Some enthusiastic tech pundits have been speculating that we could see fleets of self-driving trucks in the next 5-10 years(!). And that's the most common profession in the vast majority of central states in the US. As Shane Greenstein explains, though, it's not likely to be the armageddon we're worried about, (instead more likely a slow displacement which our society will hopefully figure out how to cope with):
Trials in long-haul trucking involve training the vehicles for trips between depots adjacent to high-ways. At those depots, the trucks are handed off to drivers, who take them into cities for short-haul delivery. Judging from recent prototypes, humans are not disappearing anytime soon. Nobody is talking about installing robots in trucks to do the loading and unloading. The hard work today focuses on other high-value propositions, such as reducing safety issues from things like inattentive driving. A little automation can go a long way for that purpose—it can stop vehicles sooner, issue warnings to drivers, and relay information to dispatchers for use by others in a fleet. The prototypes also continue trends that began with the introduction of electronics into trucking long ago. Partial automation can enable longer continuous vehicle operation, better fuel consumption, and reduced maintenance expenses.
So what limits progress? Like many applications in machine learning, there are too many “edge cases” that the software cannot yet satisfactorily handle—such as road construction, a vehicle stopped at the side of the road, unexpected detours, pedestrians unexpectedly on the side of the highway, a dead animal carcass in the road, and so on. AI researchers know this problem well. Routine work is not as routine as it seems. Humans are pretty good at handling millions of variants of the little unexpected aspects of road work, police stops, bad weather, poor drivers, and break-downs.
The statistics of edge cases are quite demanding. Software can be trained to handle much of this, perhaps 99 percent of the issues in a typical drive. But 99 percent is not anywhere near good enough. If, say, 1 percent is still left for humans, that translates into more than half a minute every hour in which a human needs to intervene. It is necessary to do much better than that to justify removing constant human awareness, and much better performance is required to get a sufficient return on the investment in the equipment to make it all work. In the lingo of the industry, partial or conditional automation is the most ambitious goal for the next several years. Full automation is a long way off.