The trucking industry is the backbone of the American economy, this is a sentence that everyone in our industry hears every now and then. We have seen many industries being completely revolutionized when automation technologies have come into play. Let’s take a modern example, you might have seen self-checkout counters popping up in malls. Stores now have fewer cashiers and the worry is that they may become obsolete. Another would be travel agents, people are now booking their own rooms, flights, and leisure activities through websites and applications.
One industry that is as big as the trucking industry was telecommunications, where calls were previously connected by an operator and are now done through automation. There might barely be anyone who still does this job. Now AI truck driving is knocking on the door, while most logistic challenges are also being tackled by software and AI. Given the track record, people in the trucking industry have every right to be worried about truck driving automation and all other forms of AI automation.
People are constantly focusing on AI truck driving, but most haven’t realized that AI technology has already been shaping the trucking industry for the past decade. Today AI makes the everyday tasks in the trucking industry faster, more scalable, and cheaper. Let’s take a look at some of the more important ones:
Yes, a TMS software like ours can help you find loads to haul automatically for you. These softwares will also update potential customers on the availability of trucks, rates, and other business-related details you would want to tell them.
The typical commercial truck consumes roughly $70,000 worth of fuel per year, and the majority of trucking companies have a number of fleets depending on the services they provide.
AI-equipped trucks have the potential to save $35 billion through increased fuel economy and a 15% reduction in fuel expenditures.
Managers can analyze fuel loss and costs with the help of the idle reporting and fuel monitoring tools found in many AI programs. Improved reporting and oversight significantly impact the quality of truck driving services.
Even though self-driving cars are still in the works, a number of businesses are enhancing safety measures with AI. For instance, Tesla is developing technology that can steer, brake, and accelerate a truck when it senses danger. Truck drivers must however always keep their hands on the steering wheel.
Semi-autonomous trucks with AI guidance can also aid truck drivers in maintaining concentration at the end of their shifts. The second half of the day is when mistakes are more likely to occur because many truck drivers spend over 10 hours on the road each day.
One of the reasons why trucking companies lose money is because they are not matching the right load to the right trucks and drivers. However, AI technology integrations collect data and use it to make better decisions.
In turn, these decisions help you save money by reducing high empty miles, matching trucks based on weight-to-power ratio, and more. Even LoadStop has the feature of load matching.
This form of AI truck driving is still in the works from what we can currently see it is very promising. There are a few companies that are utilizing self-driving trucks within their operations, one such example is ‘Scania’ an Australian mining company. However, most of these companies operate these trucks in very low-population areas.
AI truck driving’s main goal would be to make the entire delivery process autonomous. Currently, this technology is only partially used in a handful of companies and these trucks are always manned by a driver, even if he/she is not operating it.
There are numerous other uses, but you all get the gist of it by now.
The impact of AI on the trucking industry in the future is likely to be even more significant than it is today. Here are some potential ways in which AI may impact the trucking industry in the future:
There is a great possibility and investment in making fully driverless trucks a reality in the industry. The goal is to diminish the reliance on drivers and save companies a ton of money in the process. These trucks are likely to be supervised by a person instead of driving them, that person will also have the option of remote overdrive, so he/she can take control of the vehicle in case there is an issue.
As AI develops, it will be able to optimize routes, cut down on empty miles, and further better fuel economy. This might result in shorter delivery times, cheaper prices, and lower carbon emissions. Moreover, since machines require zero to no amount of rest, they can work 24/7. Also since machines are less likely to make errors, less time would be wasted trying to correct those errors. Moreover, you will also require fewer employees to manage tasks.
Platforms driven by AI can gather and analyze information on consumer preferences and demands, allowing carriers to provide more individualized services and customized solutions. AI will be able to detect the inefficiencies within your business
AI machine learning on a global scale would mean that these machines have learned how different types of accidents occur and how they can be prevented. An AI override will help assist with braking and acceleration to provide optimal safety standards. So say goodbye to blind corners you can’t see the AI will detect them, rough cornering can also become a thing of the past, and so will unsafe acceleration, and other such driving behaviors.
AI can give carriers real-time access to the supply chain, allowing them to track shipments more precisely and react to changes faster.
All things considered, AI has the potential to drastically change the trucking industry in ways that we have yet to even comprehend. It will probably increase productivity, security, and profitability, but it might also call for new business strategies and careful management to guarantee that the rewards are distributed fairly.
With the advancement of autonomous driving technology, it is conceivable that some portions of truck driving may be automated in the future, although it is unlikely that truck drivers will be entirely replaced by AI any time soon.
Driving a truck demands decision-making, problem-solving, and the capacity to react to unforeseen circumstances in addition to the physical task of directing the vehicle. Despite the rapid advancement of AI, machines are still unable to match the adaptability and flexibility of the human mind.
A truck driver's employment also includes a variety of non-driving duties like loading and unloading freight, inspecting vehicles, and interacting with dispatchers and clients. These tasks demand human involvement and are difficult to automate.
As a result, the duties of truck drivers may change as technology advances. However, it is doubtful that AI will replace them entirely anytime soon.
It is not easy to predict with complete certainty when self-driving trucks will take over, as it depends on various factors such as technological advancements, regulatory frameworks, and societal acceptance. However, it is clear that self-driving trucks are currently being tested and deployed in certain contexts.
In the United States, for example, several companies are testing autonomous trucks in certain regions and on specific routes. The adoption of truck driving automation is expected to be gradual, with autonomous driving technology being integrated into existing trucking operations rather than replacing human drivers entirely.
Regulatory frameworks will play a significant role in the adoption of truck driving automation. Government agencies will need to ensure that autonomous trucks meet safety standards and are capable of navigating the complexities of the road network.
Finally, societal acceptance will also be a factor in the adoption of self-driving trucks. Some people may be hesitant to share the road with autonomous trucks, while others may be concerned about the impact on jobs in the trucking industry.
Overall, it is difficult to predict an exact timeline for when self-driving trucks will take over, but it is clear that they are likely to become more common in the coming years as technology and regulations continue to evolve.
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