With Autonomous Cars, Small Detections Are A Huge Deal: Why Tesla Motors Inc. (NASDAQ:TSLA) ’s Autopilot is Fundamentally Flawed by Dr. Alex Lidow (full bio below)
In recent months, the public has learned of at least two crashes involving the Tesla Model S, which is the company’s luxury sedan that boasts of “Autopilot” capabilities designed to “make highway driving not only safer, but stress free.” In both crashes however, Tesla’s Autopilot feature was found to be at fault, including one on May 7 that killed the driver Joshua Brown. The National Transportation Safety Board (NTSB), which is conducting an investigation, released a preliminary report indicating that Autopilot’s driving assist system was in operation at the time of the crash.
Further, a few weeks later, Tesla admitted that neither Autopilot nor the driver noticed the white side of the tractor-trailer against a brightly lit sky. Last month, the company released an updated version of Autopilot, one it thinks will solve the problems that have vexed earlier versions of the software: rather than relying primarily on cameras and secondarily on radar, Autopilot 8 will lean mainly on the use of radar. As the company stated at the time of Autopilot 8’s release, “after careful consideration, we now believe it [radar] can be used as a primary control sensor without requiring the camera to confirm visual image recognition.”
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Clearly a change was in order. However, there is still one major problem: radar is not the best choice technology in the context of autonomous or even semi-autonomous driving. And, it’s the inherent deficiencies of radar that I fear will lead to more Tesla S crashes in the future.
There are two key issues with radar: radar penetrates flesh, whereby human beings – adults and small children – not to mention dogs and other animals, appear semi-transparent. Secondly, radar only creates a “fuzzy” image of the surroundings much like a human with very poor vision. So in order to understand its surroundings, the vehicle must complement the radar with cameras. And in order to reconcile the two, computation is needed. And computation takes time. Which means there’s latency between when an object appears in front of a vehicle and when the vehicle actually recognizes it. Needless to say, all of this is problematic when speeding down the highway.
Put another way, radar doesn’t offer a direct view of a vehicle’s surroundings, but rather, an interpretation of what’s around it. And, that information can be interpreted erroneously.
So, the obvious question is, is there an alternative technology that doesn’t suffer from the same inherent limitations of radar? It turns out, there is.
LiDAR vs. Radar
LiDAR (light detecting and ranging, or light radar) is a technology that measures distance using laser light. Put simply, LiDAR systems fire laser beams in every direction and gauge the time it takes for the light to bounce back. By doing so, it creates an extremely precise 3D map of the car’s surroundings. The car then uses this information to determine what to do next. LiDAR is precise down to a resolution of just a couple of centimeters. Conversely, radar measures distance down to, at minimum, a few feet.
And then there’s the matter of speed. With virtually no computation required of LiDAR systems, latency is dramatically lower than with radar, allowing the system to create a detailed understanding of any obstacles in just a fraction of a millisecond. To put this in perspective, a car driving at 60 miles per hour travels just one inch in a millisecond.
Understanding all of this, are there any technological advantages where radar is superior to LiDAR? In a word, no. The myth of LiDAR not being able to see through rain and fog is just that. In fact, LiDAR sees through poor weather even better than people do. I don’t think we want vehicles on the road in weather conditions that are so poor that humans and LiDAR cannot see objects a few feet ahead.
And as noted earlier, the crash that killed Joshua Brown happened on a sunny day when the car’s Autopilot system couldn’t differentiate a white truck turning across the road in front of it from the bright sky behind it. LiDAR, unlike radar, can differentiate between a white truck and bright sky and would have prevented the fatal collision.
Where do Google, Ford and other big players stand?
While Tesla has opted to use radar, a number of large players in the autonomous car industry have already started to embrace LiDAR. Google is the most obvious example – anyone who has seen a Google self-driving car has noticed the LiDAR system on the roofs of these vehicles. Other big companies that have self-driving car projects involving LiDAR include Uber, Toyota, General Motors, Ford, Delphi, BMW, and Volkswagen, to name a few.
And, while the advantages of LiDAR are undeniable, the technology is only going to get better. In addition to the companies noted above, other organizations are making significant innovations in this area. For instance, MIT and the federal government’s Defense Advanced Research Projects Agency (DARPA) recently announced a collaboration in which they plan to squeeze an entire LiDAR system onto a single chip. My company, EPC, is another example: we make semiconductors, based on Gallium Nitride (GaN), that are hundreds of times faster than traditional silicon chips. All LiDAR systems on the road today use these chips in order to paint an extremely fast and accurate picture of a vehicle’s surroundings.
Where Is This All Going?
Despite LiDAR’s technological prowess, there’s no denying that, compared with radar, these systems have been too expensive. Until recently, LiDAR systems have cost as much as $75,000. However, a number of companies are rapidly bringing these costs down. For example, Quanergy Systems and Israeli startup, Innoviz Technologies, have pledged to introduce LiDAR systems that cost less than $250 by 2018. Moreover, the aforementioned effort by MIT and DARPA would enable LiDAR system chips to be manufactured in many commercial chip foundries, thereby lowering the cost of a LiDAR system dramatically, perhaps down to a few pennies per system.
Historically we have seen widespread adoption when technologies are both better and cheaper than the alternative. Which is why in another five to eight years if not sooner, I expect LiDAR, not radar to become as standard a technology as anti-lock brakes and airbags. If this claim sounds hard to believe, realize that many of the automotive innovations we now consider standard were at one time either prohibitively expensive or simply seemed in the realm of fantasy.
For instance, 36 years ago, I worked with General Motors, which told my team that it needed our help in devising a panic-stop capability that would actually prevent the wheels from completely locking up when drivers slammed on the brakes. This request sounded crazy at first. That is, until GM explained how anti-lock brakes worked. It then became obvious how such a safety mechanism could reduce accidents and save lives.
Given its high price point however – thousands of dollars per system – the technology didn’t immediately reach consumers. Rather, it initially was integrated into aircrafts, then in commercial trucks, later into high-end cars, and then in mid-tier cars as an option. A few years later, as the cost of anti-lock brakes plummeted even further, these systems finally became a standard feature on virtually every car on the road.
I believe that LiDAR will follow a similar evolution to mass adoption. Eventually, these systems will shrink in size and cost to such a degree that we will have two to four LiDAR sensors on our cars. Moreover, the LiDAR system will function as the primary technology to allow the car to drive autonomously. In fact, if recent signs are any indication, we may be closer to such a future than any of us would have thought possible as recently as a year ago.
In April, Ford announced that it is using LiDAR on Fusion sedan pilot vehicles as part of its autonomous car efforts. These same vehicles are being used in a much-publicized partnership with Uber that’s offering free autonomous taxi rides in Pittsburgh.
Interestingly, a few weeks ago, a Model S test car with LiDAR equipment on its roof was seen driving close to Tesla’s Palo Alto headquarters. Apparently, this isn’t the first time this has happened in recent months.
I have much respect for Tesla and Elon Musk’s keen sense of innovation and commitment to safety. And although the company hasn’t provided commentary, I would be profoundly surprised if LiDAR technology is not added to future Tesla models as the company doubles down on its desire to be a leader in the emerging and white-hot but highly competitive market for autonomous cars.
Alex Lidow is CEO and co-founder of Efficient Power Conversion Corporation (EPC). Since 1977 Dr. Lidow has been dedicated to making power conversion more efficient with the belief that reducing the harm to our environment through more efficient energy production and consumption.
In order to pursue this mission, in 1977 he joined International Rectifier as an R&D engineer. In 1978 Dr. Lidow co-invented the HEXFET power MOSFET, a power transistor that launched the modern power conversion market and displaced the aging bipolar transistor. Over the 30 years he was employed at IRF and was CEO for 12 years.
Dr. Lidow holds many patents in power semiconductor technology, including basic patents in power MOSFETs as well as in GaN devices. He has authored numerous publications on related subjects, and recently co-authored the first textbook on GaN transistors, “GaN Transistors for Efficient Power Conversion”, now in its second edition published by John Wiley and Sons.
In 2004 he was elected to the Engineering Hall of Fame, and in 2005 IRF, under Dr. Lidow’s leadership, International Rectifier was named one of the best managed companies in America by Forbes magazine.
Dr. Lidow earned his Bachelor of Science in Applied Physics from Caltech in 1975, and his PhD in Applied Physics from Stanford in 1977 as a Fannie and John Hertz Foundation Fellow.
Since 1998 Dr. Lidow has been a member of the Board of Trustees of the California Institute of Technology.
Images courtesy of LiDAR
Why Tesla Motors’ Autopilot is Fundamentally Flawed