In the last years, there have been breakthrough advancements in the development of autonomous vehicles. What seemed like science fiction a decade ago is very close to being accomplished. Companies like Uber, Google and Tesla have begun the race to develop the first fully functional prototypes. But contrary to what many might think, transportation experts expect that the earliest applications will be in self-driving trucks, not cars. Trucking routes usually consist of long-haul drives on highways, which make them more predictable compared to cities . In this particular industry, Otto (acquired by Uber in 2016) is one of the main players. In October of last year, Otto managed to transport 50,000 cans of Budweiser, making this the first commercial delivery by an autonomous truck .
Problems in the Trucking Industry
In the U.S. more than 70% of goods are transported by trucks, which translates into a $700 billion industry  . Despite being the preferred way of moving goods across the country, traditional trucking has severe drawbacks. Truck and bus crashes are responsible for 4,000 deaths and 100,000 injuries a year, 90% of them caused by driver error . Other important issues are truck driver shortages and turnover rate. In 2017 the American Trucking Association calculated that there was a 50,000 shortage of truck drivers and that yearly turnover rate was 90%. If the trend continued the shortage of truck drivers will hit 174,000 by 2026 . Self-driving trucks, even if not fully autonomous, have the potential to drastically reduce these problems by cutting down the number of accidents and reducing drivers’ workload.
Figure 1: Projections of Truck Driver Shortages
The Road Ahead
With the truck Uber used for the Budweiser it reached a “Level 4” autonomy, which meant that the vehicle was “fully autonomous” in a certain domain (in this case the highway)  . In the next couple of years, Uber planned to continue to develop the technology so that trucks were able to handle any situation they encountered. Other areas of opportunity where improving acceleration, deceleration and lane control. They were also working on predicting behavior for other drivers and dealing with changing weather . Although reaching “Level 5” autonomy was the ultimate goal, in the short-term Uber would concentrate on improving “Level 4” performance. That meant that the self-driving trucks will still need a human driver especially in the cities, where the truck couldn’t operate on its own.
Figure 2: Autonomous Vehicle Levels
Uber estimates that it could reach “fully autonomous” trucks at a large scale within the next decade. Lior Ron, co-founder of Otto, expects that by that time driverless trucks would routinely drive throughout the U.S. highways . This would have significant effects on the efficiency of the transport industry as it would reduce labor and increase fuel efficiency. Labor and fuel are the most important costs of operating a truck, representing 40% and 25% of the total cost respectively . Even if trucks couldn’t reach “Level 5” autonomy and would still require a driver, labor could be better utilized and substantial cost reduction could be achieved.
Even though the self-driving truck industry may appear very attractive, it faces intense competition. Competitors such as Google and Tesla are making huge investments to develop competing technology. This industry is attracting billions of dollars from start-ups to the biggest trucking operators . Given that “Level 5” autonomy is still far away from a technology and regulatory standpoint it is important for Uber to begin with driver assistance technology. Building a commercially viable prototype, even if not fully autonomous will allow the company to slowly enter the industry and be a step ahead of the competition. Incremental changes in this technology can have big impacts on fuel efficiency, labor cost and churn rate which would make it an attractive product.
The ability to have trucks on the road will also allow Uber to quickly improve the technology. By analyzing in real conditions when and how human drivers take control of the vehicle can help the company fine-tune their algorithms. The more data that can be collected, the more autonomous the vehicle will be as it will learn how to act in a wider range of scenarios. Uber has a competitive advantage compared to competitors in this regard. Having access to tens of thousands of drivers in hundreds of cities could help the company in this data collection stage. Even though autonomous trucks and cars are different, there are still conclusions that could be drawn using Uber drivers.
Even though there has been a lot of advancements in the industry, there are still many open questions. How can Uber and other competitors lobby for legislation that will allow self-driving trucks at the expense truck driving jobs? How many years will it take to produce the first commercially viable self-driving truck? Is there enough space in the industry for a few players or is it a “winner takes it all” market?
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