For that reason, Woodrow says that he saw their version of self-driving trucks as complementing humans, not replacing them. To make their case, Uber created a model of the industry’s labor market based on Bureau of Labor Statistics data. Then, they created scenarios that looked at a range of self-driving-truck adoption rates and how often those autonomous trucks would be on the road in comparison to human-driven vehicles.
Their numbers for autonomous-truck adoption are intentionally very aggressive, Woodrow says, corresponding to 25, 50, and 70 percent of today’s trucks being self-driven. These do not reflect an Uber prediction that between 500,000 and 1.5 million self-driving trucks will be on the road by 2028, but rather they allow the model to show the dynamics in the labor market that might result from widespread adoption. “Imagine that self-driving trucks are incredibly successful and impactful,” he says. “What would that mean?”
The other set of numbers in the model—the utilization rate of the self-driving trucks—is the component that leads Uber to a different analysis of the effect that these vehicles will have on truckers. Basically, if the self-driving trucks are used far more efficiently, it would drive down the cost of freight, which would stimulate demand, leading to more business. And, if more freight is out on the roads, and humans are required to run it around local areas, then there will be a greater, not lesser, need for truck drivers.