Auto industry leaders have been expressing caution that fully autonomous vehicles aren't as close as some people thought three to four years ago. But automakers and suppliers haven't given up on providing vehicles the ability to safely and reliably drive themselves. Nvidia is a leading supplier of artificial intelligence solutions that will be central to future autonomous vehicles.
Nvidia Senior Director of Automotive Danny Shapiro, 54, spoke with Automotive News Europe Managing Editor Douglas A. Bolduc about current challenges and the new perceptions of what's happening with the technology. Here are excerpts from the conversation.
Q: Why have the bold predictions about putting autonomous vehicles on the road changed over the past few years?
A: The industry has realized that fully autonomous vehicles aren't as close as we thought they were three or four years ago. It's a really hard problem to solve. This means more computing, more sensors and more software is required.
Has the enormity of the problem led some people to back away?
What we are seeing is people saying, "We can still bring technology to market that is the foundation for autonomous driving, but there is still going to be a human in the loop."
What will we see?
For now it is "Level 2-plus," which can be a really robust system that can prevent a lot of accidents or save the driver if something bad happens, like the person falls asleep or has a medical emergency.
Is it more realistic that we won't see fully autonomous cars on the road until 2030?
If you are talking about the Holy Grail — the car that will pick you up anywhere and take you anywhere — yes, that is quite far out. I don't think it's that far out if you mean very specific kinds of deployments. It could be robotaxis or shuttles on fixed routes or in geofenced areas. When it comes to highway auto pilots and hub-to-hub trucking, I think we are going to see a lot more in terms of the movement of goods before [the movement of] people.
Could you elaborate?
It means delivery bots of all shapes and sizes. We are involved in virtually all these delivery trial programs.
There has been one fatal accident involving an AV with a safety driver and a recent nonfatal accident. Have these events forced you to double down on making AVs as safe as possible?
We have always had that practice. I think Nvidia and the industry underestimated the complexity at the outset. I don't think it was a matter of us not being safe. We are figuring out how to solve these challenges — and on the way, we realized there is a lot more to it than was initially planned.
What's being done to address this overestimation?
It has shown the need for more high-resolution sensors on the car, and the need for diversity and redundancy of these sensors, of the algorithms, of the systems to ensure the highest level of safety that we possibly can.
There is this insatiable desire for more computing because it's not just one algorithm running. You have dozens of different neural nets that are all running in the car simultaneously. That's why we hear the customers we are working with, such as Mercedes-Benz, saying, "We need more computing horsepower in the car." That's because the complexity of the software is growing and growing.
Is creating a safe, reliable fully autonomous car the toughest challenge Nvidia has ever undertaken?
It's like comparing apples to oranges because we are also trying to help cure cancer. They both involve saving a lot of lives. AI computing is fundamental to that. There is a lot more real-time concern over the autonomous car vs. going off and solving some of these other problems that are very complex. When you are driving an autonomous car it's life or death, second by second, so you could say there is potentially more on the line there. There is incredible complexity in trying to analyze human behavior. Predict human behavior. Humans are not predictable.
What's being done to help offset some of that unpredictability?
I think we are going to see deployments in places where we can remove that human randomness. This could be dedicated roadways, fixed routes and geofenced areas. It could be cities that ban human-driven cars in certain areas, or they have humans on a different plain, such as having autonomous vehicles on one level of a highway and pedestrians on another.
What is being done to overcome the "fear of the unknown" connected to AVs?
There's definitely an awareness and education piece to this, which is why we joined PAVE — the partnership for autonomous vehicle education. It is a U.S. initiative that includes Mercedes, Nvidia and a bunch of others.
Autonomous vehicle education is crucial because most people don't know what's in their cars today, what the technology is capable of and what is coming in the future. They have never experienced it or read a story about it, and they think of the Terminator when they think of artificial intelligence.