Research — 29 Mar, 2022
Autonomous vehicle summit focused on production challenges
Introduction
After a two-year hiatus from in-person events, Automotive IQ recently held its 11th annual autonomous vehicles summit in Santa Clara, Calif. The Feb. 22-24 event was fairly small but included many of the major technology players in autonomous vehicle technology today, including IT vendors like Dell Technologies Inc., digital providers such as trucking automation software company Locomation Inc., and automotive industry enterprises like Ford Motor Co. The focus of the event was on the hindrances in moving from proof-of-concept autonomous vehicles, or AVs, s to production vehicles, and the steps that must be taken up and down the stack to get there.
In some respects, the summit was a day of reckoning. It was just a few years ago when several companies in the space predicted mass adoption of AVs in the near future. That prediction did not come to fruition when many said it would, which was largely related to the headline-grabbing area where AV adoption was often promised: robo-taxis. In truth, autonomous vehicles are in operation in many business use cases today, including heavy industry, distribution yards, on-road trucking and sidewalk delivery. Operating robo-taxis in busy urban centers means accounting for many more factors than, say, driving 500 miles on an interstate freeway. Urban robo-taxis increase the technological challenge exponentially, and this was a primary focus of the event.
Iyer acknowledged that the future of autonomous vehicles — robo-taxis, autonomous fleets — was supposed to be now. Why isn't it? He stated that some effects from the COVID-19 pandemic have slowed development. Auto sales dropped and manufacturing plants closed down, leading to innovation taking a back seat. As the economy rebounded, demand for new cars, and the chips included, far outstripped supply, leading to shortages that further slowed recovery and hampered innovation.
The pandemic is not the only factor here, though. For robo-taxis, many believe that infrastructure connectivity and communication with AVs are requirements, which has lagged. Public perception of AVs, which could rightly be defined as skeptical, is another major factor. According to the 451 Research's Voice of the Connected User Landscape: Consumer Population Representative Survey, less than 15% of consumers say they would be comfortable with the type of autonomy that driverless robo-taxis would require.
Raj Rajkumar is co-director of the General Motors-CMU Autonomous Driving Collaborative Research Lab at Carnegie Mellon University and was part of the 2007 team that won the Defense Advanced Research Projects Agency Grand Challenge. Aside from Rajkumar, the team's alumni include Chris Urmson, the cofounder and CEO of AV technology company Aurora Innovation Inc. and one of the original leaders of Google LLC's self-driving car project; Bryan Salesky, founder and CEO of AV tech company Argo AI LLC; and Dave Ferguson, co-founder and president of AV provider Nuro Inc.
At the summit, Rajkumar spoke of how crucial it was to have sensor redundancy in developing AVs for production. Tesla Inc. CEO Elon Musk has famously eschewed radar and lidar to focus primarily on cameras for perception, a move that has drawn questions about the safety of the company's assisted driving features. Rajkumar argued that each sensor type has its strengths and weaknesses, and that only by combining them can AVs get a consistently complete picture of their surroundings. In addition to the three perception sensors already listed, Rajkumar added infrared and microphones. Rajkumar also argued that artificial intelligence can only do so much. Without sensor redundancy, there will be gaps in perception that AI will not necessarily cover for.
Successful proof-of-concept tests and beta projects for AVs have been around for years. In instances where a safety driver is aboard to take over, engagement percentages — a measure of how much the AV system did the driving — are frequently north of 99%, while videos of these autonomous drives and tests are common on YouTube. Despite that, AVs have not been massively deployed. What will it take to get there? In a panel at the event, several players in the AV industry gave their takes.
Arne Stoschek, project executive for machine learning and autonomy at Airbus SE's Acubed, raised the issue of consumer perception. He and others intimated that consumers are inherently less trusting of automated driving systems controlling vehicles than they are of human drivers. This is despite the fact that tens of thousands of people die in motor vehicle crashes every year, and nearly 95% of them are due to human error. Nonetheless, the fact remains that consumer acceptance of AVs will likely only come when it is demonstrated that they are orders of magnitude safer than human drivers. How high that multiple must be is up for debate.
Steve Kenner, chief product and safety officer at autonomous trucking tech company Locomation, mentioned some of the technological difficulties of getting to production. AV test drives with 99% engagement look great, but what a driverless AV system does in those 1% of circumstances is what really matters. Getting from that 99% to 100% becomes increasingly difficult, given it encompasses the management of rarer and rarer edge cases that AV software has little to no experience managing, either in simulation or production.
Locomation's current strategy is "platooning" — essentially its take on convoying. This involves two human drivers in two long-haul trucks. The lead driver manually operates the lead vehicle while the second vehicle follows autonomously so the driver in that vehicle can rest. The vehicles then occasionally switch so that the lead driver becomes the rider in the following vehicle and can rest.
This article was published by S&P Global Market Intelligence and not by S&P Global Ratings, which is a separately managed division of S&P Global.
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