Everyone involved in the transportation industry knows that autonomous vehicle (AV) technology is poised to disrupt some sectors and solve persistent inefficiencies in others. The federal government anticipates big gains in highway safety; carriers want to move their trucks free from HOS burdens; customers want freight deliveries—whether to a home, warehouse, or store—flowing smoothly at all hours of the day, not bunched into peaks and troughs.
But what about shippers, especially manufacturers? What do they have to gain from the impending revolution in autonomous vehicles? On February 2, PricewaterhouseCoopers (PwC) released a research report entitled “Industrial Mobility: How autonomous vehicles can change manufacturing” based on their study of manufacturers’ adoption of AV technology and their perceptions of the advantages and disadvantages of integrating autonomous machines into their operations.
“We call this industrial mobility,” PwC wrote, “and it covers a wide swath of transportation modes—from mobile and autonomous robots on factory floors, to autonomous trucking, drones, rail and marine transport in public roads, air space, tracks, and waterways.” In other words, autonomous mobility both within private facilities and outside, on public transportation infrastructure.
Only about 9% of manufacturers say they have adopted some kind of semi-autonomous or autonomous mobility within their operations, with another 11% saying they expect to do so in the next three years. Those numbers are low, but PwC writes that if ‘mainstreaming’ can be considered 30% adoption, then industrial mobility technologies are well on their way to the mainstream.
From the survey numbers that PwC presents in its report, it appears that most manufacturers are waiting for autonomous mobility to demonstrate a return on investment. 86% of manufacturers surveyed said that cost advantage would be the top trigger for them to invest in industrial mobility solutions, and 60% of manufacturers said that cost was the top barrier to adoption of semi-autonomous and autonomous vehicles within their plants. Furthermore, 81% of survey respondents who have already adopted semi-autonomous vehicles in their operations said they experienced no annual cost savings thus far. The other top barriers to adoption cited by manufacturers were immature technology (42%), safety issues (32%), and lack of talent (32%).
Shippers are keenly anticipating autonomous trucks. 90% of the manufacturers surveyed said that they believe ‘fully autonomous trucks’ could, when mainstreamed, save up to 25% of their total trucking costs. By ‘fully autonomous’ PwC seems to mean ‘completely driverless’, a threshold that’s a decade or more away for trucks.
“I think the technology to support autonomous long-haul trucking technology will approach maturity in the next five to ten years. However, we’re still 10 to 20 years off from having fully driverless trucks be a common sight. I think the fear of displacing human workers and the general public’s initial safety concerns will keep drivers in the trucks for at least another decade, maybe two, beyond that,” Greg Rogers, Policy Analyst at the Eno Center for Transportation, said in an interview with PwC.
The survey indicates that manufacturers have given the most thought to autonomous trucks, which represent one of the most advanced forms of the technology and one of the last to see widespread adoption. Manufacturers seem to have given comparatively less attention to autonomous, mobile robots inside warehouse and plant walls. PwC made the point that since 2014, while Amazon has hired 50,000 new human workers at its warehouse facilities, it has also added 30,000 robots to work with them.
Tim Harris, CEO of SwiftNav, spoke to PwC about the complex, challenging operating environments that autonomous vehicles will have to navigate before completely driverless trucks are mainstreamed. “You can build a self-driving car in a weekend, but under which conditions will it be able to operate? The world is extraordinarily complex. Can it operate in such a world? We are figuring out decision-making algorithms, building neural nets, but there will always be more new information to add to these neural nets, and getting machines to learn as well as they need to will be an enormous undertaking. For example, consider all the unpredictable events that occur when you drive a car. To an autonomous vehicle, a black plastic bag flying out the window of a truck in front of you could indicate a real danger. To a human driver, it’s just a plastic bag.”
Tesla CEO Elon Musk had some provocative things to say about unrealized manufacturing efficiencies during the automaker’s Q4 2017 earnings call. “It sounds like some of the fastest car factories produce a car maybe every 25 seconds,” said Musk. “That sounds fast. But if you think of a 5-meter long car, including gap, and a 4.5 meter car with a half meter gap or something, that’s only 0.2 meters per second. Like grandma with a walker can exceed the speed of the fastest production line we’re in, so really no that fast. Walking speed is one meter per second, so five times faster than the fastest production line on earth. Why shouldn’t it at least be jogging speed? I mean in the limit, companies should start caring about the aero drag in the factory, which that’s maybe around 20 miles or 30 miles an hour, or call it 30 kilometers an hour, 40 kilometers an hour. It’s like, stuff should be moving at that speed.”
There are other statistics suggesting that the full impact of autonomous vehicle technology on industrial operations has not yet even begun to be felt. Unmanned aerial vehicles (UAVs; drones) are still more of a toy than a tool. PwC expects global consumer drone sales to top 10M for 2017, two orders of magnitude above global enterprise drone sales (102K in 2016).
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