AI-Powered Robotic Trucks: The Future of Transportation
“ The coming era of Artificial Intelligence will not be the era of war but be the era of deep compassion, and love. ” – Amit Ray
Economists and policymakers are growing more concerned about how automation and artificial intelligence will affect the workforce, especially whether some occupations may completely disappear. The trucking industry is frequently regarded as one of the first to face grave risk. The work is challenging, dangerous, and frequently fatal, and the business is plagued by high rates of driver turnover.
As a result, the field of autonomous trucks has seen a lot of technical advancement and investment, and some experts predict that one of the first significant industries to be affected by AI-driven automation would be trucking.
Robotic trucks are very unlikely to completely replace the trucking industry in a single abrupt phase shift, but technology-driven unemployment is a serious concern. A gradual slope rather than a sharp cliff is more likely to characterize the road to completely autonomous haulage; this trajectory will also be influenced by social, legal, and cultural considerations.
In addition to driving trucks, a truck driver’s everyday employment involves several complicated duties that are significantly more challenging to automate than highway driving, including maintenance, inspections, customer interaction, and the protection of precious products.
Then, rather than worrying about a sudden surge of trucker layoffs, we should consider how AI will alter the nature of truckers’ work in the long run. There will continue to be human truckers for a very long time, but this does not preclude a significant change in what it means to be a human trucker.
As truckers are required to coordinate their work and themselves with the technology, autonomous technologies may require human and machine integration over a long period of time rather than the complete replacement of human truckers.
“ The ultimate search engine would understand everything in the world. It would understand everything that you asked it and give you back the exact right thing instantly. You could ask ‘what should I ask Larry?’ and it would tell you. ” – Larry Page
There are various shapes that this integration could take,
Transfer of the Baton
In one futuristic vision, people and machines work together. The worker completes the duties to which she is best equipped, and the machine does the same. In this concept, people and machines “carry the baton” back and forth to one another, like runners in a relay. For instance, a person might handle duties in exceptional situations or step in to take over when the robot’s capabilities are surpassed, while a robot handles dull or normal work.
Teams that combine humans and robots show some potential since they aim to capitalize on each party’s respective capabilities and because the model assumes that people will keep their jobs. In fact, if robots can take on more of the “grunt work” that humans are now required to complete, some people think that human professions might become more exciting and meaningful under such a model.
The idea of a human/robot partnership for transportation labor is not entirely unbelievable. In fact, most of us come across a variation of this model every time we operate a vehicle. Most modern vehicles provide technical aid to human drivers (sometimes referred to as “advanced driver-assistance systems”). As an illustration, the adaptive cruise control automatically changes the vehicle’s speed to maintain a predetermined driving distance from the vehicles in front of it when a human driver enables it.
Dividing the opponents
The division of labor between people and robots can also be viewed as a broader systemic question of work-sharing. We may consider how humans and machines share truck driving tasks in a broader sense, for as by allocating duties throughout the route, rather than only focusing on in-the-moment driving.
“ Machine intelligence is the last invention that humanity will ever need to make. ” – Nick Bostrom
Truck driving has been conceptualized as a series of quick, frequently concurrent driving actions like changing lanes, applying the brakes, and keeping an eye out for traffic obstructions. Instead, we may think of it as a sequence of foreseeable steps: drive down the interstate, turn off the main road and go on minor roads, and avoid the receiver’s docks.
Like how you and a friend could alternate driving on a road trip, people and robots in this model still share the labor of trucking, but they alternately take full responsibility for driving at predetermined periods in time and space. As part of their “drive team” strategy, some truck drivers already do this (often while one driver sleeps).
A second type of integration called network coordination develops when we consider human/robot teams cooperating over these segments. Many trucking technology companies have their eyes on this kind of approach.
The Robo Trucker’s Ascent
These baton-passing or network-coordination forms of shared labor may one day be how trucking operates. But now, trucking’s human-machine connection looks extremely different. A much less defined division of labor between humans and machines is what we are currently witnessing in the trucking industry. Instead, the physical bodies and sophisticated systems of truckers are fusing together.
Two different technologies make truckers into Robo Truckers,
- The first category includes wearables, which track certain internal body functions and use them as management KPIs.
- The second group of technologies consists of cameras pointing at the driver that is intended to determine his level of sleepiness, frequently by keeping an eye on his eyelids to follow his gaze and seek indications of “microsleep.” One of the many businesses that sell driver-facing cameras that employ computer vision to watch a driver’s eyelids and head posture for indicators of sleepiness or inattention includes Seeing Machines.
From the perspective of the truckers, the micromanagement made possible by this technology is viscerally repulsive. The felt reality of artificial intelligence in trucking labor today is that it addresses human “weakness” through ongoing, sensory monitoring.
The narrative of displacement that permeates most of the public discourse about AI’s implications on truckers and how these consequences are really being felt as a result of these technologies are vastly different.
Instead, the threat posed by technologies like those we have seen here is different and simultaneous: the threat of forced hybridization, an intimate intrusion into their bodies and jobs.
Today’s AI in trucking does not eject you from the cab; instead, it texts your wife and employer, shines lights in your eyes, and gooses your behind. Although truckers are now still in the cab, intelligent systems are starting to inhabit these places as well, fusing the tension between humans and machines.
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