efficient. This system reduces idle driver time, optimizes fuel efficiency, enhances safety, reduces paperwork, and allows for increased supply chain transparency for company and clients alike.
Truck-to-truck communication platooning
Platooning links several vehicles for trips on long highways. The first truck has a driver and is the lead vehicle, and the remaining trucks, which are autonomous, follow a digital tether. The lead vehicles control the speed, distance, and stoppage of all vehicles, which respond with near-zero reaction time. Although autonomous trucks are supervised by humans for now, it’s only a matter of time until they will be fully autonomous. It will save labour cost, fuel consumption, and make trucks safer and more fuel efficient.
Obviously, this is where it’s all heading! With the drastic growth in AI technology, various companies are coming up with self-driving trucks which will have enormous impact on the whole industry: Increased supply chain efficiency, dramatic decrease in shipping cost, reduced density of warehouse networks, the truck driver shortage problem will be solved, and lives will be saved with fewer accidents. We’re not there yet, but it’s closer than one thinks.
Predictive decision-making systems
All industries are taking advantage of historical data and trucking is certainly one of them. By applying advanced analytics and AI, road freight companies are making better predictions that impact the business as whole: Predictive pricing optimisation, routing, quoting clients based on real-time data, predictive maintenance, and customer churn modeling to name a few, are all based on sophisticated data science practices that are gradually finding its way into trucking companies worldwide.
The problems the trucking industry has been facing; security on the roads and driver shortage, have been the fuel behind the rapid evolution of automation within the industry. Obviously, the financial aspect is tremendous as both time and money will be saved throughout the supply chain, so clearly that’s also a driving factor. But the industry is in early stages of a major transformation and the change is happening faster than anticipated. In the next decade or so, we believe we’ll be witnessing the trucking industry as a whole go through a complete data-driven transformation, leading to safer roads and major efficiency improvements.